Alignment and position visualization methods for the biomedical imaging and therapy (BMIT) MRT lift
Bibliographic record
Abstract
The Microbeam Radiation Therapy (MRT) Lift is an eight stage positioning and scanning system at the Canadian Light Source’s BMIT Facility. Alignment of the sample with the beam using the MRT Lift is a time consuming and challenging task. The BMIT Group has developed a Python-based MRT Lift positioning and control program that uses a combination of computational and iterative methods to independently adjust the sample’s X, Y, Z, pitch and roll positions. The program offers “1-Click” alignment of the sample to the beam. Use of a wireframe visualization technique enables even minute movements to be illustrated. Proposed movements and the resulting MRT Lift position can be manually verified before being applied. Optional integration with the SolidWorks modelling platform allows high quality renderings of the MRT Lift in its current or proposed position to be displayed in real time. Human factors principles are incorporated into the program with the objective of delivering easy to use controls for this complex device.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 0.005 |
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".