MétaCan
Menu
Back to cohort
Record W4207023711 · doi:10.1093/jme/tjab233

Development of a Simple Trap That Captures Ticks (Acari) on Their Dorsal Surface

2022· article· en· W4207023711 on OpenAlexaff
Matthew W. Yans, Alyssa S Branca, Noel Hahn, Sydney E Crawley, Anastasia C Figurskey, Kenneth R. Hobson, Michael G Banfield, John H. Borden

Bibliographic record

VenueJournal of Medical Entomology · 2022
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Vectors
Canadian institutionsSimon Fraser University
FundersNational Institute of Food and AgricultureU.S. Department of Agriculture
KeywordsAcariBiologyIxodidaeNymphParasitiformesTrap (plumbing)EcologyPhysics

Abstract

fetched live from OpenAlex

We tested two versions of a trap that captures climbing ticks on their dorsum. A prototype based on a decades old model had three components, a truncated pyramidal base with steep sloping walls, downward facing sticky-tape extending beyond and spanning the boundary of the flat upper surface, on which ticks become dorsally immobilized, and a reservoir for gaseous CO2 emission from dry ice that rests on the flat upper surface. A preoperational trap was made of thermoformed plastic and differed from the prototype by its circular structure, a central depression suitable for future housing of a biotic CO2 generator and supplemental volatile lures and a transparent sticky ceiling that enables ticks to exhibit a phototactic response and allows users to see captured ticks without disturbing the traps. Field testing of the prototype in Florida and both trap types in Oklahoma and North Carolina achieved high catches of lone star ticks, Amblyomma americanum (L.) (Acari: Ixodidae), e.g. mean catches of >70 ticks (adults plus nymphs) in 4 h in both the prototype and preoperational traps in North Carolina, and significantly higher yields of ticks than on dry ice baited 1 m2 white sheets.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.046
GPT teacher head0.330
Teacher spread0.284 · 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 designBench or experimental
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

Citations7
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Medical EntomologySame topicViral Infections and VectorsFrench-language works237,207