{"id":"W2768490607","doi":"10.1016/j.jenvman.2017.10.065","title":"Stabilisation and dewatering of primary sludge using ferrate(VI) pre-treatment followed by freeze-thaw in simulated drainage beds","year":2017,"lang":"en","type":"article","venue":"Journal of Environmental Management","topic":"Freezing and Crystallization Processes","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Potassium ferrate; Chemistry; Fecal coliform; Dewatering; Turbidity; Potassium; Chemical oxygen demand; Meltwater; Environmental chemistry; Suspended solids; Pulp and paper industry; Sewage treatment; Environmental engineering; Nuclear chemistry; Wastewater; Environmental science; Ecology; Water quality; Biology; Geology; Organic chemistry","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":[0.0002642585,0.0002623919,0.000370515,0.0001355616,0.0002831387,0.0003563217,0.000253813,0.000296037,0.0007080093],"category_scores_gemma":[0.0003410345,0.0001238881,0.0003117982,0.00009615256,0.0002379248,0.0002410718,0.0001813297,0.000355942,0.0001203306],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000414532,"about_ca_system_score_gemma":0.0003718511,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003852757,"about_ca_topic_score_gemma":0.004946451,"domain_scores_codex":[0.9998987,0.00001523973,0.00001134125,0.00002278883,0.00002293087,0.00002912136],"domain_scores_gemma":[0.9998993,0.00003073543,0.00001879167,0.000008121849,0.0000262104,0.00001684158],"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":[0.0005761535,0.0000663215,0.0006409253,0.00006490947,0.000009532811,0.00004770499,0.00006771593,0.001133551,0.9944851,0.00005492334,0.00004186437,0.002811261],"study_design_scores_gemma":[0.00001551667,0.0003403935,0.001746665,0.000006065531,0.000008171502,0.00001760457,0.0000412991,0.002156534,0.9953451,0.00002912838,0.0002878956,0.000005568837],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993691,0.00007277091,0.0003131278,0.00001537288,0.0000104238,0.000006367979,0.00003762018,0.000008996001,0.0001662914],"genre_scores_gemma":[0.9988081,0.0001034333,0.0004323612,0.00000735207,0.000002311354,0.000005167552,0.00004474833,0.000004057226,0.0005924503],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003852757,"threshold_uncertainty_score":0.007660687,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01012669417412723,"score_gpt":0.2096858162046402,"score_spread":0.199559122030513,"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."}}