{"id":"W2751794303","doi":"10.1101/184754","title":"A Neuroeconomic Framework for Creative Cognition","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Creativity in Education and Neuroscience","field":"Psychology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Neuroeconomics; Falsifiability; Creativity; Cognition; Psychology; Cognitive science; Value (mathematics); Process (computing); Cognitive psychology; Neuroscience; Social psychology; Computer science; Epistemology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004585584,0.0004633734,0.0005082922,0.0002442211,0.000467272,0.0004362714,0.0008562166,0.000555063,0.0004775053],"category_scores_gemma":[0.001365691,0.0005436212,0.0002133347,0.0001237858,0.0003347023,0.0001621379,0.0002498405,0.0007978369,0.0003771708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001411213,"about_ca_system_score_gemma":0.0004619504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004774423,"about_ca_topic_score_gemma":0.000001676654,"domain_scores_codex":[0.9973999,0.0001657852,0.0004058072,0.00131774,0.0001658323,0.0005449579],"domain_scores_gemma":[0.9962856,0.0004398527,0.0007887106,0.001894433,0.0003404355,0.0002509243],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001522052,0.006247275,0.03375091,0.00180906,0.001573466,0.0002352601,0.001567899,0.00007332308,0.5456841,0.3588792,0.04848028,0.000177179],"study_design_scores_gemma":[0.002255694,0.0005148142,0.8013035,0.001158483,0.0006746498,1.292056e-7,0.00008537104,0.0003588112,0.123407,0.001010589,0.06623186,0.002999114],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9573597,0.0004019385,0.02113533,0.001610216,0.01470693,0.00237073,0.001292258,0.0005071437,0.000615776],"genre_scores_gemma":[0.992148,0.0000840247,0.004378564,0.000787361,0.0009800532,0.001405884,6.221762e-7,0.0001134032,0.0001021025],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7675526,"threshold_uncertainty_score":0.9997016,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04906389641003737,"score_gpt":0.3342670043739254,"score_spread":0.285203107963888,"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."}}