{"id":"W1931956593","doi":"10.1109/solsen.1992.228282","title":"A vertical Hall magnetic field sensor using CMOS-compatible micromachining techniques","year":2003,"lang":"en","type":"article","venue":"","topic":"Magnetic Field Sensors Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Surface micromachining; Hall effect sensor; Magnetic field; CMOS; Hall effect; Bulk micromachining; Materials science; Field (mathematics); Uniqueness; Optoelectronics; Electronic engineering; Electrical engineering; Physics; Engineering; Magnet; Fabrication","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001306118,0.0002236242,0.0002287087,0.0001256252,0.00005542331,0.00005335056,0.0001425668,0.0001935632,0.001527012],"category_scores_gemma":[0.00009845335,0.0002258731,0.0000693035,0.0001557803,0.00003216575,0.00007370616,0.00002612718,0.0002924342,0.00002949532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004074461,"about_ca_system_score_gemma":0.00001475773,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002046304,"about_ca_topic_score_gemma":0.00002219998,"domain_scores_codex":[0.9988996,0.00004867688,0.0002977441,0.0002179219,0.0001451631,0.0003908648],"domain_scores_gemma":[0.9993761,0.0001383754,0.00001101702,0.0003457175,0.00003237561,0.00009646086],"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":[0.000009677052,0.00005813462,0.001349865,0.000146298,0.00002439624,0.00004311214,0.0003242795,0.000189061,0.9726613,0.006492164,0.009757309,0.008944395],"study_design_scores_gemma":[0.00012491,0.000202649,0.0000819447,0.00005680892,0.00001918552,0.00007036874,0.0000511604,0.02031054,0.9699047,0.0006509773,0.008165958,0.000360853],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6563268,0.0002657637,0.07071816,0.0001194699,0.0001573479,0.0003934819,0.000001076534,0.002780204,0.2692377],"genre_scores_gemma":[0.790378,0.00001701532,0.2088206,0.0003492404,0.00003840225,0.00001311,7.986178e-7,0.00004432164,0.0003385278],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2688992,"threshold_uncertainty_score":0.9993857,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01227417874103994,"score_gpt":0.2342233832561797,"score_spread":0.2219492045151397,"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."}}