Bowen Ratio Method for Measuring Heat Transfer on Land Cover Change in Establishing Green Patch in Urban Heat Island of Bangkok
Bibliographic record
Abstract
Due to the rapid growth of urban heat island (UHI) in Bangkok, which is covered by 1,568.7 sq.km and 1.5 mMSL and surrounded by the Gulf of Thailand and Chao Phraya river, has been gradual.ly extended through suburban areas that making ambient air temperature increased about 0.03 °C/y for 56-year period (1957 to 2013). The Bowen ratio found between 3.20 to 3.25 that required to select the green patches 25% to 75 % of the total landscape for enough heat absorbent from urban heat island in Bangkok city that being full of concrete construction and dense population. Landscape design for reduction heat from UHI unit areas should be considered in four orders of magnitude, i.e., landscape macro-designing, green patch localization, cooling housing design and construction, and housing landscape design.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".