{"id":"W318450921","doi":"10.2166/wst.2015.226","title":"Enhanced coagulation with in situ manganese dioxide on removal of humic acid in micro-polluted water","year":2015,"lang":"en","type":"article","venue":"Water Science & Technology","topic":"Geochemistry and Elemental Analysis","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Humic acid; Chemistry; Coagulation; Manganese; Permanganate; In situ; Sulfate; Environmental chemistry; Water treatment; Potassium permanganate; Nuclear chemistry; Inorganic chemistry; Environmental engineering; 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":[0.0004472048,0.0001062276,0.0001754476,0.0006325892,0.00005842458,0.00001426072,0.0003795282,0.00008284814,0.00008008598],"category_scores_gemma":[0.00001386943,0.0000600043,0.00001638298,0.001037915,0.0005038574,0.0002049579,0.00003779296,0.0001230613,0.00007686054],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002228509,"about_ca_system_score_gemma":0.00003035659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006076191,"about_ca_topic_score_gemma":0.00521149,"domain_scores_codex":[0.9987755,0.0000185514,0.000213557,0.0003300847,0.0002413164,0.0004209632],"domain_scores_gemma":[0.9996339,0.000004256736,0.00003690513,0.0002308065,0.00004152738,0.0000526086],"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":[0.00006792654,0.00002346185,0.06011563,0.000004551495,0.000002020475,0.00005143979,0.0006608526,0.001503464,0.9356645,0.000005472694,0.000001080371,0.001899607],"study_design_scores_gemma":[0.0003682717,0.000162197,0.01477882,0.00001673937,0.000003516455,0.0000438435,0.0006136058,0.0003496574,0.982792,0.000719062,0.00004942389,0.0001028633],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977172,0.00002903623,0.00003886409,0.000676057,0.00003442797,0.00008142845,0.000002902194,0.00002663441,0.001393439],"genre_scores_gemma":[0.9993058,0.000001648973,0.0004910849,0.00003710177,0.000006179996,0.000001731804,0.00003293057,0.000001458905,0.000122042],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04712751,"threshold_uncertainty_score":0.2908134,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009185768259799405,"score_gpt":0.2034960688736697,"score_spread":0.1943103006138703,"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."}}