{"id":"W4401415931","doi":"10.1016/j.fuel.2024.132708","title":"More efficient way of clean hydrogen production: The synergetic roles of magnetic effects and effective catalysts","year":2024,"lang":"en","type":"article","venue":"Fuel","topic":"Electrocatalysts for Energy Conversion","field":"Energy","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Electrolysis of water; Electrolysis; Anode; Hydrogen production; Catalysis; Hydrogen; Process engineering; Water splitting; Electrolytic process; Cathode; Materials science; Efficient energy use; Chemical engineering; Environmental science; Chemistry; Electrode; Engineering; Electrical engineering","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":[0.000303409,0.0002723057,0.0004325459,0.0005710633,0.0002281142,0.0009133531,0.0003528388,0.0005135444,0.001742222],"category_scores_gemma":[0.0004294717,0.0002110237,0.0003148345,0.0004140174,0.0002732974,0.001162324,0.0004324958,0.0005027758,0.0004268731],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000298982,"about_ca_system_score_gemma":0.0001904696,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003403738,"about_ca_topic_score_gemma":0.001065758,"domain_scores_codex":[0.9997013,0.00003372481,0.00001520389,0.00004687882,0.0001671848,0.00003557365],"domain_scores_gemma":[0.9998361,0.00006106171,0.00003151901,0.00001844603,0.00004327983,0.000009689424],"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":[0.0002218299,0.0001795864,0.001418648,0.001642452,0.0000559711,0.0003668403,0.0001099319,0.001776016,0.9242027,0.004651397,0.0007961066,0.06457864],"study_design_scores_gemma":[0.00002034587,0.000788957,0.004308539,0.0000732527,0.0001065362,0.0005887072,0.0002421524,0.006433093,0.9619058,0.001294671,0.02421072,0.00002735868],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8814483,0.03446879,0.03718921,0.001066399,0.000267433,0.0001191861,0.0003270718,0.0003519279,0.0447617],"genre_scores_gemma":[0.97763,0.006239089,0.01209662,0.000093043,0.00004371559,0.00002293512,0.0001259016,0.00003718802,0.003711521],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001742222,"threshold_uncertainty_score":0.005828261,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002888642521419709,"score_gpt":0.1990388629453425,"score_spread":0.1961502204239227,"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."}}