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Diagnóstico de criptococose canina pela citologia aspirativa por agulha fina

2008· article· pt· W2110456499 on OpenAlexaboutno aff
Danieli Brolo Martins, Anna Laetícia Trindade Barbosa, Ayrton Sydnei Cavalheiro, Sônia Terezinha dos Anjos Lopes, Janio M. Santurio, João Eduardo Wallau Schossler, Alexandre Mazzantí

Bibliographic record

VenueCiência Rural · 2008
Typearticle
Languagept
FieldMedicine
TopicFungal Infections and Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Relata-se um caso de criptococose canina de caráter sistêmico e neurológico diagnosticado com o auxílio da citologia aspirativa por agulha fina (CAAF). O paciente, da raça Labrador, 1 ano e 5 meses, macho, apresentava sinais de depressão/estupor, hiporexia, presença de uma massa cervical delimitada entre os dois linfonodos submandibulares e aumento de linfonodos. A punção aspirativa da massa cervical e dos linfonodos poplíteo, pré-escapular e submandibular revelaram presença de fungos compatíveis com Cryptococcus neoformans, o qual foi então confirmado pela cultura fúngica, e classificado como sorotipo D. A CAAF mostrou ser um método rápido, seguro e eficaz em casos de criptococose canina com presença de linfoadenomegalia.

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)0.003
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 score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.036
GPT teacher head0.285
Teacher spread0.249 · 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

Citations11
Published2008
Admission routes1
Has abstractyes

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