{"id":"W4319748793","doi":"10.3389/fmicb.2023.1073753","title":"Spatio-temporal connectivity of the aquatic microbiome associated with cyanobacterial blooms along a Great Lake riverine-lacustrine continuum","year":2023,"lang":"en","type":"article","venue":"Frontiers in Microbiology","topic":"Microbial Community Ecology and Physiology","field":"Environmental Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Institut National de la Recherche Scientifique; Ministry of the Environment, Conservation and Parks; University of Windsor; National Research Council Canada; University of Calgary; Trent University; McMaster University; Environment and Climate Change Canada","funders":"National Institute of Environmental Health Sciences; Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Watershed; Environmental science; Ecology; Lake ecosystem; Bloom; Aquatic ecosystem; Algal bloom; Phytoplankton; Metagenomics; Ecosystem; Geography; Nutrient; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0001837839,0.0001002402,0.0001975401,0.0006644549,0.0003690954,0.0005376555,0.0001401549,0.0002482036,0.0007253254],"category_scores_gemma":[0.0004768544,0.0001253314,0.000183594,0.0009827572,0.0003384174,0.0002377255,0.0007643838,0.000231798,0.00008236997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005701235,"about_ca_system_score_gemma":0.0005184631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06269959,"about_ca_topic_score_gemma":0.1544008,"domain_scores_codex":[0.9998608,0.00001771501,0.000007106479,0.00005319541,0.00001810466,0.00004298739],"domain_scores_gemma":[0.9996462,0.00007719437,0.000116457,0.00001785557,0.00007630332,0.00006604358],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001505065,0.00001744238,0.9766014,0.0000413472,0.00007422882,0.0001701283,0.001561073,0.0003198916,0.01710209,0.00007971067,0.0001857786,0.003696512],"study_design_scores_gemma":[8.491579e-7,0.000009438219,0.9992206,0.000002515029,0.000004279188,0.00001781479,0.0004538482,0.000108368,0.00007280654,0.00000801722,0.00009946207,0.000002033282],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995711,0.00003226438,0.00003867772,0.00001414581,4.651119e-7,0.000001618705,0.0002126354,0.00000275162,0.0001262618],"genre_scores_gemma":[0.9992269,0.00003014137,0.00012331,0.00001694041,0.000001033299,0.000007008664,0.0003893079,0.000001450926,0.000203914],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06269959,"threshold_uncertainty_score":0.1246693,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007057331614995011,"score_gpt":0.1920619891885224,"score_spread":0.1850046575735274,"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."}}