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Record W2173798547 · doi:10.1093/infdis/jiv475

Asymptomatic and Submicroscopic Carriage of<i>Plasmodium knowlesi</i>Malaria in Household and Community Members of Clinical Cases in Sabah, Malaysia

2015· article· en· W2173798547 on OpenAlexfundno aff
Kimberly Fornace, Nor Afizah Nuin, Martha Betson, Matthew J. Grigg, Timothy William, Nicholas M. Anstey, Tsin Wen Yeo, Jonathan Cox, Lau Tiek Ying, Chris Drakeley

Bibliographic record

VenueThe Journal of Infectious Diseases · 2015
Typearticle
Languageen
FieldMedicine
TopicMalaria Research and Control
Canadian institutionsnot available
FundersNational Health and Medical Research CouncilBiotechnology and Biological Sciences Research CouncilMedical Research CouncilRoyal Veterinary CollegeMinistry of Health, British Columbia
KeywordsPlasmodium knowlesiAsymptomaticMalariaCarriageParasitemiaMedicinePopulationConfidence intervalPlasmodium (life cycle)VirologyImmunologyEnvironmental healthInternal medicinePlasmodium falciparumPlasmodium vivaxPathologyParasite hosting

Abstract

fetched live from OpenAlex

Although asymptomatic carriage of human malaria species has been widely reported, the extent of asymptomatic, submicroscopic Plasmodium knowlesi parasitemia is unknown. In this study, samples were obtained from individuals residing in households or villages of symptomatic malaria cases with the aim of detecting submicroscopic P. knowlesi in this population. Four published molecular assays were used to confirm the presence of P. knowlesi. Latent class analysis revealed that the estimated proportion of asymptomatic individuals was 6.9% (95% confidence interval, 5.6%-8.4%). This study confirms the presence of a substantial number of asymptomatic monoinfections across all age groups; further work is needed to estimate prevalence in the wider community.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.001
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 head0.054
GPT teacher head0.341
Teacher spread0.287 · 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 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

Citations92
Published2015
Admission routes1
Has abstractyes

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