Improving Energy Efficiency by Household Consumers in the Republic of Tajikistan Based on the Developed Forecasting Method
Why this work is in the frame
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Bibliographic record
Abstract
The work is devoted to the assessment of energy efficiency in electricity consumption by household consumers in the city of the Republic of Tajikistan. Methods of forecasting taking into account factor dependencies are proposed. According to the data obtained from the readings of electricity metering devices for groups of household consumers with different climates, meteorological conditions of the area and geographic area, comparisons of the actual power consumption with standard values were made. A non-standard excess of the actual specific loads in winter about the standard values was established, leading to a violation of the operating mode. The applied methods for calculating the proposed average monthly loads of all consumers and the average values of the electrical loads of the cities under consideration. It is substantiated that the proposed method makes it possible to increase the energy efficiency of urban electrical networks of 10 / 0.4 kV without violating the standard values.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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