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Record W2717036600 · doi:10.1097/poc.0000000000000088

Molecular Diagnosis of Malaria in Low-Resource Settings

2016· article· en· W2717036600 on OpenAlexaff
Stephanie K. Yanow

Bibliographic record

VenuePoint of Care The Journal of Near-Patient Testing & Technology · 2016
Typearticle
Languageen
FieldMedicine
TopicMalaria Research and Control
Canadian institutionsAlberta Advanced EducationUniversity of Alberta
Fundersnot available
KeywordsMolecular diagnosticsMalariaDeveloping countryLimited resourcesResource (disambiguation)Computer scienceRisk analysis (engineering)BusinessMedicineData scienceBiologyImmunologyEconomic growthBioinformaticsEconomics

Abstract

fetched live from OpenAlex

In developed nations, there has been a dramatic shift in the paradigm for diagnostics of infectious diseases. Traditional methods of culture and serology are being superseded by molecular diagnostics. These tests, for example real-time polymerase chain reaction (PCR), have exquisite sensitivity in detecting low-level infections and by combining different tests in one, they have the specificity to identify a pathogen to the resolution of the genotype. However, they are also costly and require sophisticated infrastructure as well as highly skilled personnel. These limitations preclude access to molecular diagnostics in rural areas, and particularly in low-resource settings in the developing world. The concept of “democratizing” molecular diagnostics points to this disparity in health care systems of developed and developing nations and urges the development of technologies that can be adapted for low-resource settings to ensure universal access.

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)0.002
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.008
GPT teacher head0.244
Teacher spread0.236 · 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
GenreReview

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

Citations2
Published2016
Admission routes1
Has abstractyes

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Same venuePoint of Care The Journal of Near-Patient Testing & TechnologySame topicMalaria Research and ControlFrench-language works237,207