Documents semi-structurés et métadonnées. Contribution à la réingénierie de collections de documents
Bibliographic record
Abstract
Considerant un document multimedia comme semi-structure (a structure irreguliere, inconnue a priori, pouvant eventuellement etre « partiellement » elicitee), nous proposons de formaliser les differentes caracteristiques extraites a partir de l'analyse des contenus sous forme de metadonnees. Ces metadonnees sont structurees en « metadocuments » qui viendront enrichir la description des documents initiaux. L'objectif est de (re)construire de facon dynamique des documents repondant aux besoins des utilisateurs. Afin d'assurer homogeneite et coherence globale dans la reingenierie de telles collections de document, nous avons decide de travailler sur la base d'une methodologie de conception d'applications hypermedias, OOHDM. Notre proposition a ce niveau consiste a etendre cette methodologie par l'integration des metadonnees dans les differentes etapes, a savoir: la conception des applications, des schemas, des contextes de navigation, et de l'interface. Les metadonnees, considerees comme toute autre donnee du document, doivent pouvoir etre affichees et utilisees lors de l'interrogation des documents.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; a candidate call from one teacher head, 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".