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Record W2574964294 · doi:10.1139/cjas-2016-0062

Off track training ameliorates emotional excitability in Purebred Arabian racehorses

2016· article· en· W2574964294 on OpenAlexvenueno aff
Iwona Janczarek, Izabela Wilk, Witold Kędzierski, Anna Stachurska, S Kowalik

Bibliographic record

VenueCanadian Journal of Animal Science · 2016
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Equine Medical Research
Canadian institutionsnot available
FundersNarodowe Centrum Badań i Rozwoju
KeywordsHeart ratePurebredTraining (meteorology)Heart rate variabilityPsychologyMedicinePhysical therapyPhysical medicine and rehabilitationAnimal scienceBiologyInternal medicine

Abstract

fetched live from OpenAlex

The aim of this study was to compare emotional excitability in purebred Arabian racehorses trained either with a standard method or with additional off-racetrack training. The study was carried out on 46 horses that were trained for racing in a home stud. The control group (CN, n = 23) was trained only on the training racetrack, whereas for the experimental group (EX, n = 23), the training schedule was alternated between work on the training track and off-racetrack training in a forest. The emotional excitability in horses was determined according to the heart rate (HR) and heart rate variability (HRV). The measurements (six times every 30 d) were taken at rest, during grooming and saddling, and during mounting and walking with a rider. The behavior of horses was also assessed. Higher activity of the parasympathetic nervous systems was found in EX horses during procedures preceding the training. This effect disappeared and the results paralleled those of CN horses once the training session with a rider began. The tested modification of the race training had a positive impact on the horse behavior of the horse during grooming, saddling, mounting, and walking with a rider. However, the modification influenced the autonomic system activity of horses only at rest and during the procedures preceding training sessions, whereas the effect was not seen during mounting and walking.

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)0.003
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.952
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.155
GPT teacher head0.377
Teacher spread0.223 · 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.

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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