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Record W3016137073

Bedside and Community : 50 Years of Contributions to the Health of Albertans from the University of Calgary

2020· book· en· W3016137073 on OpenAlexaboutno aff
Diana Mansell, Frank W. Stahnisch, Paula Larsson

Bibliographic record

Venuenot available
Typebook
Languageen
FieldHealth Professions
TopicPublic Health Policies and Education
Canadian institutionsnot available
Fundersnot available
KeywordsOutreachExcellenceContext (archaeology)Health careLibrary scienceIndigenousMedical educationCommunity healthCenter of excellenceTransformative learningSociologyMedicinePolitical sciencePedagogyGeography
DOInot available

Abstract

fetched live from OpenAlex

Bedside and Community is the inside story of fifty years of health care and health research at the University of Calgary. Drawing on the first–person accounts of researchers, administrators, faculty, and students along with archival research, and faculty histories, this collection celebrates the many significant contributions the University of Calgary has made to the health of Albertans. With contributions from the Cummings School of Medicine, the Faculty of Nursing, Faculty of Kinesiology, Faculty of Veterinary Medicine, Faculty of Environmental Design, Department of Psychology, and Indigenous Health Initiatives Bedside and Community is a truly collaborative history. Addressing the links between departments, the relationship between the university and the community, and evolving research and teaching methods, this book places the University of Calgary within a wider national context and shows how it has addressed the unique health needs of Southern Alberta. With a pioneering focus on primary care and commitment to interdisciplinary connections, the University of Calgary has made strides in heath research, health education, and community outreach. Bedside and Community tells the story of a tradition of excellence that will light the way to future outreach and discovery

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.957
Threshold uncertainty score0.425

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0220.011
Scholarly communication0.0090.003
Open science0.0010.004
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0120.002

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 head0.058
GPT teacher head0.403
Teacher spread0.346 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations2
Published2020
Admission routes1
Has abstractyes

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