{"id":"W2038601075","doi":"10.1126/science.1174301","title":"Positive Selection of Tyrosine Loss in Metazoan Evolution","year":2009,"lang":"en","type":"article","venue":"Science","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":95,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; University of Toronto; Mount Sinai Hospital","funders":"National Institute of General Medical Sciences","keywords":"Multicellular organism; Biology; Evolutionary biology; Receptor tyrosine kinase; Selection (genetic algorithm); Tyrosine; Lineage (genetic); Phenotype; Organism; Computational biology; Gene; Genetics; Computer science; Signal transduction; Artificial intelligence","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":[0.0008236396,0.0003875605,0.0004684091,0.000972592,0.0009342662,0.0009105265,0.0004677282,0.0009130973,0.001990783],"category_scores_gemma":[0.0009936705,0.0002766586,0.0003143277,0.0008637432,0.00107178,0.0006047356,0.001429967,0.0007249349,0.0004611421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001096412,"about_ca_system_score_gemma":0.000419454,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001525226,"about_ca_topic_score_gemma":0.002343594,"domain_scores_codex":[0.9994949,0.00007299764,0.00002222887,0.0001897652,0.0001349024,0.000085133],"domain_scores_gemma":[0.9995146,0.00006914367,0.0001460709,0.00006233244,0.0001111038,0.00009687727],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0009552804,0.00005627086,0.1358239,0.0008024561,0.0005298355,0.002304808,0.00175767,0.003629875,0.75583,0.01081203,0.00117199,0.08632591],"study_design_scores_gemma":[0.0001081272,0.0004757328,0.8829458,0.0001467419,0.0003575412,0.006250492,0.001356398,0.005595325,0.04933557,0.007687298,0.04561135,0.0001296503],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9861143,0.004185243,0.002625701,0.0006093431,0.00004556873,0.00001191844,0.0002362323,0.00008696329,0.006084756],"genre_scores_gemma":[0.9954273,0.001753321,0.001252085,0.0002568591,0.00004026413,0.00001196144,0.0001590039,0.00003967817,0.001059621],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001990783,"threshold_uncertainty_score":0.007955074,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003804146537482121,"score_gpt":0.2521783379463893,"score_spread":0.2483741914089072,"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."}}