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Record W2524038973 · doi:10.5326/jaaha-ms-6436

Border Collie Collapse: Owner Survey Results and Veterinary Description of Videotaped Episodes

2016· article· en· W2524038973 on OpenAlexaff
Susan Taylor, Katie M. Minor, Cindy L. Shmon, G. Diane Shelton, Edward E. Patterson, James R. Mickelson

Bibliographic record

VenueJournal of the American Animal Hospital Association · 2016
Typearticle
Languageen
FieldImmunology and Microbiology
TopicRabies epidemiology and control
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMedicineVeterinary medicineFamily medicine

Abstract

fetched live from OpenAlex

Completed surveys were obtained from owners of 165 border collies experiencing repeated episodes of abnormal gait or collapse during strenuous exercise. Unremarkable veterinary evaluation and lack of disease progression over time made common systemic, cardiac, and neurologic causes of exercise intolerance unlikely. Survey questions addressed signalment, age of onset, description of episodes, and owner perception of factors associated with collapse. Most dogs were young adults (median 2 yr) when episodes began, and they had experienced from 2 to more than 100 episodes (median 6) prior to their owners completing the survey. Retrieving was the activity most commonly associated with episodes (112/165 dogs, 68%), followed by herding stock (39/165 dogs, 24%). Owners reported that high environmental temperatures (111/165 dogs, 67%) and excitement (67/165 dogs, 41%) increased the likelihood of their dog having an episode during strenuous activity. Veterinary evaluation of videotapes of presumed border collie collapse (BCC) episodes (40 dogs) were used to provide a description of the typical features of BCC episodes. Altered mentation, symmetrical ataxia affecting all four limbs, increased pelvic limb extensor tone and toe scuffing or knuckling, truncal swaying, and falling to the side were common features, suggesting that BCC may be an episodic diffuse central nervous system disorder.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.371
Threshold uncertainty score0.461

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.015
GPT teacher head0.261
Teacher spread0.246 · 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

Citations7
Published2016
Admission routes1
Has abstractyes

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