Bibliographic record
Abstract
Pontifícia Universidade Católica do Rio de Janeiro.Forty years of experience in electrical engineering, with emphasis on grounding electrodes design for HVDC transmission systems, and study/design of grounding and lightning protection systems for transmission lines, highvoltage substations, industrial and commercial installations in medium-and low-voltage installations, telecommunication infrastructure and transport systems (railway, subway and monorail).Interference studies of AC/DC systems in transmission networks, telephone lines and metallic pipes.Design of electrical infrastructure (power supply, grounding and lightning protection) for electronic equipment installations (data processing, communications, supervisory and control systems).Railroad electrification studies.Short-circuit studies, power flow and transient stability for transmission and for industrial systems.Induction motor starting studies.for industrial plants.Static compensator modeling in transient stability software.Measurement and analysis of electrical parameters (grounding resistance and ground resistivity, magnetic fields, power, currents and voltages at fundamental frequency and harmonics).Instructor and speaker in technical courses and events.Twenty-five papers presented in technical events in Brazil and abroad (USA, South Africa, Canada and France).Development of computer software in Fortran for calculations and simulations in the several above-mentioned areas.
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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".