{"id":"W2153943598","doi":"10.3141/2082-08","title":"Hybrid Choice Modeling of New Technologies for Car Choice in Canada","year":2008,"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":156,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Structural equation modeling; Latent variable; Context (archaeology); Discrete choice; Choice set; Econometrics; Computer science; Representation (politics); Perception; Set (abstract data type); Process (computing); Mathematics; Machine learning; Psychology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001972807,0.0001498122,0.0004899674,0.0007148489,0.0002301658,0.00001812651,0.0007209249,0.00009498014,0.0001181349],"category_scores_gemma":[0.0003135737,0.0001434654,0.0002139265,0.0006214131,0.0002083338,0.000457521,0.000006178261,0.0008617425,0.000006983382],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008520491,"about_ca_system_score_gemma":0.001079238,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8618386,"about_ca_topic_score_gemma":0.913467,"domain_scores_codex":[0.9968218,0.00009746769,0.001699427,0.0003216526,0.0005210504,0.0005386506],"domain_scores_gemma":[0.9980334,0.0005773155,0.0005584097,0.0003158999,0.0003807975,0.0001341697],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001669102,0.00006705046,0.9601322,0.000106592,0.00005197421,0.000009297753,0.0005685993,0.034371,0.0001506766,0.001700253,0.001684513,0.0009909037],"study_design_scores_gemma":[0.001667552,0.0001896008,0.9769813,0.0001155085,0.000008432914,3.540637e-7,0.001021617,0.006633415,0.0007405979,0.00798726,0.00450215,0.0001522474],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992623,0.0008397549,0.003480657,0.001848415,0.0002583807,0.0006944001,0.0001536632,0.000007856235,0.00009381992],"genre_scores_gemma":[0.996387,0.001631256,0.001475823,0.00002119235,0.00006618116,0.0000459997,0.00001651125,0.00003019968,0.0003258616],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05162841,"threshold_uncertainty_score":0.5850348,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2522969677592016,"score_gpt":0.325271099537861,"score_spread":0.07297413177865941,"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."}}