The Terry Fox Research Institute’s West Coast Dialogue: Are We Prepared for Personalized Medicine?
Bibliographic record
Abstract
This meeting report is the second in a series by the Terry Fox Research Institute about its Pan-Canadian Dialogue Series on Cancer: Let’s Get Personal, a public research and outreach project. The inaugural dialogue was held in St. John’s, Newfoundland and Labrador, in April 2010 on the thirtieth anniversary of the Marathon of Hope. That dialogue launched a continuing conversation that the Institute is having with the Canadian public during 2010. This report summarizes the dialogue held at Simon Fraser University’s Morris J. Wosk Centre for Dialogue in Vancouver, 12 May 2010: “Are We Prepared for Personalized Medicine?” The world is in the midst of a technology renaissance that will change medical practices and improve cancer treatment for every individual. Do we know how society will be affected by personalized medicine over the coming decades? Members of the medical and scientific communities in British Columbia and the public, including cancer survivors, patients, and caregivers, discussed the challenges that lie ahead for Canadians—ethically, economically, socially, clinically, and from a health management perspective—in preparing for personalized medicine, which some experts predict to be fewer than five years away. New technology, including advances in dna sequencing, will require tough choices and decisions to be made by society, and values will be at the centre of those decisions. The directions taken will change health care as we know it today. Issues such as societal values, freedom of information, access, consent, and having personal genomic information literally at our fingertips will form the heart of the discussion.
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 | 0.034 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.034 | 0.015 |
| Scholarly communication | 0.018 | 0.009 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.014 | 0.027 |
| Insufficient payload (model declined to judge) | 0.018 | 0.004 |
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".