{"id":"W2160621862","doi":"10.5539/mas.v7n11p26","title":"Microtesla Sensitivity and Noise of a Triple Collector Magnetotransistor","year":2013,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Magnetic Field Sensors Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sensitivity (control systems); Noise (video); Materials science; Substrate (aquarium); Doping; Base (topology); Nuclear magnetic resonance; Electron; Acoustics; Optoelectronics; Analytical Chemistry (journal); Physics; Chemistry; Computer science; Electronic engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007304612,0.0002392118,0.0003459868,0.000275439,0.0002115371,0.0005093063,0.0003754828,0.0007642618,0.0006052422],"category_scores_gemma":[0.002169807,0.0002183755,0.0001595389,0.0001693486,0.0004542726,0.0004439032,0.0003620148,0.0004513907,0.0002432384],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004106072,"about_ca_system_score_gemma":0.0001550604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004282778,"about_ca_topic_score_gemma":0.0006246605,"domain_scores_codex":[0.9989806,0.0001619088,0.00003687021,0.0002289327,0.0005074327,0.00008416463],"domain_scores_gemma":[0.9976518,0.001199178,0.000295595,0.0001655387,0.0005769432,0.0001111365],"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":[0.000104109,0.00001068253,0.0006796633,0.00003321477,0.000008324126,0.00004746231,0.00007526804,0.0002268898,0.9971721,0.0001284868,0.00003463378,0.001479251],"study_design_scores_gemma":[0.000008145987,0.0006438477,0.005446475,0.00001348941,0.00002057571,0.0003139932,0.00007572693,0.008293401,0.9843556,0.00008692782,0.0007198975,0.0000219174],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9780552,0.000990421,0.01860669,0.0002045643,0.00009634445,0.00002257069,0.0001239478,0.0002073176,0.001693107],"genre_scores_gemma":[0.9932966,0.0001639195,0.005199175,0.00004725031,0.00003357855,0.00001694365,0.00005535644,0.00001423269,0.001172909],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007642618,"threshold_uncertainty_score":0.003863037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004541333649579555,"score_gpt":0.172415329210053,"score_spread":0.1678739955604735,"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."}}