{"id":"W4403125882","doi":"10.1109/pesgm51994.2024.10688749","title":"Optimal Electrochemical Model Parameters Identification for Utility-Scale PEM Electrolyzers","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Identification (biology); Proton exchange membrane fuel cell; Scale (ratio); Electrochemistry; Computer science; Process engineering; Fuel cells; Chemical engineering; Chemistry; Engineering; Electrode","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":[0.0004561428,0.0005888181,0.0005612992,0.0002745193,0.0002653408,0.0007559885,0.0004316019,0.0007334883,0.000529739],"category_scores_gemma":[0.001439582,0.0003006215,0.0003895333,0.0002664111,0.0003045035,0.0006853892,0.0004246111,0.0006562421,0.0001495243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003053577,"about_ca_system_score_gemma":0.0006190378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004528731,"about_ca_topic_score_gemma":0.003550719,"domain_scores_codex":[0.999879,0.00003591755,0.00001047242,0.00003325362,0.00002882046,0.00001251545],"domain_scores_gemma":[0.9997205,0.0001610686,0.00004219314,0.00002536019,0.00004494222,0.000005937418],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002557294,0.00002006588,0.000592398,0.0000391052,0.00001089882,0.0000270778,0.00002470901,0.9854628,0.002583485,0.0006334408,0.0001037999,0.01047666],"study_design_scores_gemma":[0.000003049649,0.00001385722,0.0002318377,0.000002596763,0.000002658105,0.000006618166,0.00001074691,0.9980977,0.001148737,0.0003558602,0.0001230668,0.000003234496],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1927933,0.0004265227,0.8025163,0.0001859607,0.00002153577,0.00007185632,0.0001625928,0.0004088095,0.003412945],"genre_scores_gemma":[0.9632843,0.0001575623,0.03562284,0.00001853637,0.000003929608,0.00009019569,0.0001027439,0.00001967728,0.0007002483],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004528731,"threshold_uncertainty_score":0.009004772,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01834196297461135,"score_gpt":0.2848892323969541,"score_spread":0.2665472694223427,"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."}}