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Record W1552184229 · doi:10.7202/705327ar

La modélisation hydrologique et la gestion de l'eau

2005· article· fr· W1552184229 on OpenAlexaff
Jean‐Pierre Villeneuve, P. Hubert, Alain Mailhot, Alain N. Rousseau

Bibliographic record

VenueRevue des sciences de l eau · 2005
Typearticle
Languagefr
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsInstitut National de la Recherche ScientifiqueInstitut National d'Optique
Fundersnot available
KeywordsHumanitiesForestryPhilosophyGeography

Abstract

fetched live from OpenAlex

Cet article brosse un portrait de différents types de modélisation hydrologique développés à ce jour. Nous passerons donc en revue l'hydrologie, à l'érosion hydrique des sols, au transport et aux transformations des polluants et à la qualité de l'eau en rivière. Ce bref survol, nous amène à conclure que si le développement de la modélisation hydrologique s'est fait jusqu'ici essentiellement en affinant la description des processus et en considérant des échelles spatiales et temporelles plus fines, l'étape suivante passe par l'intégration de ces divers modèles. Cette intégration permettra dès lors de considérer un ensemble de problématiques directement liées aux aspects de gestion environnementale.

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 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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.147
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.004
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.042
GPT teacher head0.294
Teacher spread0.251 · 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 teacher head, not a consensus.

Study designSimulation or modeling
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

Citations7
Published2005
Admission routes1
Has abstractyes

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