Bibliographic record
Abstract
La perte de richesse liée au confinement forcé de la COVID-19 pour l’ensemble des Québécois se chiffrera à environ 100 milliards de dollars. Selon les données de la Center of Disease Control des États-Unis, le nombre de décès causés par la COVID-19 se serait chiffré à environ 47 000 au Québec si rien n’avait été fait pour endiguer la pandémie. Selon le modèle de l’Institut Pasteur en France, le nombre de décès se serait chiffré à environ 21 500. En fonction du modèle français ou des données américaines, la SAAQ aurait versé entre 2, 6 et 9, 0 milliards de dollars, respectivement, aux conjoints de ces victimes si elles étaient mortes d’un accident de la route plutôt que de la COVID-19. Les versements forfaitaires de la SAAQ sont trop faibles et devraient être augmentés par un facteur de 10 à 40.
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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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".