{"id":"W2349329374","doi":"","title":"A System of Detecting and Processing Weak Magnetic Signals Based on STM32","year":2011,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Magnetic Field Sensors Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"STM32; Computer science; Interface (matter); Power consumption; SIGNAL (programming language); Data acquisition; Signal processing; Power (physics); Computer hardware; Digital signal processing; Physics; Telecommunications; Operating system","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006567375,0.0001041786,0.0001229164,0.0001039884,0.00004174587,0.00001527493,0.0001175575,0.00005859655,0.00001784223],"category_scores_gemma":[3.383545e-7,0.0001092516,0.00002303547,0.0001306132,0.00002700458,0.00002280536,0.00002032361,0.00008448786,0.000005297395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001563317,"about_ca_system_score_gemma":0.000006783947,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001459351,"about_ca_topic_score_gemma":0.000002014744,"domain_scores_codex":[0.9994613,0.00001180932,0.0002003092,0.0001494292,0.0000570073,0.0001201552],"domain_scores_gemma":[0.9996749,0.00003872972,0.00003616306,0.0001777466,0.00003583492,0.00003664018],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00000858425,0.00008866504,0.0002563206,0.001846722,0.00001293464,0.000001876432,0.001566487,0.0008533025,0.2426398,0.0008990638,0.0003438113,0.7514825],"study_design_scores_gemma":[0.0004125177,0.0002525761,0.002276439,0.0004436685,0.0000498138,0.00003224772,0.0002098371,0.4313574,0.5553206,0.0003126709,0.008857831,0.0004744517],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04705903,0.0002725864,0.9395939,0.00001169739,0.00000669064,0.0006513508,0.000004277021,0.0006635796,0.01173688],"genre_scores_gemma":[0.787899,0.000002209791,0.2118706,0.0000193773,0.00002044682,0.0001586459,6.957104e-7,0.00001721698,0.00001192199],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.751008,"threshold_uncertainty_score":0.4455153,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01000719634562626,"score_gpt":0.1953191613848513,"score_spread":0.1853119650392251,"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."}}