Coverage-Based Variable Precision (I, PSO)-Fuzzy Rough Sets with Applications to Emergency Decision-Making
Why this work is in the frame
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Bibliographic record
Abstract
Considering the characteristics of imprecise, incomplete and fuzzy data in emergency environment, a novel emergency decision-making method based on coverage-based variable precision ( I , PSO )-fuzzy rough set model is proposed. First, an improved ( I , PSO )-fuzzy rough set model is proposed, which combines the covering-based fuzzy rough set (CFRS) and the variable precision fuzzy rough set (VPFRS). Second, inspired by the idea of attribute reduction, a novel method for determining attribute weights is introduced to optimize weight assignment in emergency decision-making. Last but not least, to illustrate the feasibility and effectiveness of the proposed method, an example of post-flood rescue force allocation in urban areas is demonstrated. Finally, the stability and superiority of the method are verified through sensitivity analysis and comparative evaluation.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 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