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Record W4206446300 · doi:10.1055/s-0038-1638611

North American Medical Informatics (NAMI)

2008· article· en· W4206446300 on OpenAlexaboutno aff

Bibliographic record

VenueYearbook of Medical Informatics · 2008
Typearticle
Languageen
FieldHealth Professions
TopicElectronic Health Records Systems
Canadian institutionsnot available
Fundersnot available
KeywordsHealth informaticsMedicineComputer scienceNursingPublic health

Abstract

fetched live from OpenAlex

Founded in 1975, COACH: Canada's Health Informatics Association is the organization focused on advancing health informatics (HI) practices and professionalism in Canada.Representing more than 1,300 members, COACH is committed to a vision of taking health informatics mainstream.The association's mandate is to promote the understanding and adoption of HI within the Canadian health system through leadership, professional development, advocacy and a strong, diverse membership.COACH focuses on fulfilling this mandate through a number of key initiatives in addition to the continued enhancement of member services in the areas of networking, information and knowledge sharing, conferences, education, alliances and thought leadership and advocacy.Completing its 32nd year as the national association for HI, COACH continues to develop significant and exciting initiatives to provide leadership in the evolution of HI as a profession in Canada.COACH continues, in conjunction with the Canadian Institute for Health Information (CIHI), to host the largest annual e-Health conference in Canada.COACH and the Canadian Healthcare Information Technology Trade Association (CHITTA) also co-host the annual Canadian Health Informatics Awards program that recognizes achievment and contribution in the HI community through a growing number of personal, project and company-based awards.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.438
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.002

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 head0.052
GPT teacher head0.414
Teacher spread0.362 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations0
Published2008
Admission routes1
Has abstractyes

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