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Record W2954359317 · doi:10.3399/bjgpopen19x101650

Research evidence is essential for the development of family medicine as a discipline in the Japanese healthcare system

2019· article· en· W2954359317 on OpenAlexaff
Makoto Kaneko, Ai Oishi, Yoshinori Matsui, Junichiro Miyachi, Takuya Aoki, Maria Mathews

Bibliographic record

VenueBJGP Open · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Systems and Reforms
Canadian institutionsLondon Health Sciences CentreWestern UniversityCentre for Family Medicine
Fundersnot available
KeywordsHealthcare systemHealth careEngineering ethicsMedicinePolitical scienceEngineeringLaw

Abstract

fetched live from OpenAlex

Japan is facing an extraordinary rapid ageing rate: approximately 40% of people will be ≥65 years of age in 2060.1 The Japanese Ministry of Health, Labour and Welfare (MHLW) have highlighted the importance of primary care physicians for coping with the ageing population and reducing healthcare expenditure.2 However, a range of stakeholders such as MHLW and the Japan Medical Association (JMA) have been debating the necessity of family medicine as a medical discipline in the Japanese healthcare system. We examined the necessity of family medicine based on the existing discussion in the Japanese healthcare system and propose future research in this area. The main characteristics of the healthcare system in Japan are universal health insurance and a free-access system, whereby patients are free to choose any healthcare facility, regardless of their insurance status or severity of illness.3 All residents of Japan including foreign nationals with a residence card are required by law to be enrolled in a health insurance programme.4 The free-access system allows patients to visit a hospital directly without referral from a family physician.3 Although the Japanese healthcare system has achieved better healthcare outcomes, such as long …

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)0.065
metaresearch head score (Gemma)0.204
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.935
Threshold uncertainty score0.345

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0650.204
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0070.006
Science and technology studies0.0030.005
Scholarly communication0.0080.011
Open science0.0030.003
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0160.002

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 head0.340
GPT teacher head0.463
Teacher spread0.123 · 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.

Study designTheoretical or conceptual
DomainMethods
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

Citations13
Published2019
Admission routes1
Has abstractyes

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