Dose measurement of cobalt-60 radiotherapy beams in treatment fields.
Bibliographic record
Abstract
BACKGROUND: Radiation-therapy is a complex process with multiple steps, each of which has an impact on the quality of treatment. Accurate dosimetry is a critical step during the radiotherapy of cancer patients.The aim of the present study was to measure and evaluate the doses of two cobalt- 60 (60Co) teletherapy units GWXJ80 of NPIC China and Theratron 780 of AECL Canada at various points within fields for different field sizes. METHODS: This cross-sectional descriptive study was done to measure the 60Co doses in the treatment fields.The dose measurements were done in air and 30x30x30 cm3 Phantom at 80 cm SSD by using calibrated NE 2570 Farmer Electrometer & NE 2571 Farmer Ionization Chamber and percentage of doses were calculated. RESULTS: The results showed that 60% central area of all fields ranging from 100-98.79% and 100-96.12% for GWXJ80 in the air and phantom, whereas for Theratron 780, they were ranging from 100-98.50% and 100-96.45% in air and phantom respectively. The percentages of doses at the edges for GWXJ80 and Theratron 780 in the air were 75.39-38.66% & 85.65-46.47% respectively and they were 82.22-40.39% & 49.05-24.55% respectively in phantom. CONCLUSIONS: The doses within 60% central area of fields in air were higher than phantom for both teletherapy units. The doses at field edges in air were lower in GWXJ80 than Theratron 780 whereas in phantom they were vice versa. But all were in the acceptable range as recommended by International Commission on Radiation Units and Measurements.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".