MO‐D‐301‐01: Joint AAPM/CCPM Sympsium: The Inverse Problem in Medical Physics Training — Defining the Objectives and Finding the Solutions
Bibliographic record
Abstract
The education and training of medical physicists has lately been a much discussed and somewhat contentious issue. There exists a spectrum of opinions on the optimal definition of the endpoint and on the appropriate pathway to get there. In order to find an optimal solution, a well‐defined objective must be established. What are the salient features of a medical physicist that education and training programs should produce? How do we best balance didactic and clinical training, and what role should research play in training programs? How many medical physicists do we need and will our training programs be able to produce them? What is the status of certification and how does this affect training? This symposium will address the following specific topics, with viewpoints from both American and Canadian speakers. Supply and Demand ‐ Michael D. Mills and Brenda Clark: How many medical physicists do we have? What are the appropriate staffing levels to provide adequate service? How many are we going to need to enter the workforce in the future? The safety of patients treated with radiation oncology associated with personnel credentialing and staffing has become the focus of national and international concern. ASTRO is revisiting the question of personnel staffing levels by organizing and re‐convening the “Blue Book” project; this is the first such effort since 1991. In addition, the International Atomic Energy Agency has convened an effort to establish recommended international staffing recommendations. A previously published supply and demand model for radiation oncology physicists is updated and presented to predict medical physicist employment market parameters through the year 2020. CAMPEP Accredited Programs ‐ Wayne Beckham: What is CAMPEP, what are the requirements for accreditation, and how does the process take place? How many accredited programs are there, and how many applications are pending? What is the future? The Status and Role of Certification ‐ G. Donald Frey and Dave Wilkins What role does certification play in the hiring and career paths of medical physicists? What is the relationship between registration, licensure, and career advancement? How many medical physicists are certified, and is this changing? How many uncertified medical physicists are in clinical practice? What are some of the barriers to certification? Educational Pathways and Training Programs ‐ Michael Herman and Jerry Battista: What should we be striving for in our training programs? What is the correct balance between didactic and clinical training? What role should research play in the training of medical physicists? Panel Discussion: The symposium will close with a panel discussion that will provide an opportunity for audience members to actively participate. Learning Objectives: 1. Understand the need to establish recommended personnel staffing levels for medical physicists 2. Understand a current model that predicts the supply and demand for radiation oncology physicists through 2020. 3. Understand the CAMPEP accreditation process 4. Understand the relevance of certification in the medical physics career path 5. Understand the need to strike a balance between clinical, didactic, and research training in the design of medical physics training programs
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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 | 0.013 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.051 | 0.028 |
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".