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Record W4280640249 · doi:10.17850/njg101-4-2

Towards a new radon hazard map of Norway using Trøndelag county as a test area

2022· article· en· W4280640249 on OpenAlexfundno aff
Odleiv Olesen, Torleif Lauritsen, Marie‐Andrée Dumais, Trond Slagstad, Frode Ofstad

Bibliographic record

VenueNorwegian Journal of Geology · 2022
Typearticle
Languageen
FieldHealth Professions
TopicRadioactivity and Radon Measurements
Canadian institutionsnot available
FundersWintershall DeaOljedirektoratetAker BPSuncor Energy IncorporatedConocoPhillips
KeywordsRadonGeologyTest (biology)HazardPaleontology

Abstract

fetched live from OpenAlex

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 Trndelag 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 Trndelag 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.496
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0070.000

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.

Opus teacher head0.084
GPT teacher head0.370
Teacher spread0.286 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2022
Admission routes1
Has abstractyes

Explore more

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