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Record W2094472381 · doi:10.1056/nejmc1410735

Spread of Artemisinin Resistance in Malaria

2014· letter· en· W2094472381 on OpenAlexaff
Michael Hawkes, Andrea L. Conroy, Kevin C. Kain

Bibliographic record

VenueNew England Journal of Medicine · 2014
Typeletter
Languageen
FieldMedicine
TopicMalaria Research and Control
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsArtesunateMalariaArtemisininMedicinePlasmodium falciparumInterquartile rangePopulationArtemether/lumefantrineSoutheast asiaInternal medicineEnvironmental healthImmunology

Abstract

fetched live from OpenAlex

To the Editor: Ashley et al. (July 31 issue)1 recently described the spread of Plasmodium falciparum resistant to artemisinin across Southeast Asia but not Africa. This and other studies2,3 included patients with uncomplicated malaria, whereas young children with severe malaria in Africa represent a key population of interest with the highest mortality burden. From the placebo group of our recent (2011 to 2013) randomized, controlled trial in Uganda,4 we quantified parasite-clearance kinetics using identical methods (standardized parasite-clearance estimator)5 among 91 children with severe falciparum malaria treated with intravenous artesunate. The median clearance half-life was 4.6 hours (interquartile range, 3.6 . . .

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)0.003
metaresearch head score (Gemma)0.018
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: Editorial · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0190.019
Insufficient payload (model declined to judge)0.0050.004

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 head0.021
GPT teacher head0.286
Teacher spread0.265 · 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
GenreEditorial

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

Citations16
Published2014
Admission routes1
Has abstractyes

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