{"id":"W4242532773","doi":"10.32920/ryerson.14649705","title":"Using bioleaching to remove metals from sewage sludge intended for land application","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Metal Extraction and Bioleaching","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bioleaching; Sewage sludge; Pulp and paper industry; Sewage sludge treatment; Chemistry; Environmental science; Sewage; Continuous stirred-tank reactor; Sewage treatment; Ferrous; Waste management; Environmental chemistry; Environmental engineering; Copper","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000200605,0.0009008538,0.0004503763,0.0003990312,0.0002116279,0.0004411499,0.0002143537,0.0003660033,0.0005447857],"category_scores_gemma":[0.0001828388,0.0001615845,0.0005502661,0.0003918699,0.0002573811,0.0002623511,0.0004789531,0.0004227752,0.0003920442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002353507,"about_ca_system_score_gemma":0.0003387013,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008697916,"about_ca_topic_score_gemma":0.002411797,"domain_scores_codex":[0.9996743,0.00005040492,0.00003199999,0.00008515526,0.0001275421,0.00003056654],"domain_scores_gemma":[0.9999173,0.00001189693,0.00002338395,0.000009123604,0.00002668685,0.00001159674],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00001585189,0.00001348455,0.0002133934,0.00007651177,0.000005071252,0.00003408042,0.00001324519,0.000033363,0.9972852,0.00001131758,0.000009070296,0.002289319],"study_design_scores_gemma":[0.000007462515,0.0005220343,0.004141765,0.00001373221,0.0000303728,0.0002329631,0.00005627967,0.0003271786,0.9928902,0.00003362472,0.001732905,0.00001140712],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9734267,0.002292073,0.02225092,0.0001545046,0.00009221861,0.0001536573,0.0003042255,0.000151789,0.001173931],"genre_scores_gemma":[0.9439502,0.004109337,0.04452546,0.0002080426,0.00002574041,0.0001234397,0.001168622,0.00005678289,0.005832356],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009008538,"threshold_uncertainty_score":0.001822472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06038639304625226,"score_gpt":0.3120310327968681,"score_spread":0.2516446397506158,"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."}}