{"id":"W2793299429","doi":"10.1007/s40820-018-0193-5","title":"Noninvasive Label-Free Detection of Cortisol and Lactate Using Graphene Embedded Screen-Printed Electrode","year":2018,"lang":"en","type":"article","venue":"Nano-Micro Letters","topic":"Advanced Sensor and Energy Harvesting Materials","field":"Engineering","cited_by":134,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Biosensor; Potentiostat; Bioconjugation; Graphene; Detection limit; Biomolecule; Nanotechnology; Point of care; Materials science; Electrode; Biological fluids; Chemistry; Computer science; Electrochemistry; Chromatography; Medicine","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":[0.00006751897,0.0001926735,0.0002425224,0.0001303606,0.0000838921,0.00002769445,0.0001137776,0.00007456245,0.00001215166],"category_scores_gemma":[0.00005444058,0.000206122,0.0000355821,0.0001898719,0.0001337044,0.0001430239,0.00004194365,0.00009188802,0.000004581043],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005169479,"about_ca_system_score_gemma":0.000007046143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001235659,"about_ca_topic_score_gemma":0.0001053628,"domain_scores_codex":[0.9990596,0.00003275498,0.0002713272,0.0002117023,0.00009930376,0.0003253322],"domain_scores_gemma":[0.9994856,0.00004022337,0.00008810669,0.0002617281,0.00006617141,0.00005819845],"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":[0.00004153702,0.00000622424,0.00006706097,0.00003948163,0.00004882751,0.000006959801,0.0001260331,0.001608352,0.9968382,0.00001047007,0.00008562384,0.001121307],"study_design_scores_gemma":[0.0006404435,0.00008937452,0.0004030764,0.0000559704,0.00003201535,0.00005697857,0.00001632545,0.001671821,0.9966429,0.00007454491,0.0001018643,0.0002146369],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9744053,0.0000647073,0.02477486,0.00002794001,0.000319146,0.00009754004,0.0000183245,0.0002013233,0.00009079775],"genre_scores_gemma":[0.9915002,0.00004058827,0.008059701,0.0001655589,0.0001571173,0.000003682255,0.000005157318,0.00005329002,0.00001467749],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01709487,"threshold_uncertainty_score":0.840541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0116861069670954,"score_gpt":0.2217887048575715,"score_spread":0.2101025978904761,"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."}}