{"id":"W2002632154","doi":"10.1134/s0097807807060140","title":"Bioindication role of higher plants in the diagnostics of aquatic ecosystems: Case study of small water bodies in St. Petersburg","year":2007,"lang":"en","type":"article","venue":"Water Resources","topic":"Soil and Environmental Studies","field":"Agricultural and Biological Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Russian Foundation for Basic Research","keywords":"Macrophyte; Environmental chemistry; Aquatic plant; Aquatic ecosystem; Environmental science; Biogeochemical cycle; Pollution; Bioaccumulation; Phytoremediation; Biomonitoring; Water pollution; Ceratophyllum demersum; Ecosystem; Ecology; Heavy metals; Chemistry; Biology","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":[0.0001431338,0.0002604671,0.0001819569,0.0007343003,0.0008671134,0.0004208325,0.000215486,0.0004301503,0.0007651125],"category_scores_gemma":[0.0002956782,0.0001759418,0.0001872647,0.0006779956,0.0007652117,0.0002463239,0.0005319351,0.0001919209,0.00008620814],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001146256,"about_ca_system_score_gemma":0.000647705,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0665805,"about_ca_topic_score_gemma":0.1348099,"domain_scores_codex":[0.9998813,0.00002933442,0.000005562743,0.00002687517,0.00001687512,0.00003992895],"domain_scores_gemma":[0.9998419,0.00005986668,0.00003478239,0.00001024198,0.00001697313,0.00003620389],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003516767,0.0004248039,0.8763508,0.0003204509,0.00006974268,0.04307163,0.009777886,0.002053625,0.02275628,0.0009391399,0.0003137502,0.04357021],"study_design_scores_gemma":[0.0000115431,0.0005159932,0.9788028,0.00002410565,0.00004717057,0.004954539,0.008067479,0.001626543,0.003367016,0.0002935177,0.002272216,0.0000169937],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993418,0.00005492326,0.0001126121,0.00001509868,9.997819e-7,0.00001694189,0.00003837887,0.00000174573,0.0004175989],"genre_scores_gemma":[0.9988747,0.0001620698,0.0003897451,0.00001305068,0.000001958081,0.000008678831,0.00003348224,0.000001000814,0.0005153788],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0665805,"threshold_uncertainty_score":0.1323859,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01983845761477627,"score_gpt":0.2072466942143147,"score_spread":0.1874082365995384,"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."}}