Neutron spectrometry and dosimetry study at two research nuclear reactors using Bonner sphere spectrometer (BSS), rotational spectrometer (ROSPEC) and cylindrical nested neutron spectrometer (NNS)
Why this work is in the frame
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Bibliographic record
Abstract
Neutron spectrometry and subsequent dosimetry measurements were undertaken at the McMaster Nuclear Reactor (MNR) and AECL Chalk River National Research Universal (NRU) Reactor. The instruments used were a Bonner sphere spectrometer (BSS), a cylindrical nested neutron spectrometer (NNS) and a commercially available rotational proton recoil spectrometer. The purposes of these measurements were to: (1) compare the results obtained by three different neutron measuring instruments and (2) quantify neutron fields of interest. The results showed vastly different neutron spectral shapes for the two different reactors. This is not surprising, considering the type of the reactors and the locations where the measurements were performed. MNR is a heavily shielded light water moderated reactor, while NRU is a heavy water moderated reactor. The measurements at MNR were taken at the base of the reactor pool, where a large amount of water and concrete shielding is present, while measurements at NRU were taken at the top of the reactor (TOR) plate, where there is only heavy water and steel between the reactor core and the measuring instrument. As a result, a large component of the thermal neutron fluence was measured at MNR, while a negligible amount of thermal neutrons was measured at NRU. The neutron ambient dose rates at NRU TOR were measured to be between 0.03 and 0.06 mSv h⁻¹, while at MNR, these values were between 0.07 and 2.8 mSv h⁻¹ inside the beam port and <0.2 mSv h⁻¹ between two operating beam ports. The conservative uncertainty of these values is 15 %. The conservative uncertainty of the measured integral neutron fluence is 5 %. It was also found that BSS over-responded slightly due to a non-calibrated response matrix.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it