{"id":"W4385738720","doi":"10.1137/22m152267x","title":"A Framework for a Generalization Analysis of Machine-Learned Interatomic Potentials","year":2023,"lang":"en","type":"article","venue":"Multiscale Modeling and Simulation","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Engineering and Physical Sciences Research Council; Shanghai Jiao Tong University; Leverhulme Trust","keywords":"Generalization; Computer science; Point (geometry); Cover (algebra); Space (punctuation); Statistical physics; Algorithm; Current (fluid); Theoretical computer science; Physics; Mathematics; Mathematical analysis; Geometry; Mechanical engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005702443,0.00125377,0.001130869,0.001436566,0.0005613054,0.001284706,0.002748707,0.001609368,0.002073253],"category_scores_gemma":[0.01999365,0.0005680792,0.00140087,0.001068591,0.002573294,0.002897095,0.003018994,0.004238052,0.0004029396],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001964145,"about_ca_system_score_gemma":0.001088768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003071218,"about_ca_topic_score_gemma":0.002220974,"domain_scores_codex":[0.998032,0.001001465,0.00008840588,0.0003161465,0.0004728843,0.00008901891],"domain_scores_gemma":[0.9910034,0.006177459,0.0007484163,0.001312946,0.0005998761,0.0001578835],"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":[0.00002235757,0.00002926371,0.001057003,0.0001155906,0.0000977078,0.00006400956,0.0000900694,0.5950257,0.0007477937,0.3784021,0.001376882,0.02297162],"study_design_scores_gemma":[0.000002351819,0.00001844154,0.00016286,0.00001852944,0.000005773248,0.00001545944,0.00000588129,0.8599659,0.0001512842,0.1387654,0.0008822372,0.000005865836],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003335078,0.0003278391,0.9946395,0.0004294197,0.00002331436,0.00002564934,0.0001005569,0.0001204461,0.0009982184],"genre_scores_gemma":[0.5736807,0.00228745,0.4167394,0.0008653839,0.0005137207,0.0006913276,0.001093964,0.0003167865,0.003811277],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005702443,"threshold_uncertainty_score":0.03015774,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04638359074766482,"score_gpt":0.3562099343743991,"score_spread":0.3098263436267343,"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."}}