Design of Strategy Generation System for Urban Comprehensive Disaster Prevention Planning Based on Transfer Bridge
Why this work is in the frame
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Bibliographic record
Abstract
The rapid development of big data and artificial intelligence (AI) makes it possible to make intelligent decisions on urban comprehensive disaster prevention planning (UCDPP).Based on extension problem model and transfer bridge, this paper formulates a strategy generation system (SGS) for the UCDPP, with the aid of the AI, database technology, and extension logic analysis tools.The established system consists of three layers and multiple libraries, namely, basic database, rule base (including strong correlation rules and problem rules), question base, example database, extension transform library, and strategy base.Compared with traditional SGSs, two libraries were added to our system, i.e. knowledge base and transfer bridge library, making our system more comprehensive.Taking gas station location problem in a city as an example, the feasibility of our system was confirmed, and the visual interface of the system was illustrated in details.The research results enable urban planners to make rational decisions in the process of the UCDPP.
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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