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Record W2136478028 · doi:10.4269/ajtmh.15-0006

Malaria Epidemiology and Control Within the International Centers of Excellence for Malaria Research

2015· article· en· W2136478028 on OpenAlex
William J. Moss, Grant Dorsey, Ivo Müeller, Miriam K. Laufer, Donald J. Krogstad, Joseph M. Vinetz, Mitchel Guzmán-Guzmán, Ángel Rosas-Aguirre, Sócrates Herrera, Myriam Arévalo‐Herrera, Laura Chery, Ashwani Kumar, Pradyumna K. Mohapatra, Lalitha Ramanathapuram, H. C. Srivastava, Liwang Cui, Guofa Zhou, Daniel M. Parker, Joaniter I. Nankabirwa, James W. Kazura

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAmerican Journal of Tropical Medicine and Hygiene · 2015
Typearticle
Languageen
FieldMedicine
TopicMalaria Research and Control
Canadian institutionsnot available
FundersSchool of Medicine, University of California, San DiegoNational Institute of Allergy and Infectious DiseasesUniversity of California, IrvineJohns Hopkins Bloomberg School of Public HealthUniversity of California, San FranciscoUniversity of California, San DiegoNational Institutes of HealthIndian Council of Medical ResearchSchool of Medicine, Case Western Reserve UniversityPennsylvania State UniversityJohns Hopkins UniversityUniversity of PennsylvaniaUniversidad del ValleCase Western Reserve UniversityYork UniversityTulane UniversityUniversity of Washington
KeywordsMalariaEpidemiologyVector (molecular biology)Environmental healthBiologyPlasmodium falciparumPsychological interventionTransmission (telecommunications)Mosquito controlMedicineImmunologyPathology

Abstract

fetched live from OpenAlex

Understanding the epidemiological features and metrics of malaria in endemic populations is a key component to monitoring and quantifying the impact of current and past control efforts to inform future ones. The International Centers of Excellence for Malaria Research (ICEMR) has the opportunity to evaluate the impact of malaria control interventions across endemic regions that differ in the dominant Plasmodium species, mosquito vector species, resistance to antimalarial drugs and human genetic variants thought to confer protection from infection and clinical manifestations of plasmodia infection. ICEMR programs are conducting field studies at multiple sites with the aim of generating standardized surveillance data to improve the understanding of malaria transmission and to monitor and evaluate the impact of interventions to inform malaria control and elimination programs. In addition, these epidemiological studies provide a vast source of biological samples linked to clinical and environmental "meta-data" to support translational studies of interactions between the parasite, human host, and mosquito vector. Importantly, epidemiological studies at the ICEMR field sites are integrated with entomological studies, including the measurement of the entomological inoculation rate, human biting index, and insecticide resistance, as well as studies of parasite genetic diversity and antimalarial drug resistance.

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.

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)0.004
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.543
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
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 head0.092
GPT teacher head0.395
Teacher spread0.303 · 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