Bibliographic record
Abstract
Medical Physics is an interdisciplinary field that applies concepts and laws of physics in medical practices. Currently, one of its main applications is the use of ionizing radiation in the treatment of oncological diseases. Due to its wide use and highly dangerous, many of radioprotection procedures should be adopted with the objective of protecting human beings from harmful effects of radiation. Thus, you can better enjoy the benefits that the practice can offer. The methodology proposed by the National Council on Radiation Protection 151 (NCRP 151), relates technical information necessary to Structural Shielding Design and Evaluation for Megavoltage X- and Gamma- Ray Radiotherapy Facilities. However, many parameters used to calculate the shield are based on estimates only, and it is an international standard that may not be adequate to the Brazilian reality. Thus, the central idea of this study is the collection of data from the routine of the Radiotherapy Service of the Real e Benemérita Associação Portuguesa de Beneficência, in particular equipment cobalt therapy Theratron 780 (Atomic Energy of Canada Ltd.) and the linear accelerator Varian Clinac 2100C for measurement of workload, number of patients, fields, and dose factors to determine the best use of barrier protection. Furthermore, this work features a profile of radiotherapy treatments carried out closer to the Brazilian reality
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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 | 0.013 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".