{"id":"W2269545180","doi":"10.1039/c5ra23889g","title":"Accelerated co-precipitation of lead, zinc and copper by carbon dioxide bubbling in alkaline municipal solid waste incinerator (MSWI) fly ash wash water","year":2016,"lang":"en","type":"article","venue":"RSC Advances","topic":"Recycling and utilization of industrial and municipal waste in materials production","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Fly ash; Precipitation; Zinc; Effluent; Chemistry; Copper; Carbon dioxide; Environmental chemistry; Coprecipitation; Incineration; Inorganic chemistry; Nuclear chemistry; Waste management; Environmental science; Environmental engineering","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":[0.0002992566,0.0001721385,0.0002953543,0.0001129836,0.00004406742,0.00001978321,0.00009439532,0.0001182701,0.00001829587],"category_scores_gemma":[0.00007304046,0.0001142881,0.00002315688,0.0001152555,0.00005995747,0.0003228234,0.0000259459,0.00008975041,0.000004938963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003660552,"about_ca_system_score_gemma":0.000007874562,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006963437,"about_ca_topic_score_gemma":0.00005702947,"domain_scores_codex":[0.9988636,0.00006718974,0.0004804659,0.0002132951,0.0001348253,0.0002406198],"domain_scores_gemma":[0.9996105,0.00005734444,0.00007090336,0.000143077,0.00007230998,0.00004584091],"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":[0.00008082778,0.00001901413,0.0003017133,0.0000642777,0.00001517696,6.866975e-7,0.0003607502,0.01804891,0.9756863,0.00001189127,0.0001251036,0.005285337],"study_design_scores_gemma":[0.0009838634,0.00007377329,0.00003730767,0.0002154036,0.00001072102,0.000001916258,0.0002912269,0.004293832,0.9880368,0.0001338427,0.005733336,0.0001879456],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976569,0.000855314,0.00009737237,0.0001150719,0.0006532616,0.0001514917,0.00002592695,0.00007968312,0.0003649792],"genre_scores_gemma":[0.9970164,0.001979283,0.0001470328,0.00001215313,0.000252886,0.00001707885,0.00005208815,0.00002733356,0.0004957088],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01375508,"threshold_uncertainty_score":0.4660534,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02367343820833377,"score_gpt":0.2775952040459549,"score_spread":0.2539217658376212,"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."}}