{"id":"W7117370765","doi":"10.1016/j.seppur.2025.136672","title":"Acid recovery with diffusion dialysis to improve rare earth extraction economics","year":2025,"lang":"en","type":"article","venue":"Separation and Purification Technology","topic":"Extraction and Separation Processes","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec en Abitibi-Témiscamingue","funders":"EIT RawMaterials; Agencia Estatal de Investigación; Ministerio de Ciencia e Innovación; Generalitat de Catalunya; Agència de Gestió d'Ajuts Universitaris i de Recerca; Institució Catalana de Recerca i Estudis Avançats","keywords":"Oxalic acid; Permeation; Extraction (chemistry); Elution; Ion exchange; Dialysis; Alkali metal; Nitric acid; Diffusion","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":[0.00007646346,0.0001333334,0.0001477519,0.0005660406,0.0001429139,0.00008016312,0.00007563084,0.0001947399,0.00004940024],"category_scores_gemma":[0.00003313676,0.000132708,0.00002106863,0.0005890541,0.00003389993,0.0003221501,0.00001148843,0.0001394452,0.00006095616],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004420617,"about_ca_system_score_gemma":0.00003550325,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003045334,"about_ca_topic_score_gemma":0.00009626352,"domain_scores_codex":[0.999292,0.00001350381,0.0002565633,0.0002619673,0.00005004636,0.0001258926],"domain_scores_gemma":[0.9995312,0.00002422804,0.00006079759,0.0002377799,0.0001004935,0.00004551459],"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":[0.0002178278,0.0001088056,0.001023888,0.0001246659,0.0001323542,0.000001173147,0.0003601469,0.01141589,0.534485,0.05320192,0.004208562,0.3947197],"study_design_scores_gemma":[0.0007095448,0.0001778589,0.003112987,0.00003166687,0.00005616068,0.00001505657,0.0005830959,0.01933514,0.5303189,0.004098248,0.4411555,0.0004058939],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6528087,0.000685466,0.3174003,0.005050538,0.0006065095,0.0006706763,0.00001857063,0.001189653,0.02156963],"genre_scores_gemma":[0.9917394,0.0009451351,0.002318019,0.0002420145,0.00003190984,0.000178817,0.00005760222,0.00001411655,0.004472974],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.436947,"threshold_uncertainty_score":0.5411674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005192523291968152,"score_gpt":0.2390109948602875,"score_spread":0.2338184715683193,"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."}}