{"id":"W1994879087","doi":"10.1109/icsens.2013.6688221","title":"Multilayer Giant Magneto-Impedance sensor for low field sensing","year":2013,"lang":"en","type":"article","venue":"","topic":"Magnetic Field Sensors Techniques","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Microfabrication; Materials science; Wafer; Fabrication; Optoelectronics; Electrical impedance; Giant magnetoimpedance; Magnetic field; Magneto; Giant magnetoresistance; Electrical engineering; Electromagnetic coil; Engineering","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":[0.0002500384,0.0006197282,0.0005158827,0.000408916,0.0001859282,0.0004098534,0.0004460657,0.0004719212,0.0008741536],"category_scores_gemma":[0.0003896774,0.0002739433,0.0003304015,0.0002339848,0.0001804195,0.000656491,0.0003570612,0.0004535262,0.0005156614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003357455,"about_ca_system_score_gemma":0.0001421105,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004073595,"about_ca_topic_score_gemma":0.001017148,"domain_scores_codex":[0.9996271,0.00003638976,0.00001815636,0.00008526095,0.0001929003,0.00004014626],"domain_scores_gemma":[0.9997181,0.00005184273,0.00007910644,0.00003144882,0.00008523546,0.0000341573],"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":[0.00005028525,0.000009459921,0.0005436768,0.00007124559,0.00001110039,0.00002700129,0.00001636474,0.0001384307,0.9946004,0.00006362236,0.0001081763,0.004360242],"study_design_scores_gemma":[0.000007717631,0.0002484073,0.002559928,0.000006307742,0.00004166807,0.0002596305,0.00002273165,0.00360997,0.9905229,0.00004526323,0.002658201,0.00001726433],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8020712,0.007224205,0.18231,0.0004754374,0.0003691813,0.0001652911,0.0006739137,0.001764058,0.004946612],"genre_scores_gemma":[0.917542,0.001115738,0.07824051,0.0001006969,0.00005092198,0.00003710395,0.0002517989,0.00004545468,0.00261573],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008741536,"threshold_uncertainty_score":0.002924383,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007358647075320981,"score_gpt":0.2126085019566792,"score_spread":0.2052498548813583,"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."}}