{"id":"W2599128650","doi":"10.1039/c7ta01114h","title":"Synthesis of ultra-small carbon nanospheres (&lt;50 nm) with uniform tunable sizes by a convenient catalytic emulsion polymerization strategy: superior supercapacitive and sorption performance","year":2017,"lang":"en","type":"article","venue":"Journal of Materials Chemistry A","topic":"Supercapacitor Materials and Fabrication","field":"Materials Science","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; Laurentian University; University of Sudbury","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Sorption; Materials science; Catalysis; Polymerization; Chemical engineering; Emulsion; Carbon fibers; Emulsion polymerization; Organic chemistry; Chemistry; Composite material; Polymer; Adsorption; Composite number","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":[0.0001783988,0.000316158,0.0001629375,0.0002299983,0.0001363066,0.0002226553,0.0002078964,0.0003456502,0.0008802317],"category_scores_gemma":[0.0002105921,0.0001511621,0.0001626879,0.0001211053,0.0002186926,0.0003672881,0.0001958365,0.0003587585,0.0002627158],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003838736,"about_ca_system_score_gemma":0.0002668351,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007062935,"about_ca_topic_score_gemma":0.001857944,"domain_scores_codex":[0.9999256,0.000004690609,0.000007765604,0.00001915882,0.0000289018,0.00001393225],"domain_scores_gemma":[0.9998816,0.00002332016,0.00002567158,0.00001198373,0.00003004044,0.00002742318],"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":[0.00001573297,0.00001252816,0.00002768018,0.00004049422,0.000003932757,0.00003440891,0.00001396314,0.0001126241,0.9970091,0.0002004131,0.0001039687,0.00242527],"study_design_scores_gemma":[0.000006057668,0.00002926342,0.0003192478,0.000001611366,0.000003918854,0.00004604915,0.000004511816,0.0006945837,0.9976857,0.00003184309,0.001173113,0.000004136013],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9656916,0.002832372,0.02503938,0.0003433162,0.00007550125,0.0001081135,0.0004013591,0.0003974141,0.005111078],"genre_scores_gemma":[0.9775764,0.0009985371,0.01766117,0.00007561577,0.00001463609,0.00005877583,0.0002736456,0.00005507836,0.003286036],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008802317,"threshold_uncertainty_score":0.002944708,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01049477840109948,"score_gpt":0.2051453234700781,"score_spread":0.1946505450689787,"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."}}