{"id":"W2088104507","doi":"10.1139/v11-046","title":"Obtaining accurate chemical shifts for all magnetic nuclei (<sup>1</sup>H, <sup>13</sup>C, <sup>17</sup>O, and <sup>27</sup>Al) in tris(2,4-pentanedionato-<i>O</i>,<i>O</i>′)aluminium(III) — A solid-state NMR case study","year":2011,"lang":"en","type":"article","venue":"Canadian Journal of Chemistry","topic":"Advanced NMR Techniques and Applications","field":"Chemistry","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; National Research Council Canada; Steacie Institute for Molecular Sciences","funders":"","keywords":"Chemistry; Homonuclear molecule; Chemical shift; NMR spectra database; Solid-state nuclear magnetic resonance; Spectral line; Magic angle spinning; Crystallography; Nuclear magnetic resonance spectroscopy; J-coupling; Analytical Chemistry (journal); Pseudopotential; Phosphorus-31 NMR spectroscopy; Spins; Nuclear magnetic resonance; Atomic physics; Physical chemistry; Molecule; Stereochemistry; Physics; Condensed matter physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.0009729081,0.00131359,0.001655163,0.0003884076,0.0005554983,0.0003333924,0.001650986,0.0007942642,0.001507875],"category_scores_gemma":[0.0004739315,0.001434639,0.0005806477,0.0006899458,0.0006660937,0.0007455717,0.0002668953,0.002357976,0.0000169205],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009445928,"about_ca_system_score_gemma":0.001569182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00226896,"about_ca_topic_score_gemma":0.0005780552,"domain_scores_codex":[0.9928336,0.00009652533,0.002619617,0.001507621,0.0007605823,0.002182093],"domain_scores_gemma":[0.9935607,0.0005164093,0.00104404,0.001389981,0.000617836,0.002871012],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.008268205,0.01010581,0.04416571,0.006989629,0.005551132,0.1210891,0.2460019,0.2011837,0.1084859,0.0004836222,0.2016199,0.04605547],"study_design_scores_gemma":[0.04755079,0.002519307,0.0002031625,0.003679054,0.002959786,0.0642078,0.1986257,0.2934964,0.1436906,0.008076197,0.2232025,0.01178884],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9927052,0.001274935,0.0002501435,0.0007113856,0.00001887933,0.001026722,0.0007240585,0.0001527808,0.003135876],"genre_scores_gemma":[0.9928594,0.0002570566,0.003241845,0.001059277,0.0006061901,0.0003464446,0.0001562866,0.000304214,0.001169244],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0923127,"threshold_uncertainty_score":0.9999616,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02418019062703786,"score_gpt":0.275323276756375,"score_spread":0.2511430861293372,"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."}}