Research on Intelligent Development Path of Countryside under New Infrastructure Construction Based on Multi-Objective Optimization
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Bibliographic record
Abstract
Aiming at the current problems of low level of intelligent development and backward infrastructure in the countryside, this paper proposes a multi-objective optimization model for rural construction.According to the overall principle of optimization and the current situation of rural infrastructure construction, model assumptions, objective functions and constraints are determined.Facing the problem of calculating the optimal values of the four objective functions, NSGA-II method is chosen to solve and analyze the problem.NSGA-II algorithm is calculated in 100 iterations, and the optimal solutions of the four objective functions are 0.813, 0.943, 0.852, and 0.886, which are better than NSGA and GA algorithms in terms of performance.In order to improve the intelligent development of the countryside, two targeted development proposals are put forward.
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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 | 0.002 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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 it