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Estudo morfológico das neoplasias melanocíticas uveais em cães

2010· dissertation· pt· W1592375916 on OpenAlexaboutno aff
Eduardo Perlmann

Bibliographic record

Venuenot available
Typedissertation
Languagept
FieldMedicine
TopicVeterinary Oncology Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicine

Abstract

fetched live from OpenAlex

\n Os tumores de origem melanocítica representam as mais frequentes neoplasias intra-oculares diagnosticadas nos cães. O presente trabalho teve por objetivo realizar estudo retrospectivo das neoplasias melanocíticas da úvea do cão analisando suas características morfológicas e epidemiológicas. Foi estudado um total de 29 casos; destas, 51,7 % foram diagnosticadas como melanocitoma, enquanto que 48,3 % como melanoma. As raças mais acometidas foram SRD (sem raça definida), Cocker Spaniel Inglês e Labrador Retriver, porém não houve predominância racial significativa. A faixa etária foi de 6 a 15 anos, com média de 10,3 anos. Os tumores acometeram igualmente machos e fêmeas. A úvea anterior foi a localização mais comum, representando 96,5 % de todos os tumores, enquanto a úvea posterior representou 3,5 %, sendo o último, um melanoma. Em 5 casos, o tumor ocupava todo espaço intra-ocular, sendo todos melanomas. Os melanocitomas apresentaram predominância de células grandes, redondas ou poliédricas, densamente pigmentadas e núcleo pequeno. Os melanomas apresentaram 2 padrões celulares distintos. Dos 14 melanomas, 8 (57,2 %) eram compostos por células epitelióides, 2 (14,3 %) por células fusiformes, e 4 (28,5%) apresentaram padrão misto. Em 7 melanomas observou-se áreas de melanocitoma, sugerindo transformação maligna.\n

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.445
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0290.012

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 head0.038
GPT teacher head0.401
Teacher spread0.363 · 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; both teacher heads agree on what is shown here.

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

Citations2
Published2010
Admission routes1
Has abstractyes

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