MétaCan
Menu
Back to cohort
Record W2096523032 · doi:10.3399/bjgp09x420626

Distilling the essence of general practice: a learning journey in progress

2009· article· en· W2096523032 on OpenAlex

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

VenueBritish Journal of General Practice · 2009
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsSelkirk College
FundersRoyal College of General Practitioners
KeywordsMedicineGeneral practiceData scienceComputer scienceMedical educationFamily medicine

Abstract

fetched live from OpenAlex

Over the past 5 years, general practice in the UK has undergone major change. Starting with the introduction of the new GMS contract in 2004, it has continued apace with the establishment of Postgraduate Medical Education Training Board, a GP training curriculum, and nMRCGP. The NHS is developing very differently in the four countries of the UK. Regulation of the profession is under review, and a system of relicensing, recertification, and revalidation is being introduced. The Essence project, initiated by RCGP Scotland in conjunction with International Futures Forum 4 years ago is a constructive response to these changes. It has included learning journeys, a discussion day for GPs, and commissioned short pieces of 100 words from GPs and patients. From an analysis of these, some characteristics of the essence of general practice have been defined. These include key roles and core personal qualities for GPs. It is argued that general practice has important and unique advantages - trust, coordination, continuity, flexibility, universal coverage, and leadership - which mean that it should continue to be central to the development of primary care throughout the UK.

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)0.007
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.610
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.004
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 head0.043
GPT teacher head0.449
Teacher spread0.406 · 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