{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002817129,0.00009423617,0.0001167222,0.0000495243,0.00009373741,0.0001242076,0.000498463,0.00004786799,0.00001967635],"category_scores_gemma":[0.0001126885,0.00008833723,0.00001327114,0.00009884232,0.00118727,0.0006838383,0.0004088902,0.00007885592,0.00006857287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003691032,"about_ca_system_score_gemma":0.00004475802,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001138055,"about_ca_topic_score_gemma":2.144792e-7,"domain_scores_codex":[0.9993502,0.00003522315,0.0001826121,0.0002204434,0.00003620063,0.0001753151],"domain_scores_gemma":[0.9992142,0.0001997787,0.00007643856,0.0003477116,0.0000858153,0.0000760339],"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":[0.000009996497,0.000009264864,0.00005844561,0.000001701571,0.00000379622,1.99674e-7,0.0002555554,0.00000251382,0.00006218092,0.9690382,0.00002997201,0.0305281],"study_design_scores_gemma":[0.0002523609,0.0003424134,0.002498227,0.00001938676,0.000003943991,0.00001976669,0.0001007345,0.4788425,0.02050305,0.4943131,0.002824067,0.0002804315],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08580267,0.000005341148,0.892579,0.000319194,0.00006334393,0.0001055295,0.000009880865,0.0002011629,0.02091385],"genre_scores_gemma":[0.7200979,0.000009294849,0.279625,0.0002096251,0.00003474372,0.000008041058,0.000001743618,0.000004255978,0.000009426698],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6342952,"threshold_uncertainty_score":0.4374545,"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."}}