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Record W4366351949 · doi:10.1242/jeb.245731

Rapid manoeuvre of fan worms (Annelida: Sabellidae) through tubes

2023· article· en· W4366351949 on OpenAlexaff
Wei Jiang, Yu Sun, Zhigang Wu, Zhao Pan, Michael J. Bok, Jianing Wu

Bibliographic record

VenueJournal of Experimental Biology · 2023
Typearticle
Languageen
FieldEngineering
TopicSoft Robotics and Applications
Canadian institutionsUniversity of Waterloo
FundersSun Yat-sen UniversityNational Natural Science Foundation of China
KeywordsBiologyDragAnatomyMarine engineeringMechanicsPhysicsEngineering

Abstract

fetched live from OpenAlex

Multiple variables determine the success of an escape response of an animal, and the rapidity of the escape manoeuvre is often the most important. Fan worms (Annelida: Sabellidae) can rapidly withdraw their tentacles, which are covered in heavily ciliated ramifications called pinnules, into their tubes to protect them from approaching threats. Here, we explore the dynamic and mechanistic features behind this escape manoeuvre. The escape responses of fan worms were recorded by high-speed videography and quantified by computerized motion analysis, showing an ultrahigh retraction speed of 272±135 mm s-1 (8±4 body lengths s-1). We found that fan worms possess powerful muscle-driven systems, which can generate contractive forces up to 36 times their body weight. In order to achieve these rapid, forceful movements through seawater without damaging their tentacles, fan worms have developed functional morphological adaptations to reduce fluidic drag, including the flattening of their radiolar pinnules and the deformation of bodily segmental ridges. Our hydrodynamic models indicate that these mechanical processes can decrease fluidic drag by 47%, trapped mass by 75% and friction coefficient by 89%. These strategies allow fan worms to execute rapid escape responses and could inspire the design of fast in-pipe robots.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.027
GPT teacher head0.289
Teacher spread0.261 · 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 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

Citations5
Published2023
Admission routes1
Has abstractyes

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