{"id":"W4320082066","doi":"10.1007/978-3-031-20719-8_6","title":"Behavioral Insights from Choice Models","year":2022,"lang":"en","type":"book-chapter","venue":"Use R!","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal; McMaster University","funders":"","keywords":"Multinomial logistic regression; Discrete choice; Mixed logit; Multinomial distribution; Econometrics; Logit; Estimation; Computer science; Logistic regression; Economics; 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":[0.00147298,0.001131129,0.0008008578,0.0007917223,0.0004201334,0.002381882,0.0007577828,0.0013958,0.02288653],"category_scores_gemma":[0.007158869,0.0005403298,0.000840609,0.001232775,0.001685322,0.004474791,0.0007474219,0.003235785,0.002517721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001113302,"about_ca_system_score_gemma":0.0005687607,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002593302,"about_ca_topic_score_gemma":0.001710333,"domain_scores_codex":[0.999353,0.000343968,0.00002346446,0.00008095383,0.0001581157,0.00004058048],"domain_scores_gemma":[0.996393,0.003024511,0.0001186111,0.0002012677,0.0001599756,0.0001024987],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00000947075,0.0000346862,0.000216327,0.00004943127,0.00001759273,0.0000159359,0.0001265011,0.002802462,0.00007466783,0.974498,0.007474763,0.01468016],"study_design_scores_gemma":[0.000002410996,0.000002446963,0.000119509,0.000009372388,0.000003197968,0.0000105788,0.00002188852,0.004439001,0.00001324676,0.9905077,0.00486792,0.000002547722],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02816355,0.01046935,0.4929408,0.03188057,0.0008720999,0.00005890698,0.001609305,0.0002977151,0.4337077],"genre_scores_gemma":[0.6831015,0.02004484,0.1084759,0.005050017,0.001944424,0.0003720475,0.001784878,0.0004331744,0.1787931],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02288653,"threshold_uncertainty_score":0.07656312,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2550763877898594,"score_gpt":0.2232328737042016,"score_spread":0.03184351408565783,"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."}}