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Record W4412079222 · doi:10.1101/2025.07.03.663096

Fish locomotor variation: connecting energetics and kinematic modulation

2025· preprint· en· W4412079222 on OpenAlexfundno aff
Yangfan Zhang, Divya Ramesh, Hungtang Ko, George Lauder

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2025
Typepreprint
Languageen
FieldEngineering
TopicRobotic Locomotion and Control
Canadian institutionsnot available
FundersOffice of Naval ResearchNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchNational Science Foundation
KeywordsEnergeticsKinematicsFish <Actinopterygii>Variation (astronomy)Modulation (music)FisheryEcologyBiologyPhysicsClassical mechanics

Abstract

fetched live from OpenAlex

Abstract Analyses of vertebrate locomotion have frequently revealed variations in locomotor energetics and movement both among individuals and through time within an individual. This variation is often collapsed into mean values for broad comparative analyses of function. However, kinematic patterns of locomotion, even when animals move at a near-constant mean speed, frequently vary with both the physical and biological context. Here we demonstrate, using analyses of fish locomotion and energetics, how variation among individuals in kinematic gaits can manifest as changes in dynamics of metabolic rate (estimated from oxygen uptake). We present kinematic data from a small school of giant danio ( Devario aequipinnatus ) to show that fish within a school frequently modulate their kinematics and change position, even when the school moves at an overall constant mean speed. We show that rainbow trout ( Oncorhynchus mykiss ), swimming over a range of speeds, exhibit considerable variation in tail beat frequency and metabolic rate among speeds. By experimentally altering the fluid dynamic environment, we demonstrate that brook trout ( Salvelinus fontinalis ) show correlated modulation of both kinematics and metabolic rate. Simultaneous measurement of energetic and biomechanical characteristics can unveil the physiological, biomechanical, and fluid dynamic mechanisms that underlie dynamic changes in vertebrate locomotor gaits.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.577
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
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 head0.008
GPT teacher head0.192
Teacher spread0.184 · 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.

Study designSimulation or modeling
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

Citations1
Published2025
Admission routes1
Has abstractyes

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