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Record W2065763387 · doi:10.7772/2159-1253.1057

Nurse–Physician Collaboration in General Internal Medicine: A Synthesis of Survey and Ethnographic Techniques

2014· article· en· W2065763387 on OpenAlexaff
Lesley Gotlib Conn, Chris Kenaszchuk, Katie N. Dainty, Merrick Zwarenstein, Scott Reeves

Bibliographic record

VenueHealth and Interprofessional Practice · 2014
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsSunnybrook Health Science CentreSunnybrook HospitalWestern UniversitySt. Michael's HospitalCentre for Addiction and Mental HealthInstitute for Clinical Evaluative Sciences
Fundersnot available
KeywordsEthnographyNursingMedicineMedical educationFamily medicineSociology

Abstract

fetched live from OpenAlex

Health, Interprofessional Practice and Education is a peer-reviewed, open access journal dedicated to increasing the availability of high-quality evidence to inform patient care and practitioner education from an interprofessional perspective. HIPE is aimed at academics, practitioners and student-practitioners who seek to become more knowledgeable and skilled at working with providers in other health disciplines for the purpose of providing compassionate, quality, integrated care to diverse patient populations.HIPE is published by Pacific University Libraries | ISSN 2641-1148

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)0.004
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.157
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.030
GPT teacher head0.478
Teacher spread0.447 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations30
Published2014
Admission routes1
Has abstractyes

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