Un appel au Centre antipoison du Québec : l’évaluation initiale de la personne intoxiquée à l’urgence
Bibliographic record
Abstract
Dans le cadre de leur travail, les infirmières qui pratiquent dans les urgences du Québec effectuent régulièrement des appels au centre antipoison du Québec (CAPQ) afin d’être guidées dans l’évaluation des personnes intoxiquées. Ces situations peuvent rapidement devenir complexes considérant les nombreuses substances potentiellement en cause, l’absence d’histoire claire et parfois même l’état critique de la personne. Lors de ces situations souvent déstabilisantes, il est important que l’infirmière d’urgence puisse identifier rapidement dans sa collecte de données les informations nécessaires qui seront utiles à communiquer avec l’infirmière du CAPQ. En ce sens, cet article vise à expliquer les différents éléments de la collecte de données en toxicologie et se veut un guide pour bien préparer l’infirmière d’urgence avant son appel au CAPQ.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".