{"id":"W4385312044","doi":"10.24852/2411-7374.2023.2.38.44","title":"ИСПОЛЬЗОВАНИЕ ИНДЕКСОВ ЗАГРЯЗНЕННОСТИ ВОДЫ ДЛЯ ОЦЕНКИ МНОГОЛЕТНЕЙ ИЗМЕНЧИВОСТИ СОСТОЯНИЯ ВИСЛИНСКОГО ЗАЛИВА","year":2023,"lang":"ru","type":"article","venue":"Российский журнал прикладной экологии","topic":"Aquatic and Environmental Studies","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Phytoplankton; Eutrophication; Oceanography; Environmental science; Water quality; Estuary; Fishery; Ecology; Biology; Geology; Nutrient","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005789739,0.0008897947,0.0007438755,0.003214715,0.005767034,0.0170207,0.001768319,0.003554821,0.06539029],"category_scores_gemma":[0.01317553,0.0009095888,0.001062562,0.003688359,0.006560081,0.007497122,0.005937879,0.004442184,0.0194998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009376388,"about_ca_system_score_gemma":0.02154232,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02759635,"about_ca_topic_score_gemma":0.03466457,"domain_scores_codex":[0.9895439,0.002814779,0.0005362259,0.001421297,0.004527274,0.001156439],"domain_scores_gemma":[0.9920947,0.002016603,0.0005830318,0.001224582,0.003090292,0.0009908015],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0001071499,0.0001085257,0.003484515,0.0006588015,0.00004812172,0.0004645971,0.006216762,0.001078159,0.002299446,0.7977026,0.05858824,0.1292431],"study_design_scores_gemma":[0.00002063108,0.00003322927,0.003610081,0.0004912639,0.00003353344,0.0003069217,0.003837612,0.000746005,0.001643287,0.1095429,0.8796542,0.00008029868],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01737289,0.007490986,0.04885173,0.02489072,0.001588672,0.0003237367,0.001505874,0.0005882696,0.897387],"genre_scores_gemma":[0.4898554,0.01668531,0.09358371,0.005378275,0.001186156,0.001195926,0.002755,0.001300358,0.3880598],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06539029,"threshold_uncertainty_score":0.2187523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02763176312846976,"score_gpt":0.2002180548086898,"score_spread":0.17258629168022,"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."}}