The\nNorth American Electric Grid as an Exchange Network:\nAn Approach for Evaluating Energy Resource Composition and Greenhouse\nGas Mitigation
Bibliographic record
Abstract
Using\na complex network framework, the North American electric\ngrid is modeled as a dynamic, equilibrium-based supply chain of more\nthan 100 interconnected power control areas (PCAs) in the contiguous\nUnited States, Canada, and Northern Mexico. Monthly generation and\nyearly inter-PCA exchange data reported by PCAs are used to estimate\na directed network topology. Variables including electricity, as well\nas primary fuels, technologies, and greenhouse gas emissions associated\nwith power generation can be traced through the network, providing\nenergy source composition statistics for power consumers at a given\nlocation. Results show opportunities for more precise measurement\nby consumers of emissions occurring on their behalf at power plants.\nSpecifically, we show a larger range of possible factors (∼0\nto 1.3 kgCO<sub>2</sub>/kWh) as compared to the range provided by\nthe EPA’s eGRID analysis (∼0.4 to 1 kgCO<sub>2</sub>/kWh). We also show that 66–73% of the variance in PCA-level\nestimated emissions savings is the result of PCA-to-PCA differences\nthat are not captured by the larger eGRID subregions. The increased\nprecision could bolster development of effective greenhouse gas reporting\nand mitigation policies. This study also highlights the need for improvements\nin the consistency and spatiotemporal resolution of PCA-level generation\nand exchange data reporting.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".