Miniature tissue‐equivalent proportional counters for BNCT and BNCEFNT dosimetry
Bibliographic record
Abstract
A dual miniature tissue-equivalent proportional counter (TEPC) system has been developed to facilitate microdosimetry for Boron Neutron Capture Therapy (BNCT). This system has been designed specifically to allow the analysis of the single event charged particle spectrum in phantom in high intensity BNCT beams and to provide this microdosimetric information with excellent spatial resolution. Paired A-150 and 10B-loaded A-150 TEPCs with 12.3 mm3 collecting volumes have been constructed. These TEPCs allow more accurate neutron dosimetry than current techniques, offer a direct measure of the boron neutron capture dose, and provide a framework for predicting the biological effectiveness of the absorbed dose. Design aspects and characterization of these detectors are reviewed, along with an exposition of the advantages of microdosimetry using these detectors over conventional dosimetry methods. In addition, the utility of this technique for boron neutron capture enhancement of fast neutron therapy (BNCEFNT) is discussed.
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 | 0.002 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".