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Record W3011497240 · doi:10.7202/1067957ar

Repenser les sources de l’histoire environnementale grâce aux outils numériques : le cas de la vallée de l’Escaut (France)

2020· article· fr· W3011497240 on OpenAlex
Matthieu Deltombe, Laëtitia Deudon

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCahiers d histoire · 2020
Typearticle
Languagefr
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.771
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0090.005
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.030
GPT teacher head0.222
Teacher spread0.192 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it