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CONSERVAÇÃO DE PEÇAS ANATÔMICAS HUMANAS EM FORMALDEÍDO E CLORETO DE SÓDIO: ANÁLISE MICROBIOLÓGICA DAS SOLUÇÕES

2023· article· pt· W4321084980 on OpenAlexaff
Marcela Fernandes Travagim, Célia Maria Gomes Labegalini, Franciele Zanardo Bohm, Hélito Volpato

Bibliographic record

VenueRevista Foco · 2023
Typearticle
Languagept
FieldEngineering
TopicAnatomy and Medical Technology
Canadian institutionsMicrosemi (Canada)
Fundersnot available
KeywordsPhysicsChemistry

Abstract

fetched live from OpenAlex

A pesquisa objetiva analisar a presença de microrganismos em soluções de formaldeído a 10% e de cloreto de sódio a 30% utilizadas para a conservação de peças anatômicas humanas. O estudo é do tipo experimental, analítico e quantitativo realizado com solução de conservação e peças anatômicas submetidas à solução de formaldeído a 10% e cloreto de sódio a 30%. As amostras foram tratadas com diferentes métodos para avaliar a presença e crescimento de microrganismos. Observou-se que não houve crescimento de microrganismos nas soluções de conservação e amostras de órgãos submetidos a diferentes metodologias. Os resultados demonstram que ambas as soluções apresentaram eficácia na conservação das peças anatômicas ao impedir o crescimento de microrganismo. O cloreto de sódio (NaCl) confere o benefício de trazer menos danos à saúde humana quando comparado ao formaldeído. Estes resultados indicam que a solução salina é mais viável para a conservação das peças anatômicas testadas devido ao baixo custo e toxicidade para os indivíduos que o manipulam.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.019
GPT teacher head0.289
Teacher spread0.270 · 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 designBench or experimental
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

Citations2
Published2023
Admission routes1
Has abstractyes

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