Regional Color Study of Traditional Village Based on Random Forest Model: Taking the Minjiang River Basin as an Example
Why this work is in the frame
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Bibliographic record
Abstract
From the color geography perspective, a field investigation was conducted in the Minjiang River Basin, constructing a color index system of traditional villages. In Python, a random forest model was constructed to screen out important color indexes for traditional village color classification and explore its influence mechanism. Among eight color indexes, the important indexes are wall form and building face form, accounting for 30.50% and 19.40%, respectively. Based on this, the basin was divided into four color zones presenting color characteristics and eight color subzones presenting architectural features. The influence mechanism concerns dialect divisions that have shaped traditional villages of different color types, and the interconnection of water systems has promoted the connections among them. The application of traditional village colors in the new urban and rural planning can enhance local characteristics. Integrating the color resources of traditional villages contributes to the regional protection of culture and economic development.
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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