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Record W2584203780 · doi:10.1136/bmjopen-2016-013351

Cohort profile: the Scottish Research register SHARE. A register of people interested in research participation linked to NHS data sets

2017· article· en· W2584203780 on OpenAlex
Brian McKinstry, Frank Sullivan, Shobna Vasishta, Roma A. Armstrong, Janet Hanley, John Haughney, Sam Philip, Blair H. Smith, Amanda Wood

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBMJ Open · 2017
Typearticle
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsUniversity of Toronto
FundersScottish GovernmentMedical Research CouncilNHS Health ScotlandWellcome Trust
KeywordsRegister (sociolinguistics)MedicineCohort studyFamily medicinePathology

Abstract

fetched live from OpenAlex

PURPOSE: Recruitment to trials is often difficult. Many trials fail to meet recruitment targets resulting in underpowered studies which waste resources and the time of those who participated. While there is evidence that many people are willing to take part in research, particularly if it involves a condition from which they suffer, researchers are unable to easily contact such people often relying on busy clinicians to identify them. Many clinicians perceive themselves as too busy to take part in research activities. The Scottish Health Research Register SHARE adopts an approach which asks the public to consent to their data held in National Health Service databases to be used to determine their suitability for research projects. Additionally, participants can consent for spare blood, left after routine venepuncture to be automatically identified in the laboratory and stored for future research studies. PARTICIPANTS: Anyone over the age of 16 years in Scotland can participate. Participants are approached through a range of methods including directly at outpatient clinics and general practitioners practices, leaflets with hospital letters and personal email from employers. FINDINGS TO DATE: SHARE has recruited around 130 000 people. SHARE has demonstrated that it can quickly and efficiently recruit to studies, over 20 until now. In addition, it can be used to administer questionnaire studies by email and recruit to patient and public involvement groups. FUTURE PLANS: SHARE continues to steadily recruit with the ambition of eventually achieving 1 000 000 people in Scotland. We are steadily increasing the number of data sets we use for identifying participants. We are adding a mobile app which will facilitate dissemination about research and allow the collection of physiological and activity data if desired. We anticipate that SHARE will soon become the main source of health research recruitment in Scotland.

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.

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)0.116
metaresearch head score (Gemma)0.243
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Open science, Research integrity
Consensus categoriesMetaresearch, Open science
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.212
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1160.243
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0080.019
Research integrity0.0000.004
Insufficient payload (model declined to judge)0.0010.001

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 head0.958
GPT teacher head0.782
Teacher spread0.176 · 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