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Record W7019384304

Gene Patents and Licensing Practices and their Impact on Patient Access to Genetic Tests

2010· other· en· W7019384304 on OpenAlexfundno aff

Bibliographic record

VenueDigitalGeorgetown (Georgetown University Library) · 2010
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
FundersNational Institutes of HealthMcGill UniversityU.S. Department of Energy
KeywordsGenetic testingTest (biology)MEDLINEGovernment (linguistics)Confidentiality
DOInot available

Abstract

fetched live from OpenAlex

SACGHS was first chartered in the fall of 2002 to formulate advice and recommendations on the range of complex and sensitive medical, ethical, legal, and social issues raised by new technological developments in human genetics, including the development and use of genetic tests.One of the specific issues that the charter calls on SACGHS to examine is "current patent policy and licensing practices for their impact on access to genetic technologies."Accordingly, during the development of its first study agenda in 2003-2004, the Committee identified the role that gene patenting and licensing practices may play in patient access to genetic tests as a priority issue.SACGHS' predecessor, the Secretary's Advisory Committee on Genetic Testing (SACGT), 1 also looked into the issue of the impact of gene patents on patient access.In 2000-following consultations with representatives from the Federal Government, industry, academia and patient communities; legal experts; clinicians; and ethicists-SACGT concluded that further data and analysis were needed to determine whether certain patenting and licensing approaches (a) have adverse effects on access to and the cost and quality of genetic tests, (b) deter laboratories from offering tests beneficial to patients because of the use of certain licensing practices, (c) affect the training of specialists who offer genetic testing services, or (d) affect the development of quality assurance programs.In a letter to the Secretary of Health and Human Services, SACGT also acknowledged that gene patents can be critical to the development and commercialization of gene-related products and services.In an August 8, 2001, reply to SACGT, the Acting

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.223
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0020.004
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.016
GPT teacher head0.231
Teacher spread0.215 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2010
Admission routes1
Has abstractyes

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