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Record W2780485402 · doi:10.21037/jphe.2017.12.01

Reporting the methods used in public health research and practice

2017· article· en· W2780485402 on OpenAlexfundno aff
Donna F. Stroup, Camille Smith, Benedict I. Truman

Bibliographic record

VenueJournal of Public Health and Emergency · 2017
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsnot available
FundersCenters for Disease Control and PreventionNational Institutes of HealthPublic Health Agency of Canada
KeywordsScrutinyPublic healthTransparency (behavior)PsychologySection (typography)Medical educationPublic relationsMedicinePolitical scienceComputer scienceNursingLaw

Abstract

fetched live from OpenAlex

The methods section of a scientific article often receives the most scrutiny from journal editors, peer reviewers, and skeptical readers because it allows them to judge the validity of the results. The methods section also facilitates critical interpretation of study activities, explains how the study avoided or corrected for bias, details how the data support the answer to the study question, justifies generalizing the findings to other populations, and facilitates comparison with past or future studies. In 2006, the Enhancing the QUAlity and Transparency Of health Research (EQUATOR) Programme began collecting and disseminating guidelines for reporting health research studies. In addition, guidelines for reporting public health investigations not classified as research have also been developed. However, regardless of the type of study or scientific report, the methods section should describe certain core elements: the study design; how participants were selected; the study setting; the period of interest; the variables and their definitions used for analysis; the procedures or instruments used to measure exposures, outcomes, and their association; and the analyses. Specific requirements for each study type should be consulted during the project planning phase and again when writing begins. We present requirements for reporting methods for public health activities, including outbreak investigations, public health surveillance programs, prevention and intervention program evaluations, research, surveys, systematic reviews, and meta-analyses.

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 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)0.862
metaresearch head score (Gemma)0.727
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Scholarly communication
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.800
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.8620.727
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0020.002
Open science0.0020.000
Research integrity0.0000.001
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 head0.986
GPT teacher head0.770
Teacher spread0.216 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations7
Published2017
Admission routes1
Has abstractyes

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