{"id":"W2195255384","doi":"10.1021/acs.jctc.5b00662","title":"Grid-Based Backbone Correction to the ff12SB Protein Force Field for Implicit-Solvent Simulations","year":2015,"lang":"en","type":"article","venue":"Journal of Chemical Theory and Computation","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":83,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"National Institute of General Medical Sciences; European Molecular Biology Organization","keywords":"Force field (fiction); Grid; Computer science; Field (mathematics); Solvent; Computational science; Solvent models; Chemistry; Artificial intelligence; Mathematics; Geometry; 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":[0.0003280941,0.00006093428,0.00007849454,0.00002023677,0.00003910597,0.00001824296,0.00006242705,0.0000545494,0.000001019727],"category_scores_gemma":[0.0003673428,0.00004256082,0.00005521609,0.00004381811,0.00001622723,0.000005110713,0.00001854079,0.00006826757,2.190415e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001164422,"about_ca_system_score_gemma":0.00004657582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":8.333096e-7,"about_ca_topic_score_gemma":0.000001116048,"domain_scores_codex":[0.9995616,0.00004695405,0.0001670593,0.00007727763,0.00007666522,0.0000704187],"domain_scores_gemma":[0.99948,0.00009862545,0.0001124092,0.00005894891,0.0001839558,0.00006602221],"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":[0.002114999,0.00004067229,0.00003848251,0.00001562713,0.0000381631,4.856797e-7,0.00009699576,0.04986748,0.9260042,0.001242151,0.002702801,0.01783789],"study_design_scores_gemma":[0.001220126,0.001179022,0.00004795452,0.00004183136,0.00004053642,0.00004028966,0.00008390515,0.02711218,0.9106448,0.05589993,0.003555298,0.0001341533],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.503247,0.00006980502,0.4959012,0.0004301517,0.0001608194,0.0001573252,0.000003482872,0.000001811315,0.00002841283],"genre_scores_gemma":[0.9958163,8.112941e-7,0.003045957,0.0006405048,0.0004180402,0.000007842768,0.00002322664,0.000005595343,0.00004170132],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4928552,"threshold_uncertainty_score":0.173558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00997756352768413,"score_gpt":0.2814683119539501,"score_spread":0.271490748426266,"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."}}