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Record W2160489798

E-health leads Nova Scotia's healthcare transformation.

2009· article· en· W2160489798 on OpenAlexaboutno aff
Patrick Powers

Bibliographic record

VenuePubMed · 2009
Typearticle
Languageen
FieldHealth Professions
TopicMedical Research and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsNova scotiaBusinessGovernment (linguistics)Health careDebtFiscal yearFinanceEconomic growthGeographyEconomicsArchaeology
DOInot available

Abstract

fetched live from OpenAlex

Nova Scotia's healthcare policy direction seems well-defined and well-established for the foreseeable future. This is the case, despite the recent electoral transition from a Progressive Conservative to a New Democratic Party government for the first time in the province's history; and despite the threat of the province's net direct debt increasing through 2012, after eight years of declining net direct debt as a percentage of the province's gross domestic product. As well, little public consideration is being given to disrupting the current regional healthcare organizational structure by further consolidating the province's nine district health authorities (DHA), as occurred last year in Alberta and New Brunswick. Moreover, the Health Information Technology Services Program of Nova Scotia (HITS-NS), the province's shared IT services or provincial service delivery organization, is steadily expanding the inventory of clinical, financial, and administrative software applications hosted for eight DHAs on a common Meditech Client-Server platform, as well as some applications for Capital Health DHA 9 (CDHA) and IWK Health Centre (IWK), the province's consolidated women's and children's hospital located in Halifax.

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)0.002
metaresearch head score (Gemma)0.006
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: Empirical · Consensus signal: none
Teacher disagreement score0.982
Threshold uncertainty score0.521

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0050.001
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0410.008

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 head0.197
GPT teacher head0.492
Teacher spread0.296 · 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
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

Citations2
Published2009
Admission routes1
Has abstractyes

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