{
 "record_id": "d8361358e99098ffa7a8408974e7bea4a38e7010",
 "eligible": true,
 "short_ref": "Liu, Chen, Orford, Tian & Zou (2024)",
 "country": "United Kingdom",
 "city": "Cardiff",
 "property_type": "mixed (detached, semi-detached, terraced, flat/maisonette)",
 "price_type": "transaction price (log)",
 "n_obs": 16297,
 "sample_period": "2001-2007",
 "data_source": "HM Land Registry (with floor area), OS street network",
 "methods_compared": [
  "XGBoost",
  "random forest",
  "gradient boosting decision tree"
 ],
 "best_method": "XGBoost",
 "metric": "R2",
 "best_value": 0.76,
 "hedonic_value": null,
 "test_set": "holdout",
 "features_ai": "none",
 "incremental_ai_gain": null,
 "incremental_ai_metric": "",
 "marginal_effects": "SHAP",
 "notes": "Four XGBoost models (closeness/betweenness at 600 m, 3 km, 6 km, 10 km radii); Table 2 reports R2 0.76/0.76/0.76/0.74, MAE 0.18-0.19 and RMSE 0.28-0.30 in log-price units on a 10% random holdout (5-fold CV for tuning). RF and GBDT were said to perform worse but their metrics are not printed; no OLS benchmark. SHAP dependence plots give nonlinear marginal effects of accessibility.",
 "confidence": "high"
}