{"id":"W854590488","doi":"10.1021/acs.jafc.5b02319","title":"Green Synthesis of Fluorescent Carbon Dots for Selective Detection of Tartrazine in Food Samples","year":2015,"lang":"en","type":"article","venue":"Journal of Agricultural and Food Chemistry","topic":"Dye analysis and toxicity","field":"Chemistry","cited_by":500,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Canada","funders":"National Natural Science Foundation of China","keywords":"Tartrazine; Fluorescence; Quantum dot; Quantum yield; Fourier transform infrared spectroscopy; Quenching (fluorescence); Photoluminescence; Materials science; Carbon fibers; Transmission electron microscopy; Analytical Chemistry (journal); Spectroscopy; Fluorescence spectroscopy; Chemistry; Chemical engineering; Photochemistry; Nuclear chemistry; Nanotechnology; Chromatography; Optoelectronics; Optics; Composite number; Composite material","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":[],"consensus_categories":[],"category_scores_codex":[0.0001451647,0.0001297341,0.0004124859,0.0000283711,0.00001707885,0.000007940044,0.0001012656,0.0001163135,0.000005089856],"category_scores_gemma":[0.0001502735,0.0000817164,0.0001538406,0.0001391438,0.00003867362,0.00006781317,0.00002322636,0.0001486381,2.641554e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005607152,"about_ca_system_score_gemma":0.00003316069,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000653893,"about_ca_topic_score_gemma":0.000111405,"domain_scores_codex":[0.99903,0.000009517823,0.0004976713,0.0001154734,0.0002186181,0.0001287391],"domain_scores_gemma":[0.9988093,0.00007524119,0.0005484446,0.00006637154,0.0004036043,0.00009707488],"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":[0.0001330227,0.0001452103,0.002071387,0.0003040982,0.0002523827,5.630183e-7,0.0001617398,0.00002380108,0.9957916,0.000001687265,0.00002293605,0.001091595],"study_design_scores_gemma":[0.0006836892,0.0002479609,0.01241639,0.0001418147,0.0001372671,0.00004794376,0.0008336972,0.00001449862,0.985236,0.0001155073,0.00002266652,0.0001025944],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988541,0.0005624115,0.000004307979,0.00006089869,0.00001418604,0.00003004966,0.00004515191,0.000003142401,0.0004257717],"genre_scores_gemma":[0.999642,0.00004611427,0.00008839367,0.000001682552,0.000176041,0.000003554373,0.000004682136,0.00000489739,0.00003261872],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0105556,"threshold_uncertainty_score":0.3332298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01581828093044099,"score_gpt":0.2060760960777308,"score_spread":0.1902578151472898,"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."}}