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Record W2063831212 · doi:10.1017/s0007485310000714

DNA barcodes for two scale insect families, mealybugs (Hemiptera: Pseudococcidae) and armored scales (Hemiptera: Diaspididae)

2011· article· en· W2063831212 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBulletin of Entomological Research · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicResearch on scale insects
Canadian institutionsUniversity of Guelph
FundersOntario Genomics InstituteGenome Canada
KeywordsDiaspididaeBiologyHemipteraScale insectMealybugBarcodeDNA barcodingInsectEcologyZoologyBotanyHomopteraPEST analysis

Abstract

fetched live from OpenAlex

Although DNA barcode coverage has grown rapidly for many insect orders, there are some groups, such as scale insects, where sequence recovery has been difficult. However, using a recently developed primer set, we recovered barcode records from 373 specimens, providing coverage for 75 species from 31 genera in two families. Overall success was >90% for mealybugs and >80% for armored scale species. The G·C content was very low in most species, averaging just 16.3%. Sequence divergences (K2P) between congeneric species averaged 10.7%, while intra-specific divergences averaged 0.97%. However, the latter value was inflated by high intra-specific divergence in nine taxa, cases that may indicate species overlooked by current taxonomic treatments. Our study establishes the feasibility of developing a comprehensive barcode library for scale insects and indicates that its construction will both create an effective system for identifying scale insects and reveal taxonomic situations worthy of deeper analysis.

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.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.548
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.138
GPT teacher head0.332
Teacher spread0.194 · 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