Mathematical Modelling and Mathematical Methods in Energy
Bibliographic record
Abstract
The workshop on Mathematical Modelling and Mathematical Methods in Energy was held in COPEL Building, Curitiba, Brazil from 29 November to 1 December 2004 with more than 100 participants. The scientific programme consisted of 20 invited talks and 20 contributed papers. All talks were well attended with deep discussions. The participants came from Brazil, Canada, China and U.S.A. The following mathematical modelling and methods applied in energy area such as petrol and electric energy were discussed: partial differential equations, singular value decomposition (SVD), eigenvalue problems, preconditioning techniques and optimization. All participants, especially people from energy engineering, recognized the importance of participation and collaboration with mathematicians for their researches. The present volume contains seven selected papers essentially devoted to numerical linear algebra with applications in energy area. We thank the referees who helped us in doing the editorial work. Their efforts and suggestions made it possible to publish scientific papers with high quality. We appreciate the support of the Scientific Committee of the Workshop consisting of José Luiz Alqueres (ALSTOM, Brazil), Ricardo Biloti (UFPR, Brazil), Mario Jorge Dias Carneiro (UFMG, Brazil), Paulo Afonso Bracarense Costa (CGEE-MCT, Brazil), Djalma M. Falcão (UFRJ, Brazil), Clovis Gonzaga (UFSC, Brazil), Sergio Granville (PSR, Brazil), Fernando Gruppelli (COPEL, Brazil), Dan Marchesin (IMPA, Brazil), Claudia Sagastizabal (IMPA, Brazil), Robson Luiz Schiefler (COPEL), Jurandyr Schmidt (PETROBRAS), Carlos Tomei (PUC-Rio, Brazil), Lei Wang (PowerTech Labs, Canada), and Jin Yun Yuan (UFPR, Brazil). The workshop was sponsored by Araucária Foundation, Brazilian National Agency of Electric Energy, Brazilian Society of Mathematics, COPEL, Global Progress of Brazilian Mathematics-Millennium Institute (IM-AGIMB), Ministry of Education, Federal University of Paraná and Federl University of Santa Catarina. Last, but not the least, we thank all participants for their contribution and efforts in making the Workshop an interesting, pleasant and successful event.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".