Medidores inteligentes: o primeiro passo em direção as redes inteligentes
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.
Bibliographic record
Abstract
Smart grids are the focus of major study today because of the necessity of modernization in electrical systems and reduction of greenhouse gas emissions that increases global warming. Reaching the best deployment method, you must first of all know the current electrical system and how to use them for the benefit of this new technology. Preparing the action plan we should be aware of the main points of smart grids in each step of the electricity system - generation, transmission and distribution. Analyzed these topics, this work will focus on the first step in the implementation of the smart grids: the smart meters, tool which is already being implemented in Brazil. The main characteristics and applications of these devices, as well as their communication structure with the core distributors will be showed during the paper. Finally, we present a case study which will be discussed and analyzed based in the results obtained with the implementation of smart meters in the city of Vancouver, Canada, where we have a considerable savings already in the first year, with fully paying the initial investment and still have a profit
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it