{"id":"W2037611121","doi":"10.1109/tcbb.2007.1047","title":"CISA: Combined NMR Resonance Connectivity Information Determination and Sequential Assignment","year":2007,"lang":"en","type":"article","venue":"IEEE/ACM Transactions on Computational Biology and Bioinformatics","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Chinese Academy of Sciences","keywords":"Key (lock); Computer science; Set (abstract data type); Chemical shift; Algorithm; Resonance (particle physics); Chemistry; Physics","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":[0.002285656,0.00202813,0.001483208,0.002910661,0.001204102,0.001288743,0.003084077,0.001216055,0.009100186],"category_scores_gemma":[0.007363759,0.0009974303,0.001737837,0.00301812,0.001130542,0.002732491,0.003039486,0.002226281,0.002332196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007927706,"about_ca_system_score_gemma":0.003073435,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004281189,"about_ca_topic_score_gemma":0.006382221,"domain_scores_codex":[0.998466,0.0003579441,0.00009154908,0.0004521805,0.0005145932,0.0001178604],"domain_scores_gemma":[0.9958273,0.002003884,0.0003819884,0.0007650414,0.0007922223,0.0002296608],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001312993,0.0005157853,0.00287194,0.0003819187,0.00030212,0.0003177115,0.0003083562,0.2726626,0.02045989,0.02415535,0.02137387,0.6553374],"study_design_scores_gemma":[0.00009825077,0.0001763197,0.0002942556,0.00001173332,0.00003899739,0.0001669836,0.00004913857,0.9700747,0.008974461,0.01415499,0.005928171,0.00003214397],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01612658,0.0001190551,0.9686486,0.0001610836,0.00005037248,0.0002271039,0.0003513048,0.01239185,0.001924043],"genre_scores_gemma":[0.09173055,0.0001253825,0.9024784,0.0001240522,0.00006177476,0.0004430151,0.001198001,0.0008533926,0.00298538],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009100186,"threshold_uncertainty_score":0.03044319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01223611763404667,"score_gpt":0.2709475571398639,"score_spread":0.2587114395058173,"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."}}