{"id":"W4400930180","doi":"10.21203/rs.3.rs-4692796/v1","title":"Microenvironment engineering by targeted delivery of activated Ag NPs for boosting electrocatalytic CO2 reduction reaction","year":2024,"lang":"en","type":"preprint","venue":"Research Square","topic":"CO2 Reduction Techniques and Catalysts","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"Natural Science Foundation of Zhejiang Province; National Natural Science Foundation of China","keywords":"Boosting (machine learning); Reduction (mathematics); Chemistry; Nanotechnology; Drug delivery; Computer science; Combinatorial chemistry; Materials science; Artificial intelligence; Mathematics","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":[0.00005995678,0.0002727027,0.0001662691,0.0001137339,0.0001069092,0.0003279036,0.0001726484,0.0003991495,0.0009044295],"category_scores_gemma":[0.00007800771,0.0001273532,0.0001612492,0.00007927211,0.0001396201,0.0002175598,0.000176222,0.0003097411,0.000330346],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002499793,"about_ca_system_score_gemma":0.0001094928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004690994,"about_ca_topic_score_gemma":0.0007331577,"domain_scores_codex":[0.9999349,0.000004681666,0.000002254572,0.00002678225,0.00001434357,0.00001702818],"domain_scores_gemma":[0.9999727,0.000004955534,0.000007203676,0.000002803297,0.000006341423,0.0000060934],"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":[0.00004023959,0.00001602012,0.00001141019,0.00001927122,0.000002013604,0.00002057632,0.000006461771,0.0001472282,0.9980885,0.0000785997,0.00007175296,0.001497933],"study_design_scores_gemma":[0.000005107338,0.00004060766,0.00009434985,8.815079e-7,0.000004830451,0.00002634008,0.000004323997,0.001343534,0.9975668,0.00002387354,0.0008870439,0.000002214676],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9707296,0.001779745,0.02233623,0.000208593,0.0001282791,0.00004922571,0.0001636549,0.0005266098,0.004077957],"genre_scores_gemma":[0.9899917,0.0004734747,0.005966784,0.00007666992,0.00001641709,0.00002457431,0.00007030971,0.00005301449,0.003327051],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009044295,"threshold_uncertainty_score":0.003025651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02245939512406507,"score_gpt":0.3051695839225074,"score_spread":0.2827101887984423,"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."}}