{"id":"W4312499318","doi":"10.1109/tbcas.2022.3230668","title":"A High Dynamic Range Dual 8×16 Capacitive Sensor Array for Life Science Applications","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Biomedical Circuits and Systems","topic":"Analytical Chemistry and Sensors","field":"Chemical Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Capacitive sensing; CMOS; Multiplexing; Dynamic range; Capacitance; Calibration; Electronic engineering; Chip; Materials science; Computer science; Electrical engineering; Engineering; Electrode; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002859203,0.0006232962,0.0004995641,0.0003310807,0.0002020793,0.0005116733,0.001034156,0.0006763361,0.002723341],"category_scores_gemma":[0.0003412607,0.0003625643,0.0002685502,0.0003243434,0.000144438,0.0008985192,0.0005629435,0.000441177,0.001330534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000255742,"about_ca_system_score_gemma":0.0003924286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002077565,"about_ca_topic_score_gemma":0.0006512741,"domain_scores_codex":[0.9996112,0.00002738425,0.00001863878,0.0001258199,0.0001834875,0.00003348025],"domain_scores_gemma":[0.9998168,0.00003411698,0.00003180714,0.00001816084,0.00007043355,0.00002864913],"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":[0.00004751504,0.00002817692,0.0001586272,0.00008500706,0.000007802869,0.00004593017,0.00001377166,0.0005137339,0.9773492,0.0002687214,0.0003443001,0.02113716],"study_design_scores_gemma":[0.00003579538,0.0004993352,0.001255497,0.00001415969,0.00003014155,0.0007671218,0.00002261991,0.02460674,0.9480388,0.0003259537,0.02433286,0.00007092495],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3082376,0.004837666,0.663705,0.0007021331,0.0007372674,0.0004796683,0.001846083,0.004582165,0.01487235],"genre_scores_gemma":[0.3996395,0.001167574,0.5869687,0.0003994355,0.0001400849,0.0002810663,0.0007756706,0.0001422916,0.01048558],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002723341,"threshold_uncertainty_score":0.009110451,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01757569125760988,"score_gpt":0.2412288979145515,"score_spread":0.2236532066569416,"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."}}