DOSIMETRIC CHARACTERISATION OF A SUB-NATURAL BACKGROUND RADIATION ENVIRONMENT FOR RADIOBIOLOGY INVESTIGATIONS
Bibliographic record
Abstract
Living systems have evolved in the presence of naturally occurring ionising radiation. REPAIR is a research project investigating the biological effects of sub-natural background radiation exposure in SNOLAB, a deep-underground laboratory. Biological systems are being cultured within a sub-background environment as well as two control locations (underground and surface). A comprehensive dosimetric analysis was performed. GEANT4 simulation was used to characterise the contribution from gamma, muons and neutrons. Additionally, dose rates from radon, 40K and 14C were calculated based on measured activity concentrations. The total absorbed dose rate in the sub-background environment was 27 times lower than the surface control, at 2.48 ± 0.20 nGy hr-1, including a >400-fold reduction in the high linear energy transfer components. This modelling quantitatively confirms that the environment within SNOLAB provides a substantially reduced background radiation dose rate, thereby setting the stage for future sub-background biological studies using a variety of model organisms.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".