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Surgical management of a double‐chambered right ventricle and chylothorax in a Labrador retriever

2006· article· en· W2049470872 on OpenAlexaboutno aff
Ryou Tanaka, Miki Shimizu, Hidehiro Hirao, Masayuki Kobayashi, Yukiko Nagashima, Noboru Machida, Yoshihisa YAMANE

Bibliographic record

VenueJournal of Small Animal Practice · 2006
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Conditions and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineVentriculotomyVentriclePericardial effusionChylothoraxSurgeryLabrador RetrieverShuntingTricuspid atresiaCardiologyInternal medicine

Abstract

fetched live from OpenAlex

A 22-month-old, male Labrador retriever was presented with anorexia, dyspnoea, and fainting. The dog was diagnosed with a double-chambered right ventricle and tricuspid valve dysplasia using echocardiography and cardiac catheterisation. A marked bilateral pleural effusion was also present and chemical analysis of the fluid confirmed the diagnosis of chylothorax. Using echocardiography, a pressure gradient of 87.1 mmHg was found between the proximal and distal chambers of the double-chambered right ventricle. Initiation of cardiopulmonary bypass allowed the anomalous muscle bundle that divided the right ventricle into two chambers to be resected via a right ventriculotomy. The fainting completely resolved postoperatively, and this treatment seemed quite effective in the reduction of pressure overload ascribable to ejection disturbance. Because the tricuspid dysplasia was not corrected in the first operation, the postoperative chyle effusion was reduced but did not cease. A combination of thoracic duct ligation and passive pleuroperitoneal shunting was effective in the resolution of the chyle effusion.

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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.275
Teacher spread0.261 · 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

Citations14
Published2006
Admission routes1
Has abstractyes

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