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Record W2117752012 · doi:10.4039/ent134647-5

Leaping behaviour and responses to moisture and sound in larvae of piophilid carrion flies

2002· article· en· W2117752012 on OpenAlexafffund
Russell Bonduriansky

Bibliographic record

VenueThe Canadian Entomologist · 2002
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForensic Entomology and Diptera Studies
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Guelph
KeywordsLarvaCarrionPredationPupaBiologyMoistureOntogenyEcologySound (geography)ZoologyMeteorologyGeologyOceanographyGeography

Abstract

fetched live from OpenAlex

Abstract Observations suggesting that mature larvae of some carrion flies (Piophilidae) tend to leap off carcasses during rain motivated an investigation of the ontogeny and possible functions of larval leaping behaviour and larval responses to two stimuli associated with rain: moisture and sound. These behaviours were investigated in larvae of Prochyliza xanthostoma Walker (Diptera: Piophilidae) by means of laboratory and field observations and experiments. Mature larvae left their feeding substrates (rotting meat) in response to either moisture or rattling sound. The response to moisture was exhibited also by immature larvae. Once on the carcass surface, however, only mature larvae leaped off and pupated in the surrounding soil. The response to sound and the ability to leap only appeared late in larval development and were lost in the prepupal stage. Because rain may facilitate larval locomotion on carcass surfaces, and leaping appears to represent a more rapid and efficient means of leaving a carcass than creeping, these responses may reduce the metabolic costs and predation risks experienced by mature larvae moving to pupation sites in the soil. Thus, the ability to leap and the responses to moisture and sound may represent “ontogenetic adaptations” associated with a brief stage of larval development.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.692
Threshold uncertainty score0.775

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 head0.037
GPT teacher head0.237
Teacher spread0.199 · 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

Citations31
Published2002
Admission routes2
Has abstractyes

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