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Record W2003622654 · doi:10.1108/14664100210815422

Clinical governance: sharing practical experiences – developing a national clinical governance resource

2002· article· en· W2003622654 on OpenAlexaff
Aidan Halligan, Deborah K. Wall, Steve O’Neill

Bibliographic record

VenueBritish Journal of Clinical Governance · 2002
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Quality and Management
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsClinical governanceCorporate governanceResource (disambiguation)MedicineKey (lock)Shared resourceKnowledge managementHealth careData sharingPublic relationsProcess managementBusinessPolitical scienceAlternative medicineComputer science

Abstract

fetched live from OpenAlex

“Learning through doing” and sharing the lessons across the NHS is an important aspect of the strategy to support the introduction of clinical governance. The CGST Web site is being developed as a national clinical governance resource. It will provide access to articles, papers and copies of presentations by members of the support team. A key part of the resource will be a collection of case studies to illustrate “Clinical Governance in Action” and show what has been achieved.

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 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)0.062
metaresearch head score (Gemma)0.055
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.062
Threshold uncertainty score0.328

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0620.055
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0070.006
Scholarly communication0.0110.014
Open science0.0030.025
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0170.004

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 head0.452
GPT teacher head0.594
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations1
Published2002
Admission routes1
Has abstractyes

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