{"id":"W3118362308","doi":"10.3390/toxins13010025","title":"Can Cyanobacterial Diversity in the Source Predict the Diversity in Sludge and the Risk of Toxin Release in a Drinking Water Treatment Plant?","year":2021,"lang":"en","type":"article","venue":"Toxins","topic":"Aquatic Ecosystems and Phytoplankton Dynamics","field":"Environmental Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; McGill University; McGill Genome Centre; National Research Council Canada; Polytechnique Montréal","funders":"Groupe de recherche interuniversitaire en limnologie; Génome Québec; National Research Council Canada; Polytechnique Montréal; Natural Sciences and Engineering Research Council of Canada; Université du Québec à Montréal; Genome Canada","keywords":"Microcystis; Cyanobacteria; Biology; Microcystis aeruginosa; Metagenomics; Bloom; Bacteroidetes; Botany; Microcystin; Proteobacteria; Microbiology; Ecology; Bacteria; 16S ribosomal RNA","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":[0.0006343271,0.00009494432,0.0001621048,0.00001662329,0.0002530336,0.0000176053,0.000234384,0.00004273748,0.0001121123],"category_scores_gemma":[0.00002332251,0.00004305091,0.00004028202,0.0001097682,0.0001454084,0.00005779388,0.0007800543,0.0001314688,0.000005189513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001580024,"about_ca_system_score_gemma":0.000009918178,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03831879,"about_ca_topic_score_gemma":0.2217371,"domain_scores_codex":[0.9988866,0.0004203427,0.0001625162,0.0001702002,0.0001799644,0.0001803242],"domain_scores_gemma":[0.9994833,0.0001934759,0.00005956308,0.0002375468,0.000001871998,0.0000242394],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001052042,0.0000869552,0.962033,0.000004595635,0.00001133682,0.00003445102,0.03601493,0.001089369,0.0002040409,0.00009930673,0.00001699296,0.0002998057],"study_design_scores_gemma":[0.002614665,0.00006460139,0.9842882,0.00003129217,0.00004020091,0.00001434641,0.003714954,0.00711923,0.0007807065,0.000633807,0.0005875995,0.0001103558],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982562,0.00001409256,0.000009364914,0.0006568923,0.00005002058,0.0002888716,0.0000781389,0.000003531247,0.0006428711],"genre_scores_gemma":[0.9996838,0.00007843734,0.000006473957,0.0001004004,0.00001699221,0.00000650683,0.00001197418,0.000002933898,0.00009246602],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1834184,"threshold_uncertainty_score":0.9680851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01136097261037005,"score_gpt":0.1845298957126784,"score_spread":0.1731689231023084,"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."}}