{"id":"W4292092838","doi":"10.26434/chemrxiv-2022-fwh4p","title":"Synthesis of Fluorescent Carbon Nanoparticles by Dispersion Polymerizationof Acetylene","year":2022,"lang":"en","type":"preprint","venue":"ChemRxiv","topic":"Carbon Nanotubes in Composites","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Dispersity; Materials science; Polymerization; Nanoparticle; Carbon fibers; Fluorescence; Nanotechnology; Nanomaterials; Dispersion (optics); Chemical engineering; Dispersion polymerization; Surface modification; Acetylene; Polymer chemistry; Polymer; Organic chemistry; Chemistry; Composite material; Composite number; Optics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001774674,0.0004156114,0.0001381826,0.0003667336,0.000167186,0.0001951377,0.0002564584,0.0003857899,0.0008720272],"category_scores_gemma":[0.0001901557,0.0001785617,0.0001760461,0.0002143694,0.0002290524,0.0002320401,0.0001998356,0.0004252073,0.0003644578],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005410041,"about_ca_system_score_gemma":0.0002518549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009531021,"about_ca_topic_score_gemma":0.002310164,"domain_scores_codex":[0.999838,0.000009565459,0.00001160529,0.00005934151,0.00005745688,0.00002403023],"domain_scores_gemma":[0.9999049,0.00002029694,0.00002310841,0.00001423608,0.00002354868,0.00001388247],"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":[0.000009831696,0.000008194926,0.00002181103,0.00002355516,0.000001308291,0.00001585607,0.000008875246,0.0001294751,0.9979581,0.000173531,0.00002266123,0.001626796],"study_design_scores_gemma":[0.000003360035,0.00003463705,0.0001748426,0.000001530627,0.000001576589,0.00001835552,0.000001245109,0.0007475495,0.9980559,0.00002413027,0.0009351889,0.00000181257],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9333113,0.001863899,0.05491173,0.0001666235,0.00009277576,0.0002700736,0.0005140114,0.000494277,0.008375244],"genre_scores_gemma":[0.9531043,0.0009621004,0.0396097,0.00005293821,0.00001564864,0.0001275166,0.0004540094,0.00007333659,0.005600534],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009531021,"threshold_uncertainty_score":0.003925264,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009706418406914545,"score_gpt":0.231413833642247,"score_spread":0.2217074152353325,"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."}}