{"id":"W2108440642","doi":"10.1016/j.tra.2012.01.007","title":"A behavioral housing search model: Two-stage hazard-based and multinomial logit approach to choice-set formation and location selection","year":2012,"lang":"en","type":"article","venue":"Transportation Research Part A Policy and Practice","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":78,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canada Research Chairs; Fleming College; University of Toronto","funders":"","keywords":"Multinomial logistic regression; Choice set; Discrete choice; Set (abstract data type); Selection (genetic algorithm); Aggregate (composite); Logit; Mixed logit; Computer science; Process (computing); Econometrics; Hazard; Operations research; Economics; Logistic regression; Engineering; Machine learning","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.005519491,0.001300564,0.003957074,0.002640324,0.001318805,0.003501674,0.008083126,0.005517539,0.01820517],"category_scores_gemma":[0.01116109,0.00231404,0.002759075,0.004059301,0.002440217,0.004832934,0.002978952,0.003132388,0.003338761],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002812795,"about_ca_system_score_gemma":0.003203675,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03714719,"about_ca_topic_score_gemma":0.03527158,"domain_scores_codex":[0.9966749,0.001842555,0.0001305851,0.0005167762,0.0002422288,0.0005928822],"domain_scores_gemma":[0.990346,0.007028131,0.0009095906,0.0004463353,0.0006029666,0.0006669332],"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":[0.0003728847,0.0006267973,0.008607313,0.0002053858,0.0002862056,0.0005311115,0.0004475031,0.7908382,0.0005625426,0.1818133,0.004131729,0.01157698],"study_design_scores_gemma":[0.00008681859,0.0000438407,0.0007750331,0.00001009315,0.00004695103,0.00004742454,0.0000744123,0.9794606,0.00005646151,0.01890533,0.0004594228,0.00003353714],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2131855,0.0007424751,0.7614374,0.005536981,0.0002446672,0.0006197483,0.005223295,0.0008431156,0.01216678],"genre_scores_gemma":[0.8676218,0.001092777,0.06016024,0.0005904073,0.0003111378,0.0009661441,0.002366986,0.00019019,0.06670023],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03714719,"threshold_uncertainty_score":0.07386196,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4713466619603244,"score_gpt":0.4243994734643794,"score_spread":0.04694718849594498,"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."}}