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Record W2106164953 · doi:10.1108/03321640810847625

State of the art of numerical modeling for induction processes

2008· article· en· W2106164953 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

VenueCOMPEL The International Journal for Computation and Mathematics in Electrical and Electronic Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicInduction Heating and Inverter Technology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsOriginalityComputer scienceData scienceCover (algebra)Management scienceOperations researchEngineeringSociologyMechanical engineeringSocial scienceQualitative research

Abstract

fetched live from OpenAlex

Purpose To provide a selective bibliography for researchers and graduate students who have an interest in induction processes applied to the electromagnetic processing of materials. Design/methodology/approach The objective is to provide references that identify seminal, early work, and references that represent the current state of the art. References are listed in categories that cover the broad range of induction modeling and application issues. Findings A brief overview of the key areas in induction processing of materials is provided, but greater emphasis and space is devoted to the references provided. Research limitations/implications The middle years of each topic area are not covered. Practical implications A very comprehensive coverage of material is provided to those with an interest in induction processing of materials. Originality/value This paper fulfils an identified information/resources need.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.647
Threshold uncertainty score0.181

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 head0.018
GPT teacher head0.243
Teacher spread0.225 · 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