{"id":"W4230792830","doi":"10.5194/gi-2018-29","title":"A Hybrid Fluxgate and Search Coil Magnetometer Concept Using a Racetrack Core","year":2018,"lang":"en","type":"preprint","venue":"","topic":"Magnetic Field Sensors Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Space Agency; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; University of Iowa","keywords":"Fluxgate compass; Magnetometer; Electromagnetic coil; Sensitivity (control systems); Search coil; Electrical engineering; Boom; Sense (electronics); Computer science; Engineering; Electronic engineering; Acoustics; Magnetic field; Physics; Magnetic flux","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":[0.0009166539,0.000551035,0.000769073,0.0005516354,0.0002832929,0.001004757,0.001600856,0.00120505,0.001669299],"category_scores_gemma":[0.0008831603,0.0003564022,0.0002764777,0.0004035512,0.0008615132,0.002345231,0.001098404,0.0005123629,0.001120455],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005215287,"about_ca_system_score_gemma":0.0004801922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001618631,"about_ca_topic_score_gemma":0.0003809771,"domain_scores_codex":[0.9992585,0.0001251991,0.0000311845,0.0001981766,0.0003264645,0.00006038088],"domain_scores_gemma":[0.9991253,0.0001388869,0.0002172656,0.0001233131,0.0002920912,0.0001032023],"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":[0.0008246756,0.0001168492,0.001335271,0.000443466,0.00005280232,0.0002033519,0.0001592683,0.002230458,0.9335737,0.01433115,0.002220852,0.0445081],"study_design_scores_gemma":[0.0001087527,0.002408469,0.002666656,0.00004716803,0.00006535991,0.001271242,0.0001040993,0.0401095,0.9096448,0.002854658,0.04063016,0.00008910506],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2507241,0.001237453,0.7255254,0.0008616174,0.0009253932,0.0005810926,0.0004185806,0.002673991,0.01705234],"genre_scores_gemma":[0.7354655,0.0002484754,0.25531,0.0003529774,0.00009518764,0.0002565183,0.0002227924,0.00008168919,0.007966825],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001669299,"threshold_uncertainty_score":0.0055843,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04313568479744846,"score_gpt":0.2851905018887209,"score_spread":0.2420548170912725,"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."}}