Bibliographic record
Abstract
In clinical studies, the relative likelihood of an event occurring between 2 groups is often expressed as the risk ratio (RR) or the odds ratio (OR). The RR is an intuitive parameter that is relatively easy to interpret. Quantitative interpretation of an OR is much more difficult and is often incorrectly equated to that of an RR. The problem is that OR may differ substantially from RR, especially when the outcome of interest is common in the study population. This article explains and clarifies controversial issues surrounding the use and interpretation of the OR. Theoretical concepts relating to ORs are illustrated by examples from the surgical literature. By reviewing articles from 5 surgical journals over a 5-year period, we show that the OR is often presented and misinterpreted as equivalent to the RR. When the discrepancy is large, using OR uncritically as an estimate of RR will strongly bias inferences about treatment effect or cause of disease by amplifying the apparent strength of an association between an exposure and an outcome.
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 | 0.069 | 0.375 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.003 | 0.028 |
| Scholarly communication | 0.012 | 0.029 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.007 | 0.013 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".