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Record W2034598088 · doi:10.1007/s00038-013-0448-3

The Registry of Knowledge Translation Methods and Tools: a resource to support evidence-informed public health

2013· article· en· W2034598088 on OpenAlexafffund
Leslea Peirson, Cristina Catallo, Sunita Chera

Bibliographic record

VenueInternational Journal of Public Health · 2013
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsMcMaster UniversityToronto Metropolitan UniversityMcMaster University Medical Centre
FundersPublic Health AgencyPublic Health Agency of CanadaMcMaster University
KeywordsKnowledge translationPublic healthFormative assessmentResource (disambiguation)MedicinePublic health informaticsMedical educationComputer scienceKnowledge managementHealth policyInternational healthPsychologyNursing

Abstract

fetched live from OpenAlex

OBJECTIVES: This paper examines the development of a globally accessible online Registry of Knowledge Translation Methods and Tools to support evidence-informed public health. METHODS: A search strategy, screening and data extraction tools, and writing template were developed to find, assess, and summarize relevant methods and tools. An interactive website and searchable database were designed to house the registry. Formative evaluation was undertaken to inform refinements. RESULTS: Over 43,000 citations were screened; almost 700 were full-text reviewed, 140 of which were included. By November 2012, 133 summaries were available. Between January 1 and November 30, 2012 over 32,945 visitors from more than 190 countries accessed the registry. Results from 286 surveys and 19 interviews indicated the registry is valued and useful, but would benefit from a more intuitive indexing system and refinements to the summaries. User stories and promotional activities help expand the reach and uptake of knowledge translation methods and tools in public health contexts. CONCLUSIONS: The National Collaborating Centre for Methods and Tools' Registry of Methods and Tools is a unique and practical resource for public health decision makers worldwide.

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)0.041
metaresearch head score (Gemma)0.026
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.868
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0410.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.879
GPT teacher head0.732
Teacher spread0.147 · 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
GenreCommentary

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

Citations17
Published2013
Admission routes2
Has abstractyes

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