{"id":"W4406314625","doi":"10.54254/2755-2721/2025.20083","title":"Performance Enhancement of Carbon Nanotube in Composites: An Analysis of Key Factors in Mechanical, Electrical, and Thermal Properties","year":2025,"lang":"en","type":"article","venue":"Applied and Computational Engineering","topic":"Conducting polymers and applications","field":"Materials Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Materials science; Carbon nanotube; Composite material; Carbon nanotube metal matrix composites; Thermal; Nanotube; Carbon nanotube actuators; Mechanical properties of carbon nanotubes","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":[0.000112904,0.0004129423,0.0002435006,0.0003091794,0.0001787046,0.0002822151,0.0001234857,0.0003190761,0.0005790283],"category_scores_gemma":[0.0001503446,0.000127685,0.0002030123,0.0003107645,0.0001236469,0.0003034365,0.00009462814,0.000227084,0.0001620971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002294529,"about_ca_system_score_gemma":0.0001172605,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002668992,"about_ca_topic_score_gemma":0.000665355,"domain_scores_codex":[0.9998978,0.000009272881,0.000004017718,0.00002068345,0.00005559571,0.00001255413],"domain_scores_gemma":[0.9999504,0.00001355312,0.0000110207,0.000002329897,0.00001847099,0.000004239346],"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":[0.00002480221,0.00002461413,0.0002507669,0.0002356546,0.000005498192,0.00005406556,0.00002801227,0.001053382,0.9847185,0.0007336637,0.0003290719,0.01254203],"study_design_scores_gemma":[0.000002236397,0.0002711049,0.004872353,0.00004115865,0.00003150126,0.0001953223,0.00005715708,0.01614361,0.9612316,0.0004885676,0.01664487,0.00002040922],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8777665,0.05913676,0.03366294,0.0007024552,0.0004365293,0.00007521285,0.0002461893,0.0002490058,0.02772423],"genre_scores_gemma":[0.9380764,0.03026556,0.02157089,0.0001178145,0.0001580681,0.0000389737,0.0001509972,0.00007295941,0.009548309],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0005790283,"threshold_uncertainty_score":0.001937032,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009754436137864685,"score_gpt":0.2131294504539561,"score_spread":0.2033750143160914,"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."}}