{"id":"W4366976834","doi":"10.1139/cjc-2022-0145","title":"A fluorescence sensor based on quantum dots for the detection of mercury ions","year":2023,"lang":"en","type":"article","venue":"Canadian Journal of Chemistry","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Chemistry; Quantum dot; Fluorescence; Biotin; Detection limit; Mercury (programming language); Streptavidin; Nanosensor; Ion; DNA; Nanotechnology; Photochemistry; Analytical Chemistry (journal); Chromatography; Biochemistry; Organic chemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0003812377,0.0006444409,0.0007511947,0.0003814648,0.0003816874,0.0004345193,0.0009299757,0.001604041,0.001079287],"category_scores_gemma":[0.0003612626,0.000522989,0.000458687,0.0004308012,0.0003690295,0.0008192682,0.0004409729,0.0006832865,0.0005341473],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005165061,"about_ca_system_score_gemma":0.0004067904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008034207,"about_ca_topic_score_gemma":0.001452211,"domain_scores_codex":[0.9994491,0.00008345788,0.00003186617,0.0001724873,0.0002135254,0.00004960264],"domain_scores_gemma":[0.9998671,0.0000356754,0.0000197006,0.00001189177,0.00004470193,0.00002100826],"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":[0.00002454886,0.00001788676,0.00006776652,0.00008380659,0.000005967569,0.00003916736,0.00001210027,0.0001445369,0.9972042,0.0001799607,0.00009089401,0.002129255],"study_design_scores_gemma":[0.00001116448,0.0001763473,0.0004247047,0.00000590563,0.00001486231,0.0001565385,0.00001251537,0.008021128,0.9878369,0.00006214566,0.003259846,0.00001801881],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5707711,0.007370244,0.4085431,0.0008388714,0.0006534141,0.0005659491,0.0009520637,0.004047108,0.006258199],"genre_scores_gemma":[0.680734,0.003450416,0.3041862,0.0004928295,0.00004933503,0.0003551663,0.0006713638,0.0001069808,0.009953726],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001604041,"threshold_uncertainty_score":0.003747523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01156963946441232,"score_gpt":0.2531576389011226,"score_spread":0.2415879994367102,"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."}}