{"id":"W2946411209","doi":"10.1002/wer.1145","title":"Fate of cellulose in primary and secondary treatment at municipal water resource recovery facilities","year":2019,"lang":"en","type":"article","venue":"Water Environment Research","topic":"Wastewater Treatment and Nitrogen Removal","field":"Environmental Science","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; Jacobs (Canada); Suez (Canada); Trojan Technologies (Canada); Western University","funders":"Research and Development; Natural Sciences and Engineering Research Council of Canada","keywords":"Resource recovery; Resource (disambiguation); Primary (astronomy); Cellulose; Waste management; Water treatment; Environmental science; Chemistry; Wastewater; Engineering; Computer science; Organic chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002348573,0.0002732679,0.0004067377,0.0003707939,0.000575684,0.0008067314,0.0002790124,0.0005208806,0.0008441211],"category_scores_gemma":[0.0002504257,0.0001093335,0.0003527993,0.0004609911,0.0002007157,0.0002731711,0.0003813335,0.0003221695,0.0003676472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009427421,"about_ca_system_score_gemma":0.0005615248,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01320627,"about_ca_topic_score_gemma":0.01541513,"domain_scores_codex":[0.9996697,0.00003054658,0.00001372163,0.00008604812,0.000116973,0.0000830624],"domain_scores_gemma":[0.999816,0.00001972201,0.00004887098,0.00001156208,0.00007309537,0.00003082645],"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":[0.000346309,0.0002092682,0.0347161,0.0001452368,0.00002588546,0.0003350392,0.0003824947,0.001878924,0.9458908,0.00004647551,0.0001246365,0.01589889],"study_design_scores_gemma":[0.00002382234,0.001848451,0.1910834,0.00003092086,0.00005335385,0.0002630407,0.0008615438,0.007049536,0.7971034,0.00006433125,0.001582988,0.00003517539],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993369,0.00003300999,0.0002588184,0.000005934336,7.282918e-7,0.00001106559,0.00007801576,0.00001116383,0.0002643272],"genre_scores_gemma":[0.9973255,0.0001144135,0.001012768,0.00001703627,0.000001524311,0.00002344613,0.0002327993,0.00001044906,0.001261872],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01320627,"threshold_uncertainty_score":0.02625883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02329663051095427,"score_gpt":0.2322773439345081,"score_spread":0.2089807134235538,"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."}}