{"id":"W4388870365","doi":"10.1021/acs.jpcb.3c06662","title":"OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials","year":2023,"lang":"en","type":"article","venue":"The Journal of Physical Chemistry B","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":469,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Cancer Institute; National Heart, Lung, and Blood Institute; Horizon 2020 Framework Programme; EMD Serono; National Institutes of Health; National Institute of General Medical Sciences; Ministerio de Ciencia e Innovación; Agencia Estatal de Investigación; XtalPi; Vir Biotechnology; Relay Therapeutics; Parker Institute for Cancer Immunotherapy; Entasis Therapeutics; Chan Zuckerberg Initiative; New York University; Cycle for Survival; Merck KGaA; Engineering and Physical Sciences Research Council; York University; AstraZeneca; Memorial Sloan-Kettering Cancer Center; Damon Runyon Cancer Research Foundation; National Science Foundation","keywords":"Computer science; Molecular dynamics; CUDA; Interface (matter); Artificial intelligence; Computational science; Machine learning; Parallel computing; Chemistry; Computational chemistry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007211110089778363,"score_gpt":0.2635682370907619,"score_spread":0.2563571270009836,"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."}}