{"id":"W4246334534","doi":"10.18063/nn.v1i1.378","title":"Designing Paste Thickeners for Copper Flotation Tailings, Using Bed depth Scale-up Factor","year":2018,"lang":"ca","type":"article","venue":"Nanoscience and Nanotechnology","topic":"Tailings Management and Properties","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Tailings; Flocculation; Volume (thermodynamics); Materials science; Copper; Environmental science; Pulp and paper industry; Metallurgy; Environmental engineering; Engineering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003982208,0.0003526806,0.0003683564,0.0004972016,0.0007387107,0.0001803156,0.0004230233,0.0005632528,0.00001937545],"category_scores_gemma":[0.0002591407,0.0003331628,0.00007695211,0.000702768,0.0009958763,0.00051594,0.0001780023,0.0002668532,0.00002929606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000108773,"about_ca_system_score_gemma":0.00009684486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007368118,"about_ca_topic_score_gemma":0.0001403619,"domain_scores_codex":[0.9978388,0.00003475709,0.0004095053,0.0006661635,0.0002368033,0.0008139638],"domain_scores_gemma":[0.999173,0.00009536711,0.0001569016,0.0003042743,0.0001814855,0.000088949],"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":[0.00007069184,0.00001338623,0.001103002,0.0001606034,0.00003012037,0.000001777949,0.001710084,0.0001500842,0.9504055,0.0006061368,0.0001703555,0.0455782],"study_design_scores_gemma":[0.0008931695,0.0006905741,0.0001564764,0.000219924,0.0001041849,0.0000131433,0.001950915,0.07289001,0.9136872,0.0006159217,0.008177564,0.0006009247],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9396636,0.001415759,0.05514977,0.0005049459,0.002095405,0.0006402121,0.00001211545,0.0003829346,0.0001352137],"genre_scores_gemma":[0.9862564,0.000385804,0.01244448,0.0001692471,0.0001994391,0.00002872834,0.000003883079,0.00004876145,0.0004633108],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07273992,"threshold_uncertainty_score":0.999912,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03184793315334474,"score_gpt":0.2614444654968963,"score_spread":0.2295965323435515,"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."}}