{"id":"W3005140969","doi":"10.1016/j.mineng.2020.106253","title":"Effect of particle size on the flocculation of sub-micron titanium dioxide by polyacrylic acid","year":2020,"lang":"en","type":"article","venue":"Minerals Engineering","topic":"Coagulation and Flocculation Studies","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; China Scholarship Council; University of Alberta","keywords":"Flocculation; Polyacrylic acid; Settling; Titanium dioxide; Particle size; Polymer; Materials science; Particle-size distribution; Particle (ecology); Chemical engineering; Chromatography; Chemistry; Analytical Chemistry (journal); Composite material; Environmental engineering; Environmental science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001323552,0.00008484387,0.0001286228,0.000006673314,0.00002412831,0.000004502691,0.00006596592,0.00002089717,0.0001675602],"category_scores_gemma":[0.0001890758,0.00006110438,0.00004329553,0.0002144636,0.00002735677,0.0000512269,0.00004550155,0.00004154148,0.00003028176],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001821101,"about_ca_system_score_gemma":9.785425e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001884371,"about_ca_topic_score_gemma":0.000001597701,"domain_scores_codex":[0.9994489,0.00002131682,0.0001693472,0.0001050881,0.000158862,0.00009651131],"domain_scores_gemma":[0.999632,0.0001764927,0.00004912142,0.0001021905,0.000005881642,0.00003432838],"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":[0.00001714265,0.000006307668,0.006530597,0.00001279613,0.000008496911,1.514427e-7,0.0001427622,0.03887673,0.9528446,0.0000741775,0.001150732,0.0003355132],"study_design_scores_gemma":[0.0001824183,0.00008308575,0.02714283,0.00000768375,0.000009575383,2.001613e-7,0.000006406393,0.04802325,0.9236282,8.686216e-7,0.0008527485,0.000062732],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964243,0.00007370153,0.002308408,0.0007523856,0.00002804325,0.000128767,0.000005339587,0.00002643372,0.0002526552],"genre_scores_gemma":[0.9997134,0.000004173573,0.00008490839,0.00009520145,0.00001838833,0.000007267451,0.000001980751,0.000008098148,0.0000666211],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02921639,"threshold_uncertainty_score":0.2491764,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007286095716566895,"score_gpt":0.1982282313125441,"score_spread":0.1909421355959772,"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."}}