{"id":"W4386758353","doi":"10.1021/acs.jpca.3c04558","title":"Accurate Potential Energy Surfaces Using Atom-Centered Potentials and Minimal High-Level Data","year":2023,"lang":"en","type":"article","venue":"The Journal of Physical Chemistry A","topic":"Advanced Chemical Physics Studies","field":"Physics and Astronomy","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"European Regional Development Fund; European Commission; British Columbia Knowledge Development Fund; Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation; Gobierno del Principado de Asturias","keywords":"Hartree; Chemistry; Density functional theory; Atom (system on chip); Approximation error; Computational chemistry; Potential energy; Representation (politics); Mean absolute percentage error; Physics; Atomic physics; Mathematics; Computer science; Applied mathematics; Mean squared error; Statistics","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":[0.0007773779,0.0006835906,0.0007373077,0.0007471809,0.0006608281,0.001047247,0.001550403,0.0009101575,0.003802395],"category_scores_gemma":[0.002121308,0.0003350536,0.0006252141,0.0009483371,0.0004442957,0.001149528,0.0008166567,0.001072666,0.001105267],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006098993,"about_ca_system_score_gemma":0.00118904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001853553,"about_ca_topic_score_gemma":0.002243348,"domain_scores_codex":[0.9995027,0.0001211621,0.00002067026,0.00003437386,0.0002781535,0.0000430855],"domain_scores_gemma":[0.9994556,0.0002505113,0.00002728474,0.0001501401,0.0001003273,0.00001617459],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004386265,0.00006555791,0.0005473914,0.0002321656,0.0000289998,0.0001308451,0.00007235861,0.8601121,0.007588767,0.09806564,0.001826978,0.03128539],"study_design_scores_gemma":[0.00001081666,0.00002684741,0.000125992,0.00001827557,0.000005786702,0.00002194654,0.00002016986,0.9735344,0.002589046,0.02120704,0.002428519,0.00001117133],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09345947,0.0007570658,0.8811023,0.0003363028,0.0001042754,0.0001085222,0.0009360049,0.00121475,0.02198133],"genre_scores_gemma":[0.6305144,0.0009705984,0.3619324,0.0001066259,0.00003140836,0.0004781245,0.002108603,0.000467807,0.003390035],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003802395,"threshold_uncertainty_score":0.01272029,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05332828684384816,"score_gpt":0.3033779593582038,"score_spread":0.2500496725143556,"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."}}