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Record W4312958907 · doi:10.2196/39798

Updating the Data on Malaria Vectors in Malaysia: Protocol for a Scoping Review

2022· review· en· W4312958907 on OpenAlexvenueno aff
Rafidah Ali, Wan Najdah Wan Mohamad Ali, Perada Wilson Putit

Bibliographic record

VenueJMIR Research Protocols · 2022
Typereview
Languageen
FieldMedicine
TopicMalaria Research and Control
Canadian institutionsnot available
FundersKementerian Kesihatan Malaysia
KeywordsProtocol (science)MalariaComputer scienceData scienceMedicineAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Malaria is still a public health threat. From 2015 to 2021, a total of 23,214 malaria cases were recorded in Malaysia. Thus, effective intervention and key entomological information are vital for interrupting or preventing malaria transmission. Therefore, the availability of malaria vector information is desperately needed. OBJECTIVE: The objective of our study is to update the list of human and zoonotic malaria vectors in Malaysia. This work will include (1) the characterization of the key behavioral traits and breeding sites of malaria vectors and (2) the determination of new and potential malaria vectors in Malaysia. The findings of our scoping review will serve as decision-making evidence that stakeholders and decision makers can use to strengthen and intensify malaria surveillance in Malaysia. METHODS: The scoping review will be conducted based on the following four electronic databases: Scopus, PubMed, Google Scholar, and Science Direct. A search strategy was conducted for articles published from database inception to March 2022. The criteria for article inclusion were any malaria vector-related studies conducted in Malaysia (with no time frame restrictions) and peer-reviewed studies. The PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) will be used to guide our systematic approach. Data from published research literature will be extracted by using a standardized data extraction framework, including the titles, abstracts, characteristics, and main findings of the included studies. To assess the risk of bias, articles will be screened independently by 2 reviewers, and a third reviewer will make the final decision if disagreements occur. RESULTS: The study commenced in June 2021, and it is planned to be completed at end of 2022. As of early 2022, we identified 631 articles. After accessing and evaluating the articles, 48 were found to be eligible. Full-text screening will be conducted in mid-2022. The results of the scoping review will be published as an open-access article in a peer-reviewed journal. CONCLUSIONS: Our novel scoping review of malaria vectors in Malaysia will provide a comprehensive evidence summary of updated, relevant information. An understanding of the status of Anopheles as malaria vectors and the knowledge generated from the behavioral characteristics of malaria vectors are the key components in making effective interventions for eliminating malaria. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/39798.

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)0.101
metaresearch head score (Gemma)0.100
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.101
Threshold uncertainty score0.536

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1010.100
Meta-epidemiology (narrow)0.0060.006
Meta-epidemiology (broad)0.0140.016
Bibliometrics0.0220.016
Science and technology studies0.0060.006
Scholarly communication0.0070.010
Open science0.0060.007
Research integrity0.0100.008
Insufficient payload (model declined to judge)0.0820.018

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 head0.642
GPT teacher head0.665
Teacher spread0.022 · 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 designSystematic review
Domainnot available
GenreProtocol

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
Published2022
Admission routes1
Has abstractyes

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