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
During the last decades, the Brazilian electric sector has introduced little changes in tariffs for end-use consumers.The most radical changes were implanted at the beginning of the eighties, with the introduction of a seasonal tariff structure called green and blue.The objective of this work is to test some possibilities to formulate a new seasonal tariff in Brazil, through a critical analysis of these tariffs in Brazil and in other countries.This was made through field researches, interviews and the measuring of some industrial consumers.The national experience analysis includes the implementation and development of the seasonal tariffsgreen, blue and yellow -, the supply curtailable rate and a complete historical of the more important facts occurred since 1957 up to 2006, together with an evaluation of the impacts in the implementation of these tariffs.In the analysis of the international experience, it was examined tariffs in France, Canada, United States and Portugal.The case study involved three researches on the field.The first one was to choose the industrial segments with larger potential for load modulation.The second research explored both footwear and furniture industries in terms of theirs demand profile and productive processes, with the objective of establishing their load modulation change possibilities more accurately.The third field research obtained the necessary technical and economical data, to work with simulations in a quantitative analysis of the economic impacts of a third tariff position during night time.The costbenefit analysis considered both consumers and Utility's point of views.The results of the simulations has shown that the cost of labor is sometimes 35 times higher than electricity bills in the footwear and furniture industries, rendering useless a possible load modulation change during the night.Furthermore, during night time the cost of labor increases.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.043 | 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 it