{"id":"W2046077477","doi":"10.1007/s11252-015-0457-5","title":"Assessing aquatic biodiversity of zooplankton communities in an urban landscape","year":2015,"lang":"en","type":"article","venue":"Urban Ecosystems","topic":"Aquatic Ecosystems and Phytoplankton Dynamics","field":"Environmental Science","cited_by":55,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; GDG Environnement; Université du Québec à Montréal","funders":"Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Biodiversity; Zooplankton; Littoral zone; Ecology; Species richness; Aquatic biodiversity research; Habitat; Urban ecology; Aquatic ecosystem; Biomass (ecology); Geography; Environmental science; 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":[0.0006804107,0.0003072582,0.0002714301,0.002246048,0.0006027966,0.0008049541,0.0003799361,0.0003252569,0.0005243262],"category_scores_gemma":[0.001414906,0.0002102336,0.0003506983,0.001752522,0.0004302783,0.0008462988,0.0009448468,0.0001546439,0.00005818642],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001066634,"about_ca_system_score_gemma":0.0005447854,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01944233,"about_ca_topic_score_gemma":0.06996124,"domain_scores_codex":[0.9996093,0.0001786146,0.00001903493,0.00005106653,0.00007776015,0.00006415742],"domain_scores_gemma":[0.99936,0.0002303073,0.000168855,0.00002788663,0.00009290563,0.0001200911],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000171928,0.0001367456,0.9700091,0.0000470906,0.0002242656,0.0001147666,0.0002912027,0.01488698,0.003779071,0.0002057049,0.00005280158,0.01008022],"study_design_scores_gemma":[0.000008448246,0.0002150525,0.9600562,0.000007922185,0.00008010575,0.00007500363,0.001782017,0.03630836,0.0009062998,0.0004013206,0.0001479179,0.0000113444],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995021,0.00001736614,0.0002528208,0.000003751721,2.391611e-7,0.000004634706,0.00004737889,0.000001604948,0.0001700729],"genre_scores_gemma":[0.9992748,0.00002292572,0.0005440394,0.000001716799,5.61824e-7,0.000005431581,0.00007840599,7.580874e-7,0.00007132073],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01944233,"threshold_uncertainty_score":0.03865832,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03803026620503178,"score_gpt":0.245641402210955,"score_spread":0.2076111360059232,"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."}}