{"id":"W4362473939","doi":"10.1038/s41467-023-37257-7","title":"Bioelectrocatalysis with a palladium membrane reactor","year":2023,"lang":"en","type":"article","venue":"Nature Communications","topic":"Enzyme Catalysis and Immobilization","field":"Biochemistry, Genetics and Molecular Biology","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research; University of British Columbia","funders":"Canada First Research Excellence Fund; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; University of British Columbia; Canada Research Chairs","keywords":"Palladium; Membrane; Computer science; Materials science; Chemistry; Nuclear engineering; Engineering; Catalysis; Biochemistry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003039797,0.0004625286,0.0003230232,0.0002722896,0.0002676308,0.0007085007,0.0007812376,0.0006844765,0.0007027558],"category_scores_gemma":[0.0002075559,0.00034235,0.0003463211,0.0002746895,0.0002826591,0.0005468996,0.0004193606,0.0009579007,0.0008336465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006791975,"about_ca_system_score_gemma":0.0003392579,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008854636,"about_ca_topic_score_gemma":0.0005905655,"domain_scores_codex":[0.9996755,0.00005307828,0.00002265025,0.0001062936,0.0001104632,0.00003207565],"domain_scores_gemma":[0.999946,0.00001427237,0.00000988601,0.00001064034,0.00001205088,0.000007107606],"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":[0.0000436921,0.00004372791,0.0001175489,0.00009961252,0.00001581332,0.00006770115,0.00001468539,0.0005565412,0.9898639,0.001236112,0.0002584124,0.007682184],"study_design_scores_gemma":[0.000008101212,0.00007914488,0.0001176457,0.000003926842,0.000007295671,0.00009676359,0.000007345028,0.005420326,0.9888971,0.0002175502,0.005139532,0.000005133425],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6885628,0.007609834,0.2841307,0.001959806,0.000626004,0.0001813621,0.0004872191,0.002997027,0.01344527],"genre_scores_gemma":[0.9262711,0.002301114,0.06341337,0.000163781,0.00004561812,0.00006998517,0.000320874,0.00005505934,0.007359018],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008854636,"threshold_uncertainty_score":0.004927933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01177995540452374,"score_gpt":0.2719068699660775,"score_spread":0.2601269145615538,"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."}}