The scholarly radiation therapist. Part one: charting the territory
Bibliographic record
Abstract
Abstract As radiation therapy practice evolves with advancing treatment and planning technologies, merging of imaging modalities, changing working models and the advancement to higher education, radiation therapists are frequently finding themselves on the frontline of translating new knowledge into practice. To a large degree, this growing involvement in self-directed original research, with associated dissemination of completed results, has led to an increasing number of therapists being encouraged to pursue an academic path in addition to a clinical career. In Canada, radiation therapists are being appointed as faculty to university departments for the first time. It is heartening that such opportunities are increasing; therapists are able to play a profound role in developing an evidence-based professional body of knowledge while at the same time being recognised for scholarly endeavours. However, despite these many positive steps, barriers and challenges to the development of a scholarly culture for radiation therapists still exist. Part one of this two-part series explores the history of the profession and the subsequent development of a scholarly culture.
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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 | 0.016 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.017 | 0.016 |
| Scholarly communication | 0.016 | 0.011 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.017 | 0.006 |
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".