{"id":"W2073753066","doi":"10.1016/s1090-7807(03)00190-3","title":"An efficient peak assignment algorithm for two-dimensional NMR correlation spectra of framework structures","year":2003,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance","topic":"Advanced NMR Techniques and Applications","field":"Chemistry","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Spectral line; Relaxation (psychology); Chemical shift; NMR spectra database; Correlation; Algorithm; Chemistry; Resolution (logic); Graph; Computer science; Mathematics; Physics; Physical chemistry; Theoretical computer science; Artificial intelligence; Geometry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001943129,0.000122599,0.0002112522,0.00004152992,0.00007084537,0.00001263068,0.0001754,0.0000878958,0.0003982864],"category_scores_gemma":[0.00008688499,0.0001054249,0.0001057066,0.00009369339,0.00006353068,0.00004448428,0.000009813085,0.0002389685,6.937674e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006437882,"about_ca_system_score_gemma":0.00006297829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001544624,"about_ca_topic_score_gemma":2.491739e-7,"domain_scores_codex":[0.998825,0.00002001618,0.0004921536,0.0001565148,0.0003412714,0.0001651067],"domain_scores_gemma":[0.9988306,0.0001672441,0.0004716759,0.0002458394,0.0002006206,0.00008406743],"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":[0.0002221531,0.001009447,0.0004461582,0.00009664499,0.00003220489,0.00001817293,0.0003021812,0.2380989,0.1717164,0.06921401,0.001470206,0.5173735],"study_design_scores_gemma":[0.004463049,0.002152653,0.007038891,0.000951537,0.0002010243,0.0004984176,0.000373634,0.2977918,0.4038011,0.2079421,0.07389297,0.0008928333],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1416064,0.005626307,0.8512265,0.0001038204,0.00007526561,0.0002360433,0.0000570816,0.00002380179,0.001044806],"genre_scores_gemma":[0.4467724,0.00004026416,0.552799,0.00003372841,0.0001463037,0.00001425452,0.000003460301,0.00001688039,0.0001736708],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5164807,"threshold_uncertainty_score":0.4360957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008870979733120964,"score_gpt":0.2843163231600026,"score_spread":0.2754453434268817,"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."}}