{"id":"W1977098838","doi":"10.3141/2133-10","title":"Reference-Dependent Residential Location Choice Model within a Relocation Context","year":2009,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":85,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Transport Canada","keywords":"Relocation; Loss aversion; Econometrics; Prospect theory; Choice set; Context (archaeology); Residential area; Mixed logit; Real estate; Copula (linguistics); Framing effect; Computer science; Economics; Statistics; Microeconomics; Logistic regression; Mathematics; Geography; Engineering; Psychology","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":[0.005738854,0.0002274107,0.0004700682,0.0008961146,0.0005618252,0.0001654032,0.0008852557,0.0002408687,0.0003550295],"category_scores_gemma":[0.000275093,0.0002129455,0.0002353099,0.001015532,0.0003122393,0.001173982,0.000006521097,0.001570592,0.0002156961],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006500433,"about_ca_system_score_gemma":0.0003282221,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.00829879,"about_ca_topic_score_gemma":0.02242604,"domain_scores_codex":[0.9953136,0.0003660401,0.002182745,0.0005289405,0.0009941648,0.0006145213],"domain_scores_gemma":[0.9967757,0.0002836564,0.001072646,0.0005338533,0.00106664,0.0002674815],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001540097,0.0009118466,0.6264413,0.0002104338,0.0002409531,0.00002577699,0.009379838,0.1049412,0.003095114,0.2341544,0.009985241,0.009073842],"study_design_scores_gemma":[0.001576701,0.0004859046,0.9322705,0.00014956,0.00002315585,4.379384e-7,0.001093138,0.00501182,0.0008097311,0.05650118,0.001847354,0.0002304901],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9816807,0.0005159726,0.01056783,0.0049884,0.000424847,0.0008246239,0.00007166852,0.00002383651,0.000902111],"genre_scores_gemma":[0.9957104,0.000728233,0.001230753,0.0001673976,0.000173397,0.00004589061,0.00004317701,0.00003737898,0.001863315],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3058292,"threshold_uncertainty_score":0.998305,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2623008584225972,"score_gpt":0.3513086230421359,"score_spread":0.08900776461953874,"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."}}