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Record W4214936379 · doi:10.4000/vertigo.34420

Historique des crues et risque d’inondation dans la vallée de la Meurthe depuis le XVIIIe siècle

2021· article· fr· W4214936379 on OpenAlexvenueno aff
Claire Delus, Éric Bonnot, Didier François, Thomas Lejeune, Xavier Rochel, Denis Mathis, Jean Abèle

Bibliographic record

VenueVertigO · 2021
Typearticle
Languagefr
FieldAgricultural and Biological Sciences
TopicSoil erosion and sediment transport
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

La connaissance des événements passés constitue désormais un des fondements de la gestion des risques naturels. Ce travail présente les résultats d’une étude historique des crues, réalisée dans le cadre de l’élaboration d’un Programme d’Action et de Prévention des Inondations (PAPI) de la rivière française de la Meurthe. Une reconstitution des hauteurs d’eau observées depuis le début du XIXe siècle a été réalisée grâce à un travail de collecte et d’analyse d’archives hydrométriques. Les sources documentaires ont permis de compléter l’inventaire des événements et d’étendre la chronologie aux trois derniers siècles. Les résultats de ces travaux constituent ainsi une base d’analyse de l’évolution de l’aléa et donc du risque inondation sur le territoire d’étude, mais soulignent aussi la difficulté à déterminer les facteurs de la variabilité des extrêmes hydrologiques. Dans la mesure où l’étude des crues historiques constitue désormais un préalable réglementaire dans les dossiers d’élaboration des PAPI, ce type d’étude est amené à se généraliser sur de nombreux cours d’eau.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.130
Threshold uncertainty score0.259

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.016
GPT teacher head0.237
Teacher spread0.221 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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Same venueVertigOSame topicSoil erosion and sediment transportFrench-language works237,207