{"id":"W2177375219","doi":"10.1093/molbev/msv223","title":"Phenoscape: Identifying Candidate Genes for Evolutionary Phenotypes","year":2015,"lang":"en","type":"article","venue":"Molecular Biology and Evolution","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; Division of Emerging Frontiers; National Evolutionary Synthesis Center; National Human Genome Research Institute; Academy of Natural Sciences of Drexel University; National Institutes of Health; National Science Foundation","keywords":"Biology; Phenotype; Candidate gene; Gene; Ictalurus; Genetics; Evolutionary biology; Model organism; Phenotypic trait; Genetic architecture; Catfish; Computational biology; Fish <Actinopterygii>","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001780108,0.0001449195,0.0001338241,0.00004330984,0.0001507038,0.00001125241,0.0000936916,0.000158763,0.000001233777],"category_scores_gemma":[0.00006061368,0.0001408334,0.00006051981,0.0000489181,0.0001313895,0.000001320106,0.0001195364,0.00003834819,0.000003974945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002154923,"about_ca_system_score_gemma":0.00007118536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005038334,"about_ca_topic_score_gemma":0.00002975187,"domain_scores_codex":[0.9991502,0.00005817002,0.0001490044,0.0003501214,0.00004562109,0.000246846],"domain_scores_gemma":[0.9995475,0.00000865725,0.00005745704,0.0001729352,0.000126895,0.00008655595],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001560956,0.00002758966,0.02076278,0.00001660415,0.0001242424,8.968111e-7,0.0000508443,0.000110607,0.9668255,0.009071703,0.0009400464,0.001913092],"study_design_scores_gemma":[0.009534354,0.004142867,0.09798828,0.00005719475,0.0005791857,0.0003224045,0.00138585,0.003148872,0.3689255,0.3220599,0.1891059,0.002749658],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8947292,0.03410733,0.06996016,0.0001720221,0.0003676994,0.0002435059,0.00005427489,0.000008328033,0.0003574944],"genre_scores_gemma":[0.994161,0.0002949162,0.004817626,0.0001205156,0.0002229837,0.00006254751,0.0001772912,0.00001590475,0.0001271791],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5979,"threshold_uncertainty_score":0.574302,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01585099537588687,"score_gpt":0.2753857895561657,"score_spread":0.2595347941802788,"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."}}