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Record W2151998529 · doi:10.1371/journal.pbio.0040321

Morphological Evolution Is Accelerated among Island Mammals

2006· article· en· W2151998529 on OpenAlexafffund
Virginie Millien

Bibliographic record

VenuePLoS Biology · 2006
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicEvolution and Paleontology Studies
Canadian institutionsMcGill University
FundersMcGill University
KeywordsBiologyMammalEcologyMainlandContext (archaeology)HabitatEvolution of mammalsAdaptation (eye)Evolutionary biologyPaleontology

Abstract

fetched live from OpenAlex

Dramatic evolutionary changes occur in species isolated on islands, but it is not known if the rate of evolution is accelerated on islands relative to the mainland. Based on an extensive review of the literature, I used the fossil record combined with data from living species to test the hypothesis of an accelerated morphological evolution among island mammals. I demonstrate that rates of morphological evolution are significantly greater--up to a factor of 3.1--for islands than for mainland mammal populations. The tendency for faster evolution on islands holds over relatively short time scales--from a few decades up to several thousands of years--but not over larger ones--up to 12 million y. These analyses form the first empirical test of the long held supposition of accelerated evolution among island mammals. Moreover, this result shows that mammal species have the intrinsic capacity to evolve faster when confronted with a rapid change in their environment. This finding is relevant to our understanding of species' responses to isolation and destruction of natural habitats within the current context of rapid climate warming.

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 score0.006

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 studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.231
Teacher spread0.200 · 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

Citations301
Published2006
Admission routes2
Has abstractyes

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