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Record W6911169658 · doi:10.5061/dryad.v5h5f

Data from: Closely related species of birds differ more in body size when their ranges overlap—in warm, but not cool, climates

2015· dataset· en· W6911169658 on OpenAlexaff

Bibliographic record

VenueData Archiving and Networked Services (DANS) · 2015
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversity of GuelphQueen's University
Fundersnot available
KeywordsAllopatric speciationSympatric speciationSympatryDivergence (linguistics)NicheBergmann's ruleLineage (genetic)

Abstract

fetched live from OpenAlex

Differences in body size are widely thought to allow closely related species to coexist in sympatry, but body size also varies as an adaptive response to climate. Here, we use a sister lineage approach to test the prediction that body size differences between closely related species of birds worldwide are greater for species whose ranges are sympatric rather than allopatric. We further test if body size differences among sympatric versus allopatric species vary with geography, evolutionary distance, and environmental temperatures. We find greater differences in size among sympatric compared with allopatric lineages, but only in closely related species that live where mean annual temperatures are above 25°C. These size differences in warm environments declined with the evolutionary distance between sister lineages. In species living in cooler regions, closely related allopatric and sympatric species did not differ significantly in size, suggesting either that colder temperatures constrain the evolutionary divergence of size in sympatry, or that the biotic selective pressures favoring size differences in sympatry are weaker in colder environments. Our results are consistent with suggestions by Wallace, Darwin, and Dobzhansky that climatic selective pressures are more important in cooler environments (e.g., high elevations and latitudes) while biotic selective pressures dominate in warm environments (e.g., lowland tropics).

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.057
Threshold uncertainty score0.192

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0570.040

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 head0.051
GPT teacher head0.284
Teacher spread0.233 · 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 designNot applicable
Domainnot available
GenreDataset

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
Published2015
Admission routes1
Has abstractyes

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