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Record W2510265391 · doi:10.1163/1568539x-00003394

Evolution of white-throated sparrow song: regional variation through shift in terminal strophe type and length

2016· article· en· W2510265391 on OpenAlexaffabout
Hannah D. Zimmerman, Scott M. Ramsay, Veronica Mesias, Marcelo Mora, Brent W. Murray, Ken A. Otter

Bibliographic record

VenueBehaviour · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Vocal Communication and Behavior
Canadian institutionsUniversity of British ColumbiaWilfrid Laurier UniversityUniversity of Northern British Columbia
Fundersnot available
KeywordsSingingSparrowWhite (mutation)PopulationVariation (astronomy)Selection (genetic algorithm)BiologyEvolutionary biologyGeographyDemographyZoologyGeneticsPhysicsAstrophysics

Abstract

fetched live from OpenAlex

We investigated the emergence over time of a novel song variant (doublet-ending song) in a western Canadian sub-population of white-throated sparrows; this variant differs from the species-typical, triplet-ending song. By analysing recent (1999–2014) and historic (1950/1960s) recordings, we show that populations west (British Columbia) and immediately east (Alberta) of the Rockies, and from central Canada (Ontario) initially all had triplet-ending songs. The shift to doublet-ending songs first arose west of the Rockies, and has increased immediately east of the Rockies in the last decade. The Ontario population retained predominantly triplet-ending songs. Note lengths have increased over time in all populations, while inter-strophe interval has decreased, allowing doublet-ending birds the ability to have greater strophe repeats for a given song length. We explore whether the emergence and apparent spread of the doublet-ending songs can be explained by cultural drift, or may be under selection by conveying an advantage during counter-singing.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.376
Threshold uncertainty score0.747

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
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 head0.031
GPT teacher head0.288
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 source (direct Gemma or distilled Codex), 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

Citations9
Published2016
Admission routes2
Has abstractyes

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