{"id":"W2040423470","doi":"10.1016/j.scitotenv.2006.08.022","title":"Do zebra mussels (Dreissena polymorpha) alter lake water chemistry in a way that favours Microcystis growth?","year":2006,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"Aquatic Ecosystems and Phytoplankton Dynamics","field":"Environmental Science","cited_by":69,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Microcosm; Dreissena; Microcystis; Water column; Environmental chemistry; Microcystis aeruginosa; Phytoplankton; Zebra mussel; Biology; Algal bloom; Nitrate; Ecology; Nutrient; Bivalvia; Chemistry; Mollusca; Mussel; Cyanobacteria; Bacteria","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002460273,0.0001814079,0.0002309722,0.000145418,0.0002392948,0.0005724797,0.0001750901,0.0007381099,0.001037059],"category_scores_gemma":[0.0005575944,0.0002624314,0.0001809206,0.0001447058,0.0004435209,0.0005677736,0.0002506143,0.0002082755,0.0003209218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002910766,"about_ca_system_score_gemma":0.0002310145,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00333587,"about_ca_topic_score_gemma":0.01199762,"domain_scores_codex":[0.9999112,0.00001388386,0.000004419997,0.00002107496,0.00001460043,0.00003484852],"domain_scores_gemma":[0.9997472,0.00003087066,0.0001086285,0.00001975555,0.00003926882,0.00005441941],"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":[0.001125623,0.0001804308,0.3987522,0.0001691333,0.0002406736,0.0003028969,0.0005078094,0.0007720458,0.578677,0.0005861004,0.0007325891,0.01795347],"study_design_scores_gemma":[0.00004828224,0.0004016464,0.9636474,0.000005583609,0.00007510548,0.0002690147,0.0009008168,0.001005673,0.03165414,0.0005935463,0.001379429,0.00001946481],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990232,0.0001346994,0.0001494975,0.0002255975,0.000007635397,0.000001835346,0.00004595254,0.000007438321,0.0004041568],"genre_scores_gemma":[0.998901,0.0001728392,0.0001202504,0.0001099513,0.000004354178,0.000002152313,0.00005036939,0.000002595574,0.0006363819],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00333587,"threshold_uncertainty_score":0.006632864,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004657235521114179,"score_gpt":0.1740434252645428,"score_spread":0.1693861897434286,"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."}}