{"id":"W2957141095","doi":"10.29363/nanoge.ngfm.2019.070","title":"1 Host-guest Chemistry Meets Electrocatalysis: Cucurbit[6]uril on a Au Surface as Hybrid System in CO2 Reduction","year":2019,"lang":"en","type":"article","venue":"Proceedings of the nanoGe Fall Meeting 2019","topic":"Physics of Superconductivity and Magnetism","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Bundesministerium für Digitalisierung und Wirtschaftsstandort; Deutsche Forschungsgemeinschaft; European Commission; Christian Doppler Forschungsgesellschaft; Royal Society; Engineering and Physical Sciences Research Council; OMV Konzern; Österreichische Nationalstiftung für Forschung, Technologie und Entwicklung","keywords":"Electrocatalyst; Reduction (mathematics); Host (biology); Chemistry; Nanotechnology; Computer science; Materials science; Physical chemistry; Electrochemistry; Electrode; Mathematics; Biology; Ecology","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":[0.0001352448,0.0003461184,0.0002980156,0.0001465377,0.0001695848,0.0004221019,0.0004098399,0.0003535491,0.0009557292],"category_scores_gemma":[0.0001138351,0.0001680359,0.0001309678,0.0001074941,0.0002773328,0.0002394091,0.0002937022,0.0003293906,0.0004285535],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003931719,"about_ca_system_score_gemma":0.0001053528,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005994235,"about_ca_topic_score_gemma":0.001086989,"domain_scores_codex":[0.9998586,0.00002792146,0.000007588274,0.00003553517,0.0000409401,0.00002943023],"domain_scores_gemma":[0.9999486,0.000009585621,0.00001437908,0.000006761548,0.00001161415,0.00000906175],"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":[0.00004526849,0.00001373539,0.00005787504,0.00004730237,0.00000341141,0.00003588595,0.00001349037,0.0002144139,0.9982238,0.0002361814,0.00004666103,0.001061864],"study_design_scores_gemma":[0.000004487532,0.0001321758,0.0003075167,0.00000260289,0.000005393442,0.00005030917,0.000006893458,0.001702727,0.9963385,0.00002101126,0.001422976,0.000005489118],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9868067,0.001977466,0.006694323,0.0001148592,0.00004811641,0.00003585443,0.00009300971,0.0002587427,0.0039709],"genre_scores_gemma":[0.994387,0.0003513868,0.003448254,0.00003598416,0.00001102694,0.00001706248,0.00007050102,0.00003407231,0.001644731],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009557292,"threshold_uncertainty_score":0.003197253,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004537715852935794,"score_gpt":0.1959212635947045,"score_spread":0.1913835477417687,"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."}}