{"id":"W1607652717","doi":"10.3390/life5021346","title":"Toxic Cyanobacterial Bloom Triggers in Missisquoi Bay, Lake Champlain, as Determined by Next-Generation Sequencing and Quantitative PCR","year":2015,"lang":"en","type":"article","venue":"Life","topic":"Aquatic Ecosystems and Phytoplankton Dynamics","field":"Environmental Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Université Laval; Institut National de Santé Publique du Québec; Université du Québec à Montréal; National Research Council Canada","funders":"Directorate for Biological Sciences; Fonds Québécois de la Recherche sur la Nature et les Technologies; National Research Council Canada; Université du Québec à Montréal","keywords":"Microcystis; Biology; Eutrophication; Microcystin; Botany; Bay; Nutrient; Phytoplankton; Algal bloom; Bloom; 16S ribosomal RNA; Cyanobacteria; Dominance (genetics); Ecology; Bacteria; Oceanography","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":[0.0002413057,0.000322941,0.0003359756,0.0006383005,0.0005878082,0.0005514606,0.0002380183,0.000346367,0.0005415215],"category_scores_gemma":[0.0003164269,0.000285753,0.0001680714,0.0006613974,0.000284426,0.0002377005,0.0005264971,0.0002893581,0.0001191792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001284702,"about_ca_system_score_gemma":0.001015965,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04219764,"about_ca_topic_score_gemma":0.1001403,"domain_scores_codex":[0.9997097,0.00001888545,0.0000163043,0.00009127389,0.0001283777,0.00003547299],"domain_scores_gemma":[0.999692,0.0000325391,0.0001093575,0.000007466806,0.0001179299,0.00004063941],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000286662,0.00005655962,0.1678472,0.0001084388,0.00002718765,0.0001859898,0.0005600121,0.0002695736,0.8266221,0.00004056994,0.0002001105,0.003795537],"study_design_scores_gemma":[0.000008544694,0.0001594095,0.9723276,0.00001113717,0.0000222525,0.00008943101,0.0004217747,0.001244441,0.02446843,0.00002855419,0.001204199,0.00001418846],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981787,0.0001510053,0.0001832484,0.00004129795,0.00000296349,0.00002606918,0.00083472,0.00001758539,0.0005643585],"genre_scores_gemma":[0.9949131,0.0002174031,0.001229783,0.0001349122,0.000005267659,0.0001282979,0.001690191,0.000007837568,0.001673296],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04219764,"threshold_uncertainty_score":0.08390403,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06359435310854557,"score_gpt":0.2559612819011691,"score_spread":0.1923669287926235,"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."}}