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Record W3005689065 · doi:10.1111/vco.12574

Refining the “double two‐thirds” rule: Genotype‐based breed grouping and clinical presentation help predict the diagnosis of canine splenic mass lesions in 288 dogs

2020· article· en· W3005689065 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueVeterinary and Comparative Oncology · 2020
Typearticle
Languageen
FieldMedicine
TopicVeterinary Oncology Research
Canadian institutionsnot available
Fundersnot available
KeywordsBreedMedicineMalignancyLabrador RetrieverGenotypeInternal medicineLogistic regressionVeterinary medicinePathologyGastroenterologyBiologyAnimal science

Abstract

fetched live from OpenAlex

Prediction of the likely histopathological diagnosis of canine splenic masses can guide appropriate decision-making. This study explores the predictive effect of breed and clinical presentation on the diagnosis of a canine splenic mass. Records from the Royal Veterinary College, United Kingdom (2007-2017) were reviewed. Dogs with a histopathologic or cytologic diagnosis from a splenic mass, or imaging findings consistent with disseminated metastatic disease, were included. Signalment, physical examination, haematology results, imaging findings and pathology reports were recorded. Breeds were grouped according to several permutations of their phenotype and then by clustering of breeds based on single nucleotide polymorphism analysis. Binary logistic regression was performed to identify predictors of malignancy and haemangiosarcoma. Two hundred and eighty-eight dogs were identified: 27% female and 63% male, 21% entire and 79% neutered; German Shepherd was the most common breed (11%). Median age was 10 years and median bodyweight 25 kg. Thirty-eight percent of dogs presented with haemoabdomen; a splenic mass was found incidentally in 28%. Sixty percent had a malignant tumour of which haemangiosarcoma comprised 66%. On multivariable analysis, genotype-based breed group (P = .004), haemoabdomen (P < .001) and neutrophil count (P = .025) predicted malignancy, and genotype-based breed group (P < .001) and haemoabdomen (P < .001) predicted haemangiosarcoma. Genotype-based breed group and occurrence of haemoabdomen may have predictive value to diagnose malignant splenic masses and more specifically haemangiosarcoma. The effect of genotype-based breed grouping was a superior predictor of the diagnosis of a canine splenic mass lesion compared with all phenotype-based groupings tested.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.043
Threshold uncertainty score0.480

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.342
GPT teacher head0.475
Teacher spread0.133 · 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