Repenser les sources de l’histoire environnementale grâce aux outils numériques : le cas de la vallée de l’Escaut (France)
Bibliographic record
Abstract
Face à la multiplication des données historiques, le recours aux outils numériques est devenu indispensable aux historiens et professionnels du patrimoine. Ces supports technologiques donnent une nouvelle lecture aux sources pour visualiser, clarifier et diffuser l’information historique. À travers l’exemple de la vallée de l’Escaut (Hauts-de-France), il s’agit ici de présenter ces outils numériques permettant de revisiter l’étude des sources historiques dans une perspective d’histoire environnementale, en adoptant une démarche à la fois scientifique, pédagogique et de valorisation. L’enjeu est de montrer l’apport de ces supports méthodologiques pour reconstituer les évolutions historiques des espaces fluviaux du Moyen Âge à l’époque contemporaine afin d’éclairer les acteurs actuels du territoire.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".