Optimal water resource planning under fixed budget by interval-parameter credibility constrained programming
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Bibliographic record
Abstract
Abstract In this study, an interval credibility constrained programming (ICCP) was developed through introducing the concept of intervals into credibility constrained programming framework. Interval credibility levels can help decision makers to reflect uncertainties of preferences. By ICCP, a water resource planning model with fixed fuzzy budget was developed for supporting the planning of agriculture development and environmental protection. Surface and ground water were planned for regional irrigation in wet and normal seasons. For the interval credibility preference, best and worst cases were analysed. The tradeoff between the budget and the benefit were studied by sensitive analysis. The results showed that the current water resource budget is reasonable. Keywords: water resourcesgroundwaterchance contrained programminginterval programmingcredibility
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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 | 0.000 | 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 | 0.000 |
| 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