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EFEITO DE FÁRMACOS ANESTÉSICOS NA FUNÇÃO RENAL DE CÃES

2016· article· pt· W2552559683 on OpenAlexaboutno aff
Rudison Da Silva Florêncio, José Aloizio Gonçalves Net, Ronaldo Eugênio de Oliveira, Kamila Teixeira Pandolfi, Gabriela Porfírio-Passos, Lenir Cardoso Porfírio

Bibliographic record

VenueRevista Univap · 2016
Typearticle
Languagept
FieldVeterinary
TopicVeterinary Pharmacology and Anesthesia
Canadian institutionsnot available
Fundersnot available
KeywordsChemistry

Abstract

fetched live from OpenAlex

Com o aumento na expectativa de vida dos animais como cães e gatos há necessidade de aperfeiçoar práticas anestésicas e fármacos para a obtenção do plano anestésico com mínimos efeitos colaterais. Os objetivos deste trabalho foram analisar parâmetros urinários antes e após os procedimentos anestésicos, a densidade urinaria, relação proteína:creatina urinária, atividade urinária das enzimas fosfatase alcalina e gama glutamiltransferase, em cães machos e fêmeas da raça labrador com aproximadamente 30 kg de peso e com uso de acepromazina na dose de 0,05 mg/Kg e meperidina 3 mg/Kg como medicação pré-anestésica, propofol na dose de 5mg/Kg para indução e a manutenção anestésica foi realizada com isofluorano em 1,5 CAM. Concluiu-se, este protocolo anestésico em procedimentos cirúrgicos não ocasionaram alterações nos parâmetros renais que indicasse lesão. Todos os valores da atividade urinária das enzimas gGT, FA, da DU e da UPC se mantiveram dentro dos parâmetros fisiológicos de cães saudáveis e não houve relação negativa pelo uso dos anestésicos nas doses utilizadas.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0010.000

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 head0.050
GPT teacher head0.336
Teacher spread0.285 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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