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Record W7083693068 · doi:10.5683/sp3/gjjle2

État des lacs de Saint-Hippolyte et de Prévost (2001-2002) | Condition of the Lakes in Saint-Hippolyte and Prévost (2001-2002)

2025· dataset· fr· W7083693068 on OpenAlexaff

Bibliographic record

VenueBorealis · 2025
Typedataset
Languagefr
FieldSocial Sciences
TopicTurkey's Politics and Society
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsDrainage basinWestern europeAquatic environment

Abstract

fetched live from OpenAlex

Ce jeu de données présente une étude approfondie des observations réalisées entre mai 2001 et août 2002 dans 16 lacs et 20 ruisseaux situés dans les municipalités de Saint-Hippolyte et de Prévost. L’objectif principal de cette étude était de constituer un carnet de bord de référence, d’identifier et de comprendre les sources de phosphore, de carbone organique et de sédiments dans les bassins versants, d’établir le budget en phosphore des principaux lacs et de formuler des recommandations pour une gestion durable des milieux aquatiques. L’analyse examine notamment l’influence du temps de séjour de l’eau, l’impact des activités humaines et la présence de milieux humides sur la fertilité, la transparence de l’eau ainsi que sur l’oxygénation des zones profondes. Une étude détaillée du réseau hydrologique du bassin du lac Connelly permet également de déterminer les coefficients d’exportation du phosphore et des sédiments, fournissant ainsi un soutien essentiel pour orienter la gestion future des lacs. Le jeu de données comprend un rapport détaillé, un tableau contenant des variables clés relatives aux caractéristiques de chaque lac et de chaque bassin versant, ainsi que d’autres informations complémentaires, telles que la délimitation des bassins versants, la bathymétrie et les photographies aériennes des lacs.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.915
Threshold uncertainty score0.170

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.018
GPT teacher head0.306
Teacher spread0.288 · 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 designNot applicable
Domainnot available
GenreDataset

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
Published2025
Admission routes1
Has abstractyes

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