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Record W2897482235 · doi:10.1093/jme/tjy164

Evaluating the Addition of CO2 to Black Light Traps for Sampling<i>Culicoides (Diptera: Ceratopogonidae) in</i>Alberta

2018· article· en· W2897482235 on OpenAlexaffabout
RAVINDRA SAMPATH WALGAMA, Tim Lysyk

Bibliographic record

VenueJournal of Medical Entomology · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicVector-Borne Animal Diseases
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsCeratopogonidaeCulicoidesAbundance (ecology)BiologyTrap (plumbing)EcologyRelative species abundanceEnvironmental science

Abstract

fetched live from OpenAlex

We examined the effect of augmenting black light trap with CO2 at two release rates for monitoring and surveillance of Culicoides at northern latitudes. Species composition was highly correlated among black light (BL) traps with no CO2 (BL0 traps) and traps augmented with 300 and 1000 ml/min CO2 (BL300 and BL1000 traps, respectively); however, traps augmented with CO2 captured one to three more rare species than BL0 traps and can detect rare species that might be missed if BL0 traps were used. Addition of CO2 increased the number of individuals captured from 1.4 to 38.5-fold for BL300 traps and from 1.5 to 153.5-fold for BL1000 traps. This advantage may be lost in areas with low abundance as might be expected at the limits of species. The daily probability of detecting a species was greater for traps augmented with CO2, but this can be compensated for by operating BL0 traps for sufficient time. The association between numbers captured by BL0 and BL300 and BL1000 traps also suggests that BL0 traps may provide useful measures of relative abundance for Culicoides sonorensis, Culicoides davisi, and Culicoides riethi, again providing the BL0 traps are left to operate for some period. Measurements of diel activity were influenced by trap type only for a single species and were primarily determined by solar radiation, temperature, and windspeed. Overall, the use of BL0 only traps for widescale surveys is supported, especially given their convenience.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.801
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.068
GPT teacher head0.362
Teacher spread0.295 · 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.

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

Citations7
Published2018
Admission routes2
Has abstractyes

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