Bibliographic record
Abstract
Crohn's disease (CD) has conventionally been considered an autoimmune disease with a genetic predisposition. However, recent advances in clinical and fundamental research have challenged this classification, pointing instead to a state of impaired innate immunity to microbial exposures. 1,2 The epidemiologic observation that Crohn's rates are increasing in many parts of the world is also consistent with an infectious disease. As such, modeling rates of CD against putative determinants may help to predict the kinds of exposures associated with the increasing burden of disease. Because CD is not a reportable disease, until recently, data on CD occurrence were limited. An important first step to address this has recently been realized, with the publication of the first global atlas of Crohn's rates.3 As it is well recognized that CD is more common in industrialized countries, we plotted the incidence of CD in 27 countries on the Y-axis against each country's per capita gross domestic product (GDP) for 2005, reported by the United Nations (www.unstats.un.org). There is a positive association (Fig. 1A), with higher rates of CD in countries with higher productivity. Nonetheless, assuming a linear trend, the R2 so generated is only 0.27, pointing to other determinants of CD incidence. Plotting CD against age-standardized cardiovascular mortality (www.who.int/infobase), a proxy for a Western diet, resulted in a weaker association (data not shown). We then explored the possible association between incidence of CD and antimycobacterial immunity, based on the hypothesis that a mycobacterial infection may have a role in the etiology of CD.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".