{"id":"W1974938846","doi":"10.2134/jeq2004.0307","title":"Bioproduction of Ferric Sulfate Used during Heavy Metals Removal from Sewage Sludge","year":2005,"lang":"en","type":"article","venue":"Journal of Environmental Quality","topic":"Metal Extraction and Bioleaching","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Ferrous; Chemistry; Sewage sludge; Ferric; Effluent; Sulfate; Sewage; Chloride; Phosphorus; Sewage treatment; Wastewater; Pulp and paper industry; Flocculation; Sewage sludge treatment; Waste management; Inorganic chemistry; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000721564,0.0001419652,0.0003283737,0.00009072931,0.00004681375,0.00001497395,0.0001087666,0.00007073927,0.0005140883],"category_scores_gemma":[0.00002666415,0.0001244467,0.0002014083,0.00006449462,0.00004080052,0.0004131975,0.00002327961,0.000295316,0.00003308314],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001907915,"about_ca_system_score_gemma":0.000004362995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002399571,"about_ca_topic_score_gemma":0.000006834819,"domain_scores_codex":[0.9984668,0.0001232019,0.0008006733,0.0001215709,0.0003450726,0.0001426274],"domain_scores_gemma":[0.9993487,0.00003536527,0.0003435823,0.0001724457,0.000005910466,0.00009397612],"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":[0.00006628322,0.0001252846,0.001309746,0.00002206425,0.000107478,0.000007704493,0.0001932745,0.003190061,0.9898717,0.000007072336,0.00002214528,0.00507719],"study_design_scores_gemma":[0.0007374163,0.00004268487,0.2512113,0.00002928085,0.00006054281,0.0001290958,0.0003117224,0.0003586687,0.7418456,0.00003807362,0.005051946,0.000183672],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977579,0.0009695056,0.0004874782,0.0000942991,0.0003819829,0.0000575767,0.00003165393,0.00002276293,0.0001968251],"genre_scores_gemma":[0.9970742,0.0002359133,0.002100372,0.00001626365,0.0003975505,4.118817e-7,0.000006667893,0.00001772445,0.000150875],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2499015,"threshold_uncertainty_score":0.5628906,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02471212661732065,"score_gpt":0.2567139280390109,"score_spread":0.2320018014216903,"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."}}