Search strategies on overall assessment of Canadian senior citizens’ oral health / Stratégies de recherche sur le portrait global de la santé buccodentaire chez les personnes âgées au Canada.
Bibliographic record
Abstract
Ce jeu de données contient les stratégies de recherche pour Medline All (Ovid), Web of Science Core Collection (ESCI, SCIe) et dans la littérature grise. Quand on les exécute dans leurs bases de données respectives, ces stratégies repêchent les articles sur les concepts de la santé buccodentaire, les personnes âgées et le Canada. Le nombre de résultats et les stratégies de recherche pour chaque base de données sont indiqués dans le fichier rtf. Les recherches ont été effectuées le 28 avril 2025 et mises à jour le 22 mai 2025. / This dataset contains search strategies for MEDLINE All (Ovid), Web of Science Core Collection (ESCI, SCIe) and the gray literature. When run in their respective databases, these strategies retrieve articles on the concepts of oral health, elderly and Canada. The number of results and search strategies for each database are indicated in the rtf file. The searches were conducted on April 28, 2025 and updated on May 22, 2025.
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 | 0.048 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.042 | 0.053 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.061 | 0.013 |
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".