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Record W2908073242 · doi:10.1111/evo.13669

Integration and modularity of teleostean pectoral fin shape and its role in the diversification of acanthomorph fishes

2018· article· en· W2908073242 on OpenAlexafffund
Trina Y. Du, Sylvie C. Tissandier, Hans C. E. Larsson

Bibliographic record

VenueEvolution · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicPaleontology and Evolutionary Biology
Canadian institutionsMcGill UniversityUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of AlbertaField Museum
KeywordsBiologyDiversification (marketing strategy)Modularity (biology)Fish finFinEvolutionary biologyZoologyFish <Actinopterygii>FisheryMarketingBusiness

Abstract

fetched live from OpenAlex

Phenotypic integration and modularity describe the strength and pattern of interdependencies between traits. Integration and modularity have been proposed to influence the trajectory of evolution, either acting as constraints or facilitators. Here, we examine trends in the integration and modularity of pectoral fin morphology in teleost fishes using geometric morphometrics. We compare the fin shapes of the highly diverse radiation of acanthomorph fishes to lower teleosts. Integration and modularity are measured using two-block partial least squares analysis and the covariance ratio coefficient between the radial bones and lepidotrichia of the pectoral fins. We show that the fins of acanthomorph fishes are more tightly integrated but also more morphologically diverse and faster evolving compared to nonacanthomorph fishes. The main pattern of shape covariation in nonacanthomorphs is concordant with the main trajectory of evolution between nonacanthomorphs and acanthomorphs. Our findings support a facilitating role for integration during the acanthomorph diversification. Potential functional consequences and developmental mechanisms of fin integration are discussed.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.042
Threshold uncertainty score0.606

Codex and Gemma teacher scores by category

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

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 head0.018
GPT teacher head0.218
Teacher spread0.199 · 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 teacher head, 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

Citations19
Published2018
Admission routes2
Has abstractyes

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