{"id":"W4408441656","doi":"10.1109/tste.2025.3551495","title":"Optimal Design and Technology Selection for Electrolyzer Hydrogen Plants Considering Hydrogen Supply and Provision of Grid Services","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Hybrid Renewable Energy Systems","field":"Energy","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Grid; Hydrogen; Selection (genetic algorithm); Hydrogen production; Environmental economics; Computer science; Engineering; Business; Electrical engineering; Environmental science; Waste management; Automotive engineering; Economics; 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":[0.0005001421,0.0009275674,0.0008925441,0.0005153877,0.0004594506,0.001662206,0.0008068237,0.001430776,0.003356291],"category_scores_gemma":[0.001161108,0.000806896,0.0006330711,0.0004577097,0.0005236678,0.001097576,0.0006989198,0.0008836102,0.0004117596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001231253,"about_ca_system_score_gemma":0.001262321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005619999,"about_ca_topic_score_gemma":0.007286901,"domain_scores_codex":[0.9997479,0.00006750209,0.000009283524,0.00005747368,0.00006947283,0.00004825169],"domain_scores_gemma":[0.9997211,0.0001410152,0.00004958629,0.00001311574,0.00005792389,0.00001720352],"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":[0.00005388683,0.00003335422,0.0003039942,0.00006470084,0.00001270743,0.00005096135,0.00001502378,0.9916281,0.002504113,0.001225472,0.0002152439,0.003892484],"study_design_scores_gemma":[0.00002264365,0.00007617484,0.0002212813,0.000007511421,0.00001617355,0.00001279029,0.00002809624,0.996891,0.001390393,0.0008942904,0.0004337802,0.00000597092],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.322761,0.001128199,0.6309486,0.0008408396,0.00009332652,0.0004418606,0.0006519639,0.0005976888,0.04253654],"genre_scores_gemma":[0.9801532,0.0002799918,0.01606321,0.00003475559,0.000006394845,0.0001178681,0.00007841171,0.00002796493,0.003238113],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005619999,"threshold_uncertainty_score":0.01122785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005146618663895479,"score_gpt":0.214176182208236,"score_spread":0.2090295635443405,"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."}}