{"id":"W4405095404","doi":"10.1016/j.decarb.2024.100091","title":"Atomically dispersed metal site materials for hydrogen energy utilization: Theoretical and experimental study in fuel cells and water electrolysis","year":2024,"lang":"en","type":"article","venue":"DeCarbon","topic":"Electrocatalysts for Energy Conversion","field":"Energy","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; École de Technologie Supérieure","funders":"Department of Education of Guizhou Province; Guizhou Science and Technology Department; National Natural Science Foundation of China; Educational Testing Service","keywords":"Electrolysis; Hydrogen fuel; Fuel cells; Electrolysis of water; Materials science; Hydrogen; Metal; Hydrogen production; Waste management; Chemical engineering; Environmental science; Metallurgy; Chemistry; Engineering; Electrode; Electrolyte","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":[0.0003119804,0.0003696369,0.0004688962,0.0004745093,0.0003109151,0.0004804593,0.0005503178,0.0007305458,0.001113014],"category_scores_gemma":[0.0003371819,0.0002730154,0.0003095339,0.0006655199,0.0004417805,0.001056687,0.0003971571,0.000702987,0.0002041918],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005366806,"about_ca_system_score_gemma":0.0003811522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009730874,"about_ca_topic_score_gemma":0.001200657,"domain_scores_codex":[0.9999129,0.00001395925,0.000004799932,0.00001820251,0.00003745655,0.00001281539],"domain_scores_gemma":[0.9999371,0.0000372098,0.000004361854,0.000004602013,0.00001348125,0.000003193012],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001586528,0.0002497933,0.00161163,0.01147934,0.000135207,0.001060096,0.0004685474,0.09011598,0.1440198,0.5813064,0.003489976,0.1659046],"study_design_scores_gemma":[0.00008986694,0.0007528112,0.004050114,0.001484812,0.0002083108,0.001085856,0.0006496862,0.3858382,0.1957376,0.2102287,0.1997285,0.0001455228],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.3391036,0.491767,0.09372795,0.003038066,0.0005922127,0.0001248568,0.0003473927,0.0001558373,0.07114308],"genre_scores_gemma":[0.7733642,0.1959285,0.02473851,0.0002429436,0.0001197409,0.00008833645,0.0002169996,0.00003629538,0.005264353],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001113014,"threshold_uncertainty_score":0.003893912,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007128229623171695,"score_gpt":0.2370790639327849,"score_spread":0.2299508343096132,"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."}}