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Evolution of bite force in Darwin's finches: a key role for head width

2005· article· en· W2161109113 on OpenAlexafffund
Anthony Herrel, Jeffrey Podos, Sarah K. Huber, Andrew P. Hendry

Bibliographic record

VenueJournal of Evolutionary Biology · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsMcGill University
FundersUniversity of Massachusetts AmherstMcGill UniversityNational Park ServiceNational Science Foundation
KeywordsBeakBiologyFinchNatural selectionBite force quotientDarwin (ADL)Head (geology)Evolutionary biologyZoologySelection (genetic algorithm)EcologyPaleontology

Abstract

fetched live from OpenAlex

Studies of Darwin's finches of the Galapagos Islands have provided pivotal insights into the interplay of ecological variation, natural selection, and morphological evolution. Here we document, across nine Darwin's finch species, correlations between morphological variation and bite force capacity. We find that bite force correlates strongly with beak depth and width but only weakly or not at all with beak length, a result that is consistent with prior demonstrations of natural selection on finch beak morphology. We also find that bite force is predicted even more strongly by head width, which exceeds all beak dimensions in predictive strength. To explain this result we suggest that head width determines the maximum size, and thus maximum force generation capacity of finch jaw adductor muscles. We suggest that head width is functionally relevant and may be a previously unrecognized locus of natural selection in these birds, because of its close relationship to bite force capacity.

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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.261
Teacher spread0.241 · 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

Citations170
Published2005
Admission routes2
Has abstractyes

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