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Record W2116148325 · doi:10.2196/jmir.2740

Scoping Review on Search Queries and Social Media for Disease Surveillance: A Chronology of Innovation

2013· article· en· W2116148325 on OpenAlexafffund
Theresa M. Bernardo, Andrijana Rajić, Ian Young, Katie Robiadek, Mai Pham, Julie A. Funk

Bibliographic record

VenueJournal of Medical Internet Research · 2013
Typearticle
Languageen
FieldMedicine
TopicData-Driven Disease Surveillance
Canadian institutionsPublic Health Agency of CanadaUniversity of Guelph
FundersCollege of Engineering, Michigan State UniversityCenters for Disease Control and PreventionPublic Health AgencyPublic Health Agency of CanadaUniversity of GuelphMichigan State University
KeywordsSocial mediaDisease surveillancePandemicOutbreakInternet privacyDiseaseInfluenza A virus subtype H5N1Warning systemCoronavirus disease 2019 (COVID-19)Computer scienceMedicineMedical emergencyData scienceWorld Wide WebInfectious disease (medical specialty)VirologyPathology

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.066
metaresearch head score (Gemma)0.195
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.934
Threshold uncertainty score0.348

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0660.195
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0070.005
Bibliometrics0.0480.050
Science and technology studies0.0020.006
Scholarly communication0.0130.017
Open science0.0030.008
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0060.001

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 head0.114
GPT teacher head0.467
Teacher spread0.352 · 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.

Study designSystematic review
DomainMethods
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

Citations171
Published2013
Admission routes2
Has abstractyes

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