{"id":"W2142971723","doi":"10.1007/978-3-642-55337-0_3","title":"Evolving Culture Versus Local Minima","year":2014,"lang":"en","type":"book-chapter","venue":"Studies in computational intelligence","topic":"Language and cultural evolution","field":"Social Sciences","cited_by":36,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Institute for Advanced Research; Université de Montréal","funders":"","keywords":"Maxima and minima; Computer science; Artificial intelligence; Representation (politics); Cognitive science; Space (punctuation); Deep learning; Artificial neural network; Theoretical computer science; Machine learning; Psychology; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005549005,0.0003284931,0.0004424525,0.0004972253,0.0006412156,0.001630089,0.0009073452,0.001036224,0.009624662],"category_scores_gemma":[0.003488871,0.000214286,0.0002585817,0.0009006977,0.002965643,0.003268895,0.001120863,0.002395051,0.0009128185],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009451588,"about_ca_system_score_gemma":0.0004118565,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009271632,"about_ca_topic_score_gemma":0.001081659,"domain_scores_codex":[0.9997998,0.00007929125,0.000007733256,0.00004719873,0.00004655854,0.00001936016],"domain_scores_gemma":[0.9993466,0.0004570219,0.00004365354,0.00007057911,0.00004956625,0.00003269169],"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":[0.000008487959,0.00001005003,0.0001135616,0.00005436266,0.000008848727,0.00002357879,0.0002877491,0.005792104,0.0002278142,0.9552227,0.004004275,0.03424656],"study_design_scores_gemma":[0.000008160454,0.00001734199,0.0001728475,0.00006772449,0.000008242847,0.00006067103,0.0001503629,0.01428945,0.0002486898,0.9566456,0.02832277,0.000008092596],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.06661641,0.03344332,0.2601224,0.01238103,0.001301832,0.00006243591,0.0001299996,0.0002076316,0.625735],"genre_scores_gemma":[0.7702054,0.01780518,0.06158533,0.001900392,0.0009767676,0.0001674898,0.0001887947,0.0004325859,0.1467381],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009624662,"threshold_uncertainty_score":0.03219771,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1123110190773361,"score_gpt":0.4049284320994243,"score_spread":0.2926174130220882,"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."}}