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Record W2140353501 · doi:10.1242/jeb.047910

Energetic cost of communication

2010· article· en· W2140353501 on OpenAlexaff
Philip K. Stoddard, Vielka L. Salazar

Bibliographic record

VenueJournal of Experimental Biology · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsCape Breton University
FundersDivision of Integrative Organismal SystemsNational Institute of General Medical SciencesNational Institutes of Health
KeywordsComputer scienceEnvironmental science

Abstract

fetched live from OpenAlex

Communication signals may be energetically expensive or inexpensive to produce, depending on the function of the signal and the competitive nature of the communication system. Males of sexually selected species may produce high-energy advertisement signals, both to enhance detectability and to signal their size and body condition. Accordingly, the proportion of the energy budget allocated to signal production ranges from almost nothing for many signals to somewhere in excess of 50% for acoustic signals in short-lived sexually selected species. Recent data from gymnotiform electric fish reveal mechanisms that regulate energy allocated to sexual advertisement signals through dynamical remodeling of the excitable membranes in the electric organ. Further, males of the short-lived sexually selected species, Brachyhypopomus gauderio, trade off among different metabolic compartments, allocating energy to signal production while reducing energy used in other metabolic functions. Female B. gauderio, by contrast, do not trade off energy between signaling and other functions. To fuel energetically expensive signal production, we expect a continuum of strategies to be adopted by animals of different life history strategies. Future studies should explore the relation between life history and energy allocation trade-offs.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.411

Codex and Gemma teacher scores by category

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 head0.028
GPT teacher head0.297
Teacher spread0.268 · 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 designBench or experimental
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

Citations74
Published2010
Admission routes1
Has abstractyes

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