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Record W2585934222 · doi:10.1093/rpd/ncw385

A DISCUSSION ON DIFFERENT APPROACHES FOR ASSESSING LIFETIME RISKS OF RADON-INDUCED LUNG CANCER

2016· article· en· W2585934222 on OpenAlexaffabout
Jing Chen, Christophe Murith, Martha Palacios, Chunhong Wang, Senlin Liu

Bibliographic record

VenueRadiation Protection Dosimetry · 2016
Typearticle
Languageen
FieldHealth Professions
TopicRadioactivity and Radon Measurements
Canadian institutionsHealth Canada
Fundersnot available
KeywordsRadonEnvironmental healthPopulationLung cancerRadiological weaponRisk assessmentStatisticMedicineEnvironmental scienceStatisticsMathematicsOncologyNuclear physics

Abstract

fetched live from OpenAlex

Lifetime risks of radon induced lung cancer were assessed based on epidemiological approaches for Canadian, Swiss and Chinese populations, using the most recent vital statistic data and radon distribution characteristics available for each country. In the risk calculation, the North America residential radon risk model was used for the Canadian population, the European residential radon risk model for the Swiss population, the Chinese residential radon risk model for the Chinese population, and the EPA/BEIR-VI radon risk model for all three populations. The results were compared with the risk calculated from the International Commission on Radiological Protection (ICRP)'s exposure-to-risk conversion coefficients. In view of the fact that the ICRP coefficients were recommended for radiation protection of all populations, it was concluded that, generally speaking, lifetime absolute risks calculated with ICRP-recommended coefficients agree reasonably well with the range of radon induced lung cancer risk predicted by risk models derived from epidemiological pooling analyses.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.678
Threshold uncertainty score0.583

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.258
GPT teacher head0.452
Teacher spread0.194 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2016
Admission routes2
Has abstractyes

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