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Record W2307992094 · doi:10.1136/vetreccr-2015-000265

Difficult orotracheal intubation in a rabbit resulting from the presence of faecal pellets in the oropharynx

2016· article· en· W2307992094 on OpenAlexaff
Sarah Engbers, Amy Larkin, Mahesh Jonnalagadda, Melanie Prebble, Nicolas Rousset, Cameron G. Knight, Daniel Pang

Bibliographic record

VenueVeterinary Record Case Reports · 2016
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Pharmacology and Anesthesia
Canadian institutionsHotchkiss Brain InstituteWestern UniversityUniversity of Calgary
Fundersnot available
KeywordsOrotracheal intubationMedicineIntubationEpiglottisAnesthesiaSedationAirwayPharynxSwallowingSurgeryLarynx

Abstract

fetched live from OpenAlex

Rabbits have a high rate of anaesthesia‐related death compared with other companion animal species. This is influenced by a variety of factors, one of which is difficulty in obtaining a secure airway. The rabbit in this report was enrolled in a larger non‐survival study that required orotracheal intubation to be performed. Orotracheal intubation was difficult, taking 306 seconds, compared with a median of 134 seconds (range 29–171 seconds) in the four preceding rabbits. Necropsy examination revealed a faecal pellet lodged in the caudal oropharynx abutting compacted faecal material, ventral to the epiglottis. Two structures of mixed gas and soft tissue attenuation were seen on CT scans obtained pre‐ and post‐intubation, at a location consistent with the faecal material, thus confirming the presence of the pellets at the time of sedation and during intubation. Oral prehension of faecal pellets before anaesthesia represents a previously unreported obstacle to orotracheal intubation in rabbits.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
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 head0.078
GPT teacher head0.339
Teacher spread0.262 · 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

Citations4
Published2016
Admission routes1
Has abstractyes

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