{"id":"W2884232848","doi":"10.1186/s12302-018-0152-2","title":"Factors associated with blooms of cyanobacteria in a large shallow lake, China","year":2018,"lang":"en","type":"article","venue":"Environmental Sciences Europe","topic":"Aquatic Ecosystems and Phytoplankton Dynamics","field":"Environmental Science","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Major Science and Technology Program for Water Pollution Control and Treatment; Government of Jiangsu Province; State Administration of Foreign Experts Affairs; Nanjing University; University of Hong Kong; Directorate for Biological Sciences; Chinese Academy of Sciences","keywords":"Phytoplankton; Species evenness; Eutrophication; Ecology; Microcystis; Environmental science; Diversity index; Species richness; Water quality; Microcystis aeruginosa; Plankton; Cyanobacteria; Biology; Nutrient","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000505253,0.0001854991,0.0002150726,0.00004063983,0.0001709762,0.00002411427,0.0004055725,0.00004843581,0.005235647],"category_scores_gemma":[0.00002958776,0.0001292534,0.00003377275,0.0004798295,0.000922494,0.0002581816,0.0002306493,0.00009484645,0.0001792717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008734754,"about_ca_system_score_gemma":0.000009506313,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009065349,"about_ca_topic_score_gemma":0.007325456,"domain_scores_codex":[0.9983348,0.0001052011,0.0002816329,0.000400664,0.0004762637,0.0004014075],"domain_scores_gemma":[0.9994753,0.00003957346,0.0001948865,0.0001960322,0.000001366101,0.00009286709],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000006306304,0.0001923842,0.9944416,0.000001689701,0.00000592027,0.000003940835,0.0006866023,0.0001350938,0.004314446,0.00006340075,0.00002472256,0.0001239353],"study_design_scores_gemma":[0.0003370637,0.0004398538,0.9942436,0.00003169474,0.000006331742,0.000001709199,0.0001259129,0.002360668,0.0007173272,0.00002678365,0.001523251,0.0001857923],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9800948,0.000007152137,0.00006549338,0.00001839511,0.00009053489,0.0001764485,0.00009270464,0.00001614413,0.01943832],"genre_scores_gemma":[0.999348,0.000006025086,0.000103084,0.00004017538,0.00001737303,0.00000349618,0.00002478773,0.00001420174,0.0004427881],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01925326,"threshold_uncertainty_score":0.9956737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01388572602976719,"score_gpt":0.2063287607747693,"score_spread":0.1924430347450021,"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."}}