{"id":"W4386965784","doi":"10.26434/chemrxiv-2023-lh7bq-v2","title":"Martini 3 Coarse-Grained Force Field for cholesterol","year":2023,"lang":"en","type":"preprint","venue":"ChemRxiv","topic":"Lipid Membrane Structure and Behavior","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Lawrence Livermore National Laboratory; Alliance de recherche numérique du Canada; Centre National de la Recherche Scientifique; National Supercomputing Center, Korea Institute of Science and Technology Information; Grand Équipement National De Calcul Intensif; Max-Planck-Gesellschaft; Canada Research Chairs; Laboratory Directed Research and Development; Fundação para a Ciência e a Tecnologia; U.S. Department of Energy","keywords":"Rigidity (electromagnetism); Force balance; Cholesterol; Permeability (electromagnetism); Force field (fiction); Nanotechnology; Lipid bilayer; Chemistry; Computer science; Biophysics; Materials science; Membrane; Mechanics; Composite material; Physics; Biochemistry; Artificial intelligence; Biology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001430061,0.0003135636,0.0002958018,0.00004431266,0.00006413931,0.00005016167,0.0004067099,0.0006752281,0.00002955566],"category_scores_gemma":[0.0001650008,0.0002976642,0.000344968,0.00004377155,0.0000445052,0.000001682747,0.0004724491,0.000253073,0.00002022276],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001023469,"about_ca_system_score_gemma":0.00009860688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001348104,"about_ca_topic_score_gemma":0.00002847389,"domain_scores_codex":[0.9985517,0.00001708818,0.0002853778,0.0006844408,0.0001118477,0.0003495848],"domain_scores_gemma":[0.9988554,0.00002956086,0.0001432237,0.0007689535,0.0001017674,0.0001011321],"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":[0.00008916626,0.00002890812,0.0007444134,0.0003346906,0.00009032669,0.000002583988,0.00004120656,0.0000204985,0.9646457,0.00001728089,0.03188197,0.002103255],"study_design_scores_gemma":[0.0006489063,0.0001500915,0.0005948648,0.00005101431,0.00009792151,0.000004429187,0.00002092044,0.00002982298,0.9570441,0.000283714,0.0407063,0.0003678894],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9917786,0.0001057681,0.002216024,0.001300496,0.002439344,0.001096693,0.00007594679,0.0001166252,0.0008705566],"genre_scores_gemma":[0.9700042,0.00006548021,0.001116205,0.001227314,0.002484562,0.00054769,0.00169921,0.0001144674,0.02274086],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0218703,"threshold_uncertainty_score":0.9999475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02688520047990929,"score_gpt":0.2939120788559905,"score_spread":0.2670268783760812,"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."}}