{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":["metaepi_narrow","insufficient_payload"],"category_scores_codex":[0.002183636,0.002141885,0.002215842,0.00080667,0.002682871,0.0006385742,0.002201927,0.001099045,0.03627183],"category_scores_gemma":[0.0004328861,0.001987792,0.001096186,0.002524529,0.001792959,0.001214332,0.0009116827,0.00174252,0.1284773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002249589,"about_ca_system_score_gemma":0.0003251737,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006642521,"about_ca_topic_score_gemma":0.002796212,"domain_scores_codex":[0.9871073,0.0007269009,0.00228331,0.00283487,0.002826211,0.004221429],"domain_scores_gemma":[0.9940616,0.001298912,0.0008522417,0.002066804,0.0001151825,0.001605234],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005551323,0.0006957662,0.4004118,0.0007292573,0.001560559,0.001534063,0.008335882,0.005210106,0.0004465602,0.0008656522,0.3935028,0.1861525],"study_design_scores_gemma":[0.003646703,0.001472197,0.529517,0.0006044637,0.0008184935,0.0001909518,0.01004872,0.01987917,0.000652032,0.004365491,0.4245795,0.00422525],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7417381,0.02324415,0.000459394,0.01482244,0.01110079,0.003593187,0.003230062,0.002406967,0.1994049],"genre_scores_gemma":[0.9181323,0.0112455,0.0008458216,0.00242739,0.002662431,0.00007506829,0.001703824,0.0001982566,0.06270941],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1819272,"threshold_uncertainty_score":0.9999723,"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."}}