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Record W2496902493 · doi:10.4324/9780429047053-18

Nuclear Waste Disposal: Technology and Environmental Hazards 1

2019· book-chapter· en· W2496902493 on OpenAlexaff
F. Kenneth Hare, A.M. Aikin

Bibliographic record

VenueNuclear Power · 2019
Typebook-chapter
Languageen
FieldHealth Professions
TopicRadioactivity and Radon Measurements
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsWaste managementRadioactive wasteEnvironmental scienceBusinessEngineering

Abstract

fetched live from OpenAlex

The waste from the nuclear industries requires comprehensive treatment if man and nature are to be protected against radioactivity. Though nuclear wastes are not alone in being dangerous to life, they have acquired special visibility in the past few years. The nuclear fuel-cycle begins with the extraction of uranium ores from rock and ends with the disposal of wastes. Radioactive wastes are produced at all stages of the nuclear fuel cycle, though the major quantities occur at the front and back ends of the cycle. Wastes from the mining operation consist of waste rock, or very low grade ore, which can be disposed of in the mine if it presents an exposure hazard and liquid waste, a combination of mine drainage and water used in the mining operation, and which is generally all used in the mill. It also include: Gaseous wastes, the exhaust ventilation, which contains radon gas as well as ore dust.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.662
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0120.010

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 head0.021
GPT teacher head0.283
Teacher spread0.261 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations4
Published2019
Admission routes1
Has abstractyes

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