{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003694745,0.0006367642,0.0003516143,0.0009955287,0.001010678,0.001724737,0.001854792,0.001349671,0.005964686],"category_scores_gemma":[0.004316163,0.00022446,0.0004821414,0.0008822461,0.001443145,0.001203913,0.001822855,0.00106336,0.001599529],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001113874,"about_ca_system_score_gemma":0.001235488,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004113913,"about_ca_topic_score_gemma":0.004673786,"domain_scores_codex":[0.9976046,0.0008087516,0.000168324,0.0003014042,0.0008374918,0.0002794755],"domain_scores_gemma":[0.9973541,0.0008402268,0.0001534211,0.0004770314,0.000846954,0.0003282778],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005822602,0.004265816,0.01475636,0.0008361529,0.00006225999,0.0009851684,0.007874214,0.02616102,0.02585564,0.004819053,0.004286161,0.9095159],"study_design_scores_gemma":[0.0005031914,0.02382377,0.05969075,0.001794227,0.0001816885,0.00451791,0.02656262,0.05738099,0.2681329,0.01965953,0.537253,0.0004993774],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8946547,0.005507362,0.05201898,0.0009764792,0.00009248232,0.0005497446,0.0002160311,0.000583801,0.04540056],"genre_scores_gemma":[0.9420912,0.004257265,0.03581277,0.0002080066,0.00004691802,0.0001136971,0.0002938869,0.0001604747,0.01701584],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005964686,"threshold_uncertainty_score":0.01995391,"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."}}