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Record W1507993573 · doi:10.1787/182801088828

An Overview of Biotechnology Statistics in Selected Countries

2003· paratext· en· W1507993573 on OpenAlexfundno aff
Andrew Devlin

Bibliographic record

VenueOECD science, technology and industry working papers · 2003
Typeparatext
Languageen
FieldBusiness, Management and Accounting
TopicIntellectual Property and Patents
Canadian institutionsnot available
FundersScience Foundation IrelandGovernment of Canada
KeywordsStatisticsBiotechnologyData scienceComputer scienceBiologyMathematics

Abstract

fetched live from OpenAlex

This report provides an update of the current state of the biotechnology industry based on primarily official statistical sources. As biotechnology becomes increasingly viewed as a strategic sector, the need for reliable biotechnology statistics from which informed policy decisions can be made grows. This report addresses that need by compiling statistics on biotechnology both on a country-by-country basis and to a limited degree across countries. Also included is a brief overview of some of the important biotechnology policies where the information is publicly available. This work has benefited from the OECD working with member countries and observer countries to develop methodological tools for measuring biotechnology. While some of this work is provisional, will change as experience in the field is gained and should not be viewed as the definitive reference, the data contained in this report represents a significant step forward from only a few years ago when only a few OECD member countries had any official statistics describing biotechnology.

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)0.005
metaresearch head score (Gemma)0.015
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: Other · Consensus signal: none
Teacher disagreement score0.046
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0460.109
Science and technology studies0.0010.000
Scholarly communication0.0050.004
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.011

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 head0.083
GPT teacher head0.275
Teacher spread0.193 · 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
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

Citations14
Published2003
Admission routes1
Has abstractyes

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