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Record W2084409992 · doi:10.1371/journal.pone.0024778

Personality May Confound Common Measures of Mate-Choice

2011· article· en· W2084409992 on OpenAlexaff
Morgan David, Frank Cézilly

Bibliographic record

VenuePLoS ONE · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsMate choicePreferencePersonalityTraitSexual selectionAffect (linguistics)Zebra finchTaeniopygiaAttractivenessMatingVariation (astronomy)PsychologyConsistency (knowledge bases)Mating preferencesBig Five personality traitsBiologyDevelopmental psychologySocial psychologyZoologyStatisticsComputer scienceCommunication

Abstract

fetched live from OpenAlex

The measurement of female mating preferences is central to the study of the evolution of male ornaments. Although several different methods have been developed to assess sexual preference in some standardized way, the most commonly used procedure consists of recording female spatial association with different males presented simultaneously. Sexual preference is then inferred from time spent in front of each male. However, the extent to which the measurement of female mate-choice is related to exploration tendencies has not been addressed so far. In the present study we assessed the influence of variation in exploration tendencies, a trait closely associated to global personality, on the measurement of female mating preference in the zebra finch (Taeniopygia guttata) using the widely used four-chamber choice-apparatus. The number of movements performed within both exploration and mate-choice apparatus was consistent within and across the two contexts. In addition, personality explained variation in selectivity, preference strength and consistency. High-exploratory females showed lower selectivity, lower preference scores and displayed more consistent preference scores. Our results suggest that variation in personality may affect the measurement of female mating preference and may contribute to explain existing inconsistencies across studies.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.489
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.287
GPT teacher head0.258
Teacher spread0.028 · 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

Citations40
Published2011
Admission routes1
Has abstractyes

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