{"id":"W3115881671","doi":"10.1109/bibe50027.2020.00027","title":"Chaos Game Representations & Deep Learning for Proteome-Wide Protein Prediction","year":2020,"lang":"en","type":"article","venue":"","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Leverage (statistics); Artificial intelligence; Convolutional neural network; Deep learning; Proteome; Machine learning; Theoretical computer science; Bioinformatics; Biology","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":[0.000652048,0.0006474782,0.0004219285,0.0005426432,0.0003129716,0.0006956865,0.00115698,0.0007913965,0.001857158],"category_scores_gemma":[0.002079772,0.0002320226,0.0004084311,0.0004816412,0.0005272175,0.001513236,0.0009920298,0.001217263,0.0003355661],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001101523,"about_ca_system_score_gemma":0.000650908,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005153977,"about_ca_topic_score_gemma":0.005965425,"domain_scores_codex":[0.9997981,0.0000607924,0.000009908576,0.00005176546,0.00004579871,0.00003363081],"domain_scores_gemma":[0.9995905,0.000188214,0.00005295349,0.00007451653,0.00005859399,0.00003530872],"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":[0.0002617753,0.0001826103,0.002272855,0.0001203468,0.00007595331,0.0001064057,0.00009216841,0.7401225,0.01052904,0.02824896,0.006797473,0.2111899],"study_design_scores_gemma":[0.000005335871,0.00001889196,0.00009857642,0.000004381932,0.000002321505,0.000006112602,0.000005507256,0.9917502,0.001171479,0.006532121,0.0004012669,0.00000377953],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2484486,0.001220697,0.7350215,0.001669475,0.0001616409,0.0001325196,0.0008363941,0.004753917,0.007755322],"genre_scores_gemma":[0.8619989,0.0002298683,0.133593,0.0002632507,0.00003029822,0.00009096762,0.0006348798,0.0001131068,0.003045661],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005153977,"threshold_uncertainty_score":0.01024795,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01594613404217509,"score_gpt":0.2699688526959189,"score_spread":0.2540227186537438,"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."}}