Nouvelles approches sigillographiques, les apports des bases de données
Bibliographic record
Abstract
Plusieurs répertoires numériques de sceaux se développent aujourd’hui à travers le monde. Ces nouveaux outils modifient en partie notre rapport à cette source jusqu’alors à la fois difficile d’accès, fragile et complexe à appréhender dans sa masse. En offrant la possibilité de répertorier, d’exposer et de décrire de façon ordonnée et ouverte des quantités considérables de sceaux, favorisant la formation et l’indexation collaborative et les échanges de données, ces nouveaux catalogues numériques invitent également à renouveler nos méthodes et suscitent de stimulantes questions et hypothèses de recherches. Mais ces outils ont leurs propres biais et limites que les projets numériques ne doivent pas ignorer pour conserver l’objectif initial de valoriser toujours plus et mieux cette source essentielle de l’histoire.
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 | 0.010 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.014 | 0.014 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.019 | 0.013 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.041 | 0.017 |
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".