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Spurious correlation #3,104 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Biomass power generated in Morocco and the second variable is The number of bailiffs in Maryland.  The chart goes from 2012 to 2021, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As the Biomass power in Morocco grew, it inadvertently sparked a surge in the energy industry. This reignited the passion for power in Maryland, leading to a shocking demand for bailiffs to help keep current flowing. It seems like the bailiffs in Maryland are just trying to branch out into a new field and establish some roots!

Model: dalle-3
Prompt: Generate an image of a futuristic landscape featuring colossal renewable energy towers set against a vibrant Moroccan backdrop. The towers, adorned with wind turbines and solar panels, dominate the scene as they harness the natural power of the environment. In Maryland, a group of eager and environmentally conscious bailiffs energetically serve legal notices and summonses, seemingly propelled by an unprecedented zeal and energy, stemming from the surplus renewable power generated in Morocco. 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: Biomass power generated in Morocco and The number of bailiffs in Maryland. 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: Cutsy graphics Futuristic Cutsy graphics Surrealism Art nouveau
ChatGPT: Futuristic

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 Biomass power generated in Morocco and The number of bailiffs in Maryland, in the following situation: The increase in biomass power generated in Morocco caused an increase in the number of bailiffs in Maryland because the surplus energy somehow manifested as an overwhelming urge for people to serve legal notices and summonses in a far-off land. It's like a modern-day version of the butterfly effect, except with tree-hugging bailiffs.. Keep the description simple.
ChatGPT: In a quirky and unexpected scene, massive fields of renewable energy towers stand tall in a colorful Moroccan landscape. As the wind turbines and solar panels harness the power of nature, a peculiar phenomenon unfolds on the other side of the globe. In Maryland, a group of environmentally conscious bailiffs eagerly rush around, serving legal notices and summonses with an unprecedented zeal, seemingly fueled by the surplus energy from far-off Morocco.

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: [ Futuristic ] and depicting this scene: In a quirky and unexpected scene, massive fields of renewable energy towers stand tall in a colorful Moroccan landscape. As the wind turbines and solar panels harness the power of nature, a peculiar phenomenon unfolds on the other side of the globe. In Maryland, a group of environmentally conscious bailiffs eagerly rush around, serving legal notices and summonses with an unprecedented zeal, seemingly fueled by the surplus energy from far-off Morocco. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a futuristic landscape featuring colossal renewable energy towers set against a vibrant Moroccan backdrop. The towers, adorned with wind turbines and solar panels, dominate the scene as they harness the natural power of the environment. In Maryland, a group of eager and environmentally conscious bailiffs energetically serve legal notices and summonses, seemingly propelled by an unprecedented zeal and energy, stemming from the surplus renewable power generated in Morocco.

*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.

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 Biomass power generated in Morocco caused The number of bailiffs in Maryland to increase. Include one good pun.

AI academic paper

(Because p < 0.01)
Biomass Power Blossoms, Bailiffs' Booms: Examining the Unlikely Link

The Journal of Energetic Ecology

Jan 2024

Reminder: This paper is AI-generated. Not real!
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 dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You write titles and abstracts of goofy academic research papers.
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, and add unexpected twists in your writing.

Please draft the title and abstract of an academic research paper presenting the findings of the connection between Biomass power generated in Morocco and The number of bailiffs in Maryland. Make lots of jokes, goofy observations, and puns.

Rhyme words in the title.

Your research team used data from Energy Information Administration and Bureau of Larbor Statistics to assess this nagging question. You found a correlation coefficient of 0.9907749 and p < 0.01 for 2012 to 2021.

Please respond in this format (replace "Lorem ipsum dolor sit" with your title and abstract)

[[TITLE]]
Lorem ipsum dolor sit

[[ABSTRACT]]
Lorem ipsum dolor sit



ChatGPT:
[[TITLE]]
Biomass Power Blossoms, Bailiffs' Booms: Examining the Unlikely Link

[[ABSTRACT]]
This research paper delves into the intriguing connection between the generation of biomass power in Morocco and the number of bailiffs in Maryland, a relationship that has remained largely unexplored until now. Using data from the Energy Information Administration and the Bureau of Labor Statistics, our research team conducted a comprehensive analysis covering the period from 2012 to 2021. The statistical analysis revealed a remarkably high correlation coefficient of 0.9907749, with a p-value less than 0.01, indicating a strong association between these seemingly unrelated variables. This unexpected correlation raises more questions than it answers, and prompts further investigation into the interplay of global energy trends and local legal enforcement dynamics. Our findings challenge conventional wisdom and highlight the delightful unpredictability of econometric relationships.


Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the introduction 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 introduction section of an academic research paper presenting the findings of the connection between Biomass power generated in Morocco and The number of bailiffs in Maryland. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Here is the title and abstract of the paper:
[[TITLE]]
Biomass Power Blossoms, Bailiffs' Booms: Examining the Unlikely Link

[[ABSTRACT]]
This research paper delves into the intriguing connection between the generation of biomass power in Morocco and the number of bailiffs in Maryland, a relationship that has remained largely unexplored until now. Using data from the Energy Information Administration and the Bureau of Labor Statistics, our research team conducted a comprehensive analysis covering the period from 2012 to 2021. The statistical analysis revealed a remarkably high correlation coefficient of 0.9907749, with a p-value less than 0.01, indicating a strong association between these seemingly unrelated variables. This unexpected correlation raises more questions than it answers, and prompts further investigation into the interplay of global energy trends and local legal enforcement dynamics. Our findings challenge conventional wisdom and highlight the delightful unpredictability of econometric relationships.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

The intersection of biomass power generation in Morocco and the quantity of bailiffs in Maryland seems like an unlikely pairing, akin to mixing peanut butter and pickles. However, delving into this unconventional relationship unveils surprising insights that would make even Sherlock Holmes do a double take. While one wouldn't expect a connection between the sizzling Sahara sun and the legal wrangling in the land of crab cakes, our research aims to shed light on this peculiar association.

Biomass power, derived from organic materials such as wood, crops, and animal waste, has been sprouting up like mushrooms after a summer rain, both in Morocco and around the world. Meanwhile, on the other side of the Atlantic, the number of bailiffs in Maryland has seen a curious uptick, reminiscent of a jack-in-the-box springing to life unexpectedly. This phenomenon has piqued the curiosity of researchers, policymakers, and armchair statisticians alike, prompting us to embark on this investigation.

In this paper, we present the findings of our comprehensive analysis, which spans the years 2012 to 2021. Our analysis hones in on the statistical relationship between the two variables, unravelling a correlation coefficient akin to the magnetic pull between two unlikely companions at a masquerade ball. The implications of this unexpected correlation transcend mere academic curiosity, peaking the interest of even the most stoic of scholars.

So, dear reader, buckle up and prepare for a rollercoaster ride through the tangled web of biomass power generation and bailiffs. This paper promises to captivate the mind and tickle the intellect, leaving you with a newfound appreciation for the delightful and confounding mysteries that lie within the realm of econometric relationships.


Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.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 Biomass power generated in Morocco and The number of bailiffs in Maryland. Make lots of 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 devolve ever further, and mention something completely ridiculous, like you conducted literature review by reading CVS receipts.

Here is the title and abstract of the paper:
[[TITLE]]
Biomass Power Blossoms, Bailiffs' Booms: Examining the Unlikely Link

[[ABSTRACT]]
This research paper delves into the intriguing connection between the generation of biomass power in Morocco and the number of bailiffs in Maryland, a relationship that has remained largely unexplored until now. Using data from the Energy Information Administration and the Bureau of Labor Statistics, our research team conducted a comprehensive analysis covering the period from 2012 to 2021. The statistical analysis revealed a remarkably high correlation coefficient of 0.9907749, with a p-value less than 0.01, indicating a strong association between these seemingly unrelated variables. This unexpected correlation raises more questions than it answers, and prompts further investigation into the interplay of global energy trends and local legal enforcement dynamics. Our findings challenge conventional wisdom and highlight the delightful unpredictability of econometric relationships.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The intersection of biomass power generation in Morocco and the quantity of bailiffs in Maryland seems like an unlikely pairing, akin to mixing peanut butter and pickles. However, delving into this unconventional relationship unveils surprising insights that would make even Sherlock Holmes do a double take. While one wouldn't expect a connection between the sizzling Sahara sun and the legal wrangling in the land of crab cakes, our research aims to shed light on this peculiar association.
Biomass power, derived from organic materials such as wood, crops, and animal waste, has been sprouting up like mushrooms after a summer rain, both in Morocco and around the world. Meanwhile, on the other side of the Atlantic, the number of bailiffs in Maryland has seen a curious uptick, reminiscent of a jack-in-the-box springing to life unexpectedly. This phenomenon has piqued the curiosity of researchers, policymakers, and armchair statisticians alike, prompting us to embark on this investigation.
In this paper, we present the findings of our comprehensive analysis, which spans the years 2012 to 2021. Our analysis hones in on the statistical relationship between the two variables, unravelling a correlation coefficient akin to the magnetic pull between two unlikely companions at a masquerade ball. The implications of this unexpected correlation transcend mere academic curiosity, peaking the interest of even the most stoic of scholars.
So, dear reader, buckle up and prepare for a rollercoaster ride through the tangled web of biomass power generation and bailiffs. This paper promises to captivate the mind and tickle the intellect, leaving you with a newfound appreciation for the delightful and confounding mysteries that lie within the realm of econometric relationships.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

Several seminal works have delved into the realm of biomass power and its implications for global energy dynamics. In "The Impact of Biomass Power on Sustainable Development," Smith and Doe explore the potential of biomass power to mitigate environmental degradation and foster economic development. Their findings underscore the multifaceted impact of biomass power generation, though unfortunately, they fail to uncover its unexpected association with the number of bailiffs in Maryland. In "Renewable Energy Policies and Technlogies in Africa," Jones presents a comprehensive overview of renewable energy initiatives in Africa, with a focus on the burgeoning biomass power sector in Morocco. While Jones provides valuable insights into the growth of biomass power in North Africa, the interconnectedness of this phenomenon with legal enforcement in the United States remains unexplored.

Turning to more general literature on energy and legal enforcement, "Energy Law in a Nutshell" by Black provides a succinct yet comprehensive overview of legal frameworks governing energy production and distribution. While insightful, this work neglects to explore the uncanny relationship between renewable energy sources in one corner of the globe and legal dynamics in a specific U.S. state. Furthermore, "Law and Disorder: The Legal System in Fiction" by White investigates the portrayal of legal professionals in literature, shedding light on the intersection of law and societal norms. This exploration of legal systems, albeit fictional, fails to anticipate the curious connection between distant energy initiatives and local legal mechanisms.

In the quest for insights into unconventional connections, the literature review journey took an unexpected turn, venturing into uncharted territories. Consulting a plethora of sources spanning from serious academic treatises to the most unexpected corners, including street signs, grocery lists, and even the ramblings of a particularly opinionated poodle, the research team left no stone unturned. Alas, those unconventional sources yielded no relevant information, but they did provide ample amusement and a newfound contemplation of the interconnectedness of all things. This whimsical journey further highlights the delightful unpredictability of research pursuits and the unexpected tangents it may entail.

Despite the dearth of direct evidence linking biomass power in Morocco to the number of bailiffs in Maryland, the literature review process has imparted a valuable lesson: sometimes, the most fruitful discoveries are made when one ventures into the most unanticipated and seemingly unrelated realms. This revelation serves as a poignant reminder to keep an open mind and an adventurous spirit when traversing the expanse of knowledge, for one never knows what delightful surprises may be unearthed amidst the scholarly pursuit.


Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.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 Biomass power generated in Morocco and The number of bailiffs in Maryland. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from Energy Information Administration and Bureau of Larbor Statistics . You used data from 2012 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]]
Biomass Power Blossoms, Bailiffs' Booms: Examining the Unlikely Link

[[ABSTRACT]]
This research paper delves into the intriguing connection between the generation of biomass power in Morocco and the number of bailiffs in Maryland, a relationship that has remained largely unexplored until now. Using data from the Energy Information Administration and the Bureau of Labor Statistics, our research team conducted a comprehensive analysis covering the period from 2012 to 2021. The statistical analysis revealed a remarkably high correlation coefficient of 0.9907749, with a p-value less than 0.01, indicating a strong association between these seemingly unrelated variables. This unexpected correlation raises more questions than it answers, and prompts further investigation into the interplay of global energy trends and local legal enforcement dynamics. Our findings challenge conventional wisdom and highlight the delightful unpredictability of econometric relationships.

[[INTRODUCTION]]
The intersection of biomass power generation in Morocco and the quantity of bailiffs in Maryland seems like an unlikely pairing, akin to mixing peanut butter and pickles. However, delving into this unconventional relationship unveils surprising insights that would make even Sherlock Holmes do a double take. While one wouldn't expect a connection between the sizzling Sahara sun and the legal wrangling in the land of crab cakes, our research aims to shed light on this peculiar association.
Biomass power, derived from organic materials such as wood, crops, and animal waste, has been sprouting up like mushrooms after a summer rain, both in Morocco and around the world. Meanwhile, on the other side of the Atlantic, the number of bailiffs in Maryland has seen a curious uptick, reminiscent of a jack-in-the-box springing to life unexpectedly. This phenomenon has piqued the curiosity of researchers, policymakers, and armchair statisticians alike, prompting us to embark on this investigation.
In this paper, we present the findings of our comprehensive analysis, which spans the years 2012 to 2021. Our analysis hones in on the statistical relationship between the two variables, unravelling a correlation coefficient akin to the magnetic pull between two unlikely companions at a masquerade ball. The implications of this unexpected correlation transcend mere academic curiosity, peaking the interest of even the most stoic of scholars.
So, dear reader, buckle up and prepare for a rollercoaster ride through the tangled web of biomass power generation and bailiffs. This paper promises to captivate the mind and tickle the intellect, leaving you with a newfound appreciation for the delightful and confounding mysteries that lie within the realm of econometric relationships.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To investigate the perplexing correlation between biomass power generation in Morocco and the number of bailiffs in Maryland, our research team embarked on a rigorous journey through a maze of data analysis and statistical interrogation. The primary sources of data for this study were the Energy Information Administration (EIA) and the Bureau of Labor Statistics (BLS), where our intrepid researchers scoured through digital archives spanning the years 2012 to 2021, akin to explorers delving into ancient scrolls in search of hidden treasures.

The first step in our convoluted methodological approach involved wrangling the disparate data sets from the EIA and BLS, akin to orchestrating a harmonious cacophony of information, by using complex algorithms and statistical software. The dance of merging these datasets was akin to a tango between a gazelle and a penguin – an unexpected pairing that required grace and finesse. After this intricate entanglement, the combined dataset was poised for scrutiny, akin to a Sherlock Holmes mystery just waiting to be deciphered.

Next, the data underwent a series of stringent statistical tests and analyses, reminiscent of a demanding fitness regimen for numbers. The team deployed a battery of statistical tools, including correlation analysis, regression models, and perhaps a touch of magic, to unravel the clandestine relationship between biomass power generation in the sun-soaked lands of Morocco and the bustling world of bailiffs in Maryland.

The statistical analyses were then performed with painstaking precision, akin to a symphony conductor delicately guiding an orchestra through a complex opus. This meticulous process ensured that no stone was left unturned and no statistical anomaly escaped our keen gaze, leaving no room for error or oversight.

After the statistical dust had settled, the results were scrutinized with the skepticism of a connoisseur examining a dubious vintage. The correlation coefficient, akin to the entwined fates of two star-crossed lovers in the world of numbers, emerged with startling clarity, fueling our academic thrill and prompting celebratory air-punches from the research team.

The unexpected correlation coefficient of 0.9907749 emerged from the statistical cauldron, accompanied by a p-value less than 0.01, which raised eyebrows and sparked fervent discussions in the hallowed halls of academia. This tantalizing statistical revelation left the research team in a state of bemused astonishment, akin to stumbling upon a hidden truffle in a humble forest, eliciting a flurry of excitement and speculation.

In conclusion, the methodology employed in this study waded through the depths of data, navigated the labyrinth of statistics, and emerged with insights that challenge conventional wisdom and delight the academic palate. The findings presented in this paper stand as a testament to the joy of unraveling the unexpected connections that lay hidden in the tangled web of econometric relationships.


Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the results section of an academic research paper. You speak in the past tense (you found...).
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 results section of an academic research paper presenting the findings of the connection between Biomass power generated in Morocco and The number of bailiffs in Maryland. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from Energy Information Administration and Bureau of Larbor Statistics .

For the time period 2012 to 2021, you found a correlation 0.9907749, r-squared of 0.9816350, and p < 0.01.

One figure will be included. The figure (Fig. 1) is a scatterplot showing the strong correlation between the two variables. You don't need to specify where; I will add the figure.

Here is the title and abstract of the paper:
[[TITLE]]
Biomass Power Blossoms, Bailiffs' Booms: Examining the Unlikely Link

[[ABSTRACT]]
This research paper delves into the intriguing connection between the generation of biomass power in Morocco and the number of bailiffs in Maryland, a relationship that has remained largely unexplored until now. Using data from the Energy Information Administration and the Bureau of Labor Statistics, our research team conducted a comprehensive analysis covering the period from 2012 to 2021. The statistical analysis revealed a remarkably high correlation coefficient of 0.9907749, with a p-value less than 0.01, indicating a strong association between these seemingly unrelated variables. This unexpected correlation raises more questions than it answers, and prompts further investigation into the interplay of global energy trends and local legal enforcement dynamics. Our findings challenge conventional wisdom and highlight the delightful unpredictability of econometric relationships.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The intersection of biomass power generation in Morocco and the quantity of bailiffs in Maryland seems like an unlikely pairing, akin to mixing peanut butter and pickles. However, delving into this unconventional relationship unveils surprising insights that would make even Sherlock Holmes do a double take. While one wouldn't expect a connection between the sizzling Sahara sun and the legal wrangling in the land of crab cakes, our research aims to shed light on this peculiar association.
Biomass power, derived from organic materials such as wood, crops, and animal waste, has been sprouting up like mushrooms after a summer rain, both in Morocco and around the world. Meanwhile, on the other side of the Atlantic, the number of bailiffs in Maryland has seen a curious uptick, reminiscent of a jack-in-the-box springing to life unexpectedly. This phenomenon has piqued the curiosity of researchers, policymakers, and armchair statisticians alike, prompting us to embark on this investigation.
In this paper, we present the findings of our comprehensive analysis, which spans the years 2012 to 2021. Our analysis hones in on the statistical relationship between the two variables, unravelling a correlation coefficient akin to the magnetic pull between two unlikely companions at a masquerade ball. The implications of this unexpected correlation transcend mere academic curiosity, peaking the interest of even the most stoic of scholars.
So, dear reader, buckle up and prepare for a rollercoaster ride through the tangled web of biomass power generation and bailiffs. This paper promises to captivate the mind and tickle the intellect, leaving you with a newfound appreciation for the delightful and confounding mysteries that lie within the realm of econometric relationships.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The statistical analysis of the data collected from the Energy Information Administration and the Bureau of Labor Statistics during the period from 2012 to 2021 revealed a strikingly high correlation coefficient of 0.9907749 between biomass power generation in Morocco and the number of bailiffs in Maryland. The coefficient of determination (r-squared) was found to be 0.9816350, further underscoring the robust relationship between these seemingly incongruous variables. This correlation coefficient is so close to 1 that it's practically the statistical equivalent of being attached at the hip, like two peas in a pod, or better yet, like peanut butter and jelly.

The p-value, which was found to be less than 0.01, highlights the statistical significance of this correlation, offering strong evidence to support the unlikely connection between these two factors. It's as if the data were saying, "Pay attention, folks! This is not just a statistical fluke; there's something real and intriguing going on here."

Figure 1 presents the scatterplot depicting the compelling association between biomass power generation in Morocco and the number of bailiffs in Maryland. The scatterplot conveys a clear pattern of co-movement between the variables, akin to the synchronized dance moves of partners in a dynamic duo.

This unexpected correlation challenges traditional notions of causality and beckons researchers to delve deeper into the underlying mechanisms at play. It's like stumbling upon a secret garden in the world of econometric relationships, where the most unlikely pairings bloom and flourish. While this study may not unravel the full mystery, it certainly sets the stage for a captivating journey into the unexplored terrain of global energy dynamics and local legal landscapes.


Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.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 Biomass power generated in Morocco and The number of bailiffs in Maryland. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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]]
Biomass Power Blossoms, Bailiffs' Booms: Examining the Unlikely Link

[[ABSTRACT]]
This research paper delves into the intriguing connection between the generation of biomass power in Morocco and the number of bailiffs in Maryland, a relationship that has remained largely unexplored until now. Using data from the Energy Information Administration and the Bureau of Labor Statistics, our research team conducted a comprehensive analysis covering the period from 2012 to 2021. The statistical analysis revealed a remarkably high correlation coefficient of 0.9907749, with a p-value less than 0.01, indicating a strong association between these seemingly unrelated variables. This unexpected correlation raises more questions than it answers, and prompts further investigation into the interplay of global energy trends and local legal enforcement dynamics. Our findings challenge conventional wisdom and highlight the delightful unpredictability of econometric relationships.

[[LITERATURE REVIEW]]
Several seminal works have delved into the realm of biomass power and its implications for global energy dynamics. In "The Impact of Biomass Power on Sustainable Development," Smith and Doe explore the potential of biomass power to mitigate environmental degradation and foster economic development. Their findings underscore the multifaceted impact of biomass power generation, though unfortunately, they fail to uncover its unexpected association with the number of bailiffs in Maryland. In "Renewable Energy Policies and Technlogies in Africa," Jones presents a comprehensive overview of renewable energy initiatives in Africa, with a focus on the burgeoning biomass power sector in Morocco. While Jones provides valuable insights into the growth of biomass power in North Africa, the interconnectedness of this phenomenon with legal enforcement in the United States remains unexplored.
Turning to more general literature on energy and legal enforcement, "Energy Law in a Nutshell" by Black provides a succinct yet comprehensive overview of legal frameworks governing energy production and distribution. While insightful, this work neglects to explore the uncanny relationship between renewable energy sources in one corner of the globe and legal dynamics in a specific U.S. state. Furthermore, "Law and Disorder: The Legal System in Fiction" by White investigates the portrayal of legal professionals in literature, shedding light on the intersection of law and societal norms. This exploration of legal systems, albeit fictional, fails to anticipate the curious connection between distant energy initiatives and local legal mechanisms.
In the quest for insights into unconventional connections, the literature review journey took an unexpected turn, venturing into uncharted territories. Consulting a plethora of sources spanning from serious academic treatises to the most unexpected corners, including street signs, grocery lists, and even the ramblings of a particularly opinionated poodle, the research team left no stone unturned. Alas, those unconventional sources yielded no relevant information, but they did provide ample amusement and a newfound contemplation of the interconnectedness of all things. This whimsical journey further highlights the delightful unpredictability of research pursuits and the unexpected tangents it may entail.
Despite the dearth of direct evidence linking biomass power in Morocco to the number of bailiffs in Maryland, the literature review process has imparted a valuable lesson: sometimes, the most fruitful discoveries are made when one ventures into the most unanticipated and seemingly unrelated realms. This revelation serves as a poignant reminder to keep an open mind and an adventurous spirit when traversing the expanse of knowledge, for one never knows what delightful surprises may be unearthed amidst the scholarly pursuit.

[[RESULTS]]
The statistical analysis of the data collected from the Energy Information Administration and the Bureau of Labor Statistics during the period from 2012 to 2021 revealed a strikingly high correlation coefficient of 0.9907749 between biomass power generation in Morocco and the number of bailiffs in Maryland. The coefficient of determination (r-squared) was found to be 0.9816350, further underscoring the robust relationship between these seemingly incongruous variables. This correlation coefficient is so close to 1 that it's practically the statistical equivalent of being attached at the hip, like two peas in a pod, or better yet, like peanut butter and jelly.
The p-value, which was found to be less than 0.01, highlights the statistical significance of this correlation, offering strong evidence to support the unlikely connection between these two factors. It's as if the data were saying, "Pay attention, folks! This is not just a statistical fluke; there's something real and intriguing going on here."
Figure 1 presents the scatterplot depicting the compelling association between biomass power generation in Morocco and the number of bailiffs in Maryland. The scatterplot conveys a clear pattern of co-movement between the variables, akin to the synchronized dance moves of partners in a dynamic duo.
This unexpected correlation challenges traditional notions of causality and beckons researchers to delve deeper into the underlying mechanisms at play. It's like stumbling upon a secret garden in the world of econometric relationships, where the most unlikely pairings bloom and flourish. While this study may not unravel the full mystery, it certainly sets the stage for a captivating journey into the unexplored terrain of global energy dynamics and local legal landscapes.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The results of our analysis confirm and extend the prior research on biomass power generation and its surprising connection to the number of bailiffs in Maryland. The remarkable correlation coefficient of 0.9907749 is in line with the findings of Smith and Doe, who highlighted the multifaceted impact of biomass power in the realm of sustainable development. Our study not only reaffirms the influence of biomass power on environmental and economic dynamics but also unearths its unforeseen association with legal enforcement in a specific U.S. state. This fortuitous discovery underscores the need to broaden the scope of energy research to encompass diverse and unexpected interconnections.

Similarly, the comprehensive overview provided by Jones on renewable energy initiatives in Africa, with a spotlight on Morocco's burgeoning biomass power sector, laid the groundwork for our exploration. While Jones primarily focused on the regional implications of biomass power, our study extends the narrative by revealing its ripple effects across continents, transcending geographical boundaries to intersect with legal phenomena in the United States.

Furthermore, the uncanny relationship between renewable energy sources and legal dynamics resonates with the nuanced insights of Black, whose work on energy law underscores the intricate web of factors shaping energy production and distribution. By unearthing the surprising correlation between biomass power in Morocco and the number of bailiffs in Maryland, our research broadens the discourse on legal systems and their interconnectedness with international energy trends, offering a fresh perspective on the complex interplay of regulatory frameworks and transcontinental energy dynamics.

As for the unexpected turn into uncharted territories during the literature review, our journey was not in vain. To our delight, the unconventional sources we sought out, including street signs, grocery lists, and the musings of an opinionated poodle, may not have directly contributed to our findings, but they engendered a newfound contemplation of the interconnectedness of the world. This serendipitous revelation underscores the potential for unconventional sources to inspire and provoke new lines of inquiry, reinforcing the significance of venturing into unanticipated realms in scholarly pursuits.

In conclusion, our study has unveiled a fascinating link between biomass power in Morocco and the number of bailiffs in Maryland, underscoring the delightful unpredictability of research endeavors. This unexpected correlation challenges conventional wisdom and highlights the interconnected nature of seemingly disparate phenomena, urging scholars to embrace the unforeseen and embark on ventures into the unexplored terrain of empirical inquiry.


Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.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 Biomass power generated in Morocco and The number of bailiffs in Maryland. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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]]
Biomass Power Blossoms, Bailiffs' Booms: Examining the Unlikely Link

[[ABSTRACT]]
This research paper delves into the intriguing connection between the generation of biomass power in Morocco and the number of bailiffs in Maryland, a relationship that has remained largely unexplored until now. Using data from the Energy Information Administration and the Bureau of Labor Statistics, our research team conducted a comprehensive analysis covering the period from 2012 to 2021. The statistical analysis revealed a remarkably high correlation coefficient of 0.9907749, with a p-value less than 0.01, indicating a strong association between these seemingly unrelated variables. This unexpected correlation raises more questions than it answers, and prompts further investigation into the interplay of global energy trends and local legal enforcement dynamics. Our findings challenge conventional wisdom and highlight the delightful unpredictability of econometric relationships.

[[INTRDUCTION]]
The intersection of biomass power generation in Morocco and the quantity of bailiffs in Maryland seems like an unlikely pairing, akin to mixing peanut butter and pickles. However, delving into this unconventional relationship unveils surprising insights that would make even Sherlock Holmes do a double take. While one wouldn't expect a connection between the sizzling Sahara sun and the legal wrangling in the land of crab cakes, our research aims to shed light on this peculiar association.
Biomass power, derived from organic materials such as wood, crops, and animal waste, has been sprouting up like mushrooms after a summer rain, both in Morocco and around the world. Meanwhile, on the other side of the Atlantic, the number of bailiffs in Maryland has seen a curious uptick, reminiscent of a jack-in-the-box springing to life unexpectedly. This phenomenon has piqued the curiosity of researchers, policymakers, and armchair statisticians alike, prompting us to embark on this investigation.
In this paper, we present the findings of our comprehensive analysis, which spans the years 2012 to 2021. Our analysis hones in on the statistical relationship between the two variables, unravelling a correlation coefficient akin to the magnetic pull between two unlikely companions at a masquerade ball. The implications of this unexpected correlation transcend mere academic curiosity, peaking the interest of even the most stoic of scholars.
So, dear reader, buckle up and prepare for a rollercoaster ride through the tangled web of biomass power generation and bailiffs. This paper promises to captivate the mind and tickle the intellect, leaving you with a newfound appreciation for the delightful and confounding mysteries that lie within the realm of econometric relationships.

[[RESULTS]]
The statistical analysis of the data collected from the Energy Information Administration and the Bureau of Labor Statistics during the period from 2012 to 2021 revealed a strikingly high correlation coefficient of 0.9907749 between biomass power generation in Morocco and the number of bailiffs in Maryland. The coefficient of determination (r-squared) was found to be 0.9816350, further underscoring the robust relationship between these seemingly incongruous variables. This correlation coefficient is so close to 1 that it's practically the statistical equivalent of being attached at the hip, like two peas in a pod, or better yet, like peanut butter and jelly.
The p-value, which was found to be less than 0.01, highlights the statistical significance of this correlation, offering strong evidence to support the unlikely connection between these two factors. It's as if the data were saying, "Pay attention, folks! This is not just a statistical fluke; there's something real and intriguing going on here."
Figure 1 presents the scatterplot depicting the compelling association between biomass power generation in Morocco and the number of bailiffs in Maryland. The scatterplot conveys a clear pattern of co-movement between the variables, akin to the synchronized dance moves of partners in a dynamic duo.
This unexpected correlation challenges traditional notions of causality and beckons researchers to delve deeper into the underlying mechanisms at play. It's like stumbling upon a secret garden in the world of econometric relationships, where the most unlikely pairings bloom and flourish. While this study may not unravel the full mystery, it certainly sets the stage for a captivating journey into the unexplored terrain of global energy dynamics and local legal landscapes.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, the peculiarly robust correlation between biomass power generation in Morocco and the number of bailiffs in Maryland has left us feeling like we stumbled into a real-life episode of "Stranger Things." The statistical analysis has unequivocally substantiated this unexpected relationship, with a correlation coefficient that's as snug as a bug in a rug, or perhaps as snug as a peanut butter and jelly sandwich. We can't help but wonder if the Sun God Ra is sending some kind of cosmic message to the land of the free and the home of the brave through this unlikely liaison.

It appears that this statistical entanglement between sustainability and legal wrangling has implications beyond the realms of academia. The strong association between these disparate variables beckons for further investigation – perhaps even a multidisciplinary approach involving both environmental scientists and legal scholars to untangle this conundrum. The implications are anything but trivial; they could spark the next great Renaissance, or at the very least, a sci-fi comedy movie script.

The unexpected correlation discovered in this study serves as a reminder that the world of economics and energy dynamics is rife with surprises, much like a game of bingo where the numbers just keep defying expectations. We can't help but be amused by the delightful caprices of econometric relationships, which, like a mischievous jester, never fail to keep us on our toes.

Having shed light on this curious association, it is evident that further research in this area is not only unnecessary, but perhaps ill-advised. After all, some mysteries are best left unsolved, much like the enigma of why socks disappear in the laundry or why people willingly participate in karaoke. The charm lies in the inexplicable, and attempting to unravel it further may remove the gleeful mystique that surrounds this uncommon pairing of biomass power generation and bailiffs in Maryland.


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 Biomass Power Blossoms, Bailiffs' Booms: Examining the Unlikely Link. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Energetic Ecology


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 Biomass Power Blossoms, Bailiffs' Booms: Examining the Unlikely Link. Respond only with the name of a fictional organization.

ChatGPT:

The Association for Sustainable Energy Policies and Practices


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 Biomass Power Blossoms, Bailiffs' Booms: Examining the Unlikely Link with an abstract of This research paper delves into the intriguing connection between the generation of biomass power in Morocco and the number of bailiffs in Maryland, a relationship that has remained largely unexplored until now. Using data from the Energy Information Administration and the Bureau of Labor Statistics, our research team conducted a comprehensive analysis covering the period from 2012 to 2021. The statistical analysis revealed a remarkably high correlation coefficient of 0.9907749, with a p-value less than 0.01, indicating a strong association between these seemingly unrelated variables. This unexpected correlation raises more questions than it answers, and prompts further investigation into the interplay of global energy trends and local legal enforcement dynamics. Our findings challenge conventional wisdom and highlight the delightful unpredictability of econometric relationships.

ChatGPT:

Biomass power generation, Morocco, bailiffs, Maryland, Energy Information Administration, Bureau of Labor Statistics, correlation coefficient, statistical analysis, global energy trends, local legal enforcement dynamics, econometric relationships

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



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Data details

Biomass power generated in Morocco
Detailed data title: Total biomass power generated in Morocco in billion kWh
Source: Energy Information Administration
See what else correlates with Biomass power generated in Morocco

The number of bailiffs in Maryland
Detailed data title: BLS estimate of bailiffs in Maryland
Source: Bureau of Larbor Statistics
See what else correlates with The number of bailiffs in Maryland

Correlation r = 0.9907749 (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 = 0.9816350 (Coefficient of determination)
This means 98.2% of the change in the one variable (i.e., The number of bailiffs in Maryland) is predictable based on the change in the other (i.e., Biomass power generated in Morocco) over the 10 years from 2012 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 3.1E-8. 0.0000000313358863691364600000
The p-value is a measure of how probable it is that we would randomly find a result this extreme. 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 0.99 in 3.1E-6% of random cases. Said differently, if you correlated 31,912,293 random variables You don't actually need 31 million variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

p-value calculations are useful for understanding the probability of a result happening by chance. They are most useful when used to highlight the risk of a fluke outcome. For example, if you calculate a p-value of 0.30, the risk that the result is a fluke is high. It is good to know that! But there are lots of ways to get a p-value of less than 0.01, as evidenced by this project.

In this particular case, the values are so extreme as to be meaningless. That's why no one reports p-values with specificity after they drop below 0.01.

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 9 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 9 because we have two variables measured over a period of 10 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.

[ 0.96, 1 ] 95% correlation confidence interval (using the Fisher z-transformation)
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: 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.
2012201320142015201620172018201920202021
Biomass power generated in Morocco (Billion kWh)0.0050.0050.0054140.0054140.0110.040.040.040.040.04
The number of bailiffs in Maryland (Bailiffs)110150120130130580570540530510




Why this works

  1. 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.
  2. Lack of causal connection: There is probably 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.
  3. 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 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.




Try it yourself

You can calculate the values on this page on your own! Try running the Python code to see the calculation results. 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([0.005,0.005,0.005414,0.005414,0.011,0.04,0.04,0.04,0.04,0.04,])
array_2 = np.array([110,150,120,130,130,580,570,540,530,510,])
array_1_name = "Biomass power generated in Morocco"
array_2_name = "The number of bailiffs in Maryland"

# 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)



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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. 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.

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Correlation ID: 3104 · Black Variable ID: 23833 · Red Variable ID: 9188
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