{"id":"W2316475507","doi":"10.1021/ja502113d","title":"Dynamic Nuclear Polarization NMR Enables the Analysis of Sn-Beta Zeolite Prepared with Natural Abundance <sup>119</sup>Sn Precursors","year":2014,"lang":"en","type":"article","venue":"Journal of the American Chemical Society","topic":"Advanced NMR Techniques and Applications","field":"Chemistry","cited_by":147,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Basic Energy Sciences; Natural Sciences and Engineering Research Council of Canada; Office of Science; National Institutes of Health; National Institute of Biomedical Imaging and Bioengineering; U.S. Department of Energy","keywords":"Chemistry; Zeolite; Unpaired electron; Tin; Natural abundance; Polarization (electrochemistry); Nuclear magnetic resonance spectroscopy; Isotope; Solid-state nuclear magnetic resonance; Catalysis; Analytical Chemistry (journal); Nuclear magnetic resonance; Physical chemistry; Molecule; Nuclear physics; Stereochemistry; Organic chemistry; Mass spectrometry; Physics","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":[0.0001865013,0.0001765808,0.0004616474,0.00002242245,0.0001609525,0.00003084187,0.0007861651,0.00006620371,0.00003363346],"category_scores_gemma":[0.00007475815,0.00009791472,0.0006433847,0.0009129868,0.0006622763,0.0001094573,0.0001165841,0.0005126218,4.298894e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001629418,"about_ca_system_score_gemma":0.00003936977,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004419271,"about_ca_topic_score_gemma":0.000002427355,"domain_scores_codex":[0.9986832,0.00003840609,0.0004466764,0.0002006935,0.0004031865,0.0002278693],"domain_scores_gemma":[0.9976617,0.0001875295,0.00132801,0.0005414767,0.0002104414,0.0000708236],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001638577,0.0001902412,0.004632475,0.00006015988,0.00161924,3.015449e-7,0.001555244,0.01400642,0.972392,0.0003970281,0.001076044,0.003907025],"study_design_scores_gemma":[0.001456851,0.0002075292,0.009996361,0.0004314537,0.005400683,0.0001029359,0.005695031,0.5577987,0.3875413,0.002326151,0.02798533,0.001057639],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954859,0.0001095143,0.002755059,0.001197918,0.000004730919,0.00007266732,0.00002838791,0.00003562802,0.0003101954],"genre_scores_gemma":[0.9880508,0.00009449786,0.01122229,0.0003541506,0.00006296228,0.000005625348,0.00001241293,0.00002707182,0.0001701631],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5848507,"threshold_uncertainty_score":0.3992846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003476225869508669,"score_gpt":0.2378775845538334,"score_spread":0.2344013586843247,"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."}}