{"id":"W4407767454","doi":"10.1007/978-3-031-81182-1_6","title":"Sustainable Supercritical Fluid Extraction of Rare Earth Elements from Canadian Ores: A Cleaner Technology for Resource Recovery","year":2025,"lang":"en","type":"book-chapter","venue":"˜The œminerals, metals & materials series","topic":"Extraction and Separation Processes","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Natural Resources Canada; University of Toronto","funders":"","keywords":"Supercritical fluid; Rare earth; Resource recovery; Resource (disambiguation); Extraction (chemistry); Environmental science; Supercritical fluid extraction; Earth (classical element); Waste management; Earth science; Natural resource economics; Geology; Engineering; Chemistry; Environmental engineering; Computer science; Economics; Chromatography; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003560375,0.0004612388,0.0008036689,0.0005178389,0.0002236199,0.0001947879,0.0003082278,0.0006081832,0.00234744],"category_scores_gemma":[0.0001398444,0.0004119982,0.0001417313,0.0001055079,0.0001490156,0.000444463,0.00005428465,0.0002237704,0.00004181761],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001221388,"about_ca_system_score_gemma":0.0002504533,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003813128,"about_ca_topic_score_gemma":0.02317947,"domain_scores_codex":[0.9979221,0.0000479345,0.0009440821,0.0003861286,0.0002162329,0.0004835322],"domain_scores_gemma":[0.9987631,0.0001732097,0.0001029487,0.0005051855,0.0003552693,0.0001002579],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005658051,0.00003900663,0.000003554718,0.002412699,0.001042599,0.00006532535,0.0002831835,0.0005850294,0.6937611,0.1554036,0.1448752,0.0009629487],"study_design_scores_gemma":[0.0002234248,0.00008041934,0.000003907337,0.0001529128,0.000203534,0.00001761496,0.0005969908,0.00002649695,0.1113623,0.01234778,0.8746344,0.0003502856],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.1337468,0.01982261,0.003290624,0.006167729,0.00979106,0.009498165,0.0199282,0.002737907,0.7950169],"genre_scores_gemma":[0.06128595,0.00114498,0.001078813,0.0003117977,0.0004872704,0.0003410777,0.001765048,0.0001676211,0.9334174],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.7297592,"threshold_uncertainty_score":0.9998332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01088691793348973,"score_gpt":0.2326011700955034,"score_spread":0.2217142521620137,"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."}}