Éléments méthodologiques pour un traitement factuel des documents administratifs et juridiques
Bibliographic record
Abstract
Le travail décrit ici vise à permettre une exploitation factuelle de documents de type administratif ou juridique. Par exploitation factuelle il faut entendre la création d’une base de données qui permette une prise en compte précise des faits et non une simple description du contenu des documents. Diverses expérimentations ont été entreprises. Elles ont abouti à une solution satisfaisante prenant la forme d’éléments méthodologiques pour la mise en place de telles applications et d’une définition des contraintes à respecter (fourniture du texte intégral, existence de moyens d’accès différenciés à l’information, fourniture d’une description de la structure de la base de données sous la forme, par exemple, d’une classification, apparition de la dimension analytique de ce type de base de données).
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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 | 0.014 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.012 | 0.008 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.005 |
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".