{"id":"W2909749882","doi":"10.1016/j.jmmm.2019.01.037","title":"In situ determination of the anisotropy field in ferromagnetic films using magnetic susceptibility measurements by MOKE","year":2019,"lang":"en","type":"article","venue":"Journal of Magnetism and Magnetic Materials","topic":"Magnetic properties of thin films","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Condensed matter physics; Anisotropy; Kerr effect; Materials science; Magnetometer; Ferromagnetism; Magnetic anisotropy; Bilayer; Thin film; Magnetic field; Magneto-optic Kerr effect; Coupling (piping); Field (mathematics); Magnetic susceptibility; In situ; Nuclear magnetic resonance; Magnetization; Optics; Physics; Nanotechnology; Chemistry; Composite material","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":[0.0002176096,0.0002861387,0.0002897429,0.0004021642,0.0005606485,0.0004555291,0.0003698945,0.0005121224,0.001577569],"category_scores_gemma":[0.0004044219,0.0003207395,0.0001353846,0.0003174507,0.0003911626,0.0003529605,0.0002439591,0.0007116344,0.0002735779],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001768446,"about_ca_system_score_gemma":0.0001088596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001551322,"about_ca_topic_score_gemma":0.003854856,"domain_scores_codex":[0.9998077,0.00004887863,0.00001009493,0.00005406859,0.00004264238,0.00003667029],"domain_scores_gemma":[0.9997956,0.00009563936,0.00002811004,0.0000277111,0.00004019809,0.00001273536],"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":[0.00006229301,0.000007319334,0.0002381417,0.0000282405,0.000005802563,0.00002686765,0.00003191869,0.00001806484,0.9984849,0.0001049021,0.00003710958,0.0009543864],"study_design_scores_gemma":[0.000007698211,0.00003914857,0.002387542,0.000004509535,0.0000112706,0.00009808724,0.00005304354,0.0005220582,0.9959429,0.00003821403,0.0008908785,0.000004638417],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9767352,0.001446,0.01757856,0.000201039,0.00007205723,0.00003111756,0.0002870422,0.0001455181,0.003503571],"genre_scores_gemma":[0.989317,0.0004399245,0.007891746,0.00004069754,0.0000151607,0.00001981466,0.0001152541,0.00002653169,0.002133816],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001577569,"threshold_uncertainty_score":0.005277455,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0126688313150534,"score_gpt":0.2352426663322612,"score_spread":0.2225738350172078,"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."}}