{"id":"W1911696222","doi":"10.48550/arxiv.1308.5032","title":"How Did Humans Become So Creative? A Computational Approach","year":2013,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Language and cultural evolution","field":"Social Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"","keywords":"Creativity; Computational creativity; Computer science; Novelty; Recall; Imitation; Focus (optics); Chaining; Artificial intelligence; Cognitive science; Convergence (economics); Simple (philosophy); Cognitive psychology; Psychology; Epistemology; Social psychology","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":[],"consensus_categories":[],"category_scores_codex":[0.0001791991,0.0002098492,0.000243914,0.00009771808,0.0007803167,0.0003288197,0.0005499789,0.0003166369,0.0004049757],"category_scores_gemma":[0.0000501741,0.0002081524,0.0002023619,0.0002842619,0.0004717443,0.0004509807,0.0003101274,0.0003878642,0.0001145493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003741923,"about_ca_system_score_gemma":0.0002371023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00650626,"about_ca_topic_score_gemma":0.0007592444,"domain_scores_codex":[0.9985629,0.0002582431,0.0001028654,0.0005970404,0.0001607882,0.000318131],"domain_scores_gemma":[0.9991106,0.00004765663,0.0001857161,0.0002422669,0.000254425,0.0001593161],"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":[0.00002895575,0.0002942394,0.005411679,0.0001049986,0.0002704498,0.00007361796,0.03106489,0.07592849,0.00001615521,0.8800884,0.005866822,0.0008512714],"study_design_scores_gemma":[0.002831752,0.0001862956,0.05148649,0.0003109666,0.0008396119,0.00000547416,0.1368502,0.159282,0.00001986372,0.5817735,0.06258804,0.003825721],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8750339,0.000198002,0.04577415,0.000699404,0.0003515174,0.0007611219,0.00004968573,0.0002908856,0.07684139],"genre_scores_gemma":[0.957845,0.000087707,0.0004827378,0.0000697522,0.0002798557,0.000002787302,0.0001610031,0.00001110334,0.04106007],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.298315,"threshold_uncertainty_score":0.9835562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07869516566250823,"score_gpt":0.2141881597959245,"score_spread":0.1354929941334163,"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."}}