{"id":"W3080498684","doi":"10.1093/bioinformatics/btaa750","title":"DELPHI: accurate deep ensemble model for protein interaction sites prediction","year":2020,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":167,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Compute Canada","keywords":"Computer science; Delphi; Deep learning; Delphi method; Ensemble learning; Data mining; Artificial intelligence; Machine learning; Ensemble forecasting; Web server; The Internet","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0009666152,0.001381161,0.001299985,0.0008187048,0.0003617173,0.0006121542,0.002345582,0.001283277,0.002521758],"category_scores_gemma":[0.001812642,0.0006173357,0.0009045997,0.0007101064,0.0003029243,0.001282009,0.00119318,0.002063015,0.0008428744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009462986,"about_ca_system_score_gemma":0.001140499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01126617,"about_ca_topic_score_gemma":0.01164844,"domain_scores_codex":[0.9996403,0.00007880746,0.00001366504,0.000104305,0.00009980855,0.00006290778],"domain_scores_gemma":[0.9995339,0.0002040885,0.00004332145,0.00005619392,0.0001109745,0.00005150176],"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":[0.0002952833,0.0001627622,0.003798926,0.0001323542,0.0002318053,0.0001516165,0.00003790781,0.8626418,0.003135254,0.002809557,0.02079638,0.1058064],"study_design_scores_gemma":[0.000006565376,0.00001095793,0.0001441787,0.000003072057,0.00000551734,0.0000105641,0.000002012995,0.9979782,0.0003407991,0.001153093,0.0003421667,0.000002976875],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.117944,0.003667313,0.8531819,0.001166642,0.0002178796,0.0001613353,0.00487202,0.01386367,0.00492528],"genre_scores_gemma":[0.7328888,0.00137701,0.2348377,0.001149332,0.0002376349,0.0004811375,0.0188285,0.0005437002,0.009656181],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01126617,"threshold_uncertainty_score":0.02240121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02283886874922888,"score_gpt":0.2581708460300953,"score_spread":0.2353319772808664,"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."}}