Bibliographic record
Abstract
Stereotactic Radiosurgery involves the use of highly focused ionizing radiation beams to treat localized cancer tumours and lesions. Due to the damaging effects of radiation on healthy tissue, quality assurance checks must take place before treatment to ensure accurate delivery. This is of critical importance in cases like brain tumours, in which the healthy tissue at risk is in close proximity to the target volume. A dodecahedral radiosurgical phantom was designed and fabricated to measure the isocentre variation of a linear accelerator at an isocentric irradiation facility. It was shown that the phantom can localize individual treatment beams to within an uncertainty of 0.2mm. Due to the intrinsic accuracy of the phantom, it was found that careful phantom design and manufacturing as well as an accurate and complex characterization, in terms of measurements, positioning and computer modeling, must take place. This accurate characterization of the phantom is crucial to ensure the accurate treatment of stereotactic radiosurgery. This research is part of a larger project to further develop the phantom we have introduced in order to exploit a wider set of functions pertaining to maintaining accurate treatment delivery.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".