{"id":"W2761605604","doi":"10.1021/acs.jctc.7b00380","title":"Accurate Prediction of NMR Chemical Shifts in Macromolecular and Condensed-Phase Systems with the Generalized Energy-Based Fragmentation Method","year":2017,"lang":"en","type":"article","venue":"Journal of Chemical Theory and Computation","topic":"Advanced Chemical Physics Studies","field":"Physics and Astronomy","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Education and Child Care","funders":"Ministry of Education of the People's Republic of China; Natural Science Foundation of Jiangsu Province; National Natural Science Foundation of China","keywords":"Polarizable continuum model; Electromagnetic shielding; Chemical shift; Density functional theory; Chemistry; Molecular dynamics; Quantum chemistry; Solvent models; Computational chemistry; Nuclear magnetic resonance spectroscopy; Statistical physics; Solvent effects; Molecule; Molecular physics; Physical chemistry; Supramolecular chemistry; Physics; Quantum mechanics; Solvent; Solvation; Organic chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002863003,0.0001032279,0.0002427679,0.00002451656,0.00007966474,0.00005384537,0.00008299733,0.00003009402,0.000001840811],"category_scores_gemma":[0.00001859432,0.00006926701,0.0000418987,0.00003813497,0.0001880968,0.000134173,0.000029709,0.0001304163,4.000892e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001478659,"about_ca_system_score_gemma":0.00002179837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006652827,"about_ca_topic_score_gemma":5.128447e-8,"domain_scores_codex":[0.999279,0.0001069802,0.0002779663,0.0001074918,0.0001441053,0.00008448545],"domain_scores_gemma":[0.9989321,0.0002803574,0.0005598696,0.00008062055,0.0001056925,0.00004140858],"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":[0.00142294,0.0002061283,0.00041553,0.00005837228,0.0002035089,0.000004775015,0.0004838074,0.01172898,0.941626,0.03498791,0.00002626272,0.008835832],"study_design_scores_gemma":[0.006391078,0.0001610655,0.0002245447,0.0001918444,0.0001564556,0.00000791162,0.0004443407,0.03523901,0.7099513,0.2470527,0.00002342132,0.0001562851],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6933843,0.00008861704,0.3063103,0.00007643365,0.00001751973,0.00005025956,0.000007824507,0.000001959846,0.0000626898],"genre_scores_gemma":[0.9976796,0.000002758376,0.002170821,0.00002507286,0.00009452869,0.000006314565,0.00001128117,0.000007621782,0.000002029845],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3042952,"threshold_uncertainty_score":0.2824627,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01321714106098192,"score_gpt":0.3081053037036139,"score_spread":0.294888162642632,"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."}}