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Record W2983915096 · doi:10.1139/cjz-2019-0018

Song characters as reliable indicators of male reproductive quality in the Savannah Sparrow (<i>Passerculus</i> <i>sandwichensis</i>)

2019· article· en· W2983915096 on OpenAlexaffvenueabout
Ha‐Cheol Sung, Paul Handford

Bibliographic record

VenueCanadian Journal of Zoology · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Vocal Communication and Behavior
Canadian institutionsWestern University
Fundersnot available
KeywordsSparrowBiologyReproductive successSexual selectionMatingMate choiceZoologyEcologyPopulationDemography

Abstract

fetched live from OpenAlex

Bird song may provide female birds with signals of male quality. To investigate this potential for sexual selection via female choice, we assessed the relationships between male song variation and male mating and reproductive success of the Savannah Sparrow (Passerculus sandwichensis (J.F. Gmelin, 1789)) over 3 years (2001–2003) in a population of Savannah Sparrows near London, Ontario, Canada. We measured song rate, as well as temporal and frequency attributes of song structure, as possible predictors of male quality, and then related these measures to attributes of male reproductive performance (mating and breeding success and territory size of males). We found significant correlations between male reproductive performance and several song features, such that the combined effects of two trill sections could potentially play an important role: males possessing such songs arrived and paired earlier and had higher fledging success. The results suggested that the trill segments of the song may signal important aspects of male quality. Possible reasons for significant roles of such songs in open-habitat birds are discussed.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.087
Threshold uncertainty score0.496

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.016
GPT teacher head0.272
Teacher spread0.256 · 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
Published2019
Admission routes3
Has abstractyes

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