{"id":"W4413397338","doi":"10.1007/s11837-025-07653-z","title":"An Efficient and Clean Method for Iron Extraction from Refractory Hematite Using Hydrogen-Based Mineral Phase Transformation","year":2025,"lang":"en","type":"article","venue":"JOM","topic":"Metal Extraction and Bioleaching","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Iron Ore Company (Canada)","funders":"Fundamental Research Funds for the Central Universities; Natural Science Foundation of Liaoning Province; National Natural Science Foundation of China; Innovative Research Group Project of the National Natural Science Foundation of China","keywords":"Hematite; Refractory (planetary science); Extraction (chemistry); Transformation (genetics); Mineral; Hydrogen; Phase (matter); Clean-up; Materials science; Metallurgy; Chemistry; Chromatography","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":[0.0001259016,0.0002773143,0.000243305,0.0002542114,0.0002242803,0.0002216665,0.000281449,0.000309652,0.0005891445],"category_scores_gemma":[0.0001045036,0.0001443961,0.0001984455,0.0002022985,0.0001901593,0.0002608934,0.000338936,0.0004569632,0.0003458285],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001815837,"about_ca_system_score_gemma":0.0003036229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004741065,"about_ca_topic_score_gemma":0.001624353,"domain_scores_codex":[0.9998907,0.00001034503,0.000006496153,0.00002136778,0.00005513648,0.00001596491],"domain_scores_gemma":[0.9999613,0.000007887852,0.000009321795,0.000005568953,0.00001027159,0.000005750933],"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":[0.00002619536,0.00001932706,0.0001261973,0.00006572199,0.000003986455,0.00005256169,0.00001300503,0.00006755978,0.9920906,0.000202532,0.0001139637,0.00721841],"study_design_scores_gemma":[0.000006297717,0.00005062755,0.0003504078,0.00000190633,0.000006298655,0.0000941213,0.00001212772,0.001053672,0.995852,0.00005092963,0.002516872,0.000004775299],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8574551,0.003069898,0.1309141,0.0004177609,0.00014072,0.0001883984,0.0003752742,0.0006657063,0.006773043],"genre_scores_gemma":[0.9603323,0.0009975727,0.03196516,0.00009062202,0.00002473233,0.00005588303,0.000290635,0.00004435606,0.006198812],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0005891445,"threshold_uncertainty_score":0.001970828,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02061476070179597,"score_gpt":0.3412375150253397,"score_spread":0.3206227543235437,"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."}}