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Record W2245821555 · doi:10.18474/0749-8004-45.1.1

Collection and Laboratory Culture of Ormia ochracea (Diptera: Tachinidae)

2010· article· en· W2245821555 on OpenAlexafffund
Crystal M. Vincent, Susan M. Bertram

Bibliographic record

VenueJournal of Entomological Science · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicDiptera species taxonomy and behavior
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Texas at Austin
KeywordsTachinidaeBiologyParasitismZoologyEcologyLarvaParasitoidHost (biology)

Abstract

fetched live from OpenAlex

The Family Tachinidae is one of the most speciose families in the Order Diptera with approximately 1300 species occurring in North America alone. Research on the species Ormia ochracea (Bigot) (Diptera: Tachinidae) has largely focused on the problems incurred by their hosts as a result of parasitism or on the mechanics of their hearing. Little research effort has been devoted to the behavior or life history of these flies. Part of the reason they have remained lightly researched is the difficultly in maintaining a laboratory culture. Herein, we provide a detailed guide to collecting O. ochracea in the field, culturing them in the laboratory, and maintaining stock populations for multiple generations. We also provide data on the effectiveness of capturing O. ochracea in wooded versus open field areas, as well as data on the effectiveness of manually parasitizing crickets with O. ochracea larvae to propagate stock fly populations in the laboratory. Our results suggest that during field collection, traps should broadcast calls in wooded areas; and that manual parasitization is an effective way of culturing small colonies of O. ochracea in the laboratory.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.004

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 head0.009
GPT teacher head0.232
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

Citations27
Published2010
Admission routes2
Has abstractyes

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