Les princes angevins du XIIIe au XVe siècle
Bibliographic record
Abstract
Ont contribué à cet ouvrageJean-Paul BOYER, Université de ProvenceHenri BRESC, Université de Paris X-NanterreCaroline BRUZELIUS, Duke UniversityMarie-Madeleine DE CEVINS, Université d'AngersPhilippe CONTAMINE, Université de Paris IV, Institut de FranceGiuseppe GALASSO, Université Frédéric II de NaplesPatrick GILLI, Université de Montpellier III, Institut universitaire de FranceMichel HÉBERT, Université du Québec à MontréalNeven BUDAK, Miljenko JURKOVIC, Université de ZagrebHalina MANIKOWSKA, Université de VarsovieChristian DE MÉRINDOL, Conservateur honoraire des Musées nationauxChristof OHNESORGE, Université de MarburgSylvie POLLASTRI, Docteur en histoireFrançoise ROBIN, Université de Montpellier III
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.023 | 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".