{"id":"W2260365916","doi":"10.3982/te2914","title":"Optimal adaptive testing: Informativeness and incentives","year":2018,"lang":"en","type":"article","venue":"Theoretical Economics","topic":"Imbalanced Data Classification Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Incentive; Computer science; Microeconomics; Economics","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":[0.02772297,0.001574085,0.002958214,0.001733546,0.001211281,0.003248444,0.003247947,0.004051382,0.005854078],"category_scores_gemma":[0.1520875,0.0009067112,0.0007782273,0.001746872,0.007094456,0.006972048,0.003230815,0.003934936,0.0006147027],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0025286,"about_ca_system_score_gemma":0.002863219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001380637,"about_ca_topic_score_gemma":0.00108395,"domain_scores_codex":[0.9766623,0.01597563,0.000914345,0.002264343,0.002915356,0.00126805],"domain_scores_gemma":[0.8258604,0.1468596,0.01251098,0.00883859,0.00350281,0.002427631],"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":[0.00105177,0.0006427811,0.0132291,0.0002561058,0.000145927,0.0004586224,0.0005361441,0.1411468,0.002060706,0.7542434,0.003032202,0.08319652],"study_design_scores_gemma":[0.0002540371,0.000190653,0.001843151,0.00006431917,0.00002494633,0.0001340044,0.00008605724,0.2988012,0.0009741799,0.6962181,0.001369345,0.00003998905],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1682306,0.00109615,0.8017228,0.008723711,0.0001107064,0.0005212202,0.0005098336,0.0002677187,0.01881729],"genre_scores_gemma":[0.9145893,0.0003303329,0.08099007,0.0005564052,0.0001697999,0.0004879909,0.0001515867,0.00004447254,0.00268001],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02772297,"threshold_uncertainty_score":0.1466148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0207522722420185,"score_gpt":0.2419940163433521,"score_spread":0.2212417441013336,"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."}}