Demand Management in the Smart Grid: An Information Processing Perspective.
Bibliographic record
Abstract
Driven by concerns regarding environmental sustainability, energy security, and economic growth, a fundamentaltransformation is taking hold in the electricity sector. Advanced communications technologies and information systems (IS)will play a central role in the realization of the âsmart gridâ, an intelligent and multi-directional electricity supply chain fromgeneration to end-user consumption. IS embedded in the smart grid will provide opportunities for improved businesspractices such as dynamic, near real-time demand management, allowing a better utilization of existing electricity supplycapacity and contributing to reductions in carbon emissions. Although opportunities exist, utilities face challenges adapting tothe smart grid environment. Drawing on information processing theory, this paper develops a model of how IS can improvethe effectiveness of electricity demand management. The model suggests practical implications for demand managementperformance of utilities and contributes to our understanding of the role information systems can play in achievingenvironmental sustainability.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| 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 | 0.004 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".