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Record W2124386244 · doi:10.1088/0741-3335/44/5a/351

A 1-D predictive model for energy and particle transport in H-mode

2002· article· en· W2124386244 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePlasma Physics and Controlled Fusion · 2002
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsInstitut National de la Recherche ScientifiqueHydro-Québec
Fundersnot available
KeywordsPedestalJet (fluid)PlasmaScalingASTRAPhysicsConsistency (knowledge bases)Computational physicsMode (computer interface)Statistical physicsMechanicsNuclear physicsComputer scienceMathematicsMechanical engineering

Abstract

fetched live from OpenAlex

In the last few years, significant progress has been made in the understanding of H-mode plasmas (e.g. ion temperature profile stiffness, pedestal physics, etc). Based on this improved understanding, a set of rules (models) comprising a physics picture of the H-mode has been implemented in the ASTRA code in order to improve the understanding of experimental observations and ultimately to provide a predictive capability for ITER complementary to the scaling relations. The model has been verified for consistency with experimental observations in ASDEX-UG and JET plasmas. Numerical coefficients for the transport, required because of simplifications or missing quantitative information, are determined for one plasma (e.g. from JET) and then held constant for all others (JET, ASDEX-UP, ITER).

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.

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 categoriesInsufficient payload (model declined to judge)
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 score0.980
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.013
GPT teacher head0.227
Teacher spread0.214 · 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