{"id":"W2990490114","doi":"10.1088/1361-648x/ab8c8d","title":"Coarse-graining in micromagnetic simulations of dynamic hysteresis loops","year":2020,"lang":"en","type":"article","venue":"Journal of Physics Condensed Matter","topic":"Magnetic properties of thin films","field":"Physics and Astronomy","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland; Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Scaling; Micromagnetics; Hysteresis; Dynamic scaling; Renormalization group; Magnetic hysteresis; Loop (graph theory); Invariant (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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00008805032,0.0001449243,0.0003775859,0.00006251625,0.00002407931,0.00003163231,0.0002659504,0.00002969762,0.001548863],"category_scores_gemma":[0.00001245389,0.0001336652,0.0001611331,0.0001537254,0.00006885824,0.0001606401,0.0000692945,0.0002674283,0.00005139334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001654777,"about_ca_system_score_gemma":0.00006730482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002403563,"about_ca_topic_score_gemma":0.000001316432,"domain_scores_codex":[0.9988122,0.00006477892,0.0006114618,0.0001244323,0.0002073283,0.0001798117],"domain_scores_gemma":[0.9990299,0.00009059067,0.000488008,0.0001605388,0.0001465737,0.00008444107],"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":[0.0002762926,0.0005362086,0.05419179,0.0003208634,0.0003655972,0.00002624022,0.007219431,0.008807479,0.9004496,0.0008112887,0.009122944,0.01787221],"study_design_scores_gemma":[0.04170949,0.005375039,0.1128592,0.003410996,0.00199224,0.00006821281,0.01289835,0.3491372,0.3646472,0.09698582,0.006097566,0.004818615],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942514,0.00006689112,0.002219857,0.001699822,0.0001092494,0.0001133619,0.00003107596,0.00000424276,0.001504065],"genre_scores_gemma":[0.9968786,4.875851e-7,0.002195665,0.0005603333,0.0001346941,0.00000114141,0.000004520026,0.00002346052,0.0002010936],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5358025,"threshold_uncertainty_score":0.9993638,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01519415678568501,"score_gpt":0.234232643985286,"score_spread":0.219038487199601,"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."}}