{"id":"W1967498598","doi":"10.1016/j.watres.2007.01.051","title":"Chemical treatment of sludge: In-depth study on toxic metal removal efficiency, dewatering ability and fertilizing property preservation","year":2007,"lang":"en","type":"article","venue":"Water Research","topic":"Heavy metals in environment","field":"Environmental Science","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"U.S. Environmental Protection Agency","keywords":"Dewatering; Chemistry; Sewage sludge; Leaching (pedology); Pulp and paper industry; Human decontamination; Hydrogen peroxide; Chloride; Ferric; Reagent; Metal; Sewage; Waste management; Environmental chemistry; Environmental science; Environmental engineering; Inorganic chemistry; Soil water; Organic chemistry","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":[0.0002357804,0.000374081,0.0005626308,0.0002736189,0.0003299032,0.0003409169,0.0001985296,0.0004380899,0.0008636325],"category_scores_gemma":[0.0002970661,0.0001858221,0.000414805,0.0003388951,0.0002314963,0.0002891154,0.0001623802,0.0003192833,0.0001285137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002968968,"about_ca_system_score_gemma":0.0004555836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003115739,"about_ca_topic_score_gemma":0.004229384,"domain_scores_codex":[0.9998392,0.00002662658,0.00001507155,0.0000289505,0.00004916611,0.00004098548],"domain_scores_gemma":[0.9998369,0.00003619132,0.00003678559,0.0000110842,0.00005307435,0.0000259659],"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":[0.00042489,0.00007074995,0.0008528635,0.00009258633,0.000009501331,0.00003914699,0.00005396461,0.0003304907,0.9955702,0.00005488044,0.00002084889,0.002479839],"study_design_scores_gemma":[0.00001638856,0.0009328034,0.004250902,0.000007441011,0.00003115627,0.00005144414,0.00009693351,0.0007997503,0.9930078,0.00004080397,0.0007561226,0.000008471652],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997862,0.0003771723,0.0008924458,0.00002798107,0.0000144857,0.00001756659,0.00007402211,0.000007777461,0.0007264285],"genre_scores_gemma":[0.9971751,0.0004489421,0.0008405327,0.00002654667,0.000009312236,0.000008572586,0.00007868151,0.000006593466,0.00140568],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003115739,"threshold_uncertainty_score":0.006195188,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1168937284403431,"score_gpt":0.3652699293410276,"score_spread":0.2483762009006846,"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."}}