Cartographier le cheminement, dans le système de soins, des patients atteints de cancer. Partie 1: Élaboration de la question de recherche
Bibliographic record
Abstract
Il s’agit du premier article d’une série rapportant les résultats detravaux de recherche qui élaboraient, à partir des sources de données disponibles, un historique complet des interactions avec le système de santé de tous les patients diagnostiqués en 1990, au Manitoba, de tumeurs primitives mammaires, colorectales ou pulmonaires et ce, à partir d’un an avant le diagnostic jusqu’à deux ans après ce dernier. Cet article présente la motivation derrière cet axe de recherche ainsi que sa genèse. L’étude qui avait pour point de départ la question “Qu’est-ce qui arrive à la personne diagnostiquée d’un cancer?” s’est transformée en une initiative de recherche majeure englobant un large éventail de questions de recherche philosophiques et cliniques. Une équipe interdisciplinaire a élaboré en collaboration les méthodes opérationnelles permettant de combiner des sources de données existantes afin de présenter sous un format uniforme les antécédents des patients atteints de cancer.
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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.014 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".