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Record W2744101728 · doi:10.7202/1050491ar

Utilisation des services écosystémiques pour la définition de seuils de rejets des eaux usées industrielles. Vers un outil d’aide à la décision pour les entreprises.

2018· article· fr· W2744101728 on OpenAlexvenueno aff
Valérie Laforest, Sophie Grazilhon, Eric Piatyszek

Bibliographic record

VenueEnvironnement urbain · 2018
Typearticle
Languagefr
FieldEnvironmental Science
TopicLand Use and Ecosystem Services
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesGeographyArt

Abstract

fetched live from OpenAlex

Cet article s’intéresse à l’utilisation des principes de gestion de la qualité prescrits par l’ISO 9000, à la gestion des effluents industriels, avec comme clients potentiels notamment les écosystèmes récepteurs. La prise en compte des écosystèmes comme clients soulève la question de l’évaluation de leurs besoins. Le territoire est alors considéré par le biais des services écosystémiques afin d’identifier des cibles humaines aptes à exprimer leurs besoins afin d’en tirer des exigences vis-à-vis du milieu qui sont ensuite converties en exigences qualitatives vis-à-vis des rejets. Cette démarche a été matérialisée sous la forme d’un outil destiné aux industriels.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.295
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0090.002

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 head0.028
GPT teacher head0.235
Teacher spread0.208 · 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; both teacher heads agree on what is shown here.

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
Published2018
Admission routes1
Has abstractyes

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