Solving the Energy Supply Strategic Planning Problem by Extended Group Multirole Assignment
Bibliographic record
Abstract
Everybody knows that China has put forward the concept of "carbon peaking and carbon neutrality" in response to climate change. This paper proposes a novel perspective from the standpoint of the Role-Based Collaboration (RBC), employing the Environment-Classes, Agents, Roles, Groups, and Objects (E-CARGO) model and the Group Multirole Assignment (GMRA) model to construct an energy supply strategic planning (ESSP) that simulates the progressive carbon peaking process in order to compare and analyze the current carbon peaking target of China. Secondly, we propose a simple method to evaluate carbon peaking schemes, and conduct simulation experiments for different schemes. It is concluded that Chinese current carbon peaking target is relatively conservative, projecting achievement by 2027 with an estimated 19.7 billion tons of CO2 emissions, while having the lowest cost per unit of emission reduction. Furthermore, a significant reduction of 66.08% in carbon intensity is projected for 2030 compared to 2005, which is 1.08% higher than the original target.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".