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Record W2964068535 · doi:10.22215/etd/2014-10558

Complex Vibratory Signalling and Putative Receptor Mechanisms in the Masked Birch Caterpillar, Drepana Arcuata (Lepidoptera, Drepanidae)

2014· dissertation· en· W2964068535 on OpenAlexafffund
Christian Nathan

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect and Arachnid Ecology and Behavior
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyCaterpillarSetaMandible (arthropod mouthpart)AnatomyLepidoptera genitaliaZoologyEvolutionary biologyNeuroscienceEcologyGenus

Abstract

fetched live from OpenAlex

The masked birch caterpillar, Drepana arcuata, uses 3 distinct signals when defending its territory from conspecific intruders.The 3 signals are anal scrape, mandible drum and mandible scrape.This study's goals were twofold: first, to test hypotheses on the functional significance of these complex signals, and second, to identify putative vibration receptors in the proleg.Based on experimental trials of size asymmetry certain signal characteristics of the mandible drum and anal scrape were observed to vary between individuals of different mass suggesting the 3 signals could be a result of content based selection and that size information is conferred during an interaction.Trials where the measuring distance was varied, only 2 characteristics of the anal scrape differed significantly between the four recording distances.A dissection study of the proleg discovered that both internal and external structures were innervated.Innervated setae and putative chordotonal organs may function as a multi-component receptor.amazing guidance and helpful comments all throughout my studies here at Carleton University.Thank you for introducing me to the importance of research and publishing as well as sharing this information with a vibrant scientific community.I would also like to thank my committee member Dr. Gabriel Blouin-Demers for providing me helpful feedback and advice on statistics.I would like to thank Dr. Jeff Dawson for his constant support and for answering my questions.I am very grateful to the members of the Yack lab who provided support over the years as well as help when editing figures, taking photos with the Zeiss camera and providing constructive feedback.The Yack lab is truly a

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.015
GPT teacher head0.264
Teacher spread0.249 · 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

Citations0
Published2014
Admission routes2
Has abstractyes

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