Bibliographic record
Abstract
Les schémas de classification encyclopédiques qui servent encore à l’organisation intellectuelle et physique des ressources documentaires dans nos bibliothèques, et de plus en plus fréquemment sur Internet, sont maintenant plus que centenaires. Sans être les dinosaures que d’aucuns se plaisent à décrire, ces systèmes sont néanmoins marqués de rides profondes qu’un épais maquillage technologique n’arrive pas toujours à masquer. Dans cet article, nous décrirons les efforts d’amélioration de la performance de ces schémas d’organisation des disciplines et des sujets, efforts qui s’actualisent dans des projets de recherche et développement portant sur les contenus et les structures, ainsi que sur les interfaces qui permettent au chercheur d’information de mieux profiter des avantages offerts par la structuration hiérarchique. Nous aborderons principalement les travaux qui s’effectuent présentement sur la Classification décimale Dewey (CDD) et sur la Classification de la Library of Congress, mais nous toucherons aussi la Classification décimale universelle (CDU) ainsi que la classification à facette de Ranganathan.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.021 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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; both teacher heads agree on what is shown here.
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".