{"id":"W4327525123","doi":"10.1080/25740881.2022.2071162","title":"Synergistic effect between graphene nanoplatelets and carbon black to improve the thermal and mechanical properties of natural rubber nanocomposites","year":2022,"lang":"en","type":"article","venue":"Polymer-Plastics Technology and Materials","topic":"Polymer Nanocomposite Synthesis and Irradiation","field":"Materials Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Materials science; Carbon black; Nanocomposite; Fourier transform infrared spectroscopy; Scanning electron microscope; Natural rubber; Composite material; Carbon nanotube; Graphene; Ultimate tensile strength; Raman spectroscopy; Chemical engineering; Nanotechnology","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":[0.0004956704,0.0002370068,0.0004938864,0.000233761,0.0003624962,0.0000646244,0.0002402332,0.000129305,0.00002640518],"category_scores_gemma":[0.00009366287,0.0001598154,0.00002355311,0.0001907714,0.0004838936,0.0000592036,0.0005723169,0.0001292465,0.000002085855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001476607,"about_ca_system_score_gemma":0.00001885989,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008962295,"about_ca_topic_score_gemma":0.000003599972,"domain_scores_codex":[0.9984807,0.0002546981,0.0003778833,0.0003839821,0.0001776786,0.0003251092],"domain_scores_gemma":[0.9992132,0.0002771147,0.0001905803,0.0002315345,0.00002375998,0.0000637971],"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":[0.0001923067,0.00002038697,0.0004626922,0.00007843305,0.00003819566,0.000002923945,0.000122273,0.000001252891,0.9952881,0.002102381,0.000003836085,0.0016872],"study_design_scores_gemma":[0.0003598454,0.0005276773,0.001339425,0.00003614868,0.000123022,0.00002463003,0.0000341751,0.00003466211,0.9970202,0.000258511,0.00004645071,0.0001952859],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961628,0.002222809,0.00001283351,0.0004952026,0.0004470166,0.0004588822,0.0001085809,0.0000746892,0.00001720563],"genre_scores_gemma":[0.9996069,0.0000290391,0.00008034075,0.00004827892,0.00005485507,0.0001113327,0.000004748349,0.00002253139,0.00004195881],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003444134,"threshold_uncertainty_score":0.6517082,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004846232474603008,"score_gpt":0.1945962322091166,"score_spread":0.1897499997345136,"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."}}