{"id":"W4403220180","doi":"10.1016/j.jenvman.2024.122687","title":"Spatiotemporal insights of phytoplankton dynamics in a northern, rural-urban lake using a 3D water quality model","year":2024,"lang":"en","type":"article","venue":"Journal of Environmental Management","topic":"Aquatic Ecosystems and Phytoplankton Dynamics","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"GDG Environnement; Institut National de la Recherche Scientifique","funders":"Mitacs","keywords":"Phytoplankton; Water quality; Environmental science; Ecology; Geography; Oceanography; Geology; Nutrient; Biology","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":[0.0001287933,0.0003073847,0.0003941931,0.0004003219,0.0004972377,0.000677961,0.0006368094,0.0008760648,0.001593678],"category_scores_gemma":[0.0004005242,0.0003446197,0.0006616546,0.000684172,0.000425981,0.0004442761,0.0005867229,0.0003442294,0.000127048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001133087,"about_ca_system_score_gemma":0.00145394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1954491,"about_ca_topic_score_gemma":0.155738,"domain_scores_codex":[0.9999365,0.00000980528,0.000004749715,0.00002006126,0.00001016403,0.00001879048],"domain_scores_gemma":[0.9998859,0.00003222821,0.00001992773,0.00001060702,0.00002493852,0.00002644375],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005545159,0.00007220308,0.01085354,0.00001362423,0.00002735966,0.00009665776,0.00005262222,0.984184,0.00217636,0.0003268917,0.000247513,0.001893686],"study_design_scores_gemma":[0.00001226757,0.0000116137,0.004096276,0.000001281617,0.000007300694,0.00000532713,0.00002719888,0.9956021,0.00008101013,0.00007255637,0.00007541575,0.000007647101],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9915146,0.0000385455,0.005408378,0.0001635448,0.00000955937,0.00001887627,0.0008454901,0.0001612828,0.001839778],"genre_scores_gemma":[0.997544,0.00003922901,0.00155131,0.00001223806,0.000003756162,0.00001678495,0.0002825198,0.00001240564,0.0005377854],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1954491,"threshold_uncertainty_score":0.3886229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01000069309859122,"score_gpt":0.227605277138661,"score_spread":0.2176045840400697,"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."}}