{"id":"W4367154982","doi":"10.36487/acg_repo/2355_26","title":"Improved slurry dewatering via process water conditioning: equipment sizing and tailings storage implications","year":2023,"lang":"en","type":"article","venue":"Paste/˜Pœaste","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":"","keywords":"Dewatering; Tailings; Sizing; Slurry; Conditioning; Waste management; Process (computing); Process engineering; Environmental science; Materials science; Engineering; Computer science; Metallurgy; Environmental engineering; Chemistry; Geotechnical 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":[],"consensus_categories":[],"category_scores_codex":[0.0001975691,0.0002240969,0.0001854079,0.0001745689,0.000274275,0.0001799337,0.0001560419,0.00006175841,0.00006340124],"category_scores_gemma":[0.000009985913,0.0001885441,0.00003970582,0.0001889512,0.00004429058,0.0003542879,0.0001520331,0.0001391111,0.0001476339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004190519,"about_ca_system_score_gemma":0.000005710092,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001370952,"about_ca_topic_score_gemma":0.000008324716,"domain_scores_codex":[0.9987993,0.00001346814,0.0002820522,0.0002850619,0.0001224878,0.0004976825],"domain_scores_gemma":[0.999588,0.00002477685,0.00003549488,0.0002109694,0.000046673,0.00009408518],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002222911,0.00001836815,0.001670011,0.001201966,0.0001621951,0.00001241416,0.008156326,0.02335957,0.9514217,0.0001215827,0.0003110485,0.01354254],"study_design_scores_gemma":[0.001893221,0.0002331589,0.004501805,0.0004059952,0.0002078557,0.00003543396,0.004932598,0.4820571,0.4739425,0.002495983,0.02727395,0.002020425],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9920744,0.0002002071,0.004143795,0.0003559012,0.0002917191,0.0003634095,0.00000774416,0.001043977,0.001518839],"genre_scores_gemma":[0.9981669,0.00004208479,0.0001808736,0.0000485397,0.0001134783,0.0001851184,0.00006948387,0.00006537268,0.001128147],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4774793,"threshold_uncertainty_score":0.7688605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01389477537737017,"score_gpt":0.2183992027386445,"score_spread":0.2045044273612744,"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."}}