Protection model based on value assessment and vulnerability curve
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Extreme weather has become one of the most serious challenges to humans' lives, its increasingly frequent occurrences affect the preservation and protection of many cultural buildings, to judge the cultural and historical value of a cultural building and its vulnerability to extreme weather, so as to further realize its preservation and protection. This paper establishes the historical and cultural value evaluation model and the vulnerability curve of cultural heritage buildings based on the AHP-Field method, Mann-Kendall test and quintile regression respectively. Taking Fujian Tulou as an example, we obtained the historical and cultural evaluation system and the vulnerability curve affected by heavy rain, and comprehensively considered the relationship between the two, and obtained comprehensive measures to protect Fujian Tulou buildings. Make feasible suggestions on how to protect ancient buildings in the case of heavy rain and provide reference for the evaluation and protection of other regions.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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