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Record W2504509072 · doi:10.5326/jaaha-ms-6361

Evaluation of Dogs with Border Collie Collapse, Including Response to Two Standardized Strenuous Exercise Protocols

2016· article· en· W2504509072 on OpenAlexaff
Susan Taylor, Cindy L. Shmon, Lillian Su, Tasha Epp, Katie M. Minor, James R. Mickelson, Edward E. Patterson, G. Diane Shelton

Bibliographic record

VenueJournal of the American Animal Hospital Association · 2016
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Orthopedics and Neurology
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMedicinePhysical therapy

Abstract

fetched live from OpenAlex

Clinical and metabolic variables were evaluated in 13 dogs with border collie collapse (BCC) before, during, and following completion of standardized strenuous exercise protocols. Six dogs participated in a ball-retrieving protocol, and seven dogs participated in a sheep-herding protocol. Findings were compared with 16 normal border collies participating in the same exercise protocols (11 retrieving, five herding). Twelve dogs with BCC developed abnormal mentation and/or an abnormal gait during evaluation. All dogs had post-exercise elevations in rectal temperature, pulse rate, arterial blood pH, PaO2, and lactate, and decreased PaCO2 and bicarbonate, as expected with strenuous exercise, but there were no significant differences between BCC dogs and normal dogs. Electrocardiography demonstrated sinus tachycardia in all dogs following exercise. Needle electromyography was normal, and evaluation of muscle biopsy cryosections using a standard panel of histochemical stains and reactions did not reveal a reason for collapse in 10 dogs with BCC in which these tests were performed. Genetic testing excluded the dynamin-1 related exercise-induced collapse mutation and the V547A malignant hyperthermia mutation as the cause of BCC. Common reasons for exercise intolerance were eliminated. Although a genetic basis is suspected, the cause of collapse in BCC was not determined.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.621
Threshold uncertainty score0.375

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
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 head0.041
GPT teacher head0.379
Teacher spread0.339 · 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

Citations13
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the American Animal Hospital AssociationSame topicVeterinary Orthopedics and NeurologyFrench-language works237,207