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Record W4360815131 · doi:10.24425/pjvs.2023.145011

Thyroid evaluation in suspicious hypothyroid adult dogs before and after treatment

2023· article· en· W4360815131 on OpenAlexaboutno aff
O. Bucalo, Katiuska Satué, Pietro Medica, Cristina Cravana, Enza Fazio

Bibliographic record

VenuePolish Journal of Veterinary Sciences · 2023
Typearticle
Languageen
FieldMedicine
TopicThyroid Disorders and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsPolyuriaMedicineInternal medicineEndocrinologyPolydipsiaThyroidBreedEuthyroidPhysiologyDiabetes mellitusBiologyAnimal science

Abstract

fetched live from OpenAlex

The purpose of this study was to measure circulating TSH, T4 and fT4 concentrations in dogs submitted to a clinical visit for general symptoms (weight gain, polyuria and polydipsia, changes in hair coat). Twenty-eight dogs, 14 cross-breed and 14 purebreds (Golden Retriever, Labrador, Doberman), of both sexes (14 males and 14 females), aged 8 to 14 years, were assessed. No significant differences of circulating TSH, T4 , fT4 concentrations between the baseline and after therapeutic treatment nor between intact and neutered females were observed. Compared to baseline values, intact males showed higher TSH concentrations (p⟨0.01), and castrated males lower TSH concentrations (p⟨0.01) after therapeutic treatment. Compared to intact males, castrated males showed baseline TSH concentrations higher (p⟨0.01), but lower (p⟨0.01) after therapeutic treatment. No significant differences of T4 and fT4 concentrations between baseline conditions and after therapeutic treatment, nor between intact and castrated males, were observed. The experimental sample considered in this study falls within that casuistry involving elevated TSH concentrations but low serum T4 and fT4 concentrations or close to the minimum physiological cut-off, in which the common clinical signs suggestive of hypothyroidism was, essentially, overweight and neglected appearance of the hair.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score0.350

Codex and Gemma teacher scores by category

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

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 head0.045
GPT teacher head0.346
Teacher spread0.301 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2023
Admission routes1
Has abstractyes

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