{"id":"W2572191671","doi":"10.1016/j.jmr.2017.01.010","title":"Indirect detection of infinite-speed MAS solid-state NMR spectra","year":2017,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance","topic":"Advanced NMR Techniques and Applications","field":"Chemistry","cited_by":46,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Ames Laboratory; Basic Energy Sciences; Natural Sciences and Engineering Research Council of Canada; Government of Canada; Iowa State University; Laboratory Directed Research and Development; U.S. Department of Energy","keywords":"Heteronuclear molecule; Homonuclear molecule; Magic angle spinning; Solid-state nuclear magnetic resonance; Chemistry; Spectral line; Magic angle; Spinning; Nuclide; Analytical Chemistry (journal); Spectral resolution; Two-dimensional nuclear magnetic resonance spectroscopy; NMR spectra database; Molecular physics; Nuclear magnetic resonance; Nuclear magnetic resonance spectroscopy; Molecule; Physics; Stereochemistry; Organic chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000173531,0.0001178138,0.0002696066,0.00005960473,0.0001429651,0.00003861272,0.0004559295,0.00007267929,0.0002001208],"category_scores_gemma":[0.0001865568,0.0001064177,0.0001202275,0.00006201631,0.0001254354,0.0001498218,0.00005206586,0.0002995414,0.000005466686],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004162466,"about_ca_system_score_gemma":0.00004132108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001230293,"about_ca_topic_score_gemma":0.00001102877,"domain_scores_codex":[0.9989398,0.000009910547,0.0005081961,0.0001256515,0.0002467424,0.000169707],"domain_scores_gemma":[0.9981931,0.00005943379,0.001015942,0.0004846808,0.000176379,0.00007049599],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001427323,0.00009142203,0.001734534,0.00005739658,0.00001100169,0.00002989831,0.0001094973,0.00009183483,0.7072611,0.0001189165,0.0002669582,0.2900847],"study_design_scores_gemma":[0.0006923875,0.0002239521,0.02542015,0.0002123719,0.00002928355,0.0001103739,0.00003063495,0.0004852487,0.8399743,0.005770532,0.126884,0.0001666855],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9747922,0.003879539,0.002911672,0.0003726706,0.00005206281,0.00009523937,0.0000246853,0.00003402186,0.01783785],"genre_scores_gemma":[0.9901557,0.001968857,0.005698599,0.00002182928,0.0001702869,0.000004174597,4.619251e-7,0.00001858171,0.001961533],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2899181,"threshold_uncertainty_score":0.4339589,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0181276730641067,"score_gpt":0.292151111464361,"score_spread":0.2740234384002543,"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."}}