Provisions provinciales et territoriales des ventes au détail de boissons alcoolisées, exercices financiers se terminant le 31 mars
Bibliographic record
Abstract
Ce tableau contient 99 seriés, avec des données pour les années 1997 - 2013 (il n'y a pas nécessairement de données pour toutes les années pour l'ensemble des combinaisons), et sa dernière date de diffusion remonte au 2015-05-04. Ce tableau contient des données telles que décrites par les dimensions suivantes (les combinaisons ne sont pas toutes disponibles): Géographie (15 éléments: Canada;Nouvelle-Écosse;Terre-Neuve-et-Labrador;Île-du-Prince-Édouard ...), Valeur, volume, nombre (3 éléments: Valeur en dollars;Volume en litres;Nombre d'établissements ...), Type de vendeur (5 éléments: Total magasins des alcools et agences;Les agences;Producteurs de vin;Magasins des alcools ...).
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Dataset About the Canadian research system: no · About a Canadian topic: yes | Not applicable | high |
| gpt | no category Domain: not available · Genre: Dataset About the Canadian research system: no · About a Canadian topic: yes | Not applicable | high |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".