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Record W3087931336 · doi:10.1136/vetreccr-2020-001231

Collision tumour of two nodal metastases (adenocarcinoma and mast cell tumour) in a dog

2020· article· en· W3087931336 on OpenAlexaboutno aff
Danielle Gibson, Samuel J. Beck, Esteban Gonzàlez‐Gasch, Aaron Harper

Bibliographic record

VenueVeterinary Record Case Reports · 2020
Typearticle
Languageen
FieldMedicine
TopicVeterinary Oncology Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHistopathologyAsymptomaticLymph nodeAdenocarcinomaLymphadenectomyRadiation therapyWide local excisionPathologyRadiologySurgeryCancerInternal medicine

Abstract

fetched live from OpenAlex

SUMMARY An 11‐year‐old female neutered Labrador retriever was referred for a large vulvar mast cell tumour that extended into the vagina. Abdominal ultrasound revealed an enlarged right medial iliac lymph node, and cytology of the node was consistent with an endocrine/neuroendocrine tumour. An approximately 1.5‐cm right anal sac mass was palpated. Medial iliac lymphadenectomy via ventral celiotomy, right anal sacculectomy and marginal vulvar mass resection were performed. Histopathology was consistent with right anal sac adenocarcinoma, vulvar mast cell tumour, and the right medial iliac lymph node showed a metastatic collision of both the adenocarcinoma and mast cell tumour cell populations. Adjunctive chemotherapy and radiotherapy were recommended to address the risk of local recurrence and further metastasis but were declined by the owner. The dog remains alive and asymptomatic with no visible evidence of recurrence 14 months after initial presentation.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.071
GPT teacher head0.350
Teacher spread0.279 · 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 designCase report
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
Published2020
Admission routes1
Has abstractyes

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