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Record W2570369989 · doi:10.18192/uojm.v6i2.1510

The WHO’s Need to Address Insecticide Resistance in Malaria Vectors

2016· article· fr· W2570369989 on OpenAlexaffvenue
Tarun Rahman

Bibliographic record

VenueUniversity of Ottawa Journal of Medicine · 2016
Typearticle
Languagefr
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMalariaInsecticide resistanceIndoor residual sprayingVector (molecular biology)Incidence (geometry)Protozoal diseaseChemical controlGeographyBiologyEnvironmental healthForestryToxicologyMedicinePlasmodium falciparumImmunologyHorticulture

Abstract

fetched live from OpenAlex

ABSTRACTSince 2000, incidence and mortality rates attributable to malaria have declined significantly. However, this decline may be short-lived due to the emergence of insecticide-resistant malaria vectors caused by the overuse of indoor residual spraying (IRS) and insecticide treated nets (ITNs). This policy paper will discuss the emergence, causes, and implications of vector resistance and will propose solu­tions to prevent a future public health crisis.RÉSUMÉDepuis 2000, l’incidence et les taux de mortalité attribuables au paludisme ont diminué significativement. Toutefois, ce déclin risque d’être de courte durée en raison de l’émergence de vecteurs du paludisme résistants aux insecticides, causée par la surutilisation de la pulvérisation intradomiciliaire (PID) et de moustiquaires imprégnées d’insecticides (MII). Cet article de politique discutera de l’émergence, des causes et des implications de la résistance des vecteurs, et proposera des solutions dans le but de prévenir une éventuelle crise sanitaire.

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)0.005
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.099
Threshold uncertainty score0.196

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0020.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0120.002

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 head0.009
GPT teacher head0.231
Teacher spread0.222 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations0
Published2016
Admission routes2
Has abstractyes

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Same venueUniversity of Ottawa Journal of MedicineSame topicMosquito-borne diseases and controlFrench-language works237,207