MétaCan
Menu
Back to cohort
Record W4412823182 · doi:10.1098/rsos.251005

Reliable reconstruction of cricket song from biophysical models and preserved specimens

2025· article· en· W4412823182 on OpenAlexafffund
Sara E. Duke, Nathan W. Bailey, Natasha Mhatre

Bibliographic record

VenueRoyal Society Open Science · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicOrthoptera Research and Taxonomy
Canadian institutionsWestern University
FundersNatural Environment Research CouncilWestern UniversityNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsFinite element methodCricketComputer scienceField (mathematics)Field cricketBiological systemArtificial intelligenceBiologyEcologyMathematicsStructural engineeringEngineering

Abstract

fetched live from OpenAlex

Predicting the function of a biological structure solely from its morphology can be a very powerful tool in several fields of biology, but especially in evolutionary reconstruction. In the field of invertebrate acoustic communication, reconstructing the acoustic properties of sound-producing forewings in crickets has been based on two very divergent methods, finite element modelling (FEM) and vibrometric measurements from preserved specimens. Both methods, however, make strong simplifying assumptions that have not been tested and the reliability of inferences made from either method remains in question. Here, we rigorously test and refine both reconstruction methods using the well-known Teleogryllus oceanicus model system and determine the appropriate conditions required to reconstruct the vibroacoustic behaviour of male forewings. We find that when using FEM it is not necessary to assume simplified boundary conditions if the appropriate parameters are found. When using preserved specimens, we find that the sample needs to be rehydrated for reliable reconstruction; however, it may be possible to accomplish rehydration in silico using FEM. Our findings provide a refined methodology for the reliable reconstruction of cricket songs, whether from fossils or preserved specimens from museums or field collections.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.558
Threshold uncertainty score0.577

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.038
GPT teacher head0.270
Teacher spread0.232 · 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 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

Citations1
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueRoyal Society Open ScienceSame topicOrthoptera Research and TaxonomyFrench-language works237,207