{"id":"W2078007789","doi":"10.1038/nature01151","title":"Macroevolution simulated with autonomously replicating computer programs","year":2002,"lang":"en","type":"article","venue":"Nature","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":88,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Oregon State University; M.J. Murdock Charitable Trust; National Science Foundation","keywords":"Macroevolution; Term (time); Adaptation (eye); Natural selection; Population; Selection (genetic algorithm); Set (abstract data type); Simple (philosophy); Computer science; Variation (astronomy); Process (computing); Type (biology); Outcome (game theory); Evolutionary biology; Mathematical economics; Biology; Artificial intelligence; Ecology; Mathematics; Genetics; Phylogenetic tree; Epistemology; Sociology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005760951,0.0003882269,0.0006196054,0.0005286409,0.0006570375,0.001026852,0.001165364,0.001146924,0.002761055],"category_scores_gemma":[0.005159087,0.0004608051,0.0006284662,0.0004759752,0.001285001,0.001046287,0.0009524894,0.001288566,0.0001967628],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006881459,"about_ca_system_score_gemma":0.0006664295,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003507584,"about_ca_topic_score_gemma":0.001794844,"domain_scores_codex":[0.9997193,0.0001230991,0.00001299133,0.00003987157,0.00006518219,0.00003950892],"domain_scores_gemma":[0.9977458,0.00157993,0.0001431656,0.0002142558,0.0001647083,0.0001520568],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007986279,0.00004887971,0.001238249,0.00002468472,0.00003170113,0.0001130025,0.0001175604,0.9690847,0.001376492,0.02412884,0.0002610835,0.003495025],"study_design_scores_gemma":[0.0000341883,0.00001568537,0.00009730185,0.000001971119,0.000005519432,0.0000099922,0.00001020357,0.9931253,0.0003532981,0.006101138,0.000240931,0.00000440278],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8372448,0.000153449,0.1484982,0.0004884077,0.0001307152,0.00007402983,0.0001116634,0.000521136,0.01277753],"genre_scores_gemma":[0.9729768,0.00007077104,0.02474518,0.00004343891,0.00001449119,0.0001020716,0.00005603311,0.00006760624,0.001923531],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003507584,"threshold_uncertainty_score":0.009236693,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005089882663750327,"score_gpt":0.2205360835521474,"score_spread":0.2154462008883971,"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."}}