{"id":"W4386391347","doi":"10.1016/j.cclet.2023.109021","title":"Functionalization of cellulose carbon dots with different elements (N, B and S) for mercury ion detection and anti-counterfeit applications","year":2023,"lang":"en","type":"article","venue":"Chinese Chemical Letters","topic":"Carbon and Quantum Dots Applications","field":"Materials Science","cited_by":30,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"Fundamental Research Funds for the Central Universities; National Natural Science Foundation of China; Henan Normal University","keywords":"Fluorescence; Metal ions in aqueous solution; Detection limit; Mercury (programming language); Aqueous solution; Chemistry; Surface modification; Nanocellulose; Ion; Photochemistry; Cellulose; Materials science; Nanotechnology; Nuclear chemistry; Chromatography; Organic chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008958951,0.0002478224,0.0000942102,0.0001321526,0.0001397938,0.0001612582,0.000162537,0.0003347365,0.001256223],"category_scores_gemma":[0.0001571877,0.0001002631,0.0001587777,0.0001198362,0.0001242184,0.0001827518,0.0001054043,0.0001846213,0.0001903984],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000260275,"about_ca_system_score_gemma":0.0001463961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00133826,"about_ca_topic_score_gemma":0.002744969,"domain_scores_codex":[0.9999344,0.000005557407,0.000004041288,0.00001851907,0.00001889995,0.00001843898],"domain_scores_gemma":[0.9999369,0.00001363525,0.000012349,0.000007463964,0.0000150147,0.00001458794],"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":[0.00003803213,0.00001193976,0.00008196791,0.00002275262,0.00000264288,0.00003108591,0.000009815558,0.0001086434,0.9981477,0.0001421162,0.00003504322,0.001368204],"study_design_scores_gemma":[0.000002925354,0.00003398194,0.0004693751,0.000001276728,0.000002725578,0.000022731,0.000006245769,0.0007796189,0.9980918,0.00001232852,0.0005744689,0.000002472287],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9934415,0.0003421112,0.003250332,0.00005815651,0.00004013284,0.00001893988,0.0001062529,0.00004514076,0.002697371],"genre_scores_gemma":[0.9946661,0.0001801087,0.003211749,0.00004672418,0.000004289891,0.00001668126,0.0001105797,0.00001251215,0.001751382],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00133826,"threshold_uncertainty_score":0.004202485,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008942545435387018,"score_gpt":0.238848223818046,"score_spread":0.2299056783826589,"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."}}