{"id":"W2325025647","doi":"10.1021/jp5063868","title":"Spies Within Metal-Organic Frameworks: Investigating Metal Centers Using Solid-State NMR","year":2014,"lang":"en","type":"article","venue":"The Journal of Physical Chemistry C","topic":"Advanced NMR Techniques and Applications","field":"Chemistry","cited_by":68,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Western University","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; Canada Research Chairs","keywords":"Density functional theory; Solid-state nuclear magnetic resonance; Metal-organic framework; Materials science; Nuclear magnetic resonance spectroscopy; Crystallography; Metal; Spectroscopy; Characterization (materials science); Computational chemistry; Chemistry; Chemical physics; Nanotechnology; Physical chemistry; Nuclear magnetic resonance; Organic chemistry; Physics; Metallurgy","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":[0.0002716657,0.0002140104,0.0003505397,0.0000120359,0.0001737625,0.00003461114,0.0004987497,0.00009966328,0.00007691274],"category_scores_gemma":[0.0002385977,0.0001487819,0.0002048801,0.000150901,0.0002498609,0.0001526165,0.0001157862,0.001130481,0.000003730285],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000750246,"about_ca_system_score_gemma":0.00004601614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004387383,"about_ca_topic_score_gemma":2.990373e-7,"domain_scores_codex":[0.9988164,0.0000260282,0.0004522098,0.0001434065,0.0003167,0.0002452518],"domain_scores_gemma":[0.998444,0.0002171442,0.0007081641,0.000357215,0.0001249437,0.0001484947],"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":[0.00001175918,0.00006762119,0.00001950879,0.00006028721,0.00007180894,0.000001267803,0.0003376043,0.005479503,0.9934741,0.0001048377,0.00003353456,0.0003381136],"study_design_scores_gemma":[0.0001777646,0.00001816058,0.000003794803,0.0001583822,0.0001630067,0.00007297855,0.0002708768,0.02538947,0.956506,0.01669125,0.0003812042,0.0001671639],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9826528,0.00005754998,0.01611597,0.0002631905,0.000009389286,0.00003137682,0.000006545967,0.00005178486,0.0008114151],"genre_scores_gemma":[0.9920611,0.00001056506,0.006946153,0.0001292759,0.0006685602,0.000002375459,0.000002763182,0.00003690941,0.0001423152],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03696821,"threshold_uncertainty_score":0.6067148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01607149444965505,"score_gpt":0.2910982468289279,"score_spread":0.2750267523792728,"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."}}