{"id":"W2052351054","doi":"10.4204/eptcs.9.12","title":"How Creative Should Creators Be To Optimize the Evolution of Ideas? A Computational Model","year":2009,"lang":"en","type":"article","venue":"Electronic Proceedings in Theoretical Computer Science","topic":"Language and cultural evolution","field":"Social Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada; Vlaamse regering","keywords":"Creativity; Function (biology); Diversity (politics); Population; Fitness function; Ideal (ethics); Sociology; Psychology; Epistemology; Computer science; Social psychology; Demography; Biology; Philosophy; Evolutionary biology","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":[0.001727443,0.0001267854,0.0001636029,0.0001374998,0.0005514898,0.0002206293,0.00083538,0.00006824431,0.00001340988],"category_scores_gemma":[0.0004834894,0.00008542499,0.00005673392,0.001688869,0.001767376,0.0006403163,0.00009463581,0.0002480847,0.000001567933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009178907,"about_ca_system_score_gemma":0.0005772875,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008155326,"about_ca_topic_score_gemma":0.00002544979,"domain_scores_codex":[0.9978213,0.00004077877,0.0001895212,0.0003840102,0.0009029154,0.0006614628],"domain_scores_gemma":[0.9991906,0.00007646631,0.00008254214,0.0000891568,0.0004226648,0.0001385838],"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":[0.00002974561,0.00004035984,0.00003652001,0.000001546785,0.000002298219,2.593521e-7,0.01064936,0.005701737,0.0003436404,0.981305,0.00009330348,0.001796254],"study_design_scores_gemma":[0.0001712338,0.0002766735,0.0007081314,0.00002955518,0.000007700465,0.000003009086,0.002345767,0.3665249,0.0003730441,0.6293744,0.00004587616,0.0001396889],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4722232,0.0001899779,0.4773841,0.03092014,0.00008186333,0.0007424469,0.000002286797,0.0001034458,0.01835264],"genre_scores_gemma":[0.9871474,0.000007190982,0.01198318,0.0006978287,0.00008040263,0.00001231346,5.193397e-7,0.000003611677,0.00006756223],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5149242,"threshold_uncertainty_score":0.651197,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01133373887865297,"score_gpt":0.2871389603538102,"score_spread":0.2758052214751572,"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."}}