{"id":"W4234766824","doi":"10.4028/www.scientific.net/ssp.121-123.1363","title":"Nanotube Encoders","year":2007,"lang":"en","type":"article","venue":"Diffusion and defect data, solid state data. Part B, Solid state phenomena/Solid state phenomena","topic":"Carbon Nanotubes in Composites","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Materials science; Scanning electron microscope; Field electron emission; Carbon nanotube; Anode; Nanotechnology; Common emitter; Nanoscopic scale; Chemical vapor deposition; Resolution (logic); Lithography; Optoelectronics; Plasma-enhanced chemical vapor deposition; Optics; Electron; Electrode; Composite material","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":["metaepi_narrow","sts","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["metaepi_narrow","open_science","insufficient_payload"],"category_scores_codex":[0.00735651,0.002427567,0.002823099,0.001147842,0.001886118,0.00196312,0.006450348,0.0003209612,0.001033831],"category_scores_gemma":[0.0005852635,0.002312798,0.0003456873,0.001592646,0.001623362,0.004028616,0.01186561,0.001323741,0.001515166],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006115094,"about_ca_system_score_gemma":0.0006089223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008414367,"about_ca_topic_score_gemma":0.001636466,"domain_scores_codex":[0.9817863,0.0009453522,0.003969319,0.005591888,0.002664893,0.005042269],"domain_scores_gemma":[0.9844139,0.001692637,0.001510519,0.009447437,0.0005805085,0.00235495],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.009022663,0.006017916,0.004945196,0.002073691,0.002136638,0.001997146,0.03308284,0.006302239,0.7487547,0.0007105437,0.1083722,0.07658428],"study_design_scores_gemma":[0.02192551,0.003235339,0.003711954,0.001103721,0.001407295,0.0006247016,0.005954504,0.05672805,0.1026476,0.01607896,0.7726391,0.01394327],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8851049,0.003539721,0.01853806,0.0004629316,0.005557416,0.003321579,0.07641709,0.001517913,0.005540421],"genre_scores_gemma":[0.9265113,0.01573789,0.005424434,0.003687624,0.00253267,0.0002542001,0.04125637,0.0009726567,0.003622776],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6642669,"threshold_uncertainty_score":0.9998794,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03526051165496145,"score_gpt":0.3125157852977778,"score_spread":0.2772552736428164,"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."}}