Langage pour bases multidimensionnelles : OLAP-SQL
Bibliographic record
Abstract
RESUME. Cet article presente un langage dedie aux bases de donnees decisionnelles implantees en relationnel OLAP. L'approche proposee permet de definir, de controler et de manipuler les donnees d'une base multidimensionnelle organisee en constellation. Ce langage repose sur l'extension multidimensionnelle du standard SQL. Le langage de definition permet de specifier simplement les composants (faits, dimensions, hierarchies) du schema multidimensionnel avec une abstraction complete des tables relationnelles. Le langage de controle permet de definir de maniere uniforme des droits sur tout ou partie du schema. Enfin, le langage de manipulation offre un mecanisme unique de consultation reposant sur l'extension de la commande SELECT. Notre langage OLAP-SQL fait l'objet d'un developpement base sur le SGBD Oracle 9i.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.007 |
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".