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Record W4410133144 · doi:10.1111/bpa.70013

Comparative pathology boards facilitate the translation of knowledge between canine and human cancer patients

2025· letter· en· W4410133144 on OpenAlexaff
Jessica A. Beck, Christina Mazcko, Sara Belluco, Mireille Bitar, Daniel J. Brat, Jonathan W. Bush, Rati Chkheidze, Kara N. Corps, Chad Frank, Caterina Giannini, Craig Horbinski, Jason T. Huse, Jennifer W. Koehler, Andrew D. Miller, C. Ryan Miller, M. Gerard O’Sullivan, Joanna J. Phillips, Daniel R. Rissi, Courtney R. Schott, Anat Stemmer‐Rachamimov, Stephen Yip, Amy K. LeBlanc

Bibliographic record

VenueBrain Pathology · 2025
Typeletter
Languageen
FieldVeterinary
TopicInfectious Diseases and Mycology
Canadian institutionsUniversity of GuelphBC Children's HospitalUniversity of British Columbia
FundersNational Cancer Institute
KeywordsTranslation (biology)PathologyCancerHuman PathologyMedicineBiologyInternal medicineDiseaseGeneticsGene

Abstract

fetched live from OpenAlex

Comparative pathology boards bring together anatomic pathologists with expertise in canine and human histology to identify shared features, including immune or TME components, tumor subtypes, or prognostic tissue biomarkers. This article summarizes feedback to improve future initiatives and enhance the translational relevance of comparative oncology for human patients.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.287
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0010.001
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 head0.082
GPT teacher head0.369
Teacher spread0.287 · 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 teacher head, not a consensus.

Study designNot applicable
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
Published2025
Admission routes1
Has abstractyes

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