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Record W4281835919 · doi:10.46380/rias.vol5.e215

Contribución de las emisiones de gas metano producidas por el ganado bovino al cambio climático

2022· article· es· W4281835919 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRevista Iberoamericana Ambiente & Sustentabilidad · 2022
Typearticle
Languagees
FieldAgricultural and Biological Sciences
TopicAgricultural and Food Production Studies
Canadian institutionsImpact
Fundersnot available
KeywordsPolitical scienceHumanitiesEnvironmental sciencePhilosophy

Abstract

fetched live from OpenAlex

El sector ganadero es uno de los principales sistemas que contribuyen al desarrollo sostenible de la agricultura, sus principales aportaciones están en la seguridad alimentaria, la nutrición y el crecimiento económico, sin embargo, este sector es responsable de la emisión de una gran cantidad de gases de efecto invernadero. Este trabajo tuvo la finalidad de mostrar las contribuciones que presenta la producción ganadera frente al cambio climático, identificando la principal fuente de contaminación del sector, así como las alternativas de mitigación para la problemática presente. Para ello se analizaron los temas relacionados de diferentes fuentes, obteniendo información relevante para el sustento del trabajo. Como resultado, se pudo evidenciar que las emisiones de gas metano producidas por el ganado bovino es uno de los factores que contribuyen al cambio climático, por lo que se ha convertido en un problema a nivel global debido a sus impactos negativos.

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.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.573
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.254
Teacher spread0.240 · 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