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Record W2943828860 · doi:10.1111/vru.12758

Small intestinal enterolith in a dog presenting for a suspected gastric foreign body

2019· article· en· W2943828860 on OpenAlexaboutno aff
Jessica A. Malberg, Adrien‐Maxence Hespel

Bibliographic record

VenueVeterinary Radiology & Ultrasound · 2019
Typearticle
Languageen
FieldMedicine
TopicForeign Body Medical Cases
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineLaparotomyBezoarForeign bodyLabrador RetrieverVomitingAnorexiaAbdomenRadiologySurgeryInternal medicine

Abstract

fetched live from OpenAlex

A 12-year-old Labrador Retriever presented for an acute onset of anorexia and vomiting. Abdominal ultrasound and abdominal radiographs were performed, and on the latter a large mineral opaque structure with concentric rings within the cranial abdomen was diagnosed as a gastric foreign body. Laparotomy revealed that the suspected gastric foreign body was a large enterolith within the small intestines. Enteroliths should be considered as one of the differential diagnoses for a large mineralized abdominal structure in a dog presented for gastrointestinal clinical signs.

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 score0.006
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.001
Science and technology studies0.0020.002
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0060.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.037
GPT teacher head0.291
Teacher spread0.254 · 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

Citations3
Published2019
Admission routes1
Has abstractyes

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