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Record W2070124772 · doi:10.1002/bies.20036

Left and right in the amphibian world: which way to develop and where to turn?

2004· review· en· W2070124772 on OpenAlexaff
Yegor Malashichev, Richard J. Wassersug

Bibliographic record

VenueBioEssays · 2004
Typereview
Languageen
FieldNeuroscience
TopicHemispheric Asymmetry in Neuroscience
Canadian institutionsDalhousie University
Fundersnot available
KeywordsChordateBiologyLateralityAmphibianVertebrateEvolutionary biologyNeuroscienceEcology

Abstract

fetched live from OpenAlex

The last decade has seen a dramatic increase in studies on the development, function and evolution of asymmetries in vertebrates, including amphibians. Here we discuss current knowledge of behavioral and anatomical asymmetries in amphibians. Behavioral laterality in the response of both adult and larval anurans to presumed predators and competitors is strong and may be related, respectively, to laterality in the telencephalon of adults and the Mauthner neurons of tadpoles. These behavior lateralities, however, do not seem to correlate with visceral asymmetries in the same animals. We briefly compare what is known about the evolution and development of asymmetry in the structure and function of amphibians with what is known about asymmetries in other chordate and non-chordate groups. Available data suggest that the majority of asymmetries in amphibians fall into two independent groups: (1) related to situs viscerum and (2) of a neurobehavioral nature. We find little evidence linking these two groups, which implies different developmental regulatory pathways and independent evolutionary histories for visceral and telencephalic lateralizations. Studies of animals other than standard model species are essential to test hypotheses about the evolution of laterality in amphibians and other chordates.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.003

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 head0.046
GPT teacher head0.330
Teacher spread0.284 · 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
GenreReview

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

Citations34
Published2004
Admission routes1
Has abstractyes

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