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Record W2499212718 · doi:10.1177/2327857916051000

Building Bridges Between Physicians And Pharmacists

2016· article· en· W2499212718 on OpenAlex
Damla Kerestecioglu, Catherine M. Burns, Kelly Grindrod

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

VenueProceedings of the International Symposium on Human Factors and Ergonomics in Health Care · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicHealthcare Systems and Technology
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPharmacistObservational studyHealth careHealth recordsNursingFamily medicineMedicineMedical educationPharmacy

Abstract

fetched live from OpenAlex

Previous studies have indicated that there is a lack of communication between healthcare providers such as pharmacists and physicians. Our study was an initial attempt to understand the relationship patterns between family doctors and pharmacists and to try to identify the reasons leading to this lack of communication. Using semi-formal interviews and observational field studies, we explored the information flow between physicians and pharmacists as well as within physicians. Suggestions to improve pharmacist-physician communication are provided. This was the first step of a multi-year project trying to understand and improve communication between healthcare providers, through a better electronic healthcare records system.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.084
Threshold uncertainty score0.342

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.301
Teacher spread0.271 · 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