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Record W619739641

Strategic science in the public interest : Canada's government laboratories and science-based agencies

2007· book· en· W619739641 on OpenAlexaboutno aff
G. Bruce Doern, Jeffrey S. Kinder

Bibliographic record

Venuenot available
Typebook
Languageen
FieldDecision Sciences
TopicResearch, Science, and Academia
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)Context (archaeology)Political scienceWildlifeSustainable developmentPublic administrationEngineeringBusinessLibrary scienceEnvironmental planningGeographyComputer science
DOInot available

Abstract

fetched live from OpenAlex

AcknowledgmentsAbbreviationsIntroductionPart One: Historical Context and Analytical Framework Government S&T Labs and Agencies as Institutions: Towards Middle-Level Approaches Analytical ApproachPart Two: Case Studies of R&D-Focused Labs and RSA-Focused Agencies The CANMET Mining and Mineral Sciences Laboratories and Canada's Transformed Mining Sector The CANMET Energy Technology Centre--Devon and the Alberta Oil Sands The Environmental Technology Centre and Environmental Protection The National Wildlife Research Centre and Frontline Sustainable Development Related Science Activities in the Regulatory and Monitoring Process ConclusionsAppendix: Canadian and Comparative Science and Technology DataReferencesIndex

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.989
Threshold uncertainty score0.955

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.018
Science and technology studies0.0110.010
Scholarly communication0.0240.008
Open science0.0020.003
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0340.004

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 head0.209
GPT teacher head0.390
Teacher spread0.180 · 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.

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

Citations8
Published2007
Admission routes1
Has abstractyes

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