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Record W6930009738 · doi:10.5281/zenodo.10035596

Scan of Canadian Strengths in Biotechnology

2005· report· en· W6930009738 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2005
Typereport
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCarcinogens and Genotoxicity Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsBlueprintCommercializationScope (computer science)Government (linguistics)Stewardship (theology)Intellectual propertyBest practicePosition (finance)Futures studies

Abstract

fetched live from OpenAlex

Demonstrating responsible world leadership on biotechnology has been one of the ten key themes of the Canadian Biotechnology Strategy (CBS) since its creation in 1998. This position was reinforced in 2004 with the launch of the Government of Canada's Blueprint for Biotechnology. The Blueprint emphasizes that "Canada's leadership, both domestically and internationally, requires that the new Stewardship Framework is supported by leading edge regulatory research, foresight, capacity-building in regulatory sciences, dialogue with Canadians, and international cooperation", and recommends various initiatives to achieve the desired international impact. One of these initiatives recognizes that the knowledge harnessed from biotechnology advances has a powerful potential to address critical issues in developing countries, and recommends the establishment of a new national initiative for international development. This initiative would facilitate the coordination of strategic research and technology development networks encompassing research centers in Canada and developing countries. As part of this initiative, the National Research Council of Canada (NRC) mandated Science-Metrix to undertake an environmental scan with the aim of identifying Canada's strengths in biotechnology in the public and private sectors, universities and hospitals. The scope of this scan includes science, research and technology developments, and innovation support activities (market intelligence, industrial technology advice, intellectual property management, commercialization support, etc.) To assess science and technology (S&T) strengths beyond anecdotal evidence, Science-Metrix performed scientometric and technometric analyses. These techniques were used to identify in particular, biotechnology niches where Canada has a favourable position within the international community. The scientometric analysis involved surveying the Medline (US National Library of Medicine) and SCI Expanded (ISI Thomson) databases while the technometric analysis surveyed the USPTO (US Patent Office) database. In addition, a review of the literature was conducted to pinpoint significant individual scientific achievements in biotechnology. Identifying the strengths in the Canadian innovation system, involved reviewing the existing literature and information available on the internet on biotechnology developments in Canada.

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)0.008
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: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.845
Threshold uncertainty score0.980

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0230.039
Science and technology studies0.0110.003
Scholarly communication0.0080.002
Open science0.0020.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0140.001

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 head0.029
GPT teacher head0.271
Teacher spread0.242 · 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
GenreReview

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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