Advances in the construction techniques of AC induction motors; Avances en las tecnicas de construccion de motores de induccion de CA
Bibliographic record
Abstract
The necessary design and production techniques for the motors of special efficiency (premium) are reviewed and the new investigations that are been made to increase its efficiency are presented, including better slots design for steel sheet plate and for copper rotors fused to pressure. The history of the special motors of special efficiency and of the corresponding Norms is discussed. The of IEEE Standards are compared to each other, those of the Canadian Standards Association (CSA), those of the International Electrotechnical Commission (IEC) and those of the Japanese Electrotechnical Commission (JEC). Also are described groups of losses in motors as well as the way they affect the efficiency. [Spanish] Se resenan las tecnicas de diseno y produccion necesarias para los motores de eficiencia especial (Premium), y se presentan las nuevas investigaciones que se hacen para aumentar su eficiencia, incluyendo mejores disenos de ranuras para laminas de acero y de rotores de cobre fundido a presion. Se revisa la historia de los motores de eficiencia especiales y de las Normas correspondientes. Se comparan entre si las Normas de IEEE, las de Canadian Standards Association (CSA), las de la Comision Internacional Electrotecnica (IEC) y las de la Comision Electrotecnica Japonesa (JEC). Tambien se describen grupos de perdidas en motor, asi como la forma en que afectan a la eficiencia.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".