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Record W1605112887

Hypoglycemia in a dog.

2009· article· en· W1605112887 on OpenAlexaff
Nicole Fernandez, Jason J.S. Barton, Tim Spotswood

Bibliographic record

VenuePubMed · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism and Genetic Disorders
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsInternal medicineCreatinineUrinalysisMedicineEndocrinologyGastroenterologyHypoglycemiaUrine specific gravityAnorexiaUrineInsulin
DOInot available

Abstract

fetched live from OpenAlex

A 6-year-old male, neutered shih tzu cross dog was presented to the referring veterinarian with a history of acute onset ataxia and anorexia of 2 d duration. On physical examination, the dog was depressed, ataxic, and disoriented, but otherwise normal with no neurologic deficits. Initial bloodwork revealed a marked fasting hypoglycemia of 1.6 mmol/L [reference interval (RI): 3.3–6.1 mmol/L]. Other abnormalities included mildly increased albumin (43 g/L; RI: 26–36 g/L), mildly increased amylase (1273 U/L; RI: 138–970 U/L) and lipase (683 U/L; RI: 0–600 U/L), and mildly decreased urea (1.78 mmol/L; RI: 2.14–8.56 mmol/L) and creatinine (44.2 μmol/L; RI: 61.9–114.9 μmol/L). Pre- and post-prandial bile acids were mildly increased (pre-prandial 16.0 μmol/L; RI: 0–15.0 μmol/L; post-prandial 28.5 μmol/L; RI: 0–22.0 μmol/L). The complete blood (cell) count (CBC) revealed only a mild stress lymphopenia. The urine specific gravity was 1.004, and the urinalysis data were unremarkable. Thoracic and abdominal radiographic findings were unremarkable.

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 score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.003
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 head0.008
GPT teacher head0.211
Teacher spread0.204 · 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

Citations10
Published2009
Admission routes1
Has abstractyes

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