Disorders of a modern lifestyle: reconciling the epidemiology of inflammatory bowel diseases
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Few would contest that advances in uncovering genetic risk factors for Crohn’s disease and ulcerative colitis over the past decade have changed the way we think about inflammatory bowel diseases (IBDs). Perhaps the most important message has been that much of the genetically determined risk lies in how the host interprets its microbial environment.1–3 However, the primacy of environmental factors was already evident from several sources; notably, studies of genetically identical twins showing a relatively low concordance rate for both Crohn’s disease (<50%) and ulcerative colitis (<10%), and the increased frequency of both disorders in many countries during a period too short to involve significant changes in the population gene pool.4 What are the environmental or lifestyle risk factors for IBD? How do they collude with genetic susceptibility? The lesson of Helicobacter pylori and peptic ulcer disease was that the solution to some chronic disorders cannot be found by studying the human host alone. Rather, the answer may lie at the interface with the microbial environment. A more sobering lesson was the failure of conventional epidemiological studies to recognise that peptic ulcer disease is caused by a transmissible agent. How did disparate epidemiological observations miss this association and fail to guide medical scientists toward this conclusion? Could IBDs (or a subset thereof) be due to an infectious agent, waiting to be identified? Or is the relationship between host susceptibility and the microbial environment a more subtle one? While the complexity and heterogeneity of these diseases surely accounts for some of this dilemma, it seems reasonable to ask whether several decades of epidemiological studies have directed or distracted researchers seeking clues to the cause of IBD. Some of the false leads and false promises of epidemiology have been highlighted elsewhere, with the most vigorous attacks in the …
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it