{"id":"W3194171315","doi":"10.3390/su13179554","title":"Microalga-Mediated Tertiary Treatment of Municipal Wastewater: Removal of Nutrients and Pathogens","year":2021,"lang":"en","type":"article","venue":"Sustainability","topic":"Algal biology and biofuel production","field":"Energy","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of British Columbia; Akademie Věd České Republiky; Department of Science and Technology, Ministry of Science and Technology, India; Ministry of Education, India; Department of Biotechnology, Ministry of Science and Technology, India","keywords":"Chlorella sorokiniana; Wastewater; Nitrate; Chemical oxygen demand; Ammonium; Pulp and paper industry; Moving bed biofilm reactor; Nutrient; Sewage treatment; Biomass (ecology); Photobioreactor; Effluent; Nitrogen; Environmental chemistry; Biochemical oxygen demand; Chemistry; Chlorella; Environmental engineering; Algae; Biology; Botany; Environmental science; Bacteria; Agronomy; Biofilm","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001692259,0.0001164532,0.0002476101,0.00003727666,0.00004782713,0.000002801709,0.00005124174,0.0001356673,0.0000526419],"category_scores_gemma":[0.0003207295,0.00009116594,0.00007792607,0.0001445018,0.0002900324,0.00004332687,0.00006564053,0.00004782486,0.000001316928],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000173565,"about_ca_system_score_gemma":0.0001307564,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007501694,"about_ca_topic_score_gemma":0.00008327651,"domain_scores_codex":[0.9989108,0.000231618,0.0002943541,0.0003007796,0.00006944353,0.0001930391],"domain_scores_gemma":[0.9990314,0.00005725335,0.00008902729,0.0003740712,0.0004029464,0.00004529631],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001310261,0.002817506,0.4753394,0.001033721,0.0003224587,0.0003888346,0.005966336,0.0000359085,0.4485269,0.00223648,0.00002904362,0.06199317],"study_design_scores_gemma":[0.001752788,0.0007278173,0.2126555,0.00001598996,0.0001091424,0.0001460259,0.003199819,0.00005007945,0.7522771,0.01222785,0.01660977,0.000228116],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976258,0.001436722,0.000002175118,0.0004502723,0.00009896103,0.0001713725,0.00003216544,0.00001882141,0.0001636919],"genre_scores_gemma":[0.9990068,0.0001689985,0.0001850516,0.00001107582,0.00003618181,0.000008052928,0.0001057643,0.00000612749,0.0004719366],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3037502,"threshold_uncertainty_score":0.3717639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009167388685982738,"score_gpt":0.2402366378420682,"score_spread":0.2310692491560854,"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."}}