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Reversal Frequency in<i>Caenorhabditis elegans</i>Represents an Integrated Response to the State of the Animal and Its Environment

2003· article· en· W4297832931 on OpenAlexafffund
Beibei Zhao, Parul Khare, Lisa Feldman, Joseph A. Dent

Bibliographic record

VenueJournal of Neuroscience · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsMcGill University
FundersNational Center for Research ResourcesCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsCaenorhabditis elegansCrawlingSet (abstract data type)BiologyAnimal behaviorNeuroscienceTrajectoryComputer scienceCommunicationPsychologyAnatomyPhysicsGeneticsZoology

Abstract

fetched live from OpenAlex

The locomotion of Caenorhabditis elegans consists of forward crawling punctuated by spontaneous reversals. To better understand the important variables that affect locomotion, we have described in detail the locomotory behavior of C. elegans and identified a set of parameters that are sufficient to describe the animal's trajectory. A model of locomotion based on these parameters indicates that reversal frequency plays a central role in locomotion. We found that several variables such as humidity, gravidity, and mechanostimulation influence reversal frequency. Specifically, both gentle and harsh touch can transiently suppress reversal frequency. Thus, reversal behavior is a model for the integration of information from numerous modalities reflecting diverse aspects of the state of an organism.

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 score0.003
Threshold uncertainty score0.006

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)0.0000.000

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 head0.012
GPT teacher head0.235
Teacher spread0.223 · 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

Citations103
Published2003
Admission routes2
Has abstractyes

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