Comparaison du maintien du rythme sinusal au contrôle de la fréquence ventriculaire chez les patients avec fibrillation auriculaire
Bibliographic record
Abstract
Patients : Les patients admissibles devaient avoir presente un episode de FA d’une duree d’au moins 1 heure dans les 12 semaines precedant la randomisation, totaliser 6 heures ou plus d’episodes de FA dans les 6 derniers mois et avoir au moins un facteur de risque additionnel d’AVC ou de deces. Ces facteurs de risque etaient un âge de 65 ans ou plus, l’hypertension, le diabete, l’insuffisance cardiaque congestive (IC), un antecedent d’accident ischemique transitoire ou d’AVC, une oreillette gauche de dimension superieure ou egale a 50 mm, une fraction d’ejection ventriculaire gauche inferieure a 40 % et une fraction de raccourcissement inferieure a 25 %. Lors de FA chronique, la duree de celle-ci devait etre inferieure a 6 mois, a moins que le rythme sinusal ait pu etre retabli et maintenu pendant au moins 24 heures. De plus, la FA devait etre jugee, par le chercheur, probablement recurrente, susceptible de causer de la morbidite ou le deces et necessiter un traitement a long terme. L’anticoagulation ne devait pas etre contre-indiquee et les patients devaient etre admissibles aux deux strategies de traitement. Interventions :
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".