MétaCan
Menu
Back to cohort
Record W1971631923 · doi:10.1017/s0266462302000211

CHALLENGES, CHOICES, AND CANADA

2002· article· en· W1971631923 on OpenAlexaboutno aff
Jill M. Sanders

Bibliographic record

VenueInternational Journal of Technology Assessment in Health Care · 2002
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsnot available
Fundersnot available
KeywordsMandateHealth technologyStakeholderHealth carePublic administrationBusinessQuality (philosophy)Council of MinistersPolitical sciencePublic relationsLawEuropean union

Abstract

fetched live from OpenAlex

The Canadian Coordinating Office for Health Technology Assessment (CCOHTA) was established by the Federal, Provincial, and Territorial Ministers of Health in 1989 for a 3-year trial period. In 1993 CCOHTA was made a permanent organization and in 1999 the Deputy Ministers of Health renewed CCOHTA's mandate and increased its funding. CCOHTA's role is to coordinate health technology assessment (HTA) priorities across jurisdictions, foster and undertake assessment activity, and function as a clearinghouse for technology assessment results while increasing healthcare system stakeholder awareness of HTA findings. The coordinated and collaborated approach adopted by CCOHTA minimizes duplication with other national and provincial organizations and contributes to the ability of the Canadian healthcare system to continue to deliver high-quality health care to its constituents.

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)0.009
metaresearch head score (Gemma)0.021
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: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.883
Threshold uncertainty score0.848

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0180.029
Scholarly communication0.0180.007
Open science0.0030.009
Research integrity0.0060.010
Insufficient payload (model declined to judge)0.0260.001

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 head0.226
GPT teacher head0.448
Teacher spread0.222 · 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
GenreCommentary

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

Citations11
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Technology Assessment in Health CareSame topicHealth Systems, Economic Evaluations, Quality of LifeFrench-language works237,207