{"id":"W2288856974","doi":"10.1016/j.biosystems.2016.01.003","title":"Computational power and generative capacity of genetic systems","year":2016,"lang":"en","type":"review","venue":"Biosystems","topic":"Origins and Evolution of Life","field":"Physics and Astronomy","cited_by":33,"is_retracted":false,"has_abstract":false,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; Russian Foundation for Basic Research","keywords":"Generativity; Semiotics; Generative grammar; Arbitrariness; Computer science; Genetic code; Semiosis; Sign (mathematics); Structuralism (philosophy of science); Expression (computer science); Cognitive science; Artificial intelligence; Linguistics; Epistemology; Biology; Mathematics; Philosophy; Programming language; Psychology; Genetics; DNA","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":[0.0001197903,0.0002535163,0.001002863,0.00008629857,0.00005941149,0.0000373704,0.0001087358,0.00009895369,0.00007020001],"category_scores_gemma":[0.000001938466,0.0001675645,0.0002061079,0.00007907212,0.00006605325,0.00003842229,0.00003563643,0.00007657655,0.00005701018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003852363,"about_ca_system_score_gemma":0.0001389036,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000969839,"about_ca_topic_score_gemma":2.898947e-7,"domain_scores_codex":[0.9987386,0.0001369801,0.0005313129,0.0002628074,0.0001737946,0.0001565228],"domain_scores_gemma":[0.9990494,0.00007297397,0.0005115729,0.0001832978,0.000097112,0.00008561141],"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":[0.000009975401,0.0004108953,0.005918441,0.06162591,0.004696233,0.000007308744,0.0004790337,0.0001226665,0.00001570467,0.4132817,0.04015613,0.473276],"study_design_scores_gemma":[0.0001221272,0.00002594328,0.00002103006,0.005353069,0.00008006963,0.000006984973,0.00002191862,0.00005096225,4.895484e-7,0.00006033459,0.9940541,0.000202942],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0002350607,0.9928561,0.002484079,0.000006108266,0.0007871428,0.0004912167,0.001764003,0.00001285019,0.00136343],"genre_scores_gemma":[0.05160846,0.9437099,0.0005964934,0.000004296659,0.002294261,0.0001443542,0.0001471662,0.00007635503,0.001418734],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.953898,"threshold_uncertainty_score":0.6833082,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03229459339887716,"score_gpt":0.283111608826802,"score_spread":0.2508170154279249,"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."}}