{"record_id": "1462a807ace2b4c97b7b8368ffbe3a1c694cd0f7", "eligible": true, "short_ref": "Solovev & Pröllochs (2021)", "country": "Germany", "city": "Berlin", "property_type": "apartments (rental listings with floor plans)", "price_type": "asking rent (rent per m2 and total rent, log)", "n_obs": 9174,
 "sample_period": "mid-2017 to end-2019 (crawled end of 2019)", "data_source": "ImmobilienScout24.de listings (web crawler)", "methods_compared": ["log-linear OLS hedonic", "log-linear OLS + floor-plan CNN score", "CatBoost", "CatBoost + floor-plan CNN score", "deep neural network", "deep neural network + floor-plan CNN score"],
 "best_method": "deep neural network + floor-plan CNN score", "metric": "MAE", "best_value": 0.0205, "hedonic_value": 0.1565,
 "test_set": "k-fold", "features_ai": "floor-plan",
 "incremental_ai_gain": -10.56, "incremental_ai_metric": "MSE (% change, DNN with vs without floor plans, rent per m2)", "marginal_effects": "coefficients", "notes": "Table 2 (rent per m2, 5-fold CV out-of-sample): benchmark log-linear OLS MSE 0.04984 / MAE 0.1565; OLS + FloorPlanSentiment MSE 0.04400 / MAE 0.1347 (MSE -11.71%, MAE -13.93%); CatBoost 0.00140/0.0262 -> 0.00134/0.0258; DNN 0.00142/0.0214 -> 0.00127/0.0205 (MSE -10.56%, MAE -4.21%). Units are log rent per m2. Floor-plan score comes from a two-stage CNN (Xception) trained on historical prices; explanatory OLS regressions report significant FloorPlanSentiment coefficients. Table 3 gives analogous results for total rent.", "confidence": "high"}