Bibliographic record
Abstract
The inflammatory bowel diseases (IBD) are believed to be environmentally driven diseases occurring in genetically susceptible individuals.1 With the advent of genome-wide association studies, over 200 susceptibility loci for IBD have been identified.2 Gene mutation studies suggest that the pathogenesis of Crohn's disease and ulcerative colitis results from an abnormal interaction between the gut's immune system and the intestinal microbiome.3 Epidemiologic studies have shown that the incidence of IBD in the Western world rose rapidly throughout the 20th century.4 In contrast, IBD was relatively rare in developing countries in the 20th century.4 However, at the start of the 21st century, newly industrialized countries in Asia, the Middle East, and South America have documented a rising incidence of IBD.5 These epidemiologic patterns imply that IBD emerges—and its incidence accelerates—as societies become similar to Western countries in such things like diet, sanitization, agriculture, manufacturing, pollution, transportation, and urbanization.6 Numerous studies have explored environmental risk factors of IBD associated with Westernization,7,8 unfortunately, few environmental determinates have been consistently demonstrated to modulate the occurrence of Crohn's disease and ulcerative colitis.9
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.015 | 0.006 |
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 source (direct Gemma or distilled Codex), 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".