{"id":"W2912317159","doi":"10.1063/1.5078687","title":"Molecular force fields with gradient-domain machine learning: Construction and application to dynamics of small molecules with coupled cluster forces","year":2019,"lang":"en","type":"article","venue":"The Journal of Chemical Physics","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":113,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"H2020 European Research Council; Institute for Information and Communications Technology Promotion; Banting and Best Diabetes Centre, University of Toronto; Bundesministerium für Bildung und Forschung; Iran Telecommunication Research Center; Berlin Center for Machine Learning; Deutsche Forschungsgemeinschaft; National Science Foundation","keywords":"Molecular dynamics; Cluster (spacecraft); Small molecule; Ab initio; Force field (fiction); Work (physics); Molecule; Dynamics (music); Coupled cluster","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005481484,0.0004622948,0.0005147412,0.0005132109,0.0004408911,0.0003506266,0.00127214,0.0008821919,0.001701046],"category_scores_gemma":[0.001142563,0.0003138952,0.0004485689,0.000596714,0.0004637281,0.0003705568,0.000680177,0.0008379176,0.0004209924],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008386964,"about_ca_system_score_gemma":0.0009891674,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004407214,"about_ca_topic_score_gemma":0.003294498,"domain_scores_codex":[0.9998341,0.00004631183,0.000005475151,0.00001782358,0.00007912256,0.00001713391],"domain_scores_gemma":[0.9998171,0.00006419861,0.00001675377,0.000038216,0.00003900253,0.00002469896],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003567682,0.00006507765,0.000411274,0.00009261289,0.00002453503,0.00008855423,0.00004181885,0.9101228,0.008869395,0.04783178,0.001378694,0.03103774],"study_design_scores_gemma":[0.000008602145,0.000006273809,0.00003843958,0.000002164495,7.584315e-7,0.000005289883,0.000001344556,0.9964007,0.0008705289,0.001806734,0.0008553301,0.000003756935],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08026931,0.0004074291,0.9097267,0.0004206567,0.0001094513,0.0002726868,0.0004244422,0.0008954991,0.00747376],"genre_scores_gemma":[0.3732508,0.0003586975,0.6219797,0.0001389582,0.0000451886,0.0007863743,0.0005712841,0.0003349663,0.002534027],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004407214,"threshold_uncertainty_score":0.008763134,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002944313012909453,"score_gpt":0.2018545748565729,"score_spread":0.1989102618436634,"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."}}