Clinician's Corner: Mastering the Ottawa Ankle Rule: What is it?
Bibliographic record
Abstract
The Ottawa Ankle Rule (OAR) is a clinical decision-making tool to help guide clinicians’ decision to obtain an ankle radiograph (x-ray) to rule out a clinically significant ankle or foot fracture among patients who have suffered a blunt, traumatic injury (Stiell et al., 1992). The Ottawa Ankle Rule (OAR) carries a 100% sensitivity for ankle or foot fractures (Stiell et al., 1992) and has been validated for use in multiple studies (Sperry et al., 1999; Stiell et al., 1993). Subsequent studies have found that the OAR can be applied to children aged 2–16 years presenting to the emergency department (ED) with similarly high sensitivity (Plint et al., 1999).
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 | 0.014 | 0.136 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.008 | 0.016 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.020 | 0.025 |
| Insufficient payload (model declined to judge) | 0.014 | 0.012 |
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".