Bibliographic record
Abstract
Introduction. The need for continuing education and professional development for pharmacists and technicians in the field of oncology was identified at the British Columbia Cancer Agency (BCCA) annual cancer care conference in November 2000. As a result, in November 2001, the position of Pharmacy Communities Oncology Network (CON) Educator was created to support oncology pharmacy educational needs throughout the province of British Columbia. Objective. To describe how a pharmacy guide, specific to the needs of hospital oncology pharmacists in British Columbia, was developed. The guide will help to provide standardized and consistent oncology care, ensuring appropriate patient care and safety. Methods. A specific needs assessment was developed and distributed to oncology pharmacists practicing in the province of British Columbia. Results were evaluated to determine the topic of the first oncology module. Results. ‘Pharmacy Guide to BC Cancer Agency Chemotherapy Protocols: The Clinical Interpretation and Application of Treatment Protocol Summaries’waspublishedanddistributedin November 2003. Conclusion. Using the results of a provincially distributed needs survey, the Pharmacy Communities Oncology Network Educators at the BC Cancer Agency were able to assess the requirements of the hospital pharmacists in the communities and produce a pharmacy oncology guide targeted to their needs.
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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.039 | 0.024 |
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".