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Record W2007794692 · doi:10.1136/vetreccr-2013-000023

Migrating sewing needle in the cervical vertebral canal in a dog

2014· article· en· W2007794692 on OpenAlexaboutno aff
Pilar Lafuente, Colin Driver

Bibliographic record

VenueVeterinary Record Case Reports · 2014
Typearticle
Languageen
FieldMedicine
TopicForeign Body Medical Cases
Canadian institutionsnot available
FundersRoyal Veterinary College
KeywordsMedicineDissection (medical)AnatomyForcepsPresentation (obstetrics)SurgeryLarynxProprioceptionDorsumNeck painForeign bodyPhysical medicine and rehabilitation

Abstract

fetched live from OpenAlex

An eight‐month‐old female labrador retriever was evaluated for progressive cervical hyperaesthesia after being seen coughing, close to a broken sewing kit two weeks prior to presentation. Physical examination showed cervical hyperaesthesia and mild proprioceptive deficits in the right thoracic and pelvic limbs. CT imaging of the neck showed a thin metallic foreign body (sewing needle) going in a ventrodorsal direction through the vertebral canal at the atlanto‐occipital junction. A ventral midline approach to the larynx, with dissection along the right side of the larynx was performed to gain access to its dorsal aspect. The exposed needle was grasped with Mosquito forceps, and removed in its entirety. Marked clinical improvement was observed the day after surgery. In a follow‐up telephone conversation four months after surgery, the owner reported a complete recovery of the patient, with return to normal activities.

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 score0.007
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0020.001
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 head0.036
GPT teacher head0.304
Teacher spread0.268 · 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

Citations6
Published2014
Admission routes1
Has abstractyes

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