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Record W2108783974 · doi:10.1242/jeb.082735

The energetics of electric organ discharge generation in gymnotiform weakly electric fish

2013· review· en· W2108783974 on OpenAlexafffund
Vielka L. Salazar, Rüdiger Krahe, John E. Lewis

Bibliographic record

VenueJournal of Experimental Biology · 2013
Typereview
Languageen
FieldEnvironmental Science
TopicFish biology, ecology, and behavior
Canadian institutionsMcGill UniversityUniversity of OttawaCape Breton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsElectric fishElectric organEnergeticsFish <Actinopterygii>BiologyElectric dischargeZoologyPhysicsEcologyFisheryGenetics

Abstract

fetched live from OpenAlex

Gymnotiform weakly electric fish produce an electric signal to sense their environment and communicate with conspecifics. Although the generation of such relatively large electric signals over an entire lifetime is expected to be energetically costly, supporting evidence to date is equivocal. In this article, we first provide a theoretical analysis of the energy budget underlying signal production. Our analysis suggests that wave-type and pulse-type species invest a similar fraction of metabolic resources into electric signal generation, supporting previous evidence of a trade-off between signal amplitude and frequency. We then consider a comparative and evolutionary framework in which to interpret and guide future studies. We suggest that species differences in signal generation and plasticity, when considered in an energetics context, will not only help to evaluate the role of energetic constraints in the evolution of signal diversity but also lead to important general insights into the energetics of bioelectric signal generation.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.927
Threshold uncertainty score0.830

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.030
GPT teacher head0.307
Teacher spread0.277 · 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 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

Citations71
Published2013
Admission routes2
Has abstractyes

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