{"id":"W4367155005","doi":"10.36487/acg_repo/2355_31","title":"Tailings dewatering with the EKS-DT process","year":2023,"lang":"en","type":"article","venue":"Paste/Paste","topic":"Tailings Management and Properties","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Banff Centre; Geomechanica (Canada); University of Alberta","funders":"Innotech Alberta; Alberta Innovates; Sustainable Development Technology Canada; Suncor Energy Incorporated; Natural Resources Canada; Canadian Natural Resources Limited","keywords":"Tailings; Dewatering; Process (computing); Environmental science; Process engineering; Computer science; Metallurgy; Materials science; Engineering; Geotechnical engineering","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":[0.0004366121,0.000407297,0.0003390124,0.000536598,0.0003465007,0.0006948002,0.0006108214,0.0005428365,0.002753288],"category_scores_gemma":[0.0005515663,0.0002450445,0.0005222759,0.0005177811,0.0003099827,0.001141453,0.0009027192,0.0009268117,0.001427074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006400787,"about_ca_system_score_gemma":0.0008475403,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002532311,"about_ca_topic_score_gemma":0.003961483,"domain_scores_codex":[0.9995539,0.00001984621,0.00003220203,0.0000857037,0.0002737857,0.00003462993],"domain_scores_gemma":[0.9998481,0.00002880867,0.00002239181,0.00002340862,0.00006386187,0.00001332631],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002929236,0.0002589178,0.002829594,0.0005253208,0.00002835388,0.000325951,0.0002594209,0.02121359,0.7593946,0.006173368,0.004384595,0.2043134],"study_design_scores_gemma":[0.00009789505,0.0004286749,0.001641224,0.00004613786,0.00003692645,0.0003053295,0.000116053,0.09525232,0.8373665,0.002128155,0.06252836,0.00005241694],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4475674,0.002365037,0.5040376,0.00105184,0.0005201832,0.000868599,0.001638039,0.005714555,0.0362367],"genre_scores_gemma":[0.7875491,0.002015347,0.1757371,0.0003927573,0.00005312003,0.000179242,0.001420317,0.0002797498,0.03237325],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002753288,"threshold_uncertainty_score":0.009210646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01039176338452718,"score_gpt":0.1885739664606312,"score_spread":0.1781822030761041,"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."}}