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Record W4400349322 · doi:10.4000/11ydz

Caractérisation de la consommation domestique d’eau potable dans le temps et dans l’espace (Gironde, France)

2024· article· fr· W4400349322 on OpenAlexvenueno aff
Sandrine Gombert-Courvoisier, Bénédicte Rulleau, Patrick Eisenbeis

Bibliographic record

VenueVertigO · 2024
Typearticle
Languagefr
FieldSocial Sciences
TopicWater Governance and Infrastructure
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

En France, l'usage domestique représente 70 à 80 % des consommations d’eau potable. La référence de 120 m3 par abonné par an ne tient compte ni de la répartition entre les usages à domicile ni de leur distribution spatiale et temporelle. Une enquête auprès de 1 026 Girondins visant à caractériser la consommation domestique d'eau potable a été réalisée et le volume d'eau par usage a été estimé. Les résultats montrent que ces consommations sont peu déportées sur d’autres lieux (travail, loisirs) ou d’autres territoires. Comparées aux résultats du CIEau, les parts concernant l'hygiène corporelle et l’arrosage sont plus élevées, à l’inverse des usages pour le linge, la vaisselle ou l'alimentation, ce qui peut être expliqué par des différences d'hypothèses (temps de présence, débits, durées, et cetera). Dans le cadre de la gestion de la ressource en eau, cette actualisation des consommations domestiques par type d’usage devrait permettre d’orienter les économies d'eau de façon plus efficace.

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 score0.230
Threshold uncertainty score0.458

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.006
GPT teacher head0.262
Teacher spread0.256 · 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
Published2024
Admission routes1
Has abstractyes

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Same venueVertigOSame topicWater Governance and InfrastructureFrench-language works237,207