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Record W2101344488 · doi:10.1667/rr0552.1

The 15-Country Collaborative Study of Cancer Risk among Radiation Workers in the Nuclear Industry: Study of Errors in Dosimetry

2007· article· en· W2101344488 on OpenAlexaff
Isabelle Thierry-Chef, M Marshall, J.J. Fix, F. Bermann, Ethel S. Gilbert, Carl D. Hacker, B. Heinmiller, Walter Murray, Mark S. Pearce, David F. Utterback, K. Bernar, P. Deboodt, Matias Eklöf, Birutė Gricienė, K Holan, H. Hyvönen, A. Kerekes, M-C. Lee, Mirjana Moser, F. Pernička, Elisabeth Cardis

Bibliographic record

VenueRadiation Research · 2007
Typearticle
Languageen
FieldMedicine
TopicRadiation Dose and Imaging
Canadian institutionsCanadian Nuclear Laboratories
FundersU.S. Public Health Service
KeywordsDosimeterDosimetryIonizing radiationNuclear medicineMedical physicsCalibrationRadiation protectionMedicinePhysicsEnvironmental scienceStatisticsIrradiationMathematicsNuclear physics

Abstract

fetched live from OpenAlex

Thierry-Chef, I., Marshall, M., Fix, J. J., Bermann, F., Gilbert, E. S., Hacker, C., Heinmiller, B., Murray, W., Pearce, M. S., Utterback, D., Bernar, K., Deboodt, P., Eklof, M., Griciene, B., Holan, K., Hyvonen, H., Kerekes, A., Lee, M-C., Moser, M., Pernicka, F. and Cardis, E. The 15-Country Collaborative Study of Cancer Risk among Radiation Workers in the Nuclear Industry: Study of Errors in Dosimetry. Radiat. Res. 167, 380–395 (2007).To provide direct estimates of cancer risk after low-dose protracted exposure to ionizing radiation, a large-scale epidemiological study of nuclear industry workers was conducted in 15 countries. As part of this study, identification and quantification of errors in historical recorded doses was conducted based on a review of dosimetric practices and technologies in participating facilities. The main sources of errors on doses from “high-energy” photons (100–3000 keV) were identified as the response of dosimeters in workplace exposure conditions and historical calibration practices. Errors related to dosimetry technology and radiation fields were quantified to derive period- and facility-specific estimates of bias and uncertainties in recorded doses. This was based on (1) an evaluation of predominant workplace radiation from measurement studies and dosimetry expert assessment and (2) an estimation of the energy and geometry response of dosimeters used historically in study facilities. Coefficients were derived to convert recorded doses to Hp (10) and organ dose, taking into account different aspects of the calibration procedures. A parametric, lognormal error structure model was developed to describe errors in doses as a function of facility and time period. Doses from other radiation types, particularly neutrons and radionuclide intake, could not be adequately reconstructed in the framework of the 15-Country Study. Workers with substantial doses from these radiation types were therefore identified and excluded from analyses. Doses from “lower-energy” photons (<100 keV) and from “higher-energy” photons (>3 MeV) were estimated to be small.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.986
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.031
GPT teacher head0.418
Teacher spread0.387 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
DomainMethods
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

Citations91
Published2007
Admission routes1
Has abstractyes

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