{"id":"W4386760368","doi":"10.1016/j.sna.2023.114652","title":"Real-time lead detection device based on nanomaterials modified microwave-microfluidic sensor","year":2023,"lang":"en","type":"article","venue":"Sensors and Actuators A Physical","topic":"Biosensors and Analytical Detection","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Tap water; Microfluidics; Materials science; Microwave; Lead (geology); Microchannel; Nanotechnology; Contamination; Process engineering; Detection limit; Spectrum analyzer; Environmental science; Computer science; Chemistry; Environmental engineering; Telecommunications; Chromatography","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001214248,0.0003145463,0.0003758427,0.000187626,0.0001511845,0.00009083204,0.00006792059,0.0001621736,0.00001486082],"category_scores_gemma":[0.0000338385,0.00027905,0.0001419976,0.0004400223,0.00006136618,0.00008039486,0.00002147375,0.0001747594,0.0005527595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005657416,"about_ca_system_score_gemma":0.000009355751,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001969395,"about_ca_topic_score_gemma":9.075222e-7,"domain_scores_codex":[0.9986821,0.00006455404,0.0002383792,0.0003765573,0.0002052162,0.0004331472],"domain_scores_gemma":[0.9993752,0.0001684624,0.00003718846,0.0002329399,0.00003241137,0.000153749],"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":[0.00004774098,0.0000353191,0.000003478524,0.00005760282,0.00002528221,0.00001631309,0.00006592819,0.0009972004,0.9880916,0.00004343071,0.0004290869,0.01018694],"study_design_scores_gemma":[0.000286572,0.00009709713,0.0004038741,0.00002853671,0.00003056469,0.000004985232,0.00002612642,0.4318846,0.5664076,0.0001446436,0.0004230129,0.0002624086],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975281,0.000008148099,0.0003048179,0.0000832587,0.0002324981,0.0001710811,0.00002946818,0.0008776078,0.0007650017],"genre_scores_gemma":[0.999057,0.0001130072,0.00005747032,0.00004515602,0.0004254333,0.00001063224,0.00001727604,0.00007302563,0.0002010123],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4308875,"threshold_uncertainty_score":0.9999661,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01010586447554849,"score_gpt":0.220251115833318,"score_spread":0.2101452513577695,"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."}}