{"id":"W1826484537","doi":"10.1093/nar/gkv494","title":"CSI 3.0: a web server for identifying secondary and super-secondary structure in proteins using NMR chemical shifts","year":2015,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":176,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Genome Alberta","keywords":"Protein secondary structure; Chemical shift; Intrinsically disordered proteins; Nuclear magnetic resonance spectroscopy; Sequence (biology); Biology; Crystallography; Physics; Nuclear magnetic resonance; Chemistry; Genetics","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":[0.00176338,0.002984656,0.002357584,0.00280773,0.001260687,0.00283382,0.004696368,0.001567697,0.04369658],"category_scores_gemma":[0.002957352,0.001948894,0.001968549,0.002788132,0.0004879671,0.003000563,0.002361084,0.002880789,0.06744939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00151069,"about_ca_system_score_gemma":0.00315056,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006686485,"about_ca_topic_score_gemma":0.005738044,"domain_scores_codex":[0.9990951,0.00008822095,0.0000766113,0.0001986615,0.0004155201,0.0001258648],"domain_scores_gemma":[0.9986681,0.0002805046,0.0001551894,0.0002636711,0.00044171,0.0001908225],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001287383,0.0001945328,0.001704436,0.001370823,0.0002171864,0.0002917584,0.0002160309,0.002478473,0.05501287,0.003549782,0.8565347,0.07714188],"study_design_scores_gemma":[0.0009149516,0.0003541993,0.008206894,0.0004188524,0.000300344,0.001331564,0.0002305877,0.08576915,0.1610793,0.01635026,0.7243989,0.0006449994],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.008886603,0.001247243,0.1807112,0.0004184231,0.0003056915,0.0004874277,0.1970192,0.5979559,0.01296837],"genre_scores_gemma":[0.03195487,0.00171391,0.3067521,0.0008491849,0.000149626,0.00112347,0.5715648,0.0701096,0.01578243],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.04369658,"threshold_uncertainty_score":0.1461796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05342225292029234,"score_gpt":0.3472585907557746,"score_spread":0.2938363378354823,"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."}}