Achieving the World Health Organization's vision for clinical pharmacology
Bibliographic record
Abstract
Clinical pharmacology is a medical specialty whose practitioners teach, undertake research, frame policy, give information and advice about the actions and proper uses of medicines in humans and implement that knowledge in clinical practice. It involves a combination of several activities: drug discovery and development, training safe prescribers, providing objective and evidence-based therapeutic information to ethics, regulatory and pricing bodies, supporting patient care in an increasingly subspecialized arena where co-morbidities, polypharmacy, altered pharmacokinetics and drug interactions are common and developing and contributing to medicines policies for Governments. Clinical pharmacologists must advocate drug quality and they must also advocate for sustainability of the Discipline. However for this they need appropriate clinical service and training support. This Commentary discusses strategies to ensure the Discipline is supported by teaching, training and policy organizations, to communicate the full benefits of clinical pharmacology services, put a monetary value on clinical pharmacology services and to grow the clinical pharmacology workforce to support a growing clinical, academic and regulatory need.
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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 | 0.010 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".