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Record W7049042955

The nature and function of song diversity in southern house wrens (Troglodytes aedon chilensis)

2018· dissertation· en· W7049042955 on OpenAlexfundno aff

Bibliographic record

VenueOpen ULeth Scholarship (OPUS) (University of Lethbridge) · 2018
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaConselho Nacional de Desenvolvimento Científico e TecnológicoFondo para la Investigación Científica y TecnológicaConsejo Nacional de Investigaciones Científicas y TécnicasUniversity of Lethbridge
KeywordsTroglodytesSexual selectionSongbirdPopulationMate choiceDiversity (politics)Selection (genetic algorithm)
DOInot available

Abstract

fetched live from OpenAlex

This thesis focused on an austral population of House Wrens breeding in the south-temperate zone in Mendoza, Argentina. A description of song organization and complexity is provided for males in this population, and comparisons are made to song patterns reported for House Wrens in the north-temperate zone. Song patterns were remarkably similar between the two zones. Further analyses revealed significant correlations between metrics of song complexity and breeding success in the focal population of House Wrens in Argentina. The latter findings suggest that pressures of sexual selection have affected song evolution in this austral population of House Wrens in ways similar to reported sexually selected effects on song for north-temperate songbird species. This outcome is not well accommodated by current theory. These findings underscore how traditional theory concerning the evolution of song could be expanded through additional studies on South American populations and species, which have been understudied to date.

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)0.000
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 score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.017
GPT teacher head0.257
Teacher spread0.240 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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