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Record W2010124986 · doi:10.1139/cjz-2014-0260

Diverse anguilliform swimming kinematics in Pacific hagfish (<i>Eptatretus</i><i> stoutii</i>) and Atlantic hagfish (<i>Myxine</i><i> glutinosa</i>)

2015· article· en· W2010124986 on OpenAlexaffvenue
Jeanette Li Li Lim, Timothy M. Winegard

Bibliographic record

VenueCanadian Journal of Zoology · 2015
Typearticle
Languageen
FieldEngineering
TopicBiomimetic flight and propulsion mechanisms
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsHagfishFish locomotionBiologyKinematicsAnatomyFisheryVertebratePhysicsFish <Actinopterygii>Classical mechanics

Abstract

fetched live from OpenAlex

Anguilliform mode swimmers pass waves of lateral bending down their elongate bodies to propel forward. Hagfishes (Myxinidae) are classified as anguilliform swimmers, but their unique habits and reduced morphology—including a flexible body lacking a vertebral column—have the potential to translate into unique swimming behaviour within this broad classification. Their roles as active scavengers and hunters can require considerable bouts of swimming, yet quantitative data on hagfish locomotion are limited. Here, we aim to provide a more complete mechanistic understanding of hagfish swimming by quantifying whole-body kinematics of steady swimming in Pacific hagfish (Eptatretus stoutii (Lockington, 1878)) and Atlantic hagfish (Myxine glutinosa L., 1758), species from the two main lineages of Myxinidae. We analyzed high-speed video of hagfishes swimming at voluntary swim speeds and found that both species swim using high-amplitude undulatory waves. Swim speed is generally frequency-modulated, but patterns in wave speed, wavelength, and amplitude along the body and across swim speeds are variable, implying versatile mechanisms for the control of swim speed in these highly flexible fishes. We propose mechanistic explanations for this kinematic variability and compare hagfish with other elongate swimmers, demonstrating that the hagfish’s rich locomotory repertoire adds variety to the already diverse set of locomotory kinematics found in anguilliform swimmers.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.474
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
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 head0.015
GPT teacher head0.190
Teacher spread0.175 · 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

Citations14
Published2015
Admission routes2
Has abstractyes

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