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Lifetime analysis of the ITER first wall under steady-state and off-normal loads

2011· article· en· W2043395204 on OpenAlexaff
R. Mitteau, M. Sugihara, R. Raffray, S. Carpentier‐Chouchana, H. Labidi, M. Merola, R.A. Pitts, P.C. Stangeby

Bibliographic record

VenuePhysica Scripta · 2011
Typearticle
Languageen
FieldMaterials Science
TopicFusion materials and technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSteady state (chemistry)MechanicsNuclear engineeringMaterials sciencePhysicsChemistry

Abstract

fetched live from OpenAlex

The lifetime of the beryllium armor of the ITER first wall is evaluated for normal and off-normal operation. For the individual events considered, the lifetime spans between 930 and 35×106 discharges. The discrepancy between low and high estimates is caused by uncertainties about the behavior of the melt layer during off-normal events, variable plasma operation parameters and variability of the sputtering yields. These large uncertainties in beryllium armor loss estimates are a good example of the experimental nature of the ITER project and will not be truly resolved until ITER begins burning plasma operation.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.024
GPT teacher head0.219
Teacher spread0.195 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations17
Published2011
Admission routes1
Has abstractyes

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