{"id":"W4285399980","doi":"10.1149/ma2022-01412445mtgabs","title":"(Digital Presentation) Assessing the Energy Intensity of Product Purification in CO<sub>2</sub> Electrolysis","year":2022,"lang":"en","type":"article","venue":"ECS Meeting Abstracts","topic":"CO2 Reduction Techniques and Catalysts","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Downstream (manufacturing); Electrolysis; Electrochemistry; Renewable energy; Process engineering; Environmental science; Electricity; Carbon dioxide; Selectivity; Electrolytic cell; Electrochemical cell; Chemistry; Chemical engineering; Pulp and paper industry; Catalysis; Electrode; Engineering; Operations management; Electrical engineering; Organic chemistry","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":[0.0002116078,0.0002538793,0.0002455972,0.0003374733,0.0001502806,0.0007042788,0.0002455677,0.0005198875,0.02474378],"category_scores_gemma":[0.000629323,0.0001037379,0.0001799432,0.0002792181,0.0001860948,0.0004248862,0.0002878241,0.0003939249,0.002092778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003073346,"about_ca_system_score_gemma":0.0001129039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001100614,"about_ca_topic_score_gemma":0.001707417,"domain_scores_codex":[0.9999006,0.000008394104,0.000002999153,0.00001601863,0.00005736154,0.00001471777],"domain_scores_gemma":[0.9997831,0.00008366621,0.00001736451,0.00001683476,0.00008432927,0.00001460705],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002612333,0.0005279668,0.01028106,0.0004555831,0.00004931882,0.0004428302,0.00009149313,0.01982761,0.804637,0.002544615,0.01346544,0.1450649],"study_design_scores_gemma":[0.00006891641,0.001344268,0.03403387,0.0000314282,0.00007842898,0.0002264556,0.0001706355,0.04500693,0.9038804,0.001617535,0.01348564,0.00005549416],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8843842,0.001186299,0.02182776,0.0006903093,0.0005108097,0.0001420097,0.002369589,0.001566782,0.08732226],"genre_scores_gemma":[0.9659184,0.0005359591,0.004750887,0.0001834365,0.00004622974,0.00003121233,0.0008366555,0.0001109253,0.02758631],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02474378,"threshold_uncertainty_score":0.08277613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01309637384697337,"score_gpt":0.2549516805233284,"score_spread":0.241855306676355,"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."}}