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Record W2584850934 · doi:10.5380/avs.v21i3.41383

SURTO DE INTOXICAÇÃO DE BOVINOS POR HEXACLOROBENZENO- BHC

2016· article· pt· W2584850934 on OpenAlexaff
Wilmar Sachetin Marçal, José Antônio da Silva Fernandes, Maísa Fabiana Menck

Bibliographic record

VenueArchives of Veterinary Science · 2016
Typearticle
Languagept
FieldAgricultural and Biological Sciences
TopicInsect and Pesticide Research
Canadian institutionsNexen (Canada)
Fundersnot available
KeywordsHumanitiesBiologyArt

Abstract

fetched live from OpenAlex

Apesar de proibido no Brasil, o Hexaclorobenzeno(BHC) é um dos poluentes ambientais, mais perigosos e sua contaminação pode comprometer o solo, plantas, mananciais hídricos e diferentes criações de animais. Nas propriedades rurais onde são utilizados, não raro, o BHC acaba sendo deixado em locais impróprios, como tulhas e paióis. Outras vezes alguns produtores rurais armazenam esse veneno em barracões desprotegidos, o que pode provocar acidentes para seres vivos, tanto ao homem, como aos animais. Isto foi evidenciado, na prática, numa propriedade rural do município paranaense de Kaloré, estado do Paraná. Além da mortalidade observada em 15 bovinos adultos, foi possível atuar de modo pericial para, ao se fechar o círculo da toxidez, fomentar o poder judiciário com a comprovação do surto e das respectivas conseqüências.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.056
GPT teacher head0.313
Teacher spread0.257 · 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 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

Citations1
Published2016
Admission routes1
Has abstractyes

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