Bibliographic record
Abstract
So why should you care about these 2 initiatives? Many hospital pharmacists perceive that the Blueprint for Pharmacy is only for community pharmacists, and others feel that the Blueprint has no relevance for them because they already practise in an advanced clinical role. However, many pharmacists face resource and staffing challenges that hinder their advancement, and the Blueprint is designed to help in addressing these issues. In addition, many objectives in the Blueprint are closely aligned with those of the CSHP 2015 initiative. Therefore, CSHP will soon be asking hospital pharmacists and pharmacy departments to endorse these 2 initiatives by signing a “Commitment to Act”. Making this formal commitment will demonstrate that you believe in what you are doing as a professional and that you believe all pharmacists should practise in an advanced clinical way. The vision for practice advancement is here, and now is the time to adopt this vision as your own. This fall, show your support by signing the Commitment to Act on CSHP 2015 and the Blueprint for Pharmacy. Doing so will be your first step in making a difference and promoting the advancement of the profession.
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 | 0.051 | 0.121 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.017 |
| Scholarly communication | 0.021 | 0.011 |
| Open science | 0.003 | 0.026 |
| Research integrity | 0.029 | 0.046 |
| Insufficient payload (model declined to judge) | 0.017 | 0.005 |
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".