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Record W4377259972 · doi:10.1515/9780773572430-001

Tables, Figures and Sidebars

2005· book-chapter· en· W4377259972 on OpenAlexaboutno aff

Bibliographic record

VenueMcGill-Queen's University Press eBooks · 2005
Typebook-chapter
Languageen
FieldEconomics, Econometrics and Finance
TopicInnovation Policy and R&D
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceHistory

Abstract

fetched live from OpenAlex

Definitions of the sectors 30 List of biotechnologies 3I Core biotechnology firms in Canada by province, 200I 33 Core biotechnology firms in Canada by area of research, 200I 33 Largest Canadian biotechnology companies by market capitalization, as of January 2003 34 Canadian core SBFS by size, as of August 2002, 35 Canadian core SBFS by province, as of August 2002 35 Canadian core SBFS' expenditure in biotechnology R&D by province, I997-2001 (c$) 36 Canadian core SBFS by province, I997-2001 37 Canadian core SBFS' revenues in biotechnology by province, I997 and 200I (c$) 37 Canadian private investments in core biotechnology firms by province, 200I (c$) 38 Canadian private investments in core biotechnology firms by city, 200I (c$) 38 Canadian venture capital in biotechnology by metropolitan area, 200I 39 Year of foundation of patenting firms existing in 2002 40

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)0.001
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.372
Threshold uncertainty score0.531

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.016
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0090.026
Science and technology studies0.0020.001
Scholarly communication0.0040.003
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.6280.505

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 head0.026
GPT teacher head0.193
Teacher spread0.168 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

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

Citations0
Published2005
Admission routes1
Has abstractyes

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