{"id":"W4283022460","doi":"10.1021/acsenergylett.2c00283","title":"Electrolytic Methane Production from Reactive Carbon Solutions","year":2022,"lang":"en","type":"article","venue":"ACS Energy Letters","topic":"CO2 Reduction Techniques and Catalysts","field":"Energy","cited_by":75,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research; University of British Columbia","funders":"Army Research Office; Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Total; Office of Energy Efficiency and Renewable Energy; Killam Trusts; Canada Foundation for Innovation; Canadian Institute for Advanced Research","keywords":"Methane; Chemistry; Anode; Electrochemistry; Cathode; Electrolyte; Inorganic chemistry; Yield (engineering); Carbon fibers; Hydrogen; Chemical engineering; Materials science; Electrode; Organic chemistry; Metallurgy; Physical chemistry","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":[0.0001946795,0.0002918324,0.0002223862,0.000203536,0.0001772263,0.0002675507,0.0004818495,0.0003846326,0.0006922823],"category_scores_gemma":[0.0002260271,0.0001407703,0.000166059,0.0001796369,0.0002079749,0.0003120519,0.0002877152,0.0004982031,0.0002766391],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003377049,"about_ca_system_score_gemma":0.0001771565,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004707672,"about_ca_topic_score_gemma":0.001128925,"domain_scores_codex":[0.9997832,0.00003190006,0.00001296122,0.00004393831,0.00009408309,0.00003395419],"domain_scores_gemma":[0.9999195,0.00002325921,0.00001858082,0.000007653523,0.00002046096,0.00001042581],"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":[0.00001618696,0.000007712044,0.00006062604,0.0000649811,0.000003640307,0.00003071991,0.00001014789,0.0001329117,0.9970278,0.0003354464,0.00007253108,0.002237218],"study_design_scores_gemma":[0.000003164509,0.00003011002,0.00008622458,0.00000162459,0.000002379697,0.00003425913,0.000004545933,0.00078023,0.9981179,0.00003955695,0.0008975113,0.000002416688],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9547598,0.003216072,0.03507972,0.0005448333,0.0001461944,0.00003949366,0.0002547842,0.0004632823,0.005495848],"genre_scores_gemma":[0.9860244,0.0009544492,0.01147295,0.00004560127,0.00001625505,0.00001229896,0.0001270291,0.0000233306,0.001323643],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006922823,"threshold_uncertainty_score":0.002450228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01118590188933047,"score_gpt":0.2114540633853403,"score_spread":0.2002681614960098,"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."}}