{"id":"W2945205068","doi":"10.5539/enrr.v9n2p102","title":"Processing of Superfine and Ultrafine Phosphate of a Phosphomud (Part Two)","year":2019,"lang":"en","type":"article","venue":"Environment and Natural Resources Research","topic":"Minerals Flotation and Separation Techniques","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Tailings; Concentrator; Phosphate; Gangue; Particle size; Mineral processing; Ultrafine particle; Composite number; Pulp and paper industry; Environmental science; Fraction (chemistry); Particle (ecology); Falcon; Process engineering; Materials science; Chemistry; Mineralogy; Metallurgy; Chemical engineering; Computer science; Nanotechnology; Chromatography; Geology; Composite material; Engineering; Telecommunications","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001774182,0.0002264147,0.0002182231,0.0003678541,0.000172422,0.0002642625,0.0001971882,0.000251361,0.001677838],"category_scores_gemma":[0.0001965916,0.00009866134,0.000297781,0.0003025237,0.0001767937,0.000208264,0.0002376283,0.0002817884,0.0003177219],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002031552,"about_ca_system_score_gemma":0.000276771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001072147,"about_ca_topic_score_gemma":0.001763462,"domain_scores_codex":[0.9998571,0.000008502495,0.000009690839,0.00003843918,0.0000650053,0.00002134779],"domain_scores_gemma":[0.9999136,0.00001526329,0.00003334626,0.000009702955,0.00001784783,0.00001017616],"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":[0.0001587552,0.00002939954,0.0011041,0.000128026,0.000005163272,0.0001366883,0.00003919578,0.0001426945,0.9867606,0.0000699766,0.00004624275,0.01137917],"study_design_scores_gemma":[0.000009171032,0.00061949,0.02024707,0.00001288107,0.00001631278,0.0003938655,0.00005142126,0.0006341605,0.9744967,0.00004374495,0.003466442,0.000008794254],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955826,0.0003241492,0.002766104,0.0000177961,0.00001125519,0.00003257167,0.0001433862,0.00003995513,0.001082132],"genre_scores_gemma":[0.9824566,0.0003872576,0.01084039,0.00004994941,0.000006306568,0.00003344151,0.0003931778,0.0000294452,0.005803418],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001677838,"threshold_uncertainty_score":0.00561291,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01777218155400088,"score_gpt":0.2935666351869092,"score_spread":0.2757944536329083,"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."}}