SU‐FF‐T‐266: Characterizing a Multi‐Axis Ion Chamber Array
Bibliographic record
Abstract
Purpose: To characterize a commercially available multi‐axis ion chamber array for use as a scanning water tank alternative. Method and Materials: The ion chamber array used in this study was the IC Profiler (Sun Nuclear Corporation: Melbourne, FL). We characterized four items of the array: reproducibility, dose linearity, backscatter response, and water tank agreement. Short and long term reproducibility's were established on a 60Co teletherapy unit (Eldorado 6; Atomic Energy of Canada Limited: Mississauga, Canada). The remaining tests were conducted with a Synergy (Elekta: Crawley, UK) linear accelerator (LINAC) operated at a nominal photon energy of 6MV. Results: Over a short time period the array displayed a maximum standard deviation of 0.55% and a mean standard deviation of 0.15%; over a long time period the array displayed a maximum standard deviation of 1.80% and a mean standard deviation of 0.76%. The array was sensitive to startup characteristics of the LINAC when operating in pulsed mode; this affected the dose linearity relative to a Farmer chamber operating under the same geometry. This effect was not observed when the array was operated in continuous mode. Both the array's central axis detector and a Farmer chamber displayed a similar increase in measured signal with increasing backscatter. However, with increasing backscatter (up to 16.6 cm) the arrays in‐beam‐profile shape changed by less than 0.7% relative to a setup with no additional backscatter. The agreement between the array and a scanning water tank differed by less than 1% in the beam. Conclusion: The IC Profiler is a viable option for water tank ‘like’ measurements. The device provides a stable platform with good dose linearity, minimal backscatter response, and uniform profile measurements. Conflict of Interest: This work was supported in part by SBIR Contract No. HHSN261200522014C, the University of Florida, and Sun Nuclear Corporation
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".