{"id":"W1986837635","doi":"10.1103/physrevlett.98.097204","title":"Exchange Bias Dependence on Interface Spin Alignment in a<mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"inline\"><mml:msub><mml:mi>Ni</mml:mi><mml:mn>80</mml:mn></mml:msub><mml:msub><mml:mi>Fe</mml:mi><mml:mn>20</mml:mn></mml:msub><mml:mo>/</mml:mo><mml:mo stretchy=\"false\">(</mml:mo><mml:mi>Ni</mml:mi><mml:mo>,</mml:mo><mml:mi>Fe</mml:mi><mml:mo stretchy=\"false\">)</mml:mo><mml:mi mathvariant=\"normal\">O</mml:mi></mml:math>Thin Film","year":2007,"lang":"lv","type":"article","venue":"Physical Review Letters","topic":"Magnetic properties of thin films","field":"Physics and Astronomy","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Exchange bias; Antiferromagnetism; Condensed matter physics; Ferromagnetism; Magnetization; Materials science; Field (mathematics); Spin (aerodynamics); Transmission electron microscopy; Physics; Magnetic field; Nanotechnology; Magnetic anisotropy; Thermodynamics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0001056033,0.0001479652,0.0001283672,0.0002041992,0.0002642872,0.000374312,0.0003281081,0.0002177023,0.005585453],"category_scores_gemma":[0.0003835577,0.0001367588,0.00006151829,0.0002288475,0.0001615494,0.000279425,0.0001583912,0.0003347381,0.0005348927],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002816348,"about_ca_system_score_gemma":0.0001384644,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002773362,"about_ca_topic_score_gemma":0.004354811,"domain_scores_codex":[0.9999207,0.000005115427,0.000004741033,0.00001835197,0.0000250412,0.0000260321],"domain_scores_gemma":[0.9997633,0.00006452125,0.0000400316,0.00001710977,0.00008077934,0.00003417292],"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":[0.0002826882,0.00003619267,0.0009353185,0.00005904385,0.000008518844,0.00009690392,0.0000808988,0.0001359138,0.9954597,0.000184588,0.0004321749,0.002288088],"study_design_scores_gemma":[0.00002022041,0.0001460154,0.009826409,0.000009437809,0.00001664827,0.00005777534,0.0001115632,0.002127476,0.9862301,0.0000382064,0.001408163,0.00000792735],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996475,0.000201267,0.000464175,0.00005731897,0.00001857378,0.000004943473,0.0002510313,0.00008176963,0.002445865],"genre_scores_gemma":[0.9974584,0.0001549042,0.0004793535,0.00002315296,0.000005207923,0.000007525408,0.0002831501,0.00003105331,0.001557222],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005585453,"threshold_uncertainty_score":0.01868522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02110283964358483,"score_gpt":0.2543959390655937,"score_spread":0.2332930994220088,"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."}}