DNA‐Sequence Patenting: National Society of Genetic Counselors (NSGC) Position Paper
Bibliographic record
Abstract
In November 2000, the Genetic Services Committee of the National Society of Genetic Counselors (NSGC) convened a working group to draft a position paper on patenting DNA-sequences. The mandate of the group was to produce general position statements that support the perspective and needs of consumers of DNA-based genetic tests and therapies (our patients and their families) and participants in DNA-based genetic research. After review and discussion of the literature on DNA-sequence patenting issues, the working group drafted position statement points that support current United States Patent and Trademark Office (USPTO) guidelines; broad licensing of DNA-sequence patents; nonenforcement of DNA-sequence patents in noncommercial research; reasonable royalty rates; an informed consent process for research participants that discloses whether they can share in any financial rewards relating to the project; the development of guidelines for licensing of DNA-sequence patents; and the establishment of oversight organizations to monitor licensing of DNA-sequence patents. These position statements were approved by the NSGC Board of Directors in the fall of 2001.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.028 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.044 | 0.011 |
| Insufficient payload (model declined to judge) | 0.022 | 0.013 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".