{"id":"W2895234710","doi":"10.1101/432146","title":"Protein model quality assessment using 3D oriented convolutional neural networks","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Stockholms Universitet; Concordia University","keywords":"CASP; Convolutional neural network; Python (programming language); Computer science; Executable; Artificial intelligence; Software; Deep learning; Artificial neural network; Source code; Machine learning; Pattern recognition (psychology); Protein structure prediction; Programming language; Protein structure","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00121855,0.001633713,0.0009560926,0.001786394,0.0004159126,0.001438763,0.002208786,0.001529901,0.002664816],"category_scores_gemma":[0.003355537,0.0006981142,0.001587307,0.0009242161,0.0005721205,0.001306872,0.001385546,0.001186674,0.0009615989],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002526747,"about_ca_system_score_gemma":0.001198582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01604816,"about_ca_topic_score_gemma":0.01599767,"domain_scores_codex":[0.9992895,0.00012184,0.00003727567,0.0001863513,0.0002783366,0.00008660714],"domain_scores_gemma":[0.9987183,0.0004468058,0.0001772736,0.0002306415,0.0003520171,0.00007499439],"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":[0.0002571235,0.0001015162,0.002957355,0.0001430285,0.0001827496,0.0001686625,0.00005561072,0.7841458,0.01045429,0.004634125,0.005735589,0.1911642],"study_design_scores_gemma":[0.000002733174,0.000007360488,0.0001012974,0.00000346559,0.000003659809,0.00001091481,0.000002011119,0.9978036,0.001068496,0.0008350395,0.0001581104,0.000003274521],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09753685,0.0009836092,0.8805065,0.0005339652,0.00009015235,0.0001217559,0.001190013,0.015464,0.003573142],"genre_scores_gemma":[0.7096562,0.0005365951,0.2804063,0.0004051838,0.00004501669,0.0001389572,0.00417361,0.0009041335,0.003733968],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01604816,"threshold_uncertainty_score":0.03190953,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01971831232525158,"score_gpt":0.2710695766718458,"score_spread":0.2513512643465942,"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."}}