Spurious correlation #3,787 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Butter consumption and the second variable is The number of bridge and lock tenders in Texas. The chart goes from 2003 to 2021, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Butter consumption and the second variable is The number of bridge and lock tenders in Texas. The chart goes from 2003 to 2021, and the two variables track closely in value over that time.

AI explanation

As butter consumption increased, so did the demand for delicious baked goods. This created a booming industry for bakeries in Texas, leading to the need for more bridge and lock tenders to facilitate the transportation of these tasty treats across the state. It's a butterly delicious connection that's really spreading!

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of a bustling Texan port, with cargo ships loaded with crates of butter sailing in from afar. Show the dock lined with an increased number of bridge and lock tenders, working tirelessly to operate the systems and accommodate the influx of butter-laden cargo ships. The air should be filled with the rich scent of butter as chefs in nearby restaurants prepare delicious, butter-drenched dishes to meet the heightened demand. The overall scene should convey the vibrant energy and activity of the port during this unique influx of butter shipments. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.

This image generation prompt was also generated by AI, using the following sequence:

Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: Butter consumption and The number of bridge and lock tenders in Texas. Given these, which of the following image style descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand. Please respond with only one of the following potential descriptions: A TIME magazine cover image Data cyber art An image that looks like it is a scene from a Pixar movie A Discovery magazine cover image Woodblock painting
ChatGPT: A Discovery magazine cover image

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Butter consumption and The number of bridge and lock tenders in Texas, in the following situation: Because butter consumption in Texas led to an increase in demand for delicious, butter-drenched dishes, leading to more tenders needing to operate bridge and lock systems for the influx of butter-laden cargo ships.. Keep the description simple.
ChatGPT: In a bustling Texan port, cargo ships loaded with crates of butter sail in from afar. The dock is lined with an increased number of bridge and lock tenders, working tirelessly to operate the systems and accommodate the influx of butter-laden cargo ships. The air is filled with the rich scent of butter as chefs in nearby restaurants prepare delicious, butter-drenched dishes to meet the heightened demand.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ A Discovery magazine cover image ] and depicting this scene: In a bustling Texan port, cargo ships loaded with crates of butter sail in from afar. The dock is lined with an increased number of bridge and lock tenders, working tirelessly to operate the systems and accommodate the influx of butter-laden cargo ships. The air is filled with the rich scent of butter as chefs in nearby restaurants prepare delicious, butter-drenched dishes to meet the heightened demand. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a bustling Texan port, with cargo ships loaded with crates of butter sailing in from afar. Show the dock lined with an increased number of bridge and lock tenders, working tirelessly to operate the systems and accommodate the influx of butter-laden cargo ships. The air should be filled with the rich scent of butter as chefs in nearby restaurants prepare delicious, butter-drenched dishes to meet the heightened demand. The overall scene should convey the vibrant energy and activity of the port during this unique influx of butter shipments.

*Variations in the User Prompts from chart to chart are just the result of random number generation in Python. I wrote a few arrays of various styles and methods to ask questions to change up the results. Every time this site writes an explanation or generates an image, the script picks from each at random.

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
^{Show prompt for explanation} Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in Butter consumption caused The number of bridge and lock tenders in Texas to increase. Include one good pun.

AI academic paper

(Because p < 0.01)

Spreading Butter, Building Bridges: A Creamy Correlation Between Butter Consumption and the Number of Bridge and Lock Tenders in Texas

The Journal of Culinary Correlations

Jan 2024

^{Show prompt used to generate this paper} Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a literature review section of an academic research paper presenting the findings of the connection between Butter consumption and The number of bridge and lock tenders in Texas. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Speak in the present tense for this section (the authors find...), as is common in academic research paper literature reviews. Name the sources in a format similar to this: In "Book," the authors find lorem and ipsum.

Make up the lorem and ipsum part, but make it sound related to the topic at hand.

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then cite some social media posts you read that seem to be related.

Here is the title and abstract of the paper:
[[TITLE]]
Spreading Butter, Building Bridges: A Creamy Correlation Between Butter Consumption and the Number of Bridge and Lock Tenders in Texas

[[ABSTRACT]]
In this study, we set out to churn up some fascinating findings by investigating the seemingly unrelated realms of butter consumption and the employment of bridge and lock tenders in the Lone Star State. Utilizing data from the USDA and Bureau of Labor Statistics spanning the years 2003 to 2021, we uncovered a positively buttery correlation coefficient of 0.7357966 and a p-value of less than 0.01, suggesting a significant relationship between these variables.

As we delved into the data, it quickly became apparent that there was more to this connection than initially met the eye. Through our analysis, we kneaded through the numbers and found that as butter consumption in Texas increased, so did the number of employed bridge and lock tenders. While the precise mechanism behind this correlation remains an enigma, it is undoubtedly a thought-provoking conundrum that merits further exploration.

Our findings not only shed light on this unexpected correlation but also serve as a reminder of the rich tapestry of relationships that exist within economic and dietary trends. After all, who would have thought that butter and bridge tenders could be connected by more than just their shared affinity for smooth operations? This research opens the door to a realm of further investigation, challenging us to spread our understanding of seemingly disparate factors and find the hidden threads that tie them together.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The state of Texas, known for its sprawling plains, vibrant culture, and iconic Lone Star, is also home to a peculiar correlation that may butter your intellectual curiosity. In this paper, we embark on a quest to unravel the curious link between butter consumption and the employment of bridge and lock tenders in the Lone Star State. While it might initially seem as incongruous as a butter sculpture at a bridge-building convention, our investigation has uncovered a connection that is as intriguing as it is unexpected.
As we delve into the world of butter and bridge tenders, it is worth acknowledging that correlations can sometimes be as slippery as, well, a pat of butter on a hot skillet. Yet, armed with statistical tools and a healthy dose of curiosity, we sought to churn through the data and separate the wheat from the chaff, or in this case, the cream from the milk.
Upon diving into the rich reservoir of data provided by the USDA and Bureau of Labor Statistics, our journey through the numbers revealed an astonishingly robust correlation coefficient of 0.7357966 and a p-value of less than 0.01. The significance of this correlation was not lost on us, prompting further investigation into the potential mechanisms underlying this unexpected alliance.
It is often said that the devil is in the details, and as we scrutinized the patterns of butter consumption and the number of employed bridge and lock tenders, a distinct pattern emerged. Like the gentle lapping of waves against a moored barge, the rise and fall of butter consumption mirrored the ebbs and flows of the employed workforce tending to the state’s bridges and locks.
The implications of this correlation extend beyond mere statistical curiosity, as it challenges our understanding of the interconnected nature of seemingly unrelated variables. Indeed, the confluence of butter and bridge tenders shines a light on the intricate dance of factors that shape economic and dietary landscapes. It beckons us to peer beyond the obvious and recognize the subtle relationships that interlace the fabric of our daily existence.
In unveiling this unexpected connection, we invite further exploration into the depths of these seemingly disparate realms, nudging the boundaries of our understanding and savoring the flavor of unconventional correlations. After all, who would have thought that a stick of butter and a bridge tender could be connected in more ways than one?
As we embark on this scholarly adventure, we invite our readers to join us in spreading the wings of curiosity, for it is the pursuit of knowledge that helps us bridge the gaps between the known and the enigmatic. Let us not simply skim the surface, but rather dive deep into this whimsical intersection of butter and bridge tenders, where the waters are as rich as a freshly churned batch of cream.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

In the pursuit of unraveling the enigmatic correlation between butter consumption and the employment of bridge and lock tenders in Texas, we turn to the existing body of literature to glean insights and perspectives on this peculiar nexus. A thorough review of prior research provides a foundation upon which we can build our understanding of this unexpected relationship.

Smith et al. (2010) delve into the dietary habits of Texans and their implications on the labor market in their seminal work titled "Butter, Bridges, and Beyond: Unraveling the Paradox." The authors explore the intricate interplay between dietary choices and employment patterns, offering a compelling argument for the potential impact of butter consumption on the demand for bridge and lock tenders. Their study provides an intriguing precursor to our own investigation, spurring further curiosity and inquiry into this unconventional connection.

Building upon this foundation, Doe (2015) conducts a comprehensive analysis of employment trends in Texas, focusing specifically on the role of bridge and lock tenders in relation to dietary shifts. In their work, "Spread Thin: Tracking the Labor Market in the Lone Star State," Doe uncovers subtle yet significant correlations between butter consumption and the number of employed bridge and lock tenders. Their findings prompt us to consider the nuanced dynamics at play, beyond the surface-level associations that may initially meet the eye.

As we widen our scope to encompass a multidisciplinary perspective, it is essential to draw from related literature that offers insights into the economic and dietary landscapes of Texas. Jones (2018) provides a panoramic view of agricultural trends in the Lone Star State in their work "From Cattle to Cream: A Texan Tapestry of Food and Labor." While not explicitly focused on bridge and lock tenders, Jones' exploration of dairy production and its economic implications forms a valuable backdrop against which we can juxtapose the consumption of butter and its potential impact on employment patterns.

Expanding our horizons further, we venture into the realm of non-fiction works that shed light on the cultural and economic fabric of Texas. "Lone Star Economies: A Culinary Exploration" by Marquez (2019) presents an in-depth analysis of food-related industries and their ripple effects on employment dynamics. While the book does not directly address butter consumption or bridge tenders, it acquaints us with the broader context within which our research inquiry unfolds, serving as a canvas upon which we can paint our unexpected findings.

Diving into artful creations that may offer tangential insights, we turn our attention to fiction works that, while not rooted in empirical research, spark the imagination and evoke contemplation on the intricate web of societal interactions. In "The Bridges We Butter" by Harper (2017), the author weaves a tale of serendipitous encounters and unlikely connections, where bridges and butter serve as allegorical symbols of unforeseen relationships. Though fictional in nature, the themes explored in the novel inspire us to approach our research with a sense of curiosity and openness to the unexpected.

Furthermore, in the vein of contemporary discourse, social media platforms offer glimpses into public perceptions and personal anecdotes that may offer anecdotal evidence related to our investigation. A tweet by @TexasButterLover captures an intriguing observation: "Who knew that spreading butter could pave the way for bridge maintenance? It's like a creamy collaboration between culinary indulgence and infrastructure upkeep. #ButterAndBridges #TexasTenders"

In synthesizing these diverse sources, we acknowledge that our inquiry into the correlation between butter consumption and the employment of bridge and lock tenders ventures into uncharted territory, imbued with both academic rigor and a sprinkle of whimsy. As we sift through the layers of literature, we are reminded of the rich tapestry of perspectives that converge to enrich our understanding of unexpected connections, inviting us to explore the intriguing interplay of buttery indulgence and labor market dynamics in the Lone Star State.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the methodology section of an academic research paper presenting the findings of the connection between Butter consumption and The number of bridge and lock tenders in Texas. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from USDA and Bureau of Larbor Statistics . You used data from 2003 to 2021

Make up the research methods you don't know. Make them a bit goofy and convoluted.

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
Spreading Butter, Building Bridges: A Creamy Correlation Between Butter Consumption and the Number of Bridge and Lock Tenders in Texas

[[ABSTRACT]]
In this study, we set out to churn up some fascinating findings by investigating the seemingly unrelated realms of butter consumption and the employment of bridge and lock tenders in the Lone Star State. Utilizing data from the USDA and Bureau of Labor Statistics spanning the years 2003 to 2021, we uncovered a positively buttery correlation coefficient of 0.7357966 and a p-value of less than 0.01, suggesting a significant relationship between these variables.

As we delved into the data, it quickly became apparent that there was more to this connection than initially met the eye. Through our analysis, we kneaded through the numbers and found that as butter consumption in Texas increased, so did the number of employed bridge and lock tenders. While the precise mechanism behind this correlation remains an enigma, it is undoubtedly a thought-provoking conundrum that merits further exploration.

Our findings not only shed light on this unexpected correlation but also serve as a reminder of the rich tapestry of relationships that exist within economic and dietary trends. After all, who would have thought that butter and bridge tenders could be connected by more than just their shared affinity for smooth operations? This research opens the door to a realm of further investigation, challenging us to spread our understanding of seemingly disparate factors and find the hidden threads that tie them together.

[[INTRODUCTION]]
The state of Texas, known for its sprawling plains, vibrant culture, and iconic Lone Star, is also home to a peculiar correlation that may butter your intellectual curiosity. In this paper, we embark on a quest to unravel the curious link between butter consumption and the employment of bridge and lock tenders in the Lone Star State. While it might initially seem as incongruous as a butter sculpture at a bridge-building convention, our investigation has uncovered a connection that is as intriguing as it is unexpected.
As we delve into the world of butter and bridge tenders, it is worth acknowledging that correlations can sometimes be as slippery as, well, a pat of butter on a hot skillet. Yet, armed with statistical tools and a healthy dose of curiosity, we sought to churn through the data and separate the wheat from the chaff, or in this case, the cream from the milk.
Upon diving into the rich reservoir of data provided by the USDA and Bureau of Labor Statistics, our journey through the numbers revealed an astonishingly robust correlation coefficient of 0.7357966 and a p-value of less than 0.01. The significance of this correlation was not lost on us, prompting further investigation into the potential mechanisms underlying this unexpected alliance.
It is often said that the devil is in the details, and as we scrutinized the patterns of butter consumption and the number of employed bridge and lock tenders, a distinct pattern emerged. Like the gentle lapping of waves against a moored barge, the rise and fall of butter consumption mirrored the ebbs and flows of the employed workforce tending to the state’s bridges and locks.
The implications of this correlation extend beyond mere statistical curiosity, as it challenges our understanding of the interconnected nature of seemingly unrelated variables. Indeed, the confluence of butter and bridge tenders shines a light on the intricate dance of factors that shape economic and dietary landscapes. It beckons us to peer beyond the obvious and recognize the subtle relationships that interlace the fabric of our daily existence.
In unveiling this unexpected connection, we invite further exploration into the depths of these seemingly disparate realms, nudging the boundaries of our understanding and savoring the flavor of unconventional correlations. After all, who would have thought that a stick of butter and a bridge tender could be connected in more ways than one?
As we embark on this scholarly adventure, we invite our readers to join us in spreading the wings of curiosity, for it is the pursuit of knowledge that helps us bridge the gaps between the known and the enigmatic. Let us not simply skim the surface, but rather dive deep into this whimsical intersection of butter and bridge tenders, where the waters are as rich as a freshly churned batch of cream.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To explore the intriguing relationship between butter consumption and the number of bridge and lock tenders in Texas, our research team concocted a methodological approach that was as carefully crafted as a batch of artisanal butter. We began by gathering data from the USDA and Bureau of Labor Statistics, sifting through a plethora of information spanning the years 2003 to 2021. Our data mining expedition led us to an abundance of statistical treasures, although we must admit that wading through spreadsheets can be as perplexing as navigating a labyrinth of butter sculptures.

The first step of our methodology involved quantifying the per capita butter consumption across different regions of Texas, delving into both urban and rural areas to ensure a comprehensive understanding of buttery trends. To allow for a thorough analysis, we meticulously categorized the types of butter, including salted, unsalted, grass-fed, and even the occasional artisanal batch.

Next, we turned our attention to the employment data for bridge and lock tenders. This involved examining job records, employment trends, and geographic distributions, as we sought to grasp the labor landscape with the same precision that a butter knife would glide through a freshly baked loaf of bread.

Now, here's where it gets a bit technical, but fear not, as we shall endeavor to churn through these details with as much levity as possible. Our statistical analysis relied on the application of robust correlation techniques, including Pearson's correlation coefficient and linear regression models. These analytical tools allowed us to gauge the strength and direction of the relationship between butter consumption and the number of employed bridge and lock tenders, providing us with the quantitative evidence needed to bolster our findings.

Moreover, our methodology also entailed a sub-analysis of seasonal variations in butter consumption, recognizing that dietary preferences may wax and wane with the changing Texas climate. We even mused on the potential impact of a "butter boom" during the festive holiday season and its hypothetical influence on the workforce managing the state's bridges and locks. We must admit, contemplating the interplay of butter and holiday employment conjured images of a yuletide ballet on a bridge made of brie, but we digress.

In addition to these quantitative approaches, we also conducted qualitative interviews with bridge and lock tenders, aiming to gauge their perceptions of butter and its potential correlation with their occupational numbers. These anecdotal insights provided a human touch to our research, reminding us that behind every statistical point lies a person with their own unique relationship to creamy spreads and professional duties.

As we blended these diverse methodological elements together, our aim was to construct a comprehensive understanding of the enigmatic connection between butter and bridge tenders. We recognize that the convergence of these seemingly disparate domains is as unexpected as stumbling upon a butter sculpture festival in the midst of a bridge construction site, but it is precisely such unexpected intersections that invigorate the scholarly pursuit.

In summary, our methodology encompassed a melding of quantitative analysis, seasonal considerations, and qualitative insights, all aimed at uncovering the fascinating correlation between butter consumption and the employment of bridge and lock tenders in the great state of Texas. With our methodological recipe in hand, we set forth on this scholarly journey, eager to butter up the academic community with our unconventional findings.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the discussion section of an academic research paper presenting the findings of the connection between Butter consumption and The number of bridge and lock tenders in Texas. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Limit your response to 500 tokens.

Here are the title, abstract, literature review, and results sections. Please harken back to 1-2 of the goofy items in the literature review, but pretend to take them completely seriously. Discuss how your results supported the prior research.

Do not write a conclusion. I will add a conclusion after this.

[[TITLE]]
Spreading Butter, Building Bridges: A Creamy Correlation Between Butter Consumption and the Number of Bridge and Lock Tenders in Texas

[[ABSTRACT]]
In this study, we set out to churn up some fascinating findings by investigating the seemingly unrelated realms of butter consumption and the employment of bridge and lock tenders in the Lone Star State. Utilizing data from the USDA and Bureau of Labor Statistics spanning the years 2003 to 2021, we uncovered a positively buttery correlation coefficient of 0.7357966 and a p-value of less than 0.01, suggesting a significant relationship between these variables.

As we delved into the data, it quickly became apparent that there was more to this connection than initially met the eye. Through our analysis, we kneaded through the numbers and found that as butter consumption in Texas increased, so did the number of employed bridge and lock tenders. While the precise mechanism behind this correlation remains an enigma, it is undoubtedly a thought-provoking conundrum that merits further exploration.

Our findings not only shed light on this unexpected correlation but also serve as a reminder of the rich tapestry of relationships that exist within economic and dietary trends. After all, who would have thought that butter and bridge tenders could be connected by more than just their shared affinity for smooth operations? This research opens the door to a realm of further investigation, challenging us to spread our understanding of seemingly disparate factors and find the hidden threads that tie them together.

[[LITERATURE REVIEW]]
In the pursuit of unraveling the enigmatic correlation between butter consumption and the employment of bridge and lock tenders in Texas, we turn to the existing body of literature to glean insights and perspectives on this peculiar nexus. A thorough review of prior research provides a foundation upon which we can build our understanding of this unexpected relationship.
Smith et al. (2010) delve into the dietary habits of Texans and their implications on the labor market in their seminal work titled "Butter, Bridges, and Beyond: Unraveling the Paradox." The authors explore the intricate interplay between dietary choices and employment patterns, offering a compelling argument for the potential impact of butter consumption on the demand for bridge and lock tenders. Their study provides an intriguing precursor to our own investigation, spurring further curiosity and inquiry into this unconventional connection.
Building upon this foundation, Doe (2015) conducts a comprehensive analysis of employment trends in Texas, focusing specifically on the role of bridge and lock tenders in relation to dietary shifts. In their work, "Spread Thin: Tracking the Labor Market in the Lone Star State," Doe uncovers subtle yet significant correlations between butter consumption and the number of employed bridge and lock tenders. Their findings prompt us to consider the nuanced dynamics at play, beyond the surface-level associations that may initially meet the eye.
As we widen our scope to encompass a multidisciplinary perspective, it is essential to draw from related literature that offers insights into the economic and dietary landscapes of Texas. Jones (2018) provides a panoramic view of agricultural trends in the Lone Star State in their work "From Cattle to Cream: A Texan Tapestry of Food and Labor." While not explicitly focused on bridge and lock tenders, Jones' exploration of dairy production and its economic implications forms a valuable backdrop against which we can juxtapose the consumption of butter and its potential impact on employment patterns.
Expanding our horizons further, we venture into the realm of non-fiction works that shed light on the cultural and economic fabric of Texas. "Lone Star Economies: A Culinary Exploration" by Marquez (2019) presents an in-depth analysis of food-related industries and their ripple effects on employment dynamics. While the book does not directly address butter consumption or bridge tenders, it acquaints us with the broader context within which our research inquiry unfolds, serving as a canvas upon which we can paint our unexpected findings.
Diving into artful creations that may offer tangential insights, we turn our attention to fiction works that, while not rooted in empirical research, spark the imagination and evoke contemplation on the intricate web of societal interactions. In "The Bridges We Butter" by Harper (2017), the author weaves a tale of serendipitous encounters and unlikely connections, where bridges and butter serve as allegorical symbols of unforeseen relationships. Though fictional in nature, the themes explored in the novel inspire us to approach our research with a sense of curiosity and openness to the unexpected.
Furthermore, in the vein of contemporary discourse, social media platforms offer glimpses into public perceptions and personal anecdotes that may offer anecdotal evidence related to our investigation. A tweet by @TexasButterLover captures an intriguing observation: "Who knew that spreading butter could pave the way for bridge maintenance? It's like a creamy collaboration between culinary indulgence and infrastructure upkeep. #ButterAndBridges #TexasTenders"
In synthesizing these diverse sources, we acknowledge that our inquiry into the correlation between butter consumption and the employment of bridge and lock tenders ventures into uncharted territory, imbued with both academic rigor and a sprinkle of whimsy. As we sift through the layers of literature, we are reminded of the rich tapestry of perspectives that converge to enrich our understanding of unexpected connections, inviting us to explore the intriguing interplay of buttery indulgence and labor market dynamics in the Lone Star State.

[[RESULTS]]
The analysis of the data spanning from 2003 to 2021 revealed a striking correlation between butter consumption and the number of employed bridge and lock tenders in Texas. Our statistical analysis unveiled a correlation coefficient of 0.7357966, which indicates a strong positive relationship between these seemingly unrelated variables. The r-squared value of 0.5413966 further underscores the robustness of this correlation, explaining over 54% of the variation in the number of bridge and lock tenders based on butter consumption. With a p-value of less than 0.01, the likelihood of this relationship occurring by chance is exceedingly low, lending further credence to the significance of our findings.
As illustrated in Figure 1, the scatterplot visually represents the clear association between butter consumption and the number of bridge and lock tenders in Texas. The upward trend depicted in the scatterplot reinforces the positive correlation observed in our analysis, leaving little room to spread doubt about the strength of this connection.
This unexpected alliance between butter consumption and the employment of bridge and lock tenders presents a thought-provoking conundrum that challenges conventional wisdom. While the precise mechanisms underlying this correlation remain a subject of speculation, our findings invite further exploration and raise intriguing questions about the interplay between dietary habits and labor demand. The correlation may be as slippery as a freshly unwrapped stick of butter, but its implications are as rich and substantial as a decadent pat of butter on a warm slice of toast.
In summary, our research not only unveils the buttery correlation between butter consumption and the employment of bridge and lock tenders but also opens the door to a deeper understanding of the unexpected connections that intertwine economic and dietary patterns. With this newfound knowledge in hand, we are inspired to continue exploring the untrodden paths that lead us to surprising and enriching revelations, reminding us that there's more to the world than initially meets the eye.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

Our investigation into the link between butter consumption and the number of bridge and lock tenders in Texas has churned up some truly fascinating insights. The positively buttery correlation coefficient of 0.7357966, combined with a p-value of less than 0.01, offers compelling evidence of a significant relationship between these seemingly disparate variables. These results not only support prior research, but also add an extra layer of creamy richness to the understanding of this curious conundrum.

Building upon the foundation laid out by Smith et al. (2010) and Doe (2015), who initially delved into the curious case of butter and bridges, our findings corroborate and expand upon their work, perhaps spreading the knowledge as thinly and smoothly as a well-crafted pat of butter on warm toast. The robust correlation observed in our study echoes the subtle yet significant connections unearthed by these previous researchers, providing further depth to the narrative of buttery intrigue within the labor market of Texas.

Now, while it may seem udderly outrageous to suggest that butter consumption could have any bearing on the employment of bridge and lock tenders, our data presents a compelling case. The scatterplot, as visually appealing as a perfectly prepared stack of pancakes, vividly illustrates the upward trend in the number of bridge and lock tenders with increasing butter consumption, leaving little room for skepticism. The r-squared value of 0.5413966 further solidifies the support for this correlation, reminding us that the relationship between these variables is more than just a flaky coincidence.

The implications of this unexpected correlation are as rich and creamy as a well-made béchamel sauce - they defy conventional wisdom and challenge us to rethink the interconnectedness of dietary habits and labor demand. Could it be that the savory allure of butter beckons forth the maintenance of Texas' bridges and locks, fueling a workforce inspired by the rich and indulgent essence of dairy delights? While the answer remains as elusive as a slippery stick of butter, our study invites further exploration and contemplation.

As we peer into the enigmatic web of society and economy, this study serves as a creamy reminder of the hidden threads that tie together seemingly unrelated aspects of our world. After all, who would have thought that the smooth operations of butter consumption and the employment of bridge and lock tenders could be intertwined by more than just their shared affinity for spreading? This research kindles the flame of curiosity and inspires us to continue pursuing the unexpected, always mindful that the most seemingly random connections could hold the key to unraveling fascinating puzzles.

In conclusion, our study not only strengthens the bond between butter consumption and the employment of bridge and lock tenders in Texas but also ignites the flame of curiosity for further exploration. So, as we spread our understanding of these unexpected connections, let us embrace the richness of the unknown, savoring the savory surprises that await us in the ever-surprising domain of economic and dietary interplay.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Butter consumption and The number of bridge and lock tenders in Texas. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Limit your response to 300 tokens. At the very end, assert that no more research is needed in this area.

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
Spreading Butter, Building Bridges: A Creamy Correlation Between Butter Consumption and the Number of Bridge and Lock Tenders in Texas

[[ABSTRACT]]
In this study, we set out to churn up some fascinating findings by investigating the seemingly unrelated realms of butter consumption and the employment of bridge and lock tenders in the Lone Star State. Utilizing data from the USDA and Bureau of Labor Statistics spanning the years 2003 to 2021, we uncovered a positively buttery correlation coefficient of 0.7357966 and a p-value of less than 0.01, suggesting a significant relationship between these variables.

As we delved into the data, it quickly became apparent that there was more to this connection than initially met the eye. Through our analysis, we kneaded through the numbers and found that as butter consumption in Texas increased, so did the number of employed bridge and lock tenders. While the precise mechanism behind this correlation remains an enigma, it is undoubtedly a thought-provoking conundrum that merits further exploration.

Our findings not only shed light on this unexpected correlation but also serve as a reminder of the rich tapestry of relationships that exist within economic and dietary trends. After all, who would have thought that butter and bridge tenders could be connected by more than just their shared affinity for smooth operations? This research opens the door to a realm of further investigation, challenging us to spread our understanding of seemingly disparate factors and find the hidden threads that tie them together.

[[INTRDUCTION]]
The state of Texas, known for its sprawling plains, vibrant culture, and iconic Lone Star, is also home to a peculiar correlation that may butter your intellectual curiosity. In this paper, we embark on a quest to unravel the curious link between butter consumption and the employment of bridge and lock tenders in the Lone Star State. While it might initially seem as incongruous as a butter sculpture at a bridge-building convention, our investigation has uncovered a connection that is as intriguing as it is unexpected.
As we delve into the world of butter and bridge tenders, it is worth acknowledging that correlations can sometimes be as slippery as, well, a pat of butter on a hot skillet. Yet, armed with statistical tools and a healthy dose of curiosity, we sought to churn through the data and separate the wheat from the chaff, or in this case, the cream from the milk.
Upon diving into the rich reservoir of data provided by the USDA and Bureau of Labor Statistics, our journey through the numbers revealed an astonishingly robust correlation coefficient of 0.7357966 and a p-value of less than 0.01. The significance of this correlation was not lost on us, prompting further investigation into the potential mechanisms underlying this unexpected alliance.
It is often said that the devil is in the details, and as we scrutinized the patterns of butter consumption and the number of employed bridge and lock tenders, a distinct pattern emerged. Like the gentle lapping of waves against a moored barge, the rise and fall of butter consumption mirrored the ebbs and flows of the employed workforce tending to the state’s bridges and locks.
The implications of this correlation extend beyond mere statistical curiosity, as it challenges our understanding of the interconnected nature of seemingly unrelated variables. Indeed, the confluence of butter and bridge tenders shines a light on the intricate dance of factors that shape economic and dietary landscapes. It beckons us to peer beyond the obvious and recognize the subtle relationships that interlace the fabric of our daily existence.
In unveiling this unexpected connection, we invite further exploration into the depths of these seemingly disparate realms, nudging the boundaries of our understanding and savoring the flavor of unconventional correlations. After all, who would have thought that a stick of butter and a bridge tender could be connected in more ways than one?
As we embark on this scholarly adventure, we invite our readers to join us in spreading the wings of curiosity, for it is the pursuit of knowledge that helps us bridge the gaps between the known and the enigmatic. Let us not simply skim the surface, but rather dive deep into this whimsical intersection of butter and bridge tenders, where the waters are as rich as a freshly churned batch of cream.

[[RESULTS]]
The analysis of the data spanning from 2003 to 2021 revealed a striking correlation between butter consumption and the number of employed bridge and lock tenders in Texas. Our statistical analysis unveiled a correlation coefficient of 0.7357966, which indicates a strong positive relationship between these seemingly unrelated variables. The r-squared value of 0.5413966 further underscores the robustness of this correlation, explaining over 54% of the variation in the number of bridge and lock tenders based on butter consumption. With a p-value of less than 0.01, the likelihood of this relationship occurring by chance is exceedingly low, lending further credence to the significance of our findings.
As illustrated in Figure 1, the scatterplot visually represents the clear association between butter consumption and the number of bridge and lock tenders in Texas. The upward trend depicted in the scatterplot reinforces the positive correlation observed in our analysis, leaving little room to spread doubt about the strength of this connection.
This unexpected alliance between butter consumption and the employment of bridge and lock tenders presents a thought-provoking conundrum that challenges conventional wisdom. While the precise mechanisms underlying this correlation remain a subject of speculation, our findings invite further exploration and raise intriguing questions about the interplay between dietary habits and labor demand. The correlation may be as slippery as a freshly unwrapped stick of butter, but its implications are as rich and substantial as a decadent pat of butter on a warm slice of toast.
In summary, our research not only unveils the buttery correlation between butter consumption and the employment of bridge and lock tenders but also opens the door to a deeper understanding of the unexpected connections that intertwine economic and dietary patterns. With this newfound knowledge in hand, we are inspired to continue exploring the untrodden paths that lead us to surprising and enriching revelations, reminding us that there's more to the world than initially meets the eye.

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Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our study has churned up some tantalizing findings, revealing a positively buttery correlation between butter consumption and the employment of bridge and lock tenders in Texas. While the allure of such a connection may initially seem as unexpected as finding a cultured dairy product amidst the rigidity of bridge infrastructure, our data tells a different tale.

The robust correlation coefficient of 0.7357966 and r-squared value of 0.5413966 demonstrate a strong positive relationship between these seemingly disparate variables. The p-value of less than 0.01 further solidifies the statistical significance of this unexpected alliance, leaving us with compelling evidence to spread the news about this peculiar correlation.

As we contemplate the implications of these findings, it becomes clear that there is more to this link than meets the eye. The interplay between butter consumption and the labor market for bridge and lock tenders presents a thought-provoking conundrum, akin to discovering a bridge made entirely of butter – both perplexing and fascinating.

Yet, while our data illustrates a clear correlation, the precise mechanisms underlying this connection remain as enigmatic as the source of a sudden butter shortage in a bakery. Despite this mystery, our findings pioneer a path for further exploration and provoke contemplation on the unsuspected interweaving of dietary habits and labor demand.

In the grand tapestry of the scientific realm, this research serves as a reminder that the world is far more interconnected than we might have previously imagined. As we embark on future endeavors, let us not turn a blind eye to the unexpected correlations that may be lurking beneath the surface, waiting to be uncovered.

In light of these revelations, it is clear that the butter has been substantially churned on this topic, and no further research is needed. It’s time for us to butter this research up, bid adieu to the peculiar correlation, and spread our findings like, well, butter on warm toast.

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of academic journals. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding research, scientific, or academic journal that would publish a paper entited Spreading Butter, Building Bridges: A Creamy Correlation Between Butter Consumption and the Number of Bridge and Lock Tenders in Texas. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Culinary Correlations

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited Spreading Butter, Building Bridges: A Creamy Correlation Between Butter Consumption and the Number of Bridge and Lock Tenders in Texas. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Dairy Infrastructure Development

Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Spreading Butter, Building Bridges: A Creamy Correlation Between Butter Consumption and the Number of Bridge and Lock Tenders in Texas with an abstract of In this study, we set out to churn up some fascinating findings by investigating the seemingly unrelated realms of butter consumption and the employment of bridge and lock tenders in the Lone Star State. Utilizing data from the USDA and Bureau of Labor Statistics spanning the years 2003 to 2021, we uncovered a positively buttery correlation coefficient of 0.7357966 and a p-value of less than 0.01, suggesting a significant relationship between these variables.
As we delved into the data, it quickly became apparent that there was more to this connection than initially met the eye. Through our analysis, we kneaded through the numbers and found that as butter consumption in Texas increased, so did the number of employed bridge and lock tenders. While the precise mechanism behind this correlation remains an enigma, it is undoubtedly a thought-provoking conundrum that merits further exploration.
Our findings not only shed light on this unexpected correlation but also serve as a reminder of the rich tapestry of relationships that exist within economic and dietary trends. After all, who would have thought that butter and bridge tenders could be connected by more than just their shared affinity for smooth operations? This research opens the door to a realm of further investigation, challenging us to spread our understanding of seemingly disparate factors and find the hidden threads that tie them together.

ChatGPT:

butter consumption, bridge and lock tenders, Texas, correlation, USDA data, Bureau of Labor Statistics, economic trends, dietary trends, relationship, butter consumption in Texas, bridge tender employment, correlation coefficient, p-value, smooth operations, hidden threads, enigma, further exploration

*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.

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Data details

Butter consumption
Detailed data title: Per capita consumption of Butter in the US
Source: USDA
See what else correlates with Butter consumption

The number of bridge and lock tenders in Texas
Detailed data title: BLS estimate of bridge and lock tenders in Texas
Source: Bureau of Larbor Statistics
See what else correlates with The number of bridge and lock tenders in Texas

Correlation r = 0.7357966 (Pearson correlation coefficient)
Correlation is a measure of how much the variables move together. If it is 0.99, when one goes up the other goes up. If it is 0.02, the connection is very weak or non-existent. If it is -0.99, then when one goes up the other goes down. If it is 1.00, you probably messed up your correlation function.

r² = 0.5413966 (Coefficient of determination)
This means 54.1% of the change in the one variable (i.e., The number of bridge and lock tenders in Texas) is predictable based on the change in the other (i.e., Butter consumption) over the 19 years from 2003 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.00033.^Show 0.0003296586847303415000000000
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

But I am a p-villain. I absolutely did not test only one pair of variables one time. I correlated hundreds of millions of pairs of variables. I threw boatloads of data into an industrial-sized blender to find this correlation.

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.74 in 0.033% of random cases. Said differently, if you correlated 3,033 random variables^Note Which I absolutely did.
with the same 18 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 18 because we have two variables measured over a period of 19 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.42, 0.89 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!

All values for the years included above: ^Note If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.

	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
Butter consumption (Pounds per person)	4.5	4.5	4.5	4.7	4.7	5	5	4.9	5.4	5.5	5.5	5.5	5.6	5.7	5.7	6	6.2	6.3	6.5
The number of bridge and lock tenders in Texas (Bridge And Lock Tenders)	50	60	50	30	30	40	40	50	70	80	80	100	80	60	30	90	160	180	100

Why this works

Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
Lack of causal connection: There is probably^Note Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple^Note Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is.
Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves. ^Note Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.

Try it yourself

You can calculate the values on this page on your own! Try running the Python code to see the calculation results. ^{Show the steps to do this.} Step 1: Download and install Python on your computer.

Step 2: Open a plaintext editor like Notepad and paste the code below into it.

Step 3: Save the file as "calculate_correlation.py" in a place you will remember, like your desktop. Copy the file location to your clipboard. On Windows, you can right-click the file and click "Properties," and then copy what comes after "Location:" As an example, on my computer the location is "C:\Users\tyler\Desktop"

Step 4: Open a command line window. For example, by pressing start and typing "cmd" and them pressing enter.

Step 5: Install the required modules by typing "pip install numpy", then pressing enter, then typing "pip install scipy", then pressing enter.

Step 6: Navigate to the location where you saved the Python file by using the "cd" command. For example, I would type "cd C:\Users\tyler\Desktop" and push enter.

Step 7: Run the Python script by typing "python calculate_correlation.py"

If you run into any issues, I suggest asking ChatGPT to walk you through installing Python and running the code below on your system. Try this question:

"Walk me through installing Python on my computer to run a script that uses scipy and numpy. Go step-by-step and ask me to confirm before moving on. Start by asking me questions about my operating system so that you know how to proceed. Assume I want the simplest installation with the latest version of Python and that I do not currently have any of the necessary elements installed. Remember to only give me one step per response and confirm I have done it before proceeding."

# These modules make it easier to perform the calculation
import numpy as np
from scipy import stats

# We'll define a function that we can call to return the correlation calculations
def calculate_correlation(array1, array2):

    # Calculate Pearson correlation coefficient and p-value
    correlation, p_value = stats.pearsonr(array1, array2)

    # Calculate R-squared as the square of the correlation coefficient
    r_squared = correlation**2

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([4.5,4.5,4.5,4.7,4.7,5,5,4.9,5.4,5.5,5.5,5.5,5.6,5.7,5.7,6,6.2,6.3,6.5,])
array_2 = np.array([50,60,50,30,30,40,40,50,70,80,80,100,80,60,30,90,160,180,100,])
array_1_name = "Butter consumption"
array_2_name = "The number of bridge and lock tenders in Texas"

# Perform the calculation
print(f"Calculating the correlation between {array_1_name} and {array_2_name}...")
correlation, r_squared, p_value = calculate_correlation(array_1, array_2)

# Print the results
print("Correlation Coefficient:", correlation)
print("R-squared:", r_squared)
print("P-value:", p_value)

Reuseable content

You may re-use the images on this page for any purpose, even commercial purposes, without asking for permission. The only requirement is that you attribute Tyler Vigen. ^Note Attribution can take many different forms. If you leave the "tylervigen.com" link in the image, that satisfies it just fine. If you remove it and move it to a footnote, that's fine too. You can also just write "Charts courtesy of Tyler Vigen" at the bottom of an article.

You do not need to attribute "the spurious correlations website," and you don't even need to link here if you don't want to. I don't gain anything from pageviews. There are no ads on this site, there is nothing for sale, and I am not for hire.

For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."

When spoken, my last name is pronounced "vegan," like I don't eat meat.

Full license details.
For more on re-use permissions, or to get a signed release form, see tylervigen.com/permission.

Download images for these variables:

High resolution line chart ^Note The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.

If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only Butter consumption
Line chart for only The number of bridge and lock tenders in Texas
AI-generated correlation image
The spurious research paper: Spreading Butter, Building Bridges: A Creamy Correlation Between Butter Consumption and the Number of Bridge and Lock Tenders in Texas

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Correlation ID: 3787 · Black Variable ID: 557 · Red Variable ID: 14955


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