{"id":"W4411227002","doi":"10.1007/s40843-025-3403-x","title":"Highly efficient recovery of light, medium and heavy rare earth elements using magnetic core-shell nanoparticles","year":2025,"lang":"en","type":"article","venue":"Science China Materials","topic":"Extraction and Separation Processes","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Materials science; Rare earth; Nanoparticle; Shell (structure); Core (optical fiber); Magnetic nanoparticles; Nanotechnology; Chemical engineering; Metallurgy; Composite material","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":[0.0003763318,0.00009195416,0.0001489537,0.000154117,0.0001229609,0.0001203946,0.0001236978,0.00002738933,0.0001330548],"category_scores_gemma":[0.00006621973,0.00008122324,0.00001169012,0.0003857558,0.0001275561,0.0002178808,0.00004264135,0.00002647074,0.000007663888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002236735,"about_ca_system_score_gemma":0.00007297904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000952057,"about_ca_topic_score_gemma":0.000003672117,"domain_scores_codex":[0.9991443,0.00001436153,0.0003009429,0.0001693918,0.0001862943,0.0001847243],"domain_scores_gemma":[0.9997007,0.00001623518,0.00005086803,0.0001271462,0.00005482091,0.0000502789],"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":[0.00001591357,0.00001569152,0.00009963641,0.0001120427,0.000002525318,6.302957e-7,0.000157913,0.002060491,0.9968804,0.0003572887,0.00005945571,0.0002379885],"study_design_scores_gemma":[0.0001442148,0.00003529656,0.00408473,0.00007249526,0.000008173968,0.000002817332,0.00006366176,0.002919905,0.9916794,0.0002739741,0.0006357269,0.00007965421],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968131,0.0002953731,0.0001100467,0.00006379748,0.001121217,0.0001263785,0.00001336365,0.00006027806,0.001396498],"genre_scores_gemma":[0.9989353,0.00006528438,0.0007181447,0.00003097521,0.00001811373,0.000004365013,0.0000014339,0.000005434632,0.0002209458],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005201073,"threshold_uncertainty_score":0.3312187,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01298614785045841,"score_gpt":0.2596575345801212,"score_spread":0.2466713867296628,"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."}}