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Record W7008354767

Benchmarking of Genomics and Health Biotechnology in Seven Developing Countries, 1991-2002: Brazil, China, Cuba, Egypt, India, Republic of Korea and South Africa. Prepared for the University of Toronto Joint Center for Bioethics

2004· other· en· W7008354767 on OpenAlexaboutno aff

Bibliographic record

VenueDigitalGeorgetown (Georgetown University Library) · 2004
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsBioethicsBenchmarkingJoint (building)Center (category theory)GenomicsPublic health
DOInot available

Abstract

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This scientometric study provides an extensive quantitative analysis of the performance of leading countries, as well as seven selected developing countries, in the domains of genomics and health biotechnology using the Science Citation Index (SCI) Expanded scientific papers database.Papers were retrieved from SCI Expanded using two sets of keywords, one for genomics and one for health biotechnology.All genomics and health biotechnology papers were normalized at the country and city levels.Therefore, significant effort was put into normalizing data for developing countries, in order to categorize institutional sectors of activity with a minimum level (1% to 4%) of unknowns, and to precisely identify the most active institutions and researchers.Using a ten year time frame (1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001), the report outlines the evolution of genomics and health biotechnology at the international and national levels in leading developed countries, as well as in seven developing countries.The report presents the scientific output performances of the developing countries using five scientometric indicators and a combined multicriteria ranking.Increasingly, developing countries are rapidly gaining a presence in the world's scientific community for life sciences.China and the Republic of Korea in particular will, in the near future, enter the league of leading countries and will overtake so-called developed countries in terms of absolute scientific output in genomics and health biotechnology.As the international community stresses the need to apply genomics and health biotechnology R&D to improve global health and sustainability in developing countries, the next decade might provide these countries with the necessary knowledge and know-how to solve the most prevalent issues of poverty, disease, high population density, and environmental problems.However, it would be of great interest to monitor and study the integration and application of the blossoming domains of biotechnological and genome science to local health and well-being needs, in order to provide insight to the developing nations that have limited scientific and technological resources. Key findings Genomics at the international levelBetween 1991 and 2002, papers in genomics increased by almost 60% at the world level; specifically, from approximately 35,000 to over 55,000 scientific papers annually. Genomics and Health Biotechnology in Seven Developing Countries vi Most active cities and institutions BrazilIn terms of the number of publications, Sao Paulo was the most active city in Brazil with 1,637 papers in genomics and 428 in health biotechnology.The leading institutions include the Universidade de São Paulo in 1 st place for both genomics and health biotechnology, the Universidade Federal do Rio de Janeiro in 2 nd place in genomics and 3 rd place in health biotechnology, and the Fundação Oswaldo Cruz governmental institute in 3 rd place in genomics and 2 nd place in health biotechnology. ChinaIn China, Beijing is the most active city in both domains, having published 2,472 papers in genomics and 623 in health biotechnology.In China, the main institutions contributing to publications in genomics and health biotechnology come from the governmental and the university sectors.The Chinese Academy of Sciences dominates in terms of scientific output.This governmental institution ranks 1 st in genomics with 1,703 papers and also in health biotechnology with 318.Fudan University leads the university sector with 590 papers in genomics and 170 papers in health biotechnology.Overall, seven universities published more papers than the country average for most active institutions in genomics, and eight universities did so in health biotechnology. CubaIn Cuba, most of the scientific activity in genomics and health biotechnology is concentrated in Havana, which holds 90% of the papers in genomics and 95% of the papers in health biotechnology.Most scientific activity in Cuba is concentrated in the government.The Centro de Ingenieria Genética y Biotechnologià on its own accounts for half of Cuba's production in both domains, with 174 papers in genomics and 119 papers in health biotechnology. EgyptWith 253 papers in genomics and 91 papers in health biotechnology, Cairo is the most active city in Egypt.In Egypt, the main institutions contributing to publications in genomics and health biotechnology come from the university and governmental sectors.The Cairo University occupied the 1 st rank in genomics with 123 papers and in health biotechnology with 33 publications.The National Research Center is the leading institution within the government and ranked 4 th in genomics and 3 rd in health biotechnology. IndiaIn India, New Delhi, with 1,294 papers in genomics and 429 papers in health biotechnology, is the most active city.With 524 papers in genomics and 117 papers in health biotechnology, the most active institution, the Indian Institute of Science, is from the university sector.However, when grouping institutes from the same governmental entity, the Council of Scientific & Industrial Research (CSIR) ranks 1 st , followed by the Indian Institute of Science and the Indian Council of Agricultural Research (ICAR). Republic of KoreaIn the Republic of Korea, Seoul is the clear leader in both genomics and health biotechnology, holding about 50% of the country's papers in both domains.Seoul National University is clearly the country's leader with 1, 587 papers in genomics and 471 papers in health biotechnology.Among developing countries, South Korean companies are the most active in peerreviewed publishing. South AfricaJohannesburg and Cape Town are clearly the two most active South African cities in both genomics and health biotechnology in terms of the absolute number of papers.Leading institutions are principally from the academic sector.The four most prolific universities in both domains are the

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)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.998
Threshold uncertainty score0.622

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.008
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.020
GPT teacher head0.220
Teacher spread0.200 · 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
DomainEvaluation
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".

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Citations0
Published2004
Admission routes1
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