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Surgical management of ileocaeco-colic intussusception in labrador retriever pup: A case report

2023· article· en· W4385699847 on OpenAlexaboutno aff
M Vigneswari, S Tina Roshini, C Chimithi, N Gurunathan, N Arivukkarasi, Sophia Kent

Bibliographic record

VenueInternational Journal of Veterinary Sciences and Animal Husbandry · 2023
Typearticle
Languageen
FieldMedicine
TopicGastrointestinal disorders and treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineExploratory laparotomyLabrador RetrieverPuppyBloodyAnusSurgeryLaparotomyPhysical examinationIntussusception (medical disorder)ImpactionPalpationGeneral surgery

Abstract

fetched live from OpenAlex

A three-month-old female Labrador Retriever puppy was presented to Department of Veterinary Surgery and Radiology, Veterinary Clinical Complex, Rajiv Gandhi Institute of Veterinary Education Research, Puducherry with the history of inappetence, tenesmus, haematochezia and protrusion of cylindrical mass from the anus for past one month. The animal was previously treated but recurrence noticed. Clinical examination revealed protrusion of the mass from rectum, abdominal pain and bloody mucoid diarrhoea. Ultrasonographic examination shown characteristic ‘target sign’ confirming the case as Intussusception. Under general anaesthesia, exploratory laparotomy was performed and the intussusception was corrected. Post operatively, antibiotics and analgesia were administered for 5 and 3 days along with fluid therapy. The skin sutures were removed on 10th post-operative day and the animal made an uneventful recovery.

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)0.002
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 score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0010.001
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 head0.050
GPT teacher head0.369
Teacher spread0.319 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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