Bibliographic record
Abstract
The Ontario Ministry of Health and Long-Term Care has received the report of the independent panel that reviewed quality assurance in the province’s cancer-drug supply chain—following the distribution of diluted chemotherapy drugs to hospitals in Ontario and New Brunswick. In early April 2013, the province called on Jake Thiessen, the founding director of the University of Waterloo’s School of Pharmacy, to lead the review. His mandate was to determine how the chemotherapy underdosing occurred and to recommend ways to prevent reoccurrences. Dr. Thiessen delivered his report to the Ministry on July 12. His work was supported by a working group that included the Ontario College of Pharmacists (OCP), the Ontario Hospital Association, Cancer Care Ontario, the New Brunswick government, Health Canada and representatives from the affected hospitals—4 in Ontario and 1 in New Brunswick. The government promised to release Dr. Thiessen’s report to the public after it was reviewed. At the time of CPJ’s publication, the province was planning that release for the end of July. On May 27, Dr. Thiessen testified on some early findings of his inquiry before a committee of the Ontario legislature. He told the committee that he had found no evidence that Marchese Hospital Solutions, the company that prepared the cancer-drug solutions, had been attempting to cut corners. “There is no evidence of any malicious or deliberate drug-sparing dilution in preparing the bags of cyclophosphamide or gemcitabine,” he testified. Meanwhile, the Ontario government did not wait for Dr. Thiessen’s report before taking action to improve oversight over the supply of cancer drugs. On May 15, the province announced it was bringing in new regulations in 2 key areas. It granted authority to the OCP to inspect premises where a pharmacist or pharmacy technician engages in or supervises drug preparation activities. It also changed regulations to require Ontario hospitals to purchase drugs only from accredited, licensed or otherwise approved suppliers.
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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 | 0.031 | 0.097 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.016 | 0.003 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.015 | 0.010 |
| Insufficient payload (model declined to judge) | 0.043 | 0.019 |
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".