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Record W4289781782

Presumptive metastatic leiomyosarcoma in a feedlot steer.

2022· article· en· W4289781782 on OpenAlexaff
Fernando J Guardado, Kamal Gabadage, Andrew L. Allen

Bibliographic record

VenuePubMed · 2022
Typearticle
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsLeiomyosarcomaMedicineAbdomenThorax (insect anatomy)Inferior vena cavaAnatomyPathologyRadiology
DOInot available

Abstract

fetched live from OpenAlex

A 14-month-old feedlot steer was depressed and died while being examined. The gross post-mortem examination of the steer conducted at the feedlot identified numerous masses within the abdomen and thorax, including a large mass in the liver that eroded into the vena cava. Many masses in the lungs appeared to be the result of hematogenous distribution. Histologic examination of the masses confirmed the presence of neoplasia. Although the histologic appearance of the neoplasms was not typical of well-differentiated leiomyosarcoma, immunohistochemical staining supported that diagnosis. Leiomyosarcomas are rare among North American cattle. In this case, the primary neoplasm appears to have originated in the wall of the vena cava within the liver. Key clinical message: This report adds to the limited information on leiomyosarcomas in cattle, while highlighting both the challenges faced by veterinarians conducting post-mortem examinations on large animals in below freezing temperatures, as well as the current methods available to arrive at a diagnosis of a rare disease.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.049
GPT teacher head0.266
Teacher spread0.216 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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