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Record W7064810245

Comparação de achados radiográficos e artroscópicos na displasia do cotovelo em cães : estudo retrospetivo

2022· dissertation· pt· W7064810245 on OpenAlexaboutno aff

Bibliographic record

VenueRepositório Científico Lusófona (Grupo Lusófona) · 2022
Typedissertation
Languagept
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Computed tomographyLesion
DOInot available

Abstract

fetched live from OpenAlex

A displasia do cotovelo é uma das principais causas de claudicação do membro torácico em cães jovens, de raça média ou grande. No presente trabalho pretendeu-se estudar o espetro de achados clínicos, radiográficos e artroscópicos observados na displasia do cotovelo, bem como avaliar a sua importância relativa no diagnóstico e despistar eventuais correlações entre os achados. Para tal, foram analisados os dados completos de 119 cães diagnosticados com displasia do cotovelo entre junho de 2011 e junho de 2021 e recorreu-se a análise estatística para identificar possíveis associações entre eles. Na amostra, a raça Labrador Retriever foi a mais afetada (48% dos cães), o rácio macho:fêmea foi 3,4:1 e a mediana de idades 11 meses. O achado prevalente na radiografia dos cotovelos foi a esclerose subtroclear (93%) e na artroscopia foi a fragmentação ou fissuração do processo coronóide medial (89%). Não foram encontradas correlações entre os sinais clínicos, radiográficos e artroscópicos, mas foram encontradas correlações significativas entre as idades e a escala de Outerbridge e entre a presença de fragmentos e a escala de Outerbridge. Concluiu-se que a artroscopia deve ser sempre usada complementarmente à radiografia porque permite avaliar diretamente, e com maior precisão, as lesões na articulação e cartilagem.

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)0.004
metaresearch head score (Gemma)0.015
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.015
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.011
GPT teacher head0.283
Teacher spread0.272 · 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
Published2022
Admission routes1
Has abstractyes

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