{"id":"W3118689300","doi":"10.1103/physrevlett.126.017203","title":"Configurable Artificial Spin Ice with Site-Specific Local Magnetic Fields","year":2021,"lang":"en","type":"article","venue":"Physical Review Letters","topic":"Advanced Condensed Matter Physics","field":"Physics and Astronomy","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; Molecular Engineering and Sciences Institute, University of Washington; University of Glasgow; Carnegie Trust for the Universities of Scotland; University of Manitoba; University of Washington; Washington Research Foundation; Clean Energy Institute; National Institutes of Health; National Science Foundation","keywords":"Spin ice; Nanomagnet; Condensed matter physics; Antiferromagnetism; Ferromagnetism; Ground state; Physics; Monte Carlo method; Magnetic field; Square lattice; Ising model; Magnetization; Magnetic monopole; Quantum mechanics","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":[0.00004361088,0.0002736609,0.0004745214,0.00001420397,0.00008451854,0.00005736919,0.0001677778,0.000009357575,0.0009394239],"category_scores_gemma":[0.00000310222,0.0002407926,0.0001868878,0.0002825586,0.000128806,0.000128664,0.00005584932,0.0003441952,0.0007550496],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002660899,"about_ca_system_score_gemma":0.00004748207,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001653899,"about_ca_topic_score_gemma":0.000002259485,"domain_scores_codex":[0.9985229,0.00007766456,0.0002533044,0.0004694752,0.0002774395,0.0003992202],"domain_scores_gemma":[0.999043,0.0001141839,0.0001029178,0.0005283162,0.00008809604,0.0001234591],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000111479,0.001731401,0.0006660922,0.002110648,0.0003128118,0.0004053771,0.0006001593,0.006288665,0.3662707,0.1329238,0.09215602,0.3964229],"study_design_scores_gemma":[0.003506017,0.0007534703,0.001106316,0.007618486,0.001268314,0.0000506758,0.0004947362,0.004745589,0.2273767,0.05989845,0.688013,0.005168237],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5684325,0.009731543,0.3691611,0.03065201,0.0004142521,0.00125428,0.00009351877,0.0002161989,0.02004465],"genre_scores_gemma":[0.9833011,0.0001264485,0.0006516603,0.01482172,0.000724335,0.00007960401,0.00008190527,0.00004538014,0.0001678383],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.595857,"threshold_uncertainty_score":0.9999738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01267668680011722,"score_gpt":0.2600695507888746,"score_spread":0.2473928639887574,"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."}}