{"id":"W3046558244","doi":"10.1109/tmag.2020.3013147","title":"Optimization of Magnetoelastic Torquemeter Designs","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Magnetics","topic":"Magnetic Properties and Applications","field":"Materials Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Mitacs","keywords":"Magnetometer; Offset (computer science); Physics; Magnetic field; Magnetization; Magnetostriction; Isotropy; Ferromagnetism; Waveform; Nuclear magnetic resonance; SIGNAL (programming language); RADIUS; Electromagnet; Magnet; Condensed matter physics; Optics; Computer science; Voltage","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":[0.0008707917,0.001332138,0.0008703309,0.000627659,0.000273422,0.0009682476,0.001021511,0.0009633427,0.001456011],"category_scores_gemma":[0.002841787,0.0006433253,0.0004222343,0.0005459025,0.0002950499,0.0007272897,0.0004517725,0.0004478814,0.0009710005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00117076,"about_ca_system_score_gemma":0.0007269214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007182638,"about_ca_topic_score_gemma":0.001110473,"domain_scores_codex":[0.9993922,0.00007596886,0.00004654874,0.000152925,0.0002451673,0.00008717525],"domain_scores_gemma":[0.9990075,0.0002706271,0.000209221,0.0001437465,0.0003113271,0.00005755503],"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":[0.0005877119,0.0003231649,0.002756588,0.0008108644,0.00008208683,0.0001992236,0.0001104001,0.2157444,0.7221232,0.004761542,0.001621586,0.0508792],"study_design_scores_gemma":[0.0002362977,0.001350805,0.004824074,0.00005641632,0.0001367392,0.0003082326,0.00008244583,0.5325156,0.4448799,0.001568525,0.01395022,0.00009075306],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5922418,0.001331413,0.3876681,0.0005756952,0.0001508397,0.000568718,0.0008658324,0.002127896,0.01446962],"genre_scores_gemma":[0.8162137,0.0004129609,0.1799581,0.00005007318,0.00001784961,0.000391457,0.0003477843,0.0001657062,0.002442442],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001456011,"threshold_uncertainty_score":0.008494437,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04144499488258564,"score_gpt":0.2302226682911248,"score_spread":0.1887776734085392,"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."}}