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Record W1985339351 · doi:10.1080/02726340490261590

Matching a Given Field Using Hierarchal Vector Basis Functions

2004· article· en· W1985339351 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

VenueElectromagnetics · 2004
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Simulation and Numerical Methods
Canadian institutionsMcGill University
Fundersnot available
KeywordsCurl (programming language)AlgorithmMatching (statistics)Basis (linear algebra)Inversion (geology)Field (mathematics)Matrix (chemical analysis)TetrahedronVector fieldMathematicsComputer scienceFinite element methodApplied mathematicsPure mathematicsGeometryPhysics

Abstract

fetched live from OpenAlex

Unlike interpolatory finite elements, hierarchal elements offer no straightforward way to approximate a given field. The vector case in particular is challenging. A solution is proposed which, though developed for a specific series of tetrahedral vector elements, is applicable to other noninterpolatory elements. The method uses a projective, rather than a point-matching, approach, for greater accuracy. It avoids the inversion of a large matrix and employs precomputed (universal) matrices wherever possible for efficiency. By considering explicitly the matching of the curl of the field as well as the field itself, it is able to maintain the asymptotic error performance associated with the use of common “mixed order” elements, such as the Whitney edge element. The error performance is demonstrated by a test case involving the dominant mode of rectangular waveguide.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.230
Threshold uncertainty score0.883

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 head0.013
GPT teacher head0.256
Teacher spread0.243 · 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