Bibliographic record
Abstract
Abstract The development of three-dimensional (3D) dosimetry was motivated by its promise as an effective methodology for the validation of the complex dose distributions achieved by modern techniques such as Intensity Modulated and Volumetric Arc Radiation Therapy. 3D techniques were first proposed in the 1980s when clinics were just starting to move from two-dimensional contour plan based delivery to more conformal techniques. Advances in dosimeter materials, readout systems, and workflow and software systems for the registration and analysis of the volumetric dose data have made 3D dosimetry more attainable, yet to date it has not made major inroads into the clinic. This keynote address will highlight some 3D dosimetry developments over the years, many of which were first revealed through the past twelve International Conferences on 3D and Advanced Radiation Dosimetry (IC3Ddose). These conferences resulted in the publication of more than 130 didactic review articles and over 650 proffered research papers, the majority openly available on the internet (years before the current drive to publishing in open access journals). In this joint keynote address to the IC3Ddose community (at the end of its conference) and to attendees of the Canadian Organization of Medical Physicists annual scientific meeting (at its start), I will briefly review the radiation sensitive materials used for 3D dosimetry, the imaging systems required to read out the volumetric dose information, the workflows and systems required for efficient analysis, and the protocols required for reproducible dosimetry, and how the dosimetry has come into the clinic. The address includes some personal reflections of the motivational and practical changes in 3D dosimetry over time. And as we are all meeting in person for the first time in over two years, the address will end with some observations on the importance of conferences for the exchange of ideas and associated debate necessary for scientific advancement.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.014 | 0.007 |
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".