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Record W2953465244 · doi:10.1111/vco.12518

Prognostic and predictive significance of KIT protein expression and <i>c‐kit</i> gene mutation in canine cutaneous mast cell tumours: A consensus of the Oncology‐Pathology Working Group

2019· review· en· W2953465244 on OpenAlexaff
Douglas H. Thamm, Anne C. Avery, Davide Berlato, Julie Bulman‐Fleming, Craig A. Clifford, Alexander Hershey, Joanne L. Intile, Pamela D. Jones, Debra A. Kamstock, Julius M. Liptak, Alana Pavuk, John R. Peauroi, Roger Powell, Kerry Rissetto, V. E. Valli, Joshua D. Webster

Bibliographic record

VenueVeterinary and Comparative Oncology · 2019
Typereview
Languageen
FieldMedicine
TopicVeterinary Oncology Research
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsMedicineCompanion diagnosticConsensus conferencePathologyMolecular pathologyAnatomical pathologyMEDLINEInternal medicineVeterinary medicineOncologyFamily medicineCancerGeneBiology

Abstract

fetched live from OpenAlex

One of the primary objectives of the Oncology-Pathology Working Group (OPWG), a joint initiative of the Veterinary Cancer Society and the American College of Veterinary Pathologists, is for oncologists and pathologists to collaboratively generate consensus documents to standardize aspects of and provide guidelines for oncologic pathology. Consensus is established through critical review of peer-reviewed literature relevant to a subgroup's particular focus. Subsequent acceptance and approval of the document by the OPWG membership at large establishes consensus. The intent of this publication is to help educate practitioners and pathologists on the value of diagnostics related to the KIT receptor tyrosine kinase for canine cutaneous mast cell tumours and to provide a guide for the use of these tests in veterinary medicine. This document represents the opinions of the OPWG and the authors and does not constitute a formal endorsement by the American College of Veterinary Pathologists or the Veterinary Cancer Society.

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)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.158
GPT teacher head0.397
Teacher spread0.239 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations32
Published2019
Admission routes1
Has abstractyes

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