The REPAIR Project, a Deep-Underground Radiobiology Experiment Investigating the Biological Effects of Natural Background Radiation: The First 6 Years
Bibliographic record
Abstract
In 2017, a special edition of Radiation Research was published [Oct; Vol. 188 4.2 (https://bioone.org/journals/radiation-research/volume-188/issue-4.2)] which focused on a recently established radiobiology project within SNOLAB, a unique deep-underground research facility. This special edition included original articles, reviews and commentaries relevant to the research goals of this new project which was titled Researching the Effects of the Presence and Absence of Ionizing Radiation (REPAIR). These research goals were founded in understanding the biological effects of terrestrial and cosmic natural background radiation (NBR). Since 2017, REPAIR has evolved into a sub-NBR radiobiology research program which investigates these effects using multiple model systems and various biological endpoints. This paper summarizes the evolution of the REPAIR project over the first 6-years including its experimental scope and capabilities as well as research accomplishments.
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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 | 0.017 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".