MétaCan
Menu
Back to cohort
Record W6996146850

Regional innovation strategies: the challenge for less favoured regions

2002· article· en· W6996146850 on OpenAlexaboutno aff

Bibliographic record

VenueORCA Online Research @Cardiff · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsnot available
Fundersnot available
KeywordsRegional developmentRegional innovation systemRegional policyResizingShift-share analysisRegional planningRegional studies
DOInot available

Abstract

fetched live from OpenAlex

Regional Innovation Strategies offers the first comprehensive analysis of the new wave of innovation-oriented regional policies. It draws conclusions from the European Regional Technology Plans and Regional Innovation Strategies, both in old industrialized areas and in regions where development is slow, and compares this with US and Canadian experiences. Anticipating the enlargement of the EU, Regional Innovation Strategies also assesses the growing interest in the subject within policy, academic and practitioner circles in Central and Eastern European countries. This book aims to provide information on the new regional innovation polices and gives the first assessment of this promising pool of regional experiences.

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)0.019
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0080.020
Scholarly communication0.0230.011
Open science0.0030.012
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0100.003

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 head0.186
GPT teacher head0.398
Teacher spread0.212 · 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 designTheoretical or conceptual
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
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueORCA Online Research @CardiffSame topicCancer, Hypoxia, and MetabolismFrench-language works237,207