Obesity: The Fat Tissue Disease Version of Cancer
Bibliographic record
Abstract
Obesity is a disease with high potential for fatality. It perfectly fits the disease definition, as cancer does. This is because it damages body structure and functions, both mechanically and biologically, and alters physical, mental, and social health. In addition, it shares many common morbid characteristics with the most feared disease, cancer. For example, it is influenced by a sophisticated interaction between a person's genetics, the environment, and an increasing number of other backgrounds. Furthermore, it displays abnormal cell growth and proliferation events, only limited to white fat, resulting in adipose tissue taking up an increasing amount of space within the body. This occurs through fat "metastases" and via altered signaling that further aggravates the pathology of obesity by inducing ubiquitous dishomeostasis. These metastases can be made graver by angiogenesis, which might boost diseased tissue growth. More common features with cancer include its progressive escalation through different levels of severity and its possibility of re-onset after recovery. Despite all these similarities with cancer, obesity is substantially less agitating for most people. Thus, the ideas proposed herein could have utility to sensitize the public opinion about the hard reality of obesity. This is increasingly needed, as the obesity pandemic has waged a fierce war against our bodies and society in general, while there is still doubt about whether it is a real disease or not. Hence, raising public consciousness to properly face health issues is crucial to improving our health instead of gaining weight unhealthily. It is obviously illogical to fight cancer extremely seriously on the one hand and to consider dying with obesity as self-inflicted on the other. In fact, obesity merits a top position among the most lethal diseases besides cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".