{"id":"W4386270606","doi":"10.1016/j.fbio.2023.103091","title":"Evaluation of antioxidant, antimicrobial and bacterial labeling capacities of four plant byproduct carbon dots","year":2023,"lang":"en","type":"article","venue":"Food Bioscience","topic":"Carbon and Quantum Dots Applications","field":"Materials Science","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"National Key Research and Development Program of China Stem Cell and Translational Research; National Key Research and Development Program of China; Higher Education Discipline Innovation Project; Government of Jiangsu Province","keywords":"Fluorescence; Fourier transform infrared spectroscopy; Chemistry; DPPH; Thermogravimetric analysis; Carbon fibers; Particle size; Nuclear chemistry; Fluorescence spectroscopy; Antimicrobial; Antioxidant; Antibacterial activity; Nanotechnology; Materials science; Chemical engineering; Organic chemistry; Bacteria; Biology","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":[0.0002450235,0.0002876993,0.0001292565,0.000203656,0.0001239779,0.0001706714,0.0001843646,0.0004847294,0.0007764102],"category_scores_gemma":[0.0002648114,0.0001040201,0.0001647781,0.000190761,0.0001501364,0.0002037383,0.0001277172,0.0002248709,0.0001237717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001723976,"about_ca_system_score_gemma":0.0001081478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004868312,"about_ca_topic_score_gemma":0.0008714757,"domain_scores_codex":[0.9998589,0.00002552796,0.000008533778,0.00003863771,0.00004229181,0.00002600771],"domain_scores_gemma":[0.9997817,0.0000635172,0.00003264055,0.00002140836,0.00007616149,0.00002456771],"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":[0.00005927353,0.00001019383,0.00006778294,0.00002629527,0.000002604178,0.00001225413,0.00001127204,0.00006547681,0.9989433,0.00004945971,0.00001109299,0.0007409821],"study_design_scores_gemma":[0.000002181159,0.0001201056,0.0002781717,0.000001505486,0.000004769932,0.000009056999,0.000005545003,0.0004345159,0.9988621,0.000007349061,0.0002728052,0.000001890376],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972355,0.0003097943,0.001580757,0.000025203,0.00001059802,0.00001584868,0.00008386894,0.00002299254,0.0007154687],"genre_scores_gemma":[0.995018,0.0002914269,0.003027513,0.00001972546,0.000002862072,0.0000206263,0.0001812626,0.0000104609,0.001428072],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007764102,"threshold_uncertainty_score":0.002597332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07053499842477816,"score_gpt":0.2733716267475728,"score_spread":0.2028366283227946,"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."}}