Passeur de textes : l’éditeur critique de textes anciens dans tous ses états!
Bibliographic record
Abstract
Le défi auquel est confronté l’éditeur critique de textes anciens est multiple : d’une part, il doit rendre lisible par un lecteur moderne des écrits qui sont tout, sauf transparents : ce qui suppose de lui une plongée dans le passé, tant du point de vue linguistique : langue profondément différente, voire devenue étrangère, sous l’aspect parfois familier des mots; référents matériels, et conceptions insolites. D’autre part, il doit les rapprocher au maximum de l’époque moderne, afin de mettre en relief ce qui, sous l’apparent changement, conserve un intérêt pour le lecteur moderne, et par là justifie son entreprise éditoriale elle-même. Cela, sans fausser outrageusement les choses. Orienter le lecteur, sans dénaturer le paysage…
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 | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.012 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".