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Record W4296700295 · doi:10.1088/1361-6498/ac9396

A review of current inventory for major industries involving naturally occurring radioactive materials in Canada

2022· review· en· W4296700295 on OpenAlexaffabout
Jing Chen

Bibliographic record

VenueJournal of Radiological Protection · 2022
Typereview
Languageen
FieldHealth Professions
TopicRadioactivity and Radon Measurements
Canadian institutionsHealth Canada
Fundersnot available
KeywordsRadioactive wasteRadiological weaponRadionuclideNatural (archaeology)BusinessEnvironmental scienceNorm (philosophy)Natural resourceHazardous wasteEnvironmental planningNatural resource economicsWaste managementEnvironmental healthEngineeringPolitical scienceGeographyMedicineChemistryRadiochemistryLawArchaeologyEconomics

Abstract

fetched live from OpenAlex

Earth materials contain radionuclides of natural origin in varying concentrations. Exposure to natural sources dominates the occupational and public exposure to ionizing radiation. Canada has one of the largest and most diverse supplies of natural resources in the world. A large quantity of material production is associated with a large quantity of waste releases to the environment. Releases from industries involving naturally occurring radioactive material (NORM) can concentrate trace amounts of natural radionuclides and are often poorly characterized. This raises concerns for occupational and public health. Currently, there are data and knowledge gaps in radiological characteristics of NORM products and waste or releases to the environment. For the evaluation of occupational and public exposure to natural sources, a review of current inventory for major industries involving NORM in Canada was conducted with the objective to provide basic information on major issues, help set the priority for research needs to filling these data and knowledge gaps.

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)0.006
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.815
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.004
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 head0.383
GPT teacher head0.461
Teacher spread0.077 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations5
Published2022
Admission routes2
Has abstractyes

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