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Record W2801499081 · doi:10.2460/javma.252.10.1272

Chylous ascites associated with abdominal trauma and intestinal resection-anastomosis in a pet ferret (Mustela putorius furo)

2018· article· en· W2801499081 on OpenAlexaff
Lucile Chassang, Isabelle Langlois, Pauline Loos, Mila Freire, Elizabeth O’Toole

Bibliographic record

VenueJournal of the American Veterinary Medical Association · 2018
Typearticle
Languageen
FieldMedicine
TopicLymphatic Disorders and Treatments
Canadian institutionsCegep de Saint Hyacinthe
Fundersnot available
KeywordsMedicineExploratory laparotomyLaparotomySurgeryOctreotideAbdominal cavityDuodenumFeeding tubeEnteral administrationChylous ascitesEffusionAbdominal traumaAscitesBluntParenteral nutritionInternal medicine

Abstract

fetched live from OpenAlex

CASE DESCRIPTION A 10-week-old 0.73-kg (1.6-lb) castrated male domestic ferret (Mustela putorius furo) was referred for exploratory laparotomy because of pneumoperitoneum and possible septic peritonitis after being bitten by the owner's dog. CLINICAL FINDINGS Abdominal exploration revealed a large laceration of the duodenum, tears of the jejunal mesentery, and 2 small tears in the abdominal wall. Chylous abdominal effusion developed 48 hours after surgery. TREATMENT AND OUTCOME Postoperative care included supportive treatment, analgesia, and antimicrobials. An abdominal drain was placed during the laparotomy and enabled monitoring of abdominal fluid production. Enteral feeding was provided through an esophagostomy tube. The chylous fluid production rapidly decreased after treatment with octreotide was initiated, and the ferret improved. Chyloabdomen resolved after 8 days of hospitalization and medical treatment. CLINICAL RELEVANCE Findings suggested that chylous ascites can potentially develop secondary to blunt abdominal trauma in ferrets. In this ferret, chyloabdomen was successfully treated with octreotide administration and abdominal drainage.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.105
Threshold uncertainty score0.380

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.017
GPT teacher head0.294
Teacher spread0.277 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

Explore more

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