{"id":"W2165364063","doi":"","title":"A rational model of preference learning and choice prediction by children","year":2008,"lang":"en","type":"article","venue":"Max Planck Digital Library","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Air Force Office of Scientific Research; Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Preference; Generalization; Preference learning; Revealed preference; Artificial intelligence; Computer science; Simple (philosophy); Machine learning; Discrete choice; Econometric model; Cognitive psychology; Psychology; Econometrics; Economics; Epistemology; Microeconomics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003651735,0.0005391961,0.0006357927,0.0006589527,0.0003701573,0.001884625,0.001264468,0.001637039,0.00650317],"category_scores_gemma":[0.01541876,0.0005657271,0.0009160235,0.0006426824,0.001862085,0.002805118,0.0008288177,0.001787498,0.0009828246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001562375,"about_ca_system_score_gemma":0.0007819366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009540439,"about_ca_topic_score_gemma":0.004603098,"domain_scores_codex":[0.998726,0.0006722809,0.00005484122,0.0002337101,0.0001566868,0.0001564932],"domain_scores_gemma":[0.9925593,0.005467608,0.0007576332,0.0006711339,0.0003372654,0.0002071083],"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":[0.0002220822,0.0001314325,0.02205066,0.0001088505,0.0001167691,0.0005128574,0.001844935,0.1175479,0.001494665,0.8265041,0.002621138,0.02684458],"study_design_scores_gemma":[0.0001045959,0.00007913109,0.007404323,0.00003355152,0.00004929812,0.0002705239,0.0002259522,0.3768445,0.0004844451,0.6113944,0.003061308,0.00004789881],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5275978,0.001012049,0.4287951,0.007519263,0.00005857315,0.0001181625,0.001087302,0.0003043716,0.0335074],"genre_scores_gemma":[0.9429597,0.0006828053,0.04584106,0.0002950659,0.00004494201,0.0001436775,0.0003410563,0.00003655207,0.00965504],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009540439,"threshold_uncertainty_score":0.02175528,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05861580380668899,"score_gpt":0.157960381385943,"score_spread":0.099344577579254,"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."}}