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Record W2513343589 · doi:10.1080/1357650x.2016.1219740

The mane effect in the horse (<i>Equus ferus caballus</i>): Right mane dominance enhanced in mares but not associated with left and right manoeuvres in a reining competition

2016· article· en· W2513343589 on OpenAlexafffund
Ian Q. Whishaw, Bryan Kolb

Bibliographic record

VenueLaterality Asymmetries of Body Brain and Cognition · 2016
Typearticle
Languageen
FieldNeuroscience
TopicHemispheric Asymmetry in Neuroscience
Canadian institutionsUniversity of Lethbridge
FundersUniversity of LethbridgeUniversity of Kentucky
KeywordsLateralityLateralization of brain functionAnatomyEquusClockwisePsychologyBiologyAudiologyNeuroscienceZoologyMedicineMathematicsGeometry

Abstract

fetched live from OpenAlex

A human physical asymmetry is the near 90% clockwise occipitoparietal scalp hair-whorl direction in Europeans, an incidence that approximates the left lateralization of speech and right-handedness. Hair-whorl direction is also asymmetric in horses, Equus ferus caballus and placement is proposed to be related to temperament and lateralized skill in equitation manoeuvres. We describe a hair-whorl asymmetry in the horse, mane direction. Of 526, 3-year-old American Quarter horses, 69% of horses had mane directed to the right and 31% had mane directed to the left. The bias was larger in females, with 74% of females vs. 65% of males having mane directed to the right. Mane direction was unrelated to coat colour. The behavioural significance of mane asymmetry was investigated using judges' scores from a reining competition requiring symmetrical maneuvers of spin, circle and roll-back to either the left or to the right. There was no relation between mane asymmetry and overall reining performance and no relation between mane direction and scores for left or right manoeuvres. The results are discussed in relation to the significance of morphological asymmetries, neural function and the influence of planar cell polarity genes, such as Frizzled, that influence epidermal hair cell patterning.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.310
Threshold uncertainty score0.586

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.009
GPT teacher head0.234
Teacher spread0.225 · 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 designBench or experimental
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

Citations3
Published2016
Admission routes2
Has abstractyes

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