{"id":"W2942457686","doi":"10.1016/j.tree.2019.03.008","title":"Experimental Evolution of Innovation and Novelty","year":2019,"lang":"en","type":"review","venue":"Trends in Ecology & Evolution","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":45,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; Gordon and Betty Moore Foundation; National Institutes of Health; National Science Foundation","keywords":"Novelty; Selection (genetic algorithm); Adaptation (eye); Variation (astronomy); Population; Evolutionary ecology; Ecology; Function (biology); Evolutionary biology; Biology; Computer science; Artificial intelligence; Host (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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003056472,0.0002941896,0.0007211771,0.0007362846,0.00003868388,0.00000523754,0.0001602605,0.0007896887,0.00003366867],"category_scores_gemma":[0.0000677183,0.0003041099,0.0001262606,0.0007487387,0.0001774789,0.000006288878,0.000164483,0.0002024509,0.00001298507],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003609986,"about_ca_system_score_gemma":0.0002753424,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002931247,"about_ca_topic_score_gemma":0.0001676451,"domain_scores_codex":[0.998159,0.0001664624,0.0007795713,0.0005216208,0.0001081732,0.0002652037],"domain_scores_gemma":[0.9990032,0.00001796752,0.0004961175,0.000353443,0.00009833704,0.00003090896],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003032679,0.00203374,0.0255651,0.007840602,0.0007817175,0.000005173481,0.0001602527,0.0008368081,0.01695529,0.04525674,0.006522384,0.8937389],"study_design_scores_gemma":[0.003829824,0.002622526,0.1024347,0.001727405,0.0007634818,0.000259239,0.0002327978,0.002292987,0.0002638712,0.000502574,0.8831949,0.001875705],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.01826757,0.9791145,0.0008996425,0.0000107312,0.0004705509,0.000312059,0.00006425456,0.00001196168,0.000848738],"genre_scores_gemma":[0.2807954,0.714624,0.0005411899,0.00001740895,0.0001611716,0.00009749382,0.001830172,0.00005172492,0.001881384],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.8918632,"threshold_uncertainty_score":0.9999411,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02764177229187136,"score_gpt":0.3424955217692228,"score_spread":0.3148537494773514,"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."}}