{"id":"W2093644962","doi":"10.1021/jp210844t","title":"Multinuclear Solid-State Nuclear Magnetic Resonance and Density Functional Theory Characterization of Interaction Tensors in Taurine","year":2012,"lang":"en","type":"article","venue":"The Journal of Physical Chemistry A","topic":"Advanced NMR Techniques and Applications","field":"Chemistry","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Steacie Institute for Molecular Sciences","funders":"","keywords":"Solid-state nuclear magnetic resonance; Characterization (materials science); Density functional theory; Nuclear magnetic resonance; Taurine; Solid-state; Chemistry; Physics; Materials science; Computational chemistry; Physical chemistry; Nanotechnology; Biochemistry; Amino acid","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":[0.0004943635,0.0002687648,0.0003617712,0.0004079455,0.0003977343,0.0002096445,0.0005776046,0.0004886774,0.0007813493],"category_scores_gemma":[0.0005295562,0.0001594991,0.0002732398,0.0003050143,0.000532678,0.0004624191,0.0002746581,0.0003373089,0.00008589173],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004588554,"about_ca_system_score_gemma":0.0004539891,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002531309,"about_ca_topic_score_gemma":0.004935987,"domain_scores_codex":[0.9998717,0.00003813667,0.000005347388,0.00001434522,0.00005515231,0.00001519518],"domain_scores_gemma":[0.9997647,0.0001005517,0.00003372425,0.00003139281,0.00004789431,0.00002169487],"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":[0.0005236421,0.0003056163,0.004244993,0.001045384,0.00008346794,0.0006148783,0.0007733055,0.362247,0.4489805,0.1440354,0.001069206,0.03607665],"study_design_scores_gemma":[0.00002864405,0.0001235408,0.002117896,0.00002524918,0.00001314695,0.0000916976,0.00011795,0.9297294,0.05522349,0.01145634,0.001035416,0.00003725202],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9385351,0.0007752149,0.05528646,0.0002007517,0.00002291558,0.00001682508,0.0001898764,0.00007219588,0.004900656],"genre_scores_gemma":[0.9748123,0.0005136215,0.02398074,0.00002010131,0.000009524409,0.00002502071,0.0002002492,0.0000153178,0.000423099],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002531309,"threshold_uncertainty_score":0.005033135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008807779958905075,"score_gpt":0.251023058893865,"score_spread":0.2422152789349599,"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."}}