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Record W4307367962 · doi:10.5750/ijpcm.v10i3.1062

EDITORIAL INTRODUCTION

2022· article· en· W4307367962 on OpenAlexaboutno aff
Paul Glare

Bibliographic record

VenueThe International Journal of Person Centered Medicine · 2022
Typearticle
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsOperationalizationHealth careNursingSpecialtyHealthcare systemIndex (typography)PsychologyMedicinePolitical scienceFamily medicineComputer science

Abstract

fetched live from OpenAlex

One of the aims of the International College of Person Centered Medicine has been the development of an operationalized measure that allows for assessment of the degree of person centeredness of health care services. With funding in part from the World Health Organization, the Person-centered Care Index (PCI) was developed and validated across three countries [1]. Representatives of patients and family organizations contributed to the development of this 33-item instrument to rate the person centeredness of a health care system, but the PCI is completed by physicians working in that system. If we seek to be truly person centered, shouldn’t we be asking the people using a health care system how they rate it, or at least how they rate the professionals they encounter within that system? This issue of the Journal presents two such studies, one from a primary care system in Brazil, the other from a specialty care setting in Canada.

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 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)0.001
metaresearch head score (Gemma)0.001
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: Editorial · Consensus signal: none
Teacher disagreement score0.682
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.220
GPT teacher head0.432
Teacher spread0.211 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEditorial

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

Citations0
Published2022
Admission routes1
Has abstractyes

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