{"id":"W2809616088","doi":"10.1002/anie.201803873","title":"Iron Porphyrins Embedded into a Supramolecular Porous Organic Cage for Electrochemical CO<sub>2</sub> Reduction in Water","year":2018,"lang":"en","type":"article","venue":"Angewandte Chemie International Edition","topic":"CO2 Reduction Techniques and Catalysts","field":"Energy","cited_by":204,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institute for Basic Science; Lawrence Berkeley National Laboratory; Canadian Institute for Advanced Research; U.S. Department of Energy; Howard Hughes Medical Institute; National Science Foundation","keywords":"Supramolecular chemistry; Electrochemistry; Faraday efficiency; Catalysis; Porosity; Substrate (aquarium); Chemical engineering; Monomer; Materials science; Chemistry; Nanotechnology; Electrode; Polymer; Molecule; Organic chemistry; Physical chemistry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001853817,0.000208486,0.0001786275,0.0002126872,0.00009126344,0.00005423017,0.0002047928,0.0002141894,0.0004443428],"category_scores_gemma":[0.00007427295,0.0002027217,0.0001178997,0.0001582277,0.0001019298,0.000306888,0.00004803246,0.0001857579,0.00007761916],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005291351,"about_ca_system_score_gemma":0.00004470118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000138861,"about_ca_topic_score_gemma":0.0001395483,"domain_scores_codex":[0.9985245,0.0000193823,0.0003694723,0.0004480917,0.0003207305,0.0003178052],"domain_scores_gemma":[0.99926,0.00001744352,0.0001042894,0.0002187473,0.0003247378,0.00007474961],"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":[0.0001922295,0.0001305519,0.000004910836,0.00001910535,0.00003448606,0.000005574222,0.0004328303,0.000002937299,0.9893667,0.0005147355,0.007740633,0.001555335],"study_design_scores_gemma":[0.0006976161,0.000144725,0.00002610084,0.00003252762,0.0000227563,0.0001069579,0.0001076495,0.00005828166,0.9804132,0.006428744,0.01171608,0.0002453527],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9785602,0.00003215978,0.01494838,0.001176042,0.001098533,0.0003323299,0.00001841779,0.000240552,0.003593361],"genre_scores_gemma":[0.992729,0.00005060095,0.000307567,0.0001937523,0.003141373,0.0002261381,0.003069865,0.00004799153,0.0002336792],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01464081,"threshold_uncertainty_score":0.8266749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00694631046723506,"score_gpt":0.2501438492567288,"score_spread":0.2431975387894938,"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."}}