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Record W3210321404 · doi:10.5281/zenodo.4116598

Plan de gestion des données du groupe de recherche en écohydrologie (Modèle)

2020· article· fr· W3210321404 on OpenAlexaff
Bhaleka Persaud, Philippe Van Cappellen, Fereidoun Reza Nezhad, Maggie Neilson, Kathy Szigeti

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2020
Typearticle
Languagefr
FieldAgricultural and Biological Sciences
TopicSoil erosion and sediment transport
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

Ce modèle de PGD a été créé par le groupe de recherche en écohydrologie de l’université de Waterloo, dans le but de fournir un gabarit de PGD standardisé pour ses nombreux projets de recherche pluridisciplinaires et transversaux. Les processus fondamentaux du groupe de recherche en écohydrologie ont été intégrés comme point de départ pour le corps professoral, le personnel et le personnel hautement qualifié (PHQ) pour l’élaboration de projets de recherche. Cet exemple démontre l’utilité d’un modèle de PDG utilisé par un groupe ou un collectif de recherche pour maintenir les meilleures pratiques en matière de gestion des données.

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)0.006
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesOpen science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.998
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0060.003
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0130.005

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 head0.401
GPT teacher head0.279
Teacher spread0.122 · 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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueZenodo (CERN European Organization for Nuclear Research)→Same topicSoil erosion and sediment transport→French-language works237,207→