{"id":"W4414353089","doi":"10.1088/1361-6544/ae0402","title":"Self-consistent Coulomb interactions for machine learning interatomic potentials","year":2025,"lang":"en","type":"article","venue":"Nonlinearity","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Air Force Research Laboratory; Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada","keywords":"Complement (music); Locality; Coulomb; Energy (signal processing); Scheme (mathematics); Charge (physics)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001494189,0.0003731861,0.0007319438,0.0007089475,0.0006545126,0.0008188995,0.001879494,0.001320797,0.002476988],"category_scores_gemma":[0.004335469,0.0003140731,0.0004625476,0.0005778634,0.001825139,0.001544592,0.001180079,0.001027911,0.0002836009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001141461,"about_ca_system_score_gemma":0.0009524091,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002560197,"about_ca_topic_score_gemma":0.002328391,"domain_scores_codex":[0.9995657,0.0002242405,0.00001822953,0.0000265477,0.0001226133,0.00004273081],"domain_scores_gemma":[0.9984895,0.00105351,0.00009811949,0.0001293243,0.0001467126,0.00008278959],"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":[0.00001863958,0.00003304466,0.0001820367,0.00003483083,0.00001310521,0.00005041603,0.00003329764,0.8280804,0.0008451688,0.1670351,0.0003265328,0.003347311],"study_design_scores_gemma":[0.000002478684,0.000002915064,0.00001253506,0.000002035871,4.115054e-7,0.000002055736,0.00000238591,0.9862621,0.00007761387,0.01356965,0.00006410755,0.000001717928],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2095291,0.0005170495,0.7750013,0.001572318,0.0001117135,0.0000958696,0.0000871831,0.0003196195,0.01276568],"genre_scores_gemma":[0.9540845,0.0001742251,0.03956614,0.0002280122,0.00005689111,0.0001434384,0.0000658758,0.0001081715,0.005572704],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002560197,"threshold_uncertainty_score":0.008286357,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0126886026030628,"score_gpt":0.309232738079337,"score_spread":0.2965441354762742,"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."}}