{"id":"W4396712437","doi":"10.1039/d4ya00179f","title":"All-iron redox flow battery in flow-through and flow-over set-ups: the critical role of cell configuration","year":2024,"lang":"en","type":"article","venue":"Energy Advances","topic":"Advanced battery technologies research","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Shell","keywords":"Flow (mathematics); Flow battery; Redox; Set (abstract data type); Battery (electricity); Computer science; Materials science; Chemistry; Mechanics; Metallurgy; Physics; Power (physics); Thermodynamics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009826262,0.000179449,0.0001886521,0.0001062398,0.00004161897,0.00004677637,0.0002099726,0.0001176958,0.0001182636],"category_scores_gemma":[0.00008096243,0.0001421523,0.00003497874,0.0002557538,0.0002162185,0.0006446419,0.00008395906,0.0003070297,0.000009738873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006397531,"about_ca_system_score_gemma":0.00001504532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002342305,"about_ca_topic_score_gemma":0.00009642768,"domain_scores_codex":[0.998856,0.00004215245,0.0002631914,0.0002817375,0.0002217649,0.0003351411],"domain_scores_gemma":[0.9992132,0.0004397161,0.00001394837,0.000280124,0.00002250392,0.00003048108],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004064514,0.00003778074,0.00009625186,0.0004973279,0.00003664045,0.00007288265,0.001036045,0.6895663,0.09546853,0.006402181,0.001277753,0.2054677],"study_design_scores_gemma":[0.0002233365,0.0000647858,0.000127017,0.0001467929,0.00001116693,0.000009962152,0.0007102095,0.6137386,0.2136424,0.0160589,0.154993,0.0002737909],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3463482,0.1701444,0.4440968,0.005492233,0.003006203,0.0007313055,0.0003013725,0.002600335,0.02727918],"genre_scores_gemma":[0.9848144,0.00446069,0.01028198,0.00008861483,0.00009605299,0.00006771499,0.00002385573,0.00004117161,0.0001254883],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6384662,"threshold_uncertainty_score":0.5796801,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008898555344010977,"score_gpt":0.2698730097028899,"score_spread":0.2609744543588789,"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."}}