{"id":"W4387033123","doi":"10.1021/acs.analchem.3c03285","title":"Boosting Electrochemiluminescence Immunoassay Sensitivity via Co–Pt Nanoparticles within a Ti<sub>3</sub>C<sub>2</sub> MXene-Modified Single Electrode Electrochemical System on Raspberry Pi","year":2023,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Tehran; Iran National Science Foundation; Agence Universitaire de la Francophonie; Chinese Academy of Sciences; National Natural Science Foundation of China","keywords":"Electrochemiluminescence; Nanotechnology; Electrode; Immunoassay; Biosensor; Chemistry; Detection limit; Miniaturization; Point-of-care testing; Point of care; Computer science; Materials science; Chromatography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002291894,0.0004154833,0.0003185226,0.0002149261,0.0001055077,0.0003733722,0.0005430215,0.0005165928,0.0005206413],"category_scores_gemma":[0.0002740813,0.0003323897,0.0002722506,0.0001511457,0.0002444168,0.0004678473,0.0003929662,0.0005677836,0.0004512005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002631886,"about_ca_system_score_gemma":0.0001448705,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002235932,"about_ca_topic_score_gemma":0.000489198,"domain_scores_codex":[0.9997013,0.00003352983,0.00001879363,0.0001093141,0.0001061421,0.00003083732],"domain_scores_gemma":[0.9998653,0.00003408573,0.00003829402,0.00001406624,0.00003522492,0.00001303869],"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":[0.00001701466,0.000005842955,0.00005242256,0.00001766607,0.000002536057,0.00002288423,0.000007698172,0.0000585995,0.9981535,0.00003700426,0.00002012614,0.001604709],"study_design_scores_gemma":[0.000002596504,0.00007335093,0.0004795743,0.000002056289,0.000007440042,0.00008108824,0.000005498183,0.001990134,0.996716,0.00001183372,0.0006250424,0.000005309425],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9123721,0.001485553,0.08191927,0.0002561149,0.0001018343,0.000110775,0.0001421249,0.0008746111,0.002737732],"genre_scores_gemma":[0.9235168,0.001009438,0.070693,0.0001546664,0.00005177189,0.0001075782,0.0001515107,0.00005295193,0.004262321],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0005430215,"threshold_uncertainty_score":0.001909554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009431647952575072,"score_gpt":0.2454039600711315,"score_spread":0.2359723121185565,"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."}}