{"id":"W2283793672","doi":"10.1007/s11356-016-6207-2","title":"Spatial monitoring of heavy metals in the inland waters of Serbia: a multispecies approach based on commercial fish","year":2016,"lang":"en","type":"article","venue":"Environmental Science and Pollution Research","topic":"Heavy metals in environment","field":"Environmental Science","cited_by":50,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Science and Engineering Research Board; National Research Council Canada; Ministarstvo Prosvete, Nauke i Tehnološkog Razvoja","keywords":"Barbel; Leuciscus; Catfish; Bioconcentration; Pollution; Fishery; Environmental science; Environmental chemistry; Sediment; Ecotoxicology; Contamination; Fish <Actinopterygii>; Biology; Ecology; Chemistry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.005376931,0.0001329717,0.0001826611,0.0001736334,0.0002860107,0.00002144903,0.0005752529,0.00006166141,0.0001966373],"category_scores_gemma":[0.0001905725,0.00007646102,0.00004144655,0.0004815153,0.004727904,0.000274105,0.0003464459,0.0001945763,0.00003438191],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004473661,"about_ca_system_score_gemma":0.00002364968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006060829,"about_ca_topic_score_gemma":0.00001233861,"domain_scores_codex":[0.9960299,0.0004555246,0.0003213064,0.0004211874,0.002273417,0.000498695],"domain_scores_gemma":[0.9992017,0.0002106891,0.00007573834,0.0003929364,0.000004952861,0.0001140049],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001488498,0.0007022221,0.5911657,0.00001398151,0.000004773923,0.000003768961,0.001607868,0.001192329,0.3666652,0.00003655658,0.0002058204,0.03825291],"study_design_scores_gemma":[0.0005093681,0.0002525618,0.9050778,0.00002779767,0.000003154342,0.000001981233,0.0008619396,0.0005508896,0.09144506,0.0000236901,0.001152845,0.00009291091],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963251,0.0000147281,0.0001972633,0.00140537,0.00005206946,0.0004322926,0.00003455671,0.000003346308,0.00153529],"genre_scores_gemma":[0.9990914,0.00008679998,0.0005713884,0.0001092351,0.00002819264,0.00004026246,0.000001185482,0.000007202179,0.00006426094],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3139121,"threshold_uncertainty_score":0.9979807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05690704770116293,"score_gpt":0.3179560467625921,"score_spread":0.2610489990614292,"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."}}