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Record W4247514453 · doi:10.1109/intmag.1992.696249

Surface power distribution in cross field heating of thin nonmagnetic plates

2005· article· en· W4247514453 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

Venue1992. Digests of Intermag. International Magnetics Conference · 2005
Typearticle
Languageen
FieldEngineering
TopicInduction Heating and Inverter Technology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsField (mathematics)Surface (topology)Integral equationPower (physics)Boundary value problemDistribution (mathematics)MechanicsBoundary (topology)Differential equationCurrent densityCurrent (fluid)Materials scienceMechanical engineeringMathematical analysisComputer scienceElectrical engineeringMathematicsPhysicsGeometryEngineeringThermodynamics

Abstract

fetched live from OpenAlex

Cross field heating is widely used in metal industry for heating of thin plates. In these systems the distribution of induced currents over the surface of the plate or the workpiece is of interest because it determines the distribution of heat over its surface. This is a three dimensional problem. Existing methods for three dimensional problems need large computer memories and are very time consuming. In the absence of boundary conditions, use of methods based on the differential equations requires that the field equations need be solved both in the region of the workpiece as well in the region outside the workpiece. In integral equation methods the field equations need be solved only in the region of interest. In this paper we use a circuit approach to obtain the induced current density and the power.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.256
Threshold uncertainty score0.720

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 head0.010
GPT teacher head0.249
Teacher spread0.239 · 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