The 2004 Helene Hudson Memorial Lecture: Telling the story of SARS: Compassionate oncology care in the face of a futuristic health crisis
Bibliographic record
Abstract
On behalf of my colleagues, Janice Stewart, Colleen Johnson and Carolyn Saunders, we would like to thank CANO for the opportunity to share our experience on how oncology nurses can make a difference in a time of crisis. We would also like to thank AMGEN for the sponsorship of the Helene Hudson lectureship. Princess Margaret Hospital (PMH) is located in downtown Toronto, Ontario. Together with the Ontario Cancer Institute, PMH is a member of the University Health Network, which also includes the Toronto General Hospital and the Toronto Western Hospital. It is the only facility in Canada devoted exclusively to cancer research, treatment and education. The patient volumes at PMH are very high. The hospital sees about 10,000 new patients a year and has 130 inpatient beds, which includes both allogeneic and autologous bone marrow transplants. On a daily basis, 500 radiation treatments, 130 outpatient chemotherapy patients and 30 outpatient blood product transfusions are given. In total, 190,000 patients are treated annually as outpatients for diagnosis, treatment and follow-up.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.013 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".