{"id":"W4405317212","doi":"10.1016/j.jocm.2024.100535","title":"Location choice of residential housing supply: An application of the multiple discrete-continuous extreme value (MDCEV) model","year":2024,"lang":"en","type":"article","venue":"Journal of Choice Modelling","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"University of Toronto","keywords":"Discrete choice; Value (mathematics); Econometrics; Economics; Extreme value theory; Business; Statistics; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001121694,0.000151993,0.0004634581,0.0002957457,0.00009241518,0.0001075311,0.0004103768,0.0001222704,0.000009505982],"category_scores_gemma":[0.000132036,0.0001439661,0.0002458862,0.0002792514,0.00006331853,0.0008160374,0.00005042352,0.0002840344,0.000004228508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001430237,"about_ca_system_score_gemma":0.0001013433,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009111764,"about_ca_topic_score_gemma":0.0001609977,"domain_scores_codex":[0.998054,0.00003187141,0.00135977,0.0002526473,0.0000992714,0.0002024293],"domain_scores_gemma":[0.9980379,0.0001819949,0.001198499,0.0003609857,0.0001532152,0.00006737497],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003854035,0.00006115433,0.01431812,0.0001561587,0.0000522988,4.038363e-7,0.0006232983,0.976536,0.001318438,0.00507851,0.00003722426,0.001779852],"study_design_scores_gemma":[0.0003352244,0.00003594736,0.0009402832,0.0002037427,0.00004718448,0.000003928737,0.00004795941,0.9822286,0.001186143,0.01416895,0.0006585539,0.000143418],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4897715,0.0009612413,0.5082033,0.0001462375,0.0003679662,0.0001030451,0.00001646736,0.000009117708,0.0004211495],"genre_scores_gemma":[0.9933649,0.0002903171,0.005745822,0.00002298968,0.0004674834,0.000002964963,0.000004652494,0.00004467725,0.00005623986],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5035934,"threshold_uncertainty_score":0.5870768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04952255018475651,"score_gpt":0.2495570566271881,"score_spread":0.2000345064424316,"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."}}