Bibliographic record
Abstract
Introduction In September 2007, the decoded genome of J. Craig Venter, a pioneering genetics researcher, was released to the world. (1) This achievement attracted worldwide media attention, with stories making the inevitable leap from the publication of one man's genome to the promise of personalized medicine for many. Globe and Mail, a Canadian national newspaper, proclaimed: Scientists have for the first time decoded the complete DNA sequences of a single human being, a mammoth feat that ... marks a historic step toward the era when medical care can be tailored to an individual's genes. (2) Remarkable advances in modern genetic research are revealing the genetic foundations of human traits, including genes that promote or protect against development of complex, common diseases. (3) As knowledge of genomics expands, patients/consumers, health care practitioners, firms that develop and sell genetic testing services and related products, and government policy-makers and regulators, all develop increasing interest in a field that may offer means to improve individual and public health. field of nutritional genomics is an area where early results from the human genome project [are being translated] into publicly accessible applications. (4) Some nutrigenetic tests are currently available for consumers to purchase directly from a company or to obtain through a health care provider. Genetic test kits for home use--where a consumer collects a genetic sample at home and then mails it to a laboratory for analysis--raise several concerns: the consumer may not fully understand the test and the benefits and risks of learning the results; the consumer may conduct the test incorrectly and submit a sample and information that are inaccurate; and the consumer may not receive adequate interpretation and follow-up regarding the results and any recommended future action. (5) Consequently, the hazards associated with genetic testing include potential physical, medical, psychological, and social and economic risks to individuals being tested and to members of their families. (6) Benefits, in contrast, include the ability to take steps to mitigate known disease risks, tailor treatment options or gain peace of mind. Concerns associated with genetic tests, particularly when marketed directly to consumers, have attracted much attention by governmental bodies, (7) watchdog agencies, (8) and academic commentators. (9) Regulation of genetic tests--and, for that matter, all medical devices--depends on the intended use and risks. Factors relevant to assessing risks involved in genetic testing include whether: the test is diagnostic or predictive; the disease is rare or common; the genetic mutation is of high or low penetrance; interventions are available for individuals who have a genetic predisposition; and affected individuals or groups will be exposed to stigmatization or discrimination. (10) mode of delivery of the test is also relevant: tests marketed for home use are typically viewed as posing greater risks than tests available only through a health care intermediary. To date, most concerns expressed about nutrigenetic tests do not focus on medical, psychological and social risks, but rest on the view that nutrigenomic science is still too premature to offer clinically useful information and advice to consumers. Trujillo and colleagues note: Although unprecedented opportunities exist for the expanded use of foods and bioactive food components to achieve genetic potential, increase productivity, and decrease risk of disease, the science to make such decisions has not reached a level of confidence to achieve personalized nutrition recommendations. (11) Arab contends: The information needed to individualize recommendations is largely unavailable for most nutrients. (12) immediate risk in nutrigenetic testing, then, is primarily economic: consumers who purchase nutrigenetic tests are wasting their money. …
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 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 | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.002 |
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".