{
 "record_id": "2cdb6f374417590715ab5db24f593d17616b9ea2",
 "eligible": true,
 "short_ref": "Han, Woo & Lee (2025)",
 "country": "South Korea",
 "city": "Seoul",
 "property_type": "single-family houses",
 "price_type": "transaction price (log)",
 "n_obs": 13776,
 "sample_period": "2017-2019",
 "data_source": "Value Up Systems transaction platform (MOU); Google Street View panoramas (233,106) segmented with DeepLab V3+",
 "methods_compared": [
  "linear regression (hedonic)",
  "random forest",
  "XGBoost",
  "gradient boosting"
 ],
 "best_method": "gradient boosting",
 "metric": "R2",
 "best_value": 0.817,
 "hedonic_value": 0.66,
 "test_set": "holdout",
 "features_ai": "street-view CNN",
 "incremental_ai_gain": null,
 "incremental_ai_metric": "",
 "marginal_effects": "SHAP",
 "notes": "Table 2, 20% holdout (2,755 test obs): R2 0.660 (linear regression), 0.318 (RF), 0.765 (XGBoost), 0.817 (gradient boost); MSE 0.056 and MAE 0.169 for GB in log-price units. All models include the street-view segmentation shares (greenery, sky, buildings, etc.); no model without them is reported, so no incremental gain. SHAP global/local plots plus PDP for key variables.",
 "confidence": "high"
}