{"id":"W4220667661","doi":"10.3390/mi13030425","title":"A Hybrid Microfluidic Electronic Sensing Platform for Life Science Applications","year":2022,"lang":"en","type":"article","venue":"Micromachines","topic":"Analytical Chemistry and Sensors","field":"Chemical Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Mitacs; CMC Microsystems","keywords":"JFET; Microfluidics; Sensitivity (control systems); Transconductance; Voltage; Materials science; Optoelectronics; Electronic engineering; Nanotechnology; Electrical engineering; Field-effect transistor; Engineering; Transistor","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002069091,0.0001384531,0.000156416,0.00006669573,0.0006566867,0.00003094083,0.0003196882,0.00002030634,0.0001018771],"category_scores_gemma":[0.0001082886,0.0001420316,0.0001030111,0.0002994477,0.0001146618,0.00006445565,0.0001442133,0.000262106,0.00001358394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001953789,"about_ca_system_score_gemma":0.0001304283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001701355,"about_ca_topic_score_gemma":3.927404e-7,"domain_scores_codex":[0.9988137,0.000004674939,0.0002006275,0.0003305797,0.0001713282,0.0004790484],"domain_scores_gemma":[0.9994484,0.00009984882,0.00004389325,0.0002355129,0.00004618879,0.0001261938],"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":[0.00001937535,0.00002847433,0.00001479356,0.00002863222,0.00001678842,0.000001306372,0.00003606199,0.0003091829,0.9964007,0.001668198,0.0006724952,0.0008040428],"study_design_scores_gemma":[0.0003978099,0.00003176739,0.000008386764,0.000004268624,0.0000385223,0.00009906322,0.00008357236,0.05195611,0.8272297,0.002275881,0.1175767,0.0002982038],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9418665,0.001223557,0.0550559,0.0003671797,0.00005411989,0.0003067685,0.00008685121,0.0002076599,0.0008314507],"genre_scores_gemma":[0.997897,0.00001113496,0.0007128364,0.0002650264,0.0001396873,0.00005313393,0.00005626886,0.00002547209,0.0008394737],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.169171,"threshold_uncertainty_score":0.5791882,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009826506196542377,"score_gpt":0.2397334056880424,"score_spread":0.2299068994915,"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."}}