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Record W4410032764 · doi:10.1097/hp.0000000000001986

Performance Evaluation of Electronic Radon Monitors Available to the General Public

2025· article· en· W4410032764 on OpenAlex
Alexander Lemieux, Pawel Mekarski, Hailey Adams, Rishi Patni, Brian Bjorndal, J. Suys, Ian T. Lawson

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 · 2025
Typearticle
Languageen
FieldHealth Professions
TopicRadioactivity and Radon Measurements
Canadian institutionsSnolabHealth Canada
Fundersnot available
KeywordsRadonRadon exposureReliability (semiconductor)BusinessEnvironmental healthComputer scienceEnvironmental scienceMedicine

Abstract

fetched live from OpenAlex

In recent years, consumer-grade electronic radon monitors (ERMs) have become increasingly popular for measuring radon in residences and public buildings. Many of these devices are designed for use by the general public, with features and price points that make them accessible alternatives to passive detection methods such as alpha track detectors. However, the influx of new devices into the market and the absence of independent performance evaluations have raised concerns about the reliability of manufacturer claims. This study evaluated the performance of 15 different consumer-grade ERMs at prices less than $400 Canadian (CAD) and which were readily available through online marketplaces under radon exposure conditions ranging from 110 to 2,400 Bq m -3 . Short-term (2- to 3-wk) tests were conducted in radon chambers at Health Canada and Radiation Safety Institute of Canada facilities. Long-term (13-wk) tests were conducted at the underground low-background counting room at SNOLAB. Testing revealed two distinct groups of high- and low-performance ERMs, with absolute mean differences (AMDs) either less than 22% or ranging from 28-238%, compared to reference devices. Long-term testing showed that most ERMs demonstrated improved accuracy with prolonged exposures. This study also highlights the impact of several environmental and technical factors on ERM performance and emphasizes the need to consider performance indicators beyond accuracy. These findings underscore the critical need for independent third-party testing to validate the performance of ERMs, alongside the establishment of robust standards and regulatory frameworks to ensure the reliability of radon measurements, protect public health, and foster consumer confidence.

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)0.004
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.433
Threshold uncertainty score0.833

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.190
GPT teacher head0.467
Teacher spread0.277 · 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