{"id":"W4392878233","doi":"10.1021/acs.analchem.3c04550","title":"High-Density Au Anchored to Ti<sub>3</sub>C<sub>2</sub>-Based Colorimetric-Fluorescence Dual-Mode Lateral Flow Immunoassay for All-Domain-Enhanced Performance and Signal Intercalibration","year":2024,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Key Research and Development Program of China; China Scholarship Council; National Natural Science Foundation of China","keywords":"Chemistry; Fluorescence; Chromatography; Detection limit; Analytical Chemistry (journal); Correlation coefficient; Coefficient of variation","routes":{"ca_aff":true,"ca_fund":false,"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":[0.000295073,0.0003954239,0.0003989202,0.00009334302,0.0001547247,0.0001390889,0.0001794763,0.0003992907,0.000002470671],"category_scores_gemma":[0.0001411508,0.0003635117,0.0002332395,0.0004054445,0.0002048084,0.00002631123,0.0001451418,0.000269331,0.000005910557],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001484758,"about_ca_system_score_gemma":0.0001605867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009004671,"about_ca_topic_score_gemma":0.00001661326,"domain_scores_codex":[0.9977913,0.00004056017,0.0004511581,0.0009211408,0.0002675329,0.0005282916],"domain_scores_gemma":[0.9989591,0.0000776839,0.00008842302,0.0004085585,0.0002141241,0.0002520594],"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":[0.0004465027,0.00007186659,0.00009299556,0.0001698646,0.0001685037,0.00001274762,0.00002187569,0.0001141252,0.9882947,0.00001055051,0.0009634049,0.009632832],"study_design_scores_gemma":[0.0004087129,0.0003034196,0.0002748293,0.0001258205,0.0001508442,0.00001421608,0.00001568264,0.03206619,0.9657673,0.00009542659,0.0003079011,0.000469682],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9589139,0.00007224943,0.04005575,0.0003614138,0.00007756891,0.0002510057,0.0001023652,0.0001161026,0.00004964652],"genre_scores_gemma":[0.9936157,0.00009834601,0.004831162,0.0002857386,0.0004345546,0.00003925669,0.0005960542,0.0000446973,0.00005446653],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03522459,"threshold_uncertainty_score":0.9998817,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006774015304255764,"score_gpt":0.2516810901002467,"score_spread":0.2449070747959909,"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."}}