Méthode et application de la documentation des oeuvres mixtes en vue de leur préservation et de leur diffusion
Bibliographic record
Abstract
Documentation, dissémination et préservation sont trois notions intimement reliées dans le contexte de la production des oeuvres mixtes. Le projet décrit dans cet article articule ces notions sur la base de l’état de l’art de la recherche empirique. Basé sur la capture de l’expertise des différents acteurs des processus créatifs et sur la mise en forme des données et des métadonnées au travers des standards de préservation, le projet vise à concevoir un cadre méthodique transférable à différents contextes de production. Dans cet article, nous spécifions les différentes étapes et enjeux pour parvenir à établir ce cadre méthodique afin de pouvoir proposer aux professionnels de la documentation des stratégies qui minimisent le caractère intrusif du processus de documentation et permettent d’établir un cercle vertueux pour la dissémination du répertoire.
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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 | 0.013 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 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".