{"id":"W2803614967","doi":"10.1149/ma2018-01/7/743","title":"Dielectrics & Electrostatics: Their Effect on Carbon Nanotube Network Field-Effect Transistors and Gas Sensors","year":2018,"lang":"en","type":"article","venue":"ECS Meeting Abstracts","topic":"Carbon Nanotubes in Composites","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Materials science; Carbon nanotube; Field-effect transistor; Carbon nanotube field-effect transistor; Nanotechnology; Gate dielectric; Ambipolar diffusion; Dielectric; Optoelectronics; Transistor; Electron; Electrical engineering; Physics","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":[0.0001918742,0.0004107544,0.0001998806,0.0003246518,0.0001926321,0.0003616085,0.0002646377,0.0005512825,0.002545052],"category_scores_gemma":[0.0003358198,0.000180798,0.0001453048,0.0003515918,0.0002810833,0.0006196487,0.0001678239,0.0002834547,0.0007181886],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002099355,"about_ca_system_score_gemma":0.00007570936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002259433,"about_ca_topic_score_gemma":0.0002474593,"domain_scores_codex":[0.9998741,0.00002413887,0.000005551161,0.00002915552,0.00005200443,0.00001502751],"domain_scores_gemma":[0.9998577,0.00005957044,0.00002764102,0.000004681049,0.00002869994,0.00002168568],"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":[0.0003537208,0.000170791,0.0004321752,0.001052389,0.00002410574,0.0004898917,0.00009580835,0.00154594,0.909304,0.005875803,0.003326179,0.07732926],"study_design_scores_gemma":[0.00003112235,0.0007116912,0.002057198,0.00008278875,0.00005265194,0.0009744537,0.00006711327,0.009388803,0.9237059,0.002447368,0.06044764,0.00003327904],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.4589743,0.4709543,0.02099133,0.003643822,0.002385795,0.0001161301,0.0003939353,0.0004015997,0.04213865],"genre_scores_gemma":[0.8028859,0.1380037,0.01886943,0.001085607,0.001431934,0.00007178486,0.0001676995,0.0001287145,0.03735517],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002545052,"threshold_uncertainty_score":0.008514047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008242772167993646,"score_gpt":0.2384178454490863,"score_spread":0.2301750732810927,"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."}}