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Record W4389073546

Notice de présentation des projections et incertitudes pour Explore2: version courte

2023· preprint· fr· W4389073546 on OpenAlexaff
Alix Reverdy, Guillaume Evin, Benoît Hingray

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2023
Typepreprint
Languagefr
FieldComputer Science
TopicData Analysis with R
Canadian institutionsEmergent BioSolutions (Canada)
Fundersnot available
KeywordsHumanitiesPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Ce document a pour objectif d’exposer brièvement les concepts des analyses d’incertitudes faites avec l’ensemble de projections hydroclimatiques d’Explore2 et d’illustrer les représentations graphiques qui seront produites pour caractériser l’évolution future de différents indicateurs hydroclimatiques telle que projetée dans cet ensemble. La méthode d’analyse fait appel à des méthodes statistiques avancées, qui permettent de produire différents types de résultats et de représentations graphiques. Le présent document en propose un niveau de lecture simplifié.

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)0.022
metaresearch head score (Gemma)0.106
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.365
Threshold uncertainty score0.905

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.106
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0010.004
Bibliometrics0.0050.006
Science and technology studies0.0020.001
Scholarly communication0.0130.007
Open science0.0030.007
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.3650.234

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 head0.057
GPT teacher head0.294
Teacher spread0.237 · 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
GenreMethods

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
Published2023
Admission routes1
Has abstractyes

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