{"id":"W4411866571","doi":"10.1021/acsaem.5c01074","title":"Sustainable PGM Recovery Processes for Fuel Cell and Electrolyzer Applications","year":2025,"lang":"en","type":"article","venue":"ACS Applied Energy Materials","topic":"Metal Extraction and Bioleaching","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Korea Evaluation Institute of Industrial Technology; Mitacs","keywords":"Electrolysis; Fuel cells; Environmental science; Sustainable energy; Waste management; Process engineering; Materials science; Chemistry; Chemical engineering; Engineering; Electrode; Renewable energy; Electrical engineering","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":[0.0001286684,0.0001252062,0.0001653919,0.00007933058,0.00009330933,0.0001160309,0.00007941209,0.00008636633,0.00002210873],"category_scores_gemma":[0.000009927189,0.0001188073,0.00001301597,0.00014207,0.00001214552,0.00007660868,0.00002470682,0.00003327315,0.000003600077],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002852146,"about_ca_system_score_gemma":0.00002849133,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002509517,"about_ca_topic_score_gemma":0.000007818555,"domain_scores_codex":[0.9993793,0.000006511297,0.0001848381,0.0001690022,0.0000361734,0.0002241796],"domain_scores_gemma":[0.999719,0.00005910754,0.00003185167,0.0001238846,0.00003699525,0.00002922656],"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":[0.0000349796,0.00001973285,9.099262e-7,0.001842415,0.00002813838,1.460643e-7,0.0000134754,0.0005565697,0.9332552,0.0589963,0.001649558,0.003602591],"study_design_scores_gemma":[0.0001862596,0.000007762897,0.000008091659,0.000005250779,0.00001888862,5.436544e-7,0.00004931653,0.00001475161,0.6668698,0.01169787,0.3210305,0.0001109594],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3760149,0.01413342,0.2737825,0.0005162093,0.001088928,0.002960664,0.0001525719,0.002204955,0.3291459],"genre_scores_gemma":[0.9911065,0.001202345,0.0006317338,0.0001914416,0.0001094653,0.001090869,0.00006384787,0.00002500658,0.005578804],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6150916,"threshold_uncertainty_score":0.4844821,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003879291957562204,"score_gpt":0.1989255435524753,"score_spread":0.1950462515949131,"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."}}