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General practice — chaos, complexity and innovation

2005· article· en· W2181371894 on OpenAlex
Carmel M. Martin, Joachim P. Sturmberg

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

VenueThe Medical Journal of Australia · 2005
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsNOSM University
Fundersnot available
KeywordsComplex adaptive systemPromotion (chess)Knowledge managementManagement scienceHealth careHealthcare systemSociologyComputer sciencePolitical scienceEconomic growthEngineeringEconomicsArtificial intelligence

Abstract

fetched live from OpenAlex

Primary health care (PHC) reforms focus on improving access to and effectiveness of general practice services, with greater emphasis on health promotion, prevention and chronic disease management, and integration with population health approaches. Currently, reforms are often based on scant evidence from the most accessible and easily known PHC domains and activities, yet most PHC is complex and poorly understood. Complexity theory is based on understanding patterns that are not predictable by traditional evidence and social knowledge, within a complex adaptive system. Complexity knowledge provides a way of understanding the general practitioner's role in PHC in self-organising local networks, with a capacity to generate new solutions integrated through historical and social connections. Complex systems provide a framework for an expanded knowledge base, debate and discussion of reforms and development of PHC goals and strategies.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.337
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.237
GPT teacher head0.534
Teacher spread0.297 · 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