{"id":"W2090515014","doi":"10.1007/s10811-010-9573-z","title":"Phytoplankton community metrics based on absolute and relative abundance and biomass: implications for multivariate analyses","year":2010,"lang":"en","type":"article","venue":"Journal of Applied Phycology","topic":"Aquatic Ecosystems and Phytoplankton Dynamics","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Museum of Nature; Institut National de la Recherche Scientifique","funders":"Parks Canada","keywords":"Phytoplankton; Abundance (ecology); Temperate climate; Environmental science; Relative species abundance; Biomass (ecology); Metric (unit); Multivariate statistics; Water quality; Nutrient; Ecology; Statistics; Mathematics; Hydrology (agriculture); 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":[0.0182995,0.001495376,0.001824609,0.002468538,0.00114984,0.00283323,0.001100031,0.0006608778,0.001527281],"category_scores_gemma":[0.09785044,0.0006407656,0.001492143,0.003671638,0.001977492,0.003528403,0.00245074,0.002181287,0.0002610992],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000809263,"about_ca_system_score_gemma":0.001262813,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003427085,"about_ca_topic_score_gemma":0.00751711,"domain_scores_codex":[0.9889952,0.007330135,0.0009833967,0.001251638,0.001192825,0.0002468978],"domain_scores_gemma":[0.9477218,0.03870401,0.003573969,0.006462016,0.002657802,0.0008804002],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001070618,0.0004639176,0.4044344,0.0006684618,0.003150307,0.0002209801,0.001479345,0.03261984,0.02429559,0.03262364,0.00590957,0.4930634],"study_design_scores_gemma":[0.0001229965,0.0005822159,0.4661281,0.0002422003,0.0007101471,0.0006511476,0.001052842,0.3537851,0.006963694,0.1657436,0.003627595,0.0003904636],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4040344,0.0009493622,0.5886467,0.0009625974,0.0001787164,0.0002295241,0.001882371,0.0007216152,0.002394727],"genre_scores_gemma":[0.8006085,0.0004274937,0.1963869,0.0001565495,0.0001338311,0.0004581559,0.001003001,0.0003212279,0.0005043542],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0182995,"threshold_uncertainty_score":0.09677821,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03513608529241725,"score_gpt":0.3154951415577709,"score_spread":0.2803590562653537,"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."}}