{"id":"W3195593976","doi":"10.1002/prot.26222","title":"Prediction of protein assemblies, the next frontier: The <scp>CASP14‐CAPRI</scp> experiment","year":2021,"lang":"en","type":"article","venue":"Proteins Structure Function and Bioinformatics","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":127,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Heart, Lung, and Blood Institute; H2020 European Institute of Innovation and Technology; Lietuvos Mokslo Taryba; National Institute of General Medical Sciences; Ministerio de Ciencia e Innovación; Narodowe Centrum Nauki; National Natural Science Foundation of China; Cancer Research UK; National Science Foundation; Department of Energy and Climate Change; National Institutes of Health; Institut national de recherche en informatique et en automatique (INRIA); Changzhou Science and Technology Bureau; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Wellcome Trust; Medical Research Council Canada; Francis Crick Institute","keywords":"CASP; Server; Computer science; Template; Protein structure prediction; Data mining; Biology; Computer network; 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":[0.01267022,0.002331733,0.001668715,0.0009952299,0.001178587,0.002021817,0.002611141,0.002012323,0.005069557],"category_scores_gemma":[0.01237264,0.0006253988,0.001643193,0.0007946055,0.0009114696,0.002621445,0.00268538,0.002854301,0.003381014],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001107734,"about_ca_system_score_gemma":0.001836578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005790666,"about_ca_topic_score_gemma":0.005787046,"domain_scores_codex":[0.9940681,0.002527854,0.0002701459,0.001072294,0.001444541,0.0006170416],"domain_scores_gemma":[0.9908971,0.003801229,0.000326878,0.002576354,0.001544202,0.000854189],"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":[0.01022746,0.004138894,0.07628708,0.001630622,0.002769778,0.001349018,0.0006946672,0.3933079,0.04743062,0.007440683,0.2645347,0.1901886],"study_design_scores_gemma":[0.0009552939,0.003187277,0.01607607,0.0000876812,0.0002776685,0.0005500045,0.0004300061,0.9030833,0.04860755,0.005263327,0.02134664,0.0001352218],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8957708,0.00335491,0.0381707,0.002762432,0.0008234711,0.0007643672,0.0145442,0.02475083,0.01905826],"genre_scores_gemma":[0.8126557,0.000464836,0.104198,0.001126858,0.0002021634,0.0005135524,0.07367487,0.001709742,0.005454205],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01267022,"threshold_uncertainty_score":0.0670073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01129118542889246,"score_gpt":0.204990011256002,"score_spread":0.1936988258271095,"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."}}