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Record W2517676488 · doi:10.14446/fi.2016.108

Frog origins: inferences based on ancestral reconstructions of locomotor performance and anatomy

2016· article· en· W2517676488 on OpenAlexaff
Anthony Herrel, C. Moureaux, Michel Laurin, Gheylen Daghfous, Kristen E. Crandell, Krystal A. Tolley, John Measey, Bike Vanhooydonck, Renaud Boistel

Bibliographic record

VenueFossil Imprint · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicAmphibian and Reptile Biology
Canadian institutionsUniversité de Montréal
FundersMuséum National d'Histoire NaturelleAgence Nationale de la Recherche
KeywordsAnatomyBiologyEvolutionary biologyNeurosciencePaleontology

Abstract

fetched live from OpenAlex

Frogs are the most species-rich and ecologically diverse group of amphibians and are characterized by a unique body plan including long legs, elongated ilia, and fused caudal vertebrae. Stem anurans such as Triadobatrachus or Czatkobatrachus have been suggested to have used jumping or hopping as part of their locomotor repertoire based on their anatomy. The earliest known true frog, Prosalirus bitis was suggested to have been a proficient jumper. However, data on jumping performance in frogs have never been used to attempt reconstruction of ancestral features at the base of the radiation. Here we provide data on jumping performance (forces and acceleration) in 20 species of extant frogs including representatives of most of the early radiating clades. We next use ancestral character value inferences to assess ancestral features. Our analyses suggest that frog ancestors were of small to medium size, had relatively short limbs, produced rather low jump forces, yet were capable of relatively high acceleration. Given the short limbs and low forces, the unique frog bauplan with a reduced vertebral column and a mobile ilio-sacral joint may not have been an adaptation for powerful jumping.

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 score0.222
Threshold uncertainty score0.913

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 studies0.0000.001
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 head0.012
GPT teacher head0.234
Teacher spread0.222 · 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

Citations18
Published2016
Admission routes1
Has abstractyes

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