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Record W7077051604 · doi:10.5281/zenodo.15082575

Résumé à l'Intention des Décideurs (RID). Interactions entre le changement climatique et le nexus eau-énergie-alimentation-écosystèmes (WEFE) dans le bassin méditerranéen

2025· report· fr· W7077051604 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typereport
Languagefr
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsNexus (standard)MetisMediterranean climateAgency (philosophy)

Abstract

fetched live from OpenAlex

Le MedECC Special Report Interlinking climate change with the Water-Energy-Food-Ecosystems (WEFE) nexus in the Mediterranean Basin (Interactions entre le changement climatique et le nexus Eau-Énergie-Alimentation-Écosystèmes (WEFE) dans le bassin méditerranéen) fournit une évaluation scientifique complète des défis interconnectés de la région liés à la rareté de l’eau, à l’insécurité alimentaire et énergétique, ainsi qu’à la dégradation des écosystèmes, tous exacerbés par le changement climatique. S’appuyant sur le First Mediterranean Assessment Report (MAR1) du MedECC, ce rapport approfondit la compréhension des interconnexions et des arbitrages au sein du nexus WEFE. Il comprend un Résumé à l’intention des décideurs (SPM), qui synthétise les messages clés. Ce travail a été rédigé par 60 auteurs issus de 15 pays, tous contribuant à titre individuel et sans rémunération financière. Le Secrétariat de la Convention de Barcelone/PAM-PNUE, à travers son Centre d’activités régionales Plan Bleu, ainsi que le Secrétariat de l’Union pour la Méditerranée, collaborent pour soutenir MedECC et contribuer à l’établissement d’un processus d’évaluation scientifique solide et transparent. Cette version est la traduction française du texte original en anglais. Le texte original a été approuvé lors de la session plénière des parties prenantes du MedECC le 29 avril 2024.

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)0.007
metaresearch head score (Gemma)0.023
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.045
Threshold uncertainty score0.149

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.023
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0040.003
Scholarly communication0.0070.003
Open science0.0010.003
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0450.014

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 head0.078
GPT teacher head0.291
Teacher spread0.213 · 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
GenreEditorial

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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