{"id":"W2055917258","doi":"10.1016/j.envres.2013.02.008","title":"Mercury in food items from the Idrija Mercury Mine area","year":2013,"lang":"en","type":"article","venue":"Environmental Research","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":44,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Research Council Canada; European Commission","keywords":"Mercury (programming language); Dry weight; Environmental chemistry; Contaminated food; Smelting; Mushroom; Chemistry; Contamination; Food contaminant; Environmental science; Food science; Horticulture; Biology; Ecology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002088819,0.0003405244,0.000296832,0.001963023,0.0007778628,0.0006600366,0.000309846,0.0004894891,0.001513488],"category_scores_gemma":[0.0003833848,0.0002451354,0.0004320782,0.001792056,0.0004573634,0.0002186038,0.0005700975,0.0002250603,0.0005447058],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005140775,"about_ca_system_score_gemma":0.0003665614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02488138,"about_ca_topic_score_gemma":0.04697231,"domain_scores_codex":[0.9997382,0.00004361517,0.00002329252,0.00006147418,0.00007779287,0.00005569412],"domain_scores_gemma":[0.9998471,0.00002854726,0.00003936656,0.000009868736,0.00005793992,0.0000172572],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009539467,0.0002210669,0.9204023,0.0003618234,0.0003960622,0.002127459,0.006891249,0.0002190923,0.0471242,0.000107564,0.0004512027,0.02074414],"study_design_scores_gemma":[0.000003572103,0.000147253,0.9930639,0.00001699048,0.00005589841,0.0004564901,0.003211688,0.00005144479,0.001983775,0.00002347011,0.0009785021,0.000006963636],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990108,0.0001254916,0.00003435841,0.00001061923,0.000003203902,0.000002825447,0.0002294804,0.000001103645,0.0005820612],"genre_scores_gemma":[0.9971276,0.0003508332,0.0001885234,0.00002649364,0.00000605934,0.000006616073,0.0004636447,0.000004580696,0.001825577],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02488138,"threshold_uncertainty_score":0.04947311,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06077411976367352,"score_gpt":0.3093318598041134,"score_spread":0.2485577400404398,"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."}}