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Record W2804530867 · doi:10.1126/sciadv.aat0496

Rapid, noninvasive detection of Zika virus in <i>Aedes aegypti</i> mosquitoes by near-infrared spectroscopy

2018· article· en· W2804530867 on OpenAlexfundno aff
Jill N. Fernandes, Lílha Maria Barbosa dos Santos, Thaís Chouin-Carneiro, Márcio G. Pavan, Gabriela A. Garcia, Mariana Rocha David, John C. Beier, Floyd E. Dowell, Rafael Maciel‐de‐Freitas, Maggy T. Sikulu-Lord

Bibliographic record

VenueScience Advances · 2018
Typearticle
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsnot available
FundersFundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de JaneiroConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorMinistério da Ciência, Tecnologia, Inovações e ComunicaçõesGovernment of CanadaMinisterio de Economía y CompetitividadUnited States Agency for International DevelopmentGrand Challenges CanadaU.S. Department of Agriculture
KeywordsArbovirusZika virusAedes aegyptiChikungunyaVirologyAedesBiologyArbovirus InfectionsVector (molecular biology)OutbreakDengue feverVirusEcologyGenetics

Abstract

fetched live from OpenAlex

mosquitoes with prediction accuracies of 94.2 to 99.3% relative to quantitative reverse transcription polymerase chain reaction (RT-qPCR). NIRS involves simply shining a beam of light on a mosquito to collect a diagnostic spectrum. We estimated in this study that NIRS is 18 times faster and 110 times cheaper than RT-qPCR. We anticipate that NIRS will be expanded upon for identifying potential arbovirus hotspots to guide the spatial prioritization of vector control.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.547

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 studies0.0000.001
Scholarly communication0.0000.001
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 head0.007
GPT teacher head0.279
Teacher spread0.272 · 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 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

Citations94
Published2018
Admission routes1
Has abstractyes

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