Comparison between two methods for evaluation of the clinical probability of pulmonary embolism in emergency department (implicit clinical judgment versus two clinical prediction rules)
Bibliographic record
Abstract
[Résumé en français]Comparaison dans un service d'urgence de l'évaluation de la probabilité clinique d'embolie pulmonaire (EP) par trois méthodes différentes : empirique, score de Genève et score Canadien. Inclusion des patients suspects d'EP (135 patients). Stratégie diagnostique de l'EP validée appliquée à tous les patients après évaluation de la probabilité clinique. La méthode empirique répartit de façon plus équilibrée les probabilités cliniques d'EP (faible, intermédiaire et forte). La prévalence globale de la maladie dans notre population est de 16,29%. La prévalence d'EP dans chacun des sous-groupes définis par le strois méthodes est également plus équilibrée lorsque la probabilité clinique est évaluée empiriquement. Globalement, la performance de l'évaluation empirique de la probabilité clinique d'EP établie par une courbe ROC est supérieure à l'évaluation par score. La méthode empirique reste la meilleure pour évaluer la probabilité clinique pré-test d'EP
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 | 0.032 | 0.112 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".