{"id":"W4239322054","doi":"10.32920/ryerson.14649705.v1","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":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bioleaching; Sewage sludge; Pulp and paper industry; Chemistry; Sewage sludge treatment; Continuous stirred-tank reactor; Sewage; Environmental science; Ferrous; Sewage treatment; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003614397,0.0003268801,0.0004703437,0.0001528555,0.00007485793,0.0002382541,0.0002225305,0.00031626,0.0001025357],"category_scores_gemma":[0.0001013289,0.0003088531,0.0002418948,0.0001082756,0.000007070488,0.0001069521,0.0002308575,0.0005437907,0.00002434995],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001516711,"about_ca_system_score_gemma":0.00002739174,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001286732,"about_ca_topic_score_gemma":0.0003978305,"domain_scores_codex":[0.9985829,0.00004971552,0.0004408854,0.0005326681,0.0001469503,0.0002469097],"domain_scores_gemma":[0.9991153,0.0001037695,0.00008945778,0.0004853767,0.00007203577,0.0001340311],"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":[0.00002152753,0.000038466,0.00009226282,0.00029611,0.0004388374,0.000003230632,0.0005021228,0.1000135,0.8511499,0.0003189705,0.0002911339,0.04683396],"study_design_scores_gemma":[0.0003376876,0.00001246487,0.0002663593,0.0003032605,0.0002191717,0.000007208282,0.0005876673,0.8713183,0.09859932,0.0008425688,0.02657795,0.0009279916],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1654335,0.0003579622,0.8282617,0.00007961296,0.00110774,0.0006797899,0.00009855782,0.0004083572,0.003572783],"genre_scores_gemma":[0.8149937,0.0000339361,0.1829471,0.0002932148,0.0004572066,0.00009756605,0.0008208712,0.00008064207,0.0002758304],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7713048,"threshold_uncertainty_score":0.9999363,"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."}}