{"id":"W3017664590","doi":"10.1115/icem2001-1262","title":"Stabilisation of Soft Tailings: Practice and Experience","year":2001,"lang":"en","type":"article","venue":"Volume 3: Hazardous Waste; Engineered/Geological Barriers in Disposal Systems; L/ILW; Radioactive Waste From Research/Industries; Spent Fuel/HLW Disposal; Public Involvement; Remediation of Uranium Mining/Milling; LL/ILW; Clearance/Exemption Levels; Mgmt. of Fissile Material; HLW; Dismantling; Reversible/Irreversible Disposal; Waste Avoidance/Minimization; Decontamination; Liquid Waste; Radioactive Waste Processing; Transport of Spent Fuel/HLW; Solid HLW Confinement; QA/QC","topic":"Tailings Management and Properties","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Syncrude (Canada)","funders":"","keywords":"Tailings; Land reclamation; Consolidation (business); Drainage; Tailings dam; Geotechnical engineering; Environmental science; Geology; Mining 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","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.005634614,0.002549744,0.004351837,0.00379276,0.0009521387,0.0006812974,0.002718552,0.00164636,0.001009656],"category_scores_gemma":[0.002967715,0.002684088,0.0007651931,0.005194345,0.002452377,0.005659329,0.0006098758,0.002084814,0.00001944066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001968867,"about_ca_system_score_gemma":0.001692372,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007078938,"about_ca_topic_score_gemma":0.0003778044,"domain_scores_codex":[0.9791873,0.001650217,0.007457341,0.003277242,0.005462934,0.002964956],"domain_scores_gemma":[0.9847578,0.001425839,0.005216773,0.001882491,0.005286922,0.001430221],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"qualitative","study_design_scores_codex":[0.03828311,0.006487248,0.09666587,0.02683765,0.007089722,0.0003934253,0.08863246,0.5672311,0.1502433,0.003500478,0.003786315,0.01084931],"study_design_scores_gemma":[0.02297018,0.007694588,0.005748327,0.0102658,0.0020748,0.00007410525,0.4716276,0.3063146,0.155927,0.0002212397,0.01072265,0.006359188],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9584234,0.00509389,0.02239779,0.001025643,0.003295813,0.006287608,0.002185527,0.0003979041,0.0008924231],"genre_scores_gemma":[0.9865248,0.00477614,0.002294951,0.00007625407,0.001015149,0.0007501579,0.003272522,0.0004077194,0.000882349],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3829951,"threshold_uncertainty_score":0.9999036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03007858645226662,"score_gpt":0.2536482879118613,"score_spread":0.2235697014595947,"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."}}