Bibliographic record
Abstract
Depending on neutron energy, a number of personnel neutron dosimeters such as NTA film, Albedo TLD dosimeter and Nuclear Track Detectors (CR39) have been developed and reported so far. At present, CR-39 is in use as personnel neutron dosimeters for neutron monitoring of occupational workers in most of the nuclear installations due to non-availability high sensitive real time gamma insensitive personnel neutron dosimeters as per ICRP recommendations. The Superheated Emulsion Detector or bubble detector assess the magnitude of detrimental effects on health of person exposed to neutron radiation in terms of absorbed dose or equivalent dose even in presence of high gamma radiations flux in real time unlike nuclear track detectors. Bubble Technology Industries (BTI), Canada and Aphel Enterprises, USA have commercialized these type of bubble detectors for neutron and gamma measurements. The paper will elaborate the basic principle, special features, mechanism of bubble formation, national and international status including it's applications in accelerator Physics, Medical sciences, nuclear submarine and neutron /gamma dose measurements in nuclear reactors. These detectors may be most popular in due course among health physicists due to it's reusability and precise measurements for neutron measurements in reactor environment, pulse neutron measurements and personal neutron dosimetery.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| 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) | 0.008 | 0.002 |
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".