{"id":"W2045567619","doi":"10.1039/c4gc02232g","title":"Thermodynamic optimization of the Dy–Nd–Fe–B system and application in the recovery and recycling of rare earth metals from NdFeB magnet","year":2015,"lang":"en","type":"article","venue":"Green Chemistry","topic":"Metallurgical Processes and Thermodynamics","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Neodymium magnet; Scrap; Magnet; Rare earth; Dysprosium; Materials science; Metal; Phase (matter); Extraction (chemistry); Phase diagram; Metallurgy; Neodymium; Chemistry; Inorganic chemistry; Mechanical engineering; Chromatography; Physics; Organic 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002012515,0.00008986308,0.0001618847,0.000009793637,0.0000156412,0.00001108079,0.0001416721,0.00008110195,0.000006078926],"category_scores_gemma":[0.00001945986,0.00005781282,0.00002598373,0.0001121508,0.00003911942,0.00005154396,0.00003418123,0.0000928599,2.4363e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001442415,"about_ca_system_score_gemma":0.000009532867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001368839,"about_ca_topic_score_gemma":0.00001932254,"domain_scores_codex":[0.9994622,0.00002394177,0.0002126211,0.0001135688,0.0001161399,0.0000714699],"domain_scores_gemma":[0.9995795,0.00006088634,0.0000867054,0.000219467,0.00002895958,0.000024507],"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":[0.0001067389,0.00006671575,0.001394773,0.003606692,0.000189665,0.000003612339,0.001391257,0.7299975,0.2503079,0.0003946201,0.000012136,0.01252844],"study_design_scores_gemma":[0.0002495975,0.000005688623,0.00100125,0.00008213554,0.00003374045,0.000006150104,0.0004221957,0.9949023,0.002749972,0.0004544297,0.00001733913,0.00007523704],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9776818,0.001192224,0.01799946,0.00002426451,0.00002180949,0.0001366483,0.00003564843,0.00001931961,0.002888894],"genre_scores_gemma":[0.9994266,0.00007028721,0.0004033038,0.000004867356,0.00002309062,0.00001104411,0.00002395331,0.00001195418,0.00002488984],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2649048,"threshold_uncertainty_score":0.2357539,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008094886699791805,"score_gpt":0.1854930547008972,"score_spread":0.1773981680011054,"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."}}