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Record W4311681286 · doi:10.22215/etd/2022-15274

Signaling Vigor in Gryllodes Sigillatus: Relationship with Age and Foreign Body Ingestion

2022· dissertation· en· W4311681286 on OpenAlexaff
Alyssa Froome

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsCarleton University
Fundersnot available
KeywordsAttractivenessBiologyZoologyIngestionMate choiceMatingDemographyEcologyEndocrinologyPsychology

Abstract

fetched live from OpenAlex

Male Gryllidae acoustic signaling behaviour varies between and within species and may be influenced by a variety of factors including age, condition, and parasitism.I investigated variation within and among male Gryllodes sigillatus' mate attraction signaling behaviour and examined how variation in signaling vigour was influenced by age.I found extensive variation in male signaling between and within individuals; males differed in signaling vigour and quality, and their signaling changed over time.I found that smaller males signaled more consistently throughout their lives while larger males rarely called when younger and increased signaling vigour with age.As males have often been found to honestly signal their body condition (i.e., body mass), parasites may influence a male's perceived attractiveness to potential mates.I therefore also investigated how signaling vigour was influenced by the ingestion of the long barbed hastisetae from a typical pest species, dermestid (Dermestes ater), that plagues rearing facilities.These foreign bodies are regularly ingested during rearing.I found that males fed the highest concentration of dermestid hastisetae behaved differently than males in the control and high treatments.As individuals aged, smaller males greatly increased their signaling vigour and produced more attractive calls while larger males decreased their signaling vigour and produced less attractive calls.While further investigation into Gryllodes sigillatus signaling behaviour is needed, my results provide interesting insights into the factors shaping signaling variation in this species.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.027
GPT teacher head0.250
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

Citations1
Published2022
Admission routes1
Has abstractyes

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