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Record W2365112007

Development of Health Decision Support System(HDSS) in Canada and its Enlightenments to China

2012· article· en· W2365112007 on OpenAlexaboutno aff
Xing Gao

Bibliographic record

VenueZhongguo xunzheng yixue zazhi · 2012
Typearticle
Languageen
FieldHealth Professions
TopicArtificial Intelligence in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsChinaGovernment (linguistics)Decision support systemBusinessInformation systemFunction (biology)Quality (philosophy)Clinical decision support systemKnowledge managementEnlightenmentControl (management)Computer scienceEngineeringPolitical scienceData miningArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

The health decision support system in Canada is embodied in Electronic Health Record Solutions,which includes Public Health Surveillance System,Drug Information Systems,Laboratory Information Systems,etc.By virtue of business intelligence and other advanced information techology,the system can realize the function of statistical analysis,data mining,prediction,and transform information into predicting and guiding knowledge,thus support health decision-making in terms of health surveillance,resources allocation and quality control.The success lie in strong support from the federal government,efficient responsible organization Infoway as well as comprehensive and strategic design,which can be served as good enlightenment for HDSS construction of China.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.173
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.112
GPT teacher head0.429
Teacher spread0.317 · 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 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

Citations0
Published2012
Admission routes1
Has abstractyes

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