{"id":"W3135833838","doi":"10.1109/tcbb.2021.3064630","title":"CoronaPep: An Anti-Coronavirus Peptide Generation Tool","year":2021,"lang":"en","type":"article","venue":"IEEE/ACM Transactions on Computational Biology and Bioinformatics","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Shanghai Jiao Tong University; Science and Technology Commission of Shanghai Municipality; Natural Science Foundation of Henan Province; Ministry of Science and Technology of the People's Republic of China; National Natural Science Foundation of China","keywords":"Coronavirus; Coronavirus disease 2019 (COVID-19); Pandemic; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Severe acute respiratory syndrome coronavirus; 2019-20 coronavirus outbreak; Computer science; Computational biology; Virology; Outbreak; Biology; Medicine; Infectious disease (medical specialty)","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":[0.0007622231,0.001166248,0.0005598694,0.001202588,0.0003844784,0.001082882,0.001470413,0.001048948,0.01548223],"category_scores_gemma":[0.00189685,0.0006312179,0.00089782,0.0007471328,0.0003100522,0.001067332,0.001340057,0.0008758946,0.006486465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002580984,"about_ca_system_score_gemma":0.0006448206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004330032,"about_ca_topic_score_gemma":0.0005386203,"domain_scores_codex":[0.9996731,0.00004371306,0.00003144075,0.00008521001,0.0001318762,0.00003453506],"domain_scores_gemma":[0.9994443,0.0003292862,0.00005975961,0.00005767076,0.00006910361,0.00003979793],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002284022,0.0003356751,0.009172901,0.001917316,0.0003437098,0.002931863,0.0004643343,0.01252359,0.09180567,0.01214439,0.3111534,0.5549233],"study_design_scores_gemma":[0.001270594,0.0006194017,0.009433163,0.0002699815,0.0001582964,0.005438701,0.0001926655,0.2851517,0.198584,0.033322,0.465255,0.0003045379],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02337844,0.001241821,0.5570188,0.000645045,0.0002921831,0.0004157174,0.0220522,0.3851252,0.009830637],"genre_scores_gemma":[0.2146932,0.001647925,0.6668531,0.001688613,0.0001872148,0.001335754,0.06413598,0.02831675,0.02114152],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01548223,"threshold_uncertainty_score":0.05179316,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.072003200099455,"score_gpt":0.3668063045907243,"score_spread":0.2948031044912693,"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."}}