{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000811044,0.0007660189,0.0007810035,0.0001125749,0.0003346732,0.00010845,0.0003685272,0.0007424803,9.578741e-7],"category_scores_gemma":[0.0008444061,0.0007513645,0.0004822339,0.0009719996,0.0003839739,0.00002060297,0.0002208562,0.0007614608,0.00003969894],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003201551,"about_ca_system_score_gemma":0.0001884762,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005820569,"about_ca_topic_score_gemma":0.00001035143,"domain_scores_codex":[0.995373,0.0001592697,0.000864994,0.001525477,0.0006675429,0.001409764],"domain_scores_gemma":[0.9977289,0.0001919954,0.0003733844,0.0009897505,0.0003308227,0.0003850945],"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":[0.0004074289,0.0002380463,0.00009610074,0.0001477448,0.0002500486,0.0001089728,0.00001129363,0.00002838277,0.9968683,0.00002235036,0.00078893,0.001032364],"study_design_scores_gemma":[0.0004901709,0.0002778494,0.00004917319,0.0001692602,0.0002096153,0.0002651756,0.00005690113,0.00709797,0.9903799,0.00005977654,0.00007363904,0.0008705549],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995503,0.000114225,0.002574129,0.0002072476,0.00003903145,0.0002224779,0.00002395681,0.0005907268,0.0007252079],"genre_scores_gemma":[0.9979519,0.00009519056,0.0002761383,0.0002605056,0.0005160673,0.00003733355,0.0006672702,0.0001086366,0.00008698968],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007069587,"threshold_uncertainty_score":0.9994937,"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."}}