{"id":"W4414231531","doi":"10.1109/amlds63918.2025.11159400","title":"Machine Learning Engine for Real Estate Price Estimation","year":2025,"lang":"en","type":"article","venue":"","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Real estate; Random forest; Estimation; Decision tree; Preprocessor; Database transaction; Feature (linguistics); Price on application","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001080546,0.0005966153,0.0004944364,0.001664479,0.0003106363,0.001247713,0.001071626,0.0006787006,0.006770796],"category_scores_gemma":[0.005521839,0.0002533742,0.0006820454,0.001518724,0.0001892745,0.001730488,0.0005079725,0.0009924661,0.004597675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000957511,"about_ca_system_score_gemma":0.0008910283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01683756,"about_ca_topic_score_gemma":0.01757031,"domain_scores_codex":[0.9994904,0.00006709069,0.00005946639,0.0001346383,0.0002003485,0.00004797253],"domain_scores_gemma":[0.9987695,0.000576793,0.00008508159,0.0001643294,0.0003792504,0.00002503258],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002468802,0.0003278751,0.01223996,0.0002759326,0.0001478021,0.0002750737,0.0001032169,0.2198322,0.003886195,0.01373864,0.03070624,0.7182199],"study_design_scores_gemma":[0.000007820334,0.00001674668,0.001401745,0.00001698706,0.00001079864,0.00004127215,0.00001700369,0.9851747,0.002620314,0.005279303,0.005404491,0.000008896351],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0527938,0.001801043,0.8960908,0.0008018227,0.0002486251,0.0002044383,0.005584952,0.03105393,0.01142056],"genre_scores_gemma":[0.5812865,0.001084789,0.3932898,0.0003172771,0.0001714435,0.0003150224,0.01001346,0.0004695562,0.01305216],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01683756,"threshold_uncertainty_score":0.03347909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004595841757500263,"score_gpt":0.2250637932813671,"score_spread":0.2204679515238668,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}