{"id":"W2328353438","doi":"10.1021/sc400289z","title":"Heavy Metal Removal (Copper and Zinc) in Secondary Effluent from Wastewater Treatment Plants by Microalgae","year":2013,"lang":"en","type":"article","venue":"ACS Sustainable Chemistry & Engineering","topic":"Algal biology and biofuel production","field":"Energy","cited_by":144,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Canada Research Chairs","keywords":"Effluent; Chlorella vulgaris; Wastewater; Sewage treatment; Scenedesmus; Zinc; Chlorella; Biosorption; Chemistry; Secondary treatment; Environmental chemistry; Pulp and paper industry; Copper; Algae; Microorganism; Chlorophyceae; Botany; Biology; Environmental engineering; Environmental science; Chlorophyta; Adsorption; Bacteria","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":[0.0000543252,0.0002573226,0.0002383893,0.0000316866,0.00006127633,0.00004086268,0.00009435217,0.0002148995,0.0002784916],"category_scores_gemma":[0.0000224202,0.000223279,0.00003748305,0.0000662523,0.00003855349,0.0002061383,0.00007909167,0.0001934084,0.00002377599],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002608699,"about_ca_system_score_gemma":0.00002730905,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002773422,"about_ca_topic_score_gemma":0.000003425822,"domain_scores_codex":[0.9988193,0.00001306693,0.000215773,0.0003986564,0.00006234034,0.0004908813],"domain_scores_gemma":[0.9995984,0.00002721208,0.00003396783,0.0002223156,0.00002835556,0.00008969558],"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":[0.00003814292,0.000054547,0.0002719747,0.0001158272,0.00008841999,0.00009010624,0.0002294535,0.0004087744,0.9968632,0.00002119775,0.0004291252,0.001389204],"study_design_scores_gemma":[0.0006427621,0.00003308028,0.0006552329,0.00001721692,0.00001614734,0.00006821348,0.0007905827,0.0001332294,0.9600495,0.0001350933,0.03719692,0.0002619924],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9940476,0.004292398,0.000002476797,0.0002169969,0.00006899547,0.0001561219,0.00001459255,0.000078917,0.001121858],"genre_scores_gemma":[0.9930452,0.0001323219,0.000179163,0.00002700522,0.0001457967,0.00006121603,0.0002512978,0.00002669242,0.006131323],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0368137,"threshold_uncertainty_score":0.9105052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003954993131970375,"score_gpt":0.1757970916757405,"score_spread":0.1718420985437701,"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."}}