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Record W4398238778 · doi:10.1093/ee/nvae018

A geometric morphometric analysis of wing variations in shape and size of the blue bottle fly, <i>Calliphora vicina</i> (Diptera: Calliphoridae)

2024· article· en· W4398238778 on OpenAlexaff
Maria Denise Gemmellaro, Elena Forzisi, Gail S. Anderson, George C. Hamilton, Lauren M. Weidner

Bibliographic record

VenueEnvironmental Entomology · 2024
Typearticle
Languageen
FieldMathematics
TopicMorphological variations and asymmetry
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsCalliphora vicinaWingCalliphoridaeBiologyAltitude (triangle)CalliphoraAnimal scienceApparent SizeZoologyAnatomyEcologyLarvaGeometryMathematics

Abstract

fetched live from OpenAlex

A geometric morphometric analysis was performed on the right wing of adult Calliphora vicina (Robineau-Desvoidy) collected across 4 altitudinal levels in Sicily. The objective of this study was to assess differences in shape and centroid size (CS) between females and males and across elevations. The wings analyzed in this study were removed from adults of C. vicina collected with baited traps at 20, 700, 1,153, and 1,552; for this study, 19 landmarks were identified in each wing. The coordinates of the landmarks were aligned and superimposed to prevent variations due to position, orientation, and scale; they were then scaled to the same CS and recentered. CS and Procrustes differences were, respectively, used to assess variations in size and shape. Significant differences were observed in wing shape between males and females but not between all altitudinal levels. Female wings were found to be significantly larger than males (P < 0.01). Wings of flies collected at the highest altitudinal level resulted in significantly larger wings than those collected at lower altitudes (P < 0.001), with CS values ranging from 12.1 to 14.1. Variation in wing shape can impact thermal regulation, and therefore, oxygen content, temperature, atmospheric pressure, and solar radiation can have an effect on an insect's body and activity levels. At high elevations and lower temperatures, larger wings could mean less energy expenditure when flying to increase body temperature.

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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.255
Teacher spread0.240 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

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