{"id":"W4297537054","doi":"10.1016/j.matcom.2022.09.015","title":"Numerical methods, energy conservation, and a new method for particle motion in magnetic fields","year":2022,"lang":"en","type":"article","venue":"Mathematics and Computers in Simulation","topic":"Particle accelerators and beam dynamics","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Energy conservation; Conservation of energy; Position (finance); Harmonic oscillator; Numerical integration; Simple (philosophy); Point (geometry); Energy (signal processing); Field (mathematics); Simple harmonic motion; Particle (ecology); Computer science; Magnetic field; Classical mechanics; Physics; Mathematics; Mathematical analysis; Geometry; Quantum mechanics; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002289374,0.00005826273,0.0001082735,0.00004550963,0.00003435888,0.00002496337,0.00003008468,0.00002360251,0.000004749415],"category_scores_gemma":[0.00001635446,0.00006421618,0.00001110883,0.0001416039,0.000004635695,0.00004971064,0.00002427123,0.0000452802,5.041072e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000256229,"about_ca_system_score_gemma":0.000004365972,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005124774,"about_ca_topic_score_gemma":0.00001451445,"domain_scores_codex":[0.9995512,0.00003334662,0.0001887074,0.00008789667,0.00004808262,0.00009081508],"domain_scores_gemma":[0.9995689,0.0003184477,0.00002047619,0.00005724033,0.000007910631,0.00002696356],"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":[0.000004877847,0.00002911884,0.001263965,0.00003561348,0.00000292889,5.340895e-7,0.0008166246,0.8957848,0.000225266,0.007824699,0.00002492031,0.09398668],"study_design_scores_gemma":[0.0004149263,0.00004143542,0.001676457,0.000006492492,0.000004245708,0.000001951732,0.00006182196,0.9623821,0.00009962677,0.03507485,0.0001669025,0.00006912446],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2809559,0.0000936088,0.7187178,0.00008365094,0.00004169717,0.0000793763,6.528025e-7,0.00001807597,0.000009179196],"genre_scores_gemma":[0.6831834,0.000004238161,0.3167014,0.00007098055,0.000008792872,0.00001886043,0.00000223507,0.000006158526,0.000004021787],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4022274,"threshold_uncertainty_score":0.261866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02872205822722908,"score_gpt":0.3051520712959835,"score_spread":0.2764300130687544,"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."}}