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Record W4387311099 · doi:10.3390/f14101991

Barcoding Hymenoptera: 11 Malaise Traps in Three Thai Forests: The First 68 Trap Weeks and 15,338 Parasitoid Wasp Sequences

2023· article· en· W4387311099 on OpenAlexafffund
Donаld L. J. Quicke, Paul D. N. Hebert, Mikko Pentinsaari, Buntikа А. Butcher

Bibliographic record

VenueForests · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicHymenoptera taxonomy and phylogeny
Canadian institutionsUniversity of Guelph
FundersNational Research Council of ThailandChulalongkorn UniversityCanada Foundation for InnovationThailand Institute of Scientific and Technological ResearchGordon and Betty Moore Foundation
KeywordsParasitoidHymenopteraIchneumonidaeBiologyDNA barcodingEulophidaeBraconidaeScelionidaeEcologyParasitoid waspZoology

Abstract

fetched live from OpenAlex

We report the results of DNA barcoding week-long Malaise trap catches from 11 sites in three Thai conservation areas, concentrating on the parasitoid Hymenoptera, particularly the superfamily Ichneumonoidea. From a total of 15,338 parasitoid wasp sequences, 13,473 were barcode compliant and could be assigned to a family based on morphology and sequence data. These collectively represented 4917 unique BINs (putative species) in 46 families, with the Scelionidae, Ichneumonidae, Eulophidae, Braconidae and Platygastridae being, by far, the most abundant. Spatial proximity had a strong positive effect on the numbers of BINs shared between traps.

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 score0.227
Threshold uncertainty score0.786

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.030
GPT teacher head0.231
Teacher spread0.201 · 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

Citations9
Published2023
Admission routes2
Has abstractyes

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