Towards a new radon hazard map of Norway using Trøndelag county as a test area
Bibliographic record
Abstract
Indoor radon constitutes a serious health concern to the population of Norway and this study discusses the need for a new and improved radon hazard map of Norway.To this end, we present a procedure for producing a radon hazard map, using Trøndelag county as a test area, based on equivalent-uranium (eU) from 12 airborne gamma-ray spectrometer surveys and 486 whole-rock chemical analyses of bedrock samples covering large tracts of the county.The current radon hazard map for Norway is based on extrapolation of indoor radon measurements using existing bedrock maps.A previously published relationship between eU concentration from airborne surveys and indoor radon measurements in the Oslo Fjord region forms the basis of the new map.Ground natural gamma-radiation measurements along main roads, supplementary XRF analyses from anomalous sites and indoor radon measurements have been used to validate the new radon hazard map.In many areas, the new radon hazard map for Trøndelag county deviates significantly from the current radon hazard map.For example, the current map shows 'Moderate to low risk' in areas with anomalous high eU values.The new Coop-project radiometric compilation also reveals other eU anomalies along the coast of southern and western Norway that are not reflected in the current radon awareness map.We conclude that there is a need to produce a new radon hazard map for all of Norway based on data with a dense regional coverage rather than sparse, clustered indoor measurements.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".