Bibliographic record
Abstract
En mars 2020, quand la pandemie de COVID-19 nous a pour ainsi dire assignes a residence, les rangees et les vitrines des detaillants se sont videes. Si, comme commercant, vous aviez la malchance de vendre des produits non essentiels, votre magasin (s’il etait ouvert) ne recevait la visite d’aucun client. Mais votre site transactionnel, lui, roulait a fond. Les contraintes auxquelles certaines regions sont toujours soumises a l’heure actuelle ont cree un choc dans le secteur du commerce de detail, qui emploie plus de 400 000 personnes au Quebec.Alternate abstract:In March 2020, when the COVID-19 pandemic put us under house arrest, the rows and storefronts of retailers emptied. If, as a merchant, you were unlucky to sell non-essential products, your store (if it was open) was not visited by any customers. But your transactional site was running at full speed. The constraints that some regions are still subject to today have created a shock in the retail sector, which employs more than 400,000 people in Quebec.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.029 | 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".