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ESTIMATE OF ANNUAL AVERAGE RADON CONCENTRATION IN THE NORMAL LIVING AREA FROM SHORT-TERM TESTS

2003· article· en· W2015241719 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueHealth Physics · 2003
Typearticle
Languageen
FieldHealth Professions
TopicRadioactivity and Radon Measurements
Canadian institutionsHealth Canada
Fundersnot available
KeywordsRadonEnvironmental scienceTerm (time)Atmospheric sciencesStatisticsMathematicsGeology

Abstract

fetched live from OpenAlex

Most residential radon guidelines refer to annual average radon concentration in the normal living area. However, decisions on whether a house needs mitigation are usually based on short term radon tests. Depending on where detectors are placed and when tests are performed, results of those measurements can differ significantly from the annual average radon concentration in the normal living area. We provide a practical method based on survey results in 5486 Canadian houses to estimate annual average radon levels from results of screening tests. The average ratio of radon concentration in the basement to that of the upper floors in a house is determined, and the average relative seasonal variations of radon levels in the basement and of the upper floors are identified. Based on these relative quantities, estimate factors are derived for four different combinations of detector location and the living area and tabulated for different calendar periods of radon testing. The annual average radon level can be estimated by multiplying the result of a short-term screening test with the appropriate estimate factor given in this study.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.458

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.100
GPT teacher head0.414
Teacher spread0.315 · 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