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Record W3094448130 · doi:10.1115/icone2020-16517

Unmet Challenges to Successfully Mitigating Severe Accidents in Multi Unit CANDU Reactors

2020· article· en· W3094448130 on OpenAlexaboutno aff
Sunil Nijhawan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicNuclear and radioactivity studies
Canadian institutionsnot available
Fundersnot available
KeywordsUnit (ring theory)Closure (psychology)Safety cultureAction (physics)EngineeringBusinessRisk analysis (engineering)Forensic engineeringAeronauticsPolitical sciencePsychologyLawEconomics

Abstract

fetched live from OpenAlex

Abstract One sees eerie similarities here in Canada to the cozy relationship between regulator and utilities in ‘pre-Fukushima’ Japan. Such ties are hardly limited to Canada though. The chronic degradation of real commitments to continued improvements in reactor safety systems and a decline in overall safety culture that discourages critical design reviews and willfully ignores well justified, safety critical hardware upgrades, has created alarming conditions that are likely inching us towards another nuclear disaster. Operating CANDU reactors are now close to being obsolete but have barely seen any substantive severe accident related risk reduction upgrades nine years after Fukushima, hoopla in Canada around some minor improvements and premature closure of even otherwise sparse and what were really weak regulatory ‘Fukushima Action Items’ notwithstanding.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.286
Threshold uncertainty score0.492

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.062
GPT teacher head0.266
Teacher spread0.204 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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