{"id":"W1980953489","doi":"10.1039/c4cp05153j","title":"Edge-to-edge interaction between carbon nanotube–pyrene complexes and electrodes for biosensing and electrocatalytic applications","year":2015,"lang":"en","type":"article","venue":"Physical Chemistry Chemical Physics","topic":"Electrochemical sensors and biosensors","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Stillwater (Canada)","funders":"National Institute of Diabetes and Digestive and Kidney Diseases; National Institutes of Health","keywords":"Stacking; Carbon nanotube; Electrode; Enhanced Data Rates for GSM Evolution; Pyrene; Biosensor; Redox; Nanotechnology; Materials science; Density functional theory; Chemistry; Carbon fibers; Nanotube; Inorganic chemistry; Chemical engineering; Computational chemistry; Organic chemistry; Composite material; Physical chemistry; Computer science","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":[0.0002547629,0.0003966419,0.0002318104,0.0001717655,0.0003217692,0.0005600301,0.0004128227,0.0006470284,0.00108526],"category_scores_gemma":[0.0003825493,0.0002248829,0.0001965035,0.0001468882,0.0002242042,0.0005594869,0.0003916815,0.0005469653,0.0004270748],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001882806,"about_ca_system_score_gemma":0.0001372046,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001341614,"about_ca_topic_score_gemma":0.0003628184,"domain_scores_codex":[0.9997244,0.0000498878,0.00001396191,0.00005253987,0.0001079675,0.00005115148],"domain_scores_gemma":[0.999844,0.00006489772,0.0000227546,0.00001599535,0.00002283301,0.0000295229],"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":[0.00003541677,0.00002405598,0.0001054745,0.00002889952,0.000004784516,0.00006408001,0.00001536442,0.0001113394,0.9977388,0.0002842976,0.0000446637,0.001542834],"study_design_scores_gemma":[0.000002981883,0.00004389239,0.0002884006,0.000001561219,0.000003840274,0.00007256584,0.000006024919,0.0007944658,0.998087,0.00004610898,0.0006505439,0.000002654239],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9636879,0.002542561,0.02883731,0.0002221649,0.0000969742,0.00007311346,0.00007804747,0.000135215,0.004326722],"genre_scores_gemma":[0.9806253,0.0008105008,0.01605879,0.0001380589,0.0000290726,0.00002957654,0.0001095173,0.00002416952,0.002175026],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00108526,"threshold_uncertainty_score":0.003630519,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01741093857331636,"score_gpt":0.2475426425136623,"score_spread":0.230131703940346,"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."}}