{"id":"W4412712223","doi":"10.1016/j.seppur.2025.134382","title":"Predicting the distribution coefficient in the solvent extraction of rare earth elements","year":2025,"lang":"en","type":"article","venue":"Separation and Purification Technology","topic":"Extraction and Separation Processes","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Bureau Veritas; University of Saskatchewan","keywords":"Rare earth; Solvent extraction; Partition coefficient; Extraction (chemistry); Solvent; Chemistry; Distribution (mathematics); Chromatography; Mineralogy; Mathematics; Organic chemistry; Mathematical analysis","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000471858,0.0003885266,0.0003457613,0.0004613975,0.0001379299,0.0004870714,0.0003594171,0.0005367978,0.0003544328],"category_scores_gemma":[0.00153169,0.0002173255,0.0003964725,0.0003652655,0.0002198152,0.0006177261,0.0002227893,0.0002884518,0.0002670306],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005473754,"about_ca_system_score_gemma":0.0005264934,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006398674,"about_ca_topic_score_gemma":0.005551778,"domain_scores_codex":[0.9998592,0.00002511535,0.00000694525,0.00004290247,0.00004766047,0.00001811206],"domain_scores_gemma":[0.9995781,0.0002906402,0.0000421171,0.00002397902,0.00005736514,0.000007955634],"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":[0.0002978961,0.0001495987,0.03099953,0.0002000878,0.0000606762,0.0001928409,0.00006417473,0.7487941,0.1711719,0.001719186,0.0004649072,0.04588521],"study_design_scores_gemma":[0.000005117476,0.00003701265,0.002728064,0.000003239495,0.000008869451,0.00003277617,0.00001259248,0.956715,0.03977742,0.0003976597,0.0002717057,0.00001053153],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8788959,0.000511328,0.1186444,0.00009128434,0.00001253769,0.00002729478,0.0002214486,0.0003957361,0.001200094],"genre_scores_gemma":[0.9861045,0.0003350129,0.01255484,0.00002139769,0.000003008875,0.00001920013,0.0001722285,0.00003314844,0.0007565831],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006398674,"threshold_uncertainty_score":0.01272285,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009903327588512102,"score_gpt":0.2845407431427364,"score_spread":0.2746374155542243,"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."}}