{"id":"W3092175249","doi":"10.1016/j.jnoncrysol.2020.120383","title":"The Czjzek distribution in solid-state NMR: Scaling properties of central and satellite transitions","year":2020,"lang":"en","type":"article","venue":"Journal of Non-Crystalline Solids","topic":"Advanced NMR Techniques and Applications","field":"Chemistry","cited_by":35,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Gaussian; Scaling; Isotropy; Distribution (mathematics); Satellite; Spectral line; Electric field gradient; Tensor (intrinsic definition); Field (mathematics); NMR spectra database; Computational physics; Chemical shift; Physics; Statistical physics; Nuclear magnetic resonance; Electric field; Materials science; Mathematics; Optics; Quantum mechanics; Mathematical analysis; 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":[0.0001402714,0.0001159601,0.0002371481,0.00002136498,0.0001020167,0.00003031411,0.0001563482,0.00005092915,0.00000613306],"category_scores_gemma":[0.00004512039,0.00008160415,0.0001005101,0.0001478412,0.0001351515,0.0001351997,0.00002692612,0.0003095881,2.130449e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004353633,"about_ca_system_score_gemma":0.00005991822,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004970091,"about_ca_topic_score_gemma":0.000007603086,"domain_scores_codex":[0.9988462,0.00001520052,0.0006488032,0.0001073773,0.0001685698,0.0002138967],"domain_scores_gemma":[0.9993179,0.00003715475,0.000290704,0.0001025138,0.000135747,0.0001160015],"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":[0.0003034954,0.0001382571,0.0003749886,0.0002452366,0.00005199757,0.00001749967,0.001773706,0.01210197,0.9740795,0.0003321893,0.0001112079,0.01046994],"study_design_scores_gemma":[0.003599056,0.0004403748,0.003126549,0.001715885,0.0002080041,0.00023858,0.004008293,0.1261442,0.80655,0.006810511,0.04638152,0.0007770162],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8806911,0.001460411,0.1130109,0.004426534,0.0000107383,0.0001276034,0.0001042562,0.00002313557,0.0001452956],"genre_scores_gemma":[0.9960494,0.002461254,0.001243343,0.00006083682,0.0001324966,0.000005931774,0.0000122069,0.00001380798,0.00002070388],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1675295,"threshold_uncertainty_score":0.3327721,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01623714955640032,"score_gpt":0.264262203066626,"score_spread":0.2480250535102256,"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."}}