MétaCan
Menu
Back to cohort
Record W1600386408 · doi:10.1007/s10654-015-0034-5

Development of the standards of reporting of neurological disorders (STROND) checklist: a guideline for the reporting of incidence and prevalence studies in neuroepidemiology

2015· article· en· W1600386408 on OpenAlexafffund
Derrick Bennett, Carol Brayne, Valery L. Feigin, Suzanne Barker‐Collo, Michael Brainin, Daniel Davis, V. Gallo, Nathalie Jetté, André Karch, John F. Kurtzke, Pablo M. Lavados, Giancarlo Logroscino, Gabriele Nagel, Pierre‐Marie Preux, Peter M. Rothwell, Lawrence W. Svenson

Bibliographic record

VenueEuropean Journal of Epidemiology · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsUniversity of AlbertaUniversity of Calgary
FundersNational Institute for Health and Care ResearchO'Brien Institute for Public Health, University of CalgaryClínica Alemana de SantiagoUniversité de LimogesUniversity of OxfordUniversidad de ChileUniversity College LondonUniversität UlmUniversity of AlbertaQueen Mary University of LondonAuckland University of Technology, New ZealandGeorgetown University
KeywordsChecklistMedicineGuidelineEpidemiologyDescriptive statisticsIncidence (geometry)Family medicineBiostatisticsDelphi methodMEDLINEEpidemiological methodPublic healthNursingPathologyPsychology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.446
metaresearch head score (Gemma)0.586
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Reporting · Consensus signal: Reporting
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.554
Threshold uncertainty score0.683

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4460.586
Meta-epidemiology (narrow)0.0040.006
Meta-epidemiology (broad)0.0120.027
Bibliometrics0.0280.020
Science and technology studies0.0050.006
Scholarly communication0.0120.007
Open science0.0160.011
Research integrity0.0120.020
Insufficient payload (model declined to judge)0.0070.006

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 head0.677
GPT teacher head0.535
Teacher spread0.142 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
DomainReporting
GenreMethods

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

Citations44
Published2015
Admission routes2
Has abstractno

Explore more

Same venueEuropean Journal of EpidemiologySame topicHealth Systems, Economic Evaluations, Quality of LifeFrench-language works237,207