MétaCan
Menu
Back to cohort
Record W2908424923 · doi:10.4000/books.irasec.2061

L’Asie du Sud-Est à la COP21 : enjeux, systèmes d’acteurs et engagements

2017· book-chapter· fr· W2908424923 on OpenAlexaff
Éric Mottet

Bibliographic record

VenueInstitut de recherche sur l’Asie du Sud-Est contemporaine eBooks · 2017
Typebook-chapter
Languagefr
FieldHealth Professions
TopicHealthcare Systems and Practices
Canadian institutionsMinistry of Natural Resources and WildlifeUniversité du Québec à Montréal
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

La 21e conférence des Parties à la Convention-cadre des Nations unies sur les changements climatiques (CCNUCC) et la 11e session de la conférence des Parties agissant comme réunion des Parties au protocole de Kyoto, couramment désignées COP21/CMP11, qui se sont tenues sur le site de Paris-Le Bourget du 30 novembre au 11 décembre 2015, ont permis de conclure un accord engageant 195 États à réduire leurs émissions de gaz à effet de serre (GES) et de tracer un aperçu de ce qui attend la communa...

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)0.003
metaresearch head score (Gemma)0.002
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: Other · Consensus signal: Other
Teacher disagreement score0.096
Threshold uncertainty score0.192

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0080.007
Scholarly communication0.0090.004
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.001

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 head0.442
GPT teacher head0.468
Teacher spread0.027 · 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
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

Citations1
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueInstitut de recherche sur l’Asie du Sud-Est contemporaine eBooksSame topicHealthcare Systems and PracticesFrench-language works237,207