{"id":"W2992594808","doi":"10.1080/08927022.2019.1697439","title":"The effect of many-body potential type and parameterisation on the accuracy of predicting mechanical properties of aluminium using molecular dynamics","year":2019,"lang":"en","type":"article","venue":"Molecular Simulation","topic":"Microstructure and mechanical properties","field":"Materials Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Embedded atom model; ReaxFF; Interatomic potential; Molecular dynamics; Aluminium; Force field (fiction); Materials science; Atom (system on chip); Atomic units; Ultimate tensile strength; Thermodynamics; Chemistry; Computational chemistry; Metallurgy; Physics","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":[0.0005436955,0.0001069291,0.0001912444,0.0000270889,0.00006549033,0.00002570172,0.0001410534,0.00007593345,0.000008927016],"category_scores_gemma":[0.0006202936,0.00005701583,0.00005177502,0.00009374547,0.00008505625,0.00006809281,0.00008452419,0.00007307733,0.000001337389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002128017,"about_ca_system_score_gemma":0.00002745589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003505901,"about_ca_topic_score_gemma":5.249998e-7,"domain_scores_codex":[0.9988407,0.0002823523,0.0003263085,0.0001611448,0.0002735672,0.0001158586],"domain_scores_gemma":[0.999073,0.0002037924,0.0002908923,0.0002791181,0.000136522,0.00001663422],"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":[0.0003682863,0.000007116009,0.0000493805,0.00009155329,0.00001566235,4.036926e-7,0.00008378414,0.04655914,0.9509522,0.001520981,1.533113e-7,0.0003513355],"study_design_scores_gemma":[0.000148391,0.000327931,0.00005082631,0.0000588904,0.00003088193,9.61619e-7,0.00003016121,0.3913129,0.6078529,0.0001486814,0.000001014294,0.00003646731],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9876786,0.0001244477,0.01142641,0.00003014659,0.0001745043,0.0005396892,0.000003990044,0.000008657399,0.00001356682],"genre_scores_gemma":[0.9997878,0.000002947774,0.0001610268,0.00001715391,0.000008930864,0.000002640958,0.000003184339,0.00001240308,0.000003882352],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3447537,"threshold_uncertainty_score":0.2325038,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01081679685091625,"score_gpt":0.2447178544913293,"score_spread":0.2339010576404131,"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."}}