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Record W7014480535

Programa del Medio Ambiente de las Naciones Unidas (UNEP), Preguntas y Respuestas acerca de los Efectos de la Disminución del Ozono, la Radiación Ultravioleta y el Clima en los humanos y el Medio Ambiente. Suplemento del Reporte de Evaluación 2022 del Panel de Evaluación de los Efectos en el Medio Ambiente de las Naciones Unidas

2023· article· es· W7014480535 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2023
Typearticle
Languagees
FieldEnvironmental Science
TopicPublic Health and Environmental Issues
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Health surveillanceInitial training
DOInot available

Abstract

fetched live from OpenAlex

Esta colección de preguntas y respuestas fue preparada por el Panel de Evaluación de los Efectos en el Medio Ambiente (EEAP por sus siglas en inglés) del Protocolo de Montreal bajo el amparo del Programa para el Medio Ambiente de las Naciones Unidas (PNUM). Este documento es un complemento de la Evaluación Cuatrienal 2022 realizada por el EEAP (https://ozone. unep.org/science/assessment/eeap), y provee de información interesante y útil para redactores de políticas públicas, maestros y científicos. Este P&Rs está escrito en un lenguaje de fácil comprensión para el público en general.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.009
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0040.003
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0170.002

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 head0.025
GPT teacher head0.362
Teacher spread0.337 · 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; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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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