Bibliographic record
Abstract
Hendrik du Toit Mouton was born in Somerset-West in 1965. In 1976 his family \nmoved from Stellenbosch to Bloemfontein where he matriculated in 1983. He \nstarted his B.Sc. at the University of the Orange Free State in 1984 and majored \nin Mathematics and Physics. After completing a B.Sc.(Hons) and M.Sc. in \nMathematics he was appointed as lecturer in Mathematics at the University \nof the Orange Free State in 1990. He completed his Ph.D. in Mathematics, \non Fredholm theory relative to Banach Algebra homomorphisms, under the \nsupervision of Prof. Heinrich Raubenheimer in 1991. During the second semester of 1992 he spent a six month \nsabbatical, during which time he collaborated with Prof. Sandy Grabiner from Pomona College in the USA and Prof. \nBernard Aupetit from Laval University in Canada. \nIn 1995 he moved to Stellenbosch and enrolled for the degree Bachelor in Electrical and Electronic Engineering, \nwhich he received in 1996. In 1997 he enrolled for a Ph.D. in Electrical Engineering under the supervision of Prof. \nJohan Enslin on a high power converter for a superconducting magnet. He was appointed as senior lecturer in Power \nElectronics in October 1997 and completed his Ph.D. in Electrical Engineering in 2000. In 2001 he was promoted \nto associate professor in Power Electronics. In 2003 he spent a sabbatical at the University of Toulouse, where he \ncollaborated with Dr Thierry Meynard, and the University of Wuppertal, where he collaborated with Prof. Ralph \nKennel. \nHis research team collaborates closely with industry and generates the majority of its research funding through \ncontract research for ESKOM. He currently collaborates on research projects with the Technical University of Munich, \nThe Royal Melbourne Institute of Technology and Hypex Electronics in Groningen. \nHis research interests include high power converters, multilevel converters, modulation theory and class-D audio \namplifiers.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".