{"id":"W3021200102","doi":"10.20886/jklh.2020.14.1.43-52","title":"KANDUNGAN MERKURI DALAM BEBERAPA MEDIA SEKITAR PENAMBANGAN EMAS SKALA KECIL (PESK) DI KALIMANTAN TENGAH","year":2020,"lang":"id","type":"article","venue":"Jurnal Ecolab","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mercury (programming language); Water quality; Environmental science; National standard; Quality standard; Mercury contamination; Sediment; Contamination; Environmental chemistry; Fishery; Chemistry; Ecology; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007020367,0.0007600433,0.0009369952,0.00009504328,0.001069804,0.0002957649,0.000794463,0.0002836642,0.00422965],"category_scores_gemma":[0.0004979086,0.0006867085,0.0004076704,0.0008118542,0.0006031482,0.0008583714,0.0006069936,0.001040174,0.004721672],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000402911,"about_ca_system_score_gemma":0.0001526901,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001366071,"about_ca_topic_score_gemma":0.0006553772,"domain_scores_codex":[0.9950395,0.0003545092,0.001045858,0.0009674832,0.001387494,0.001205118],"domain_scores_gemma":[0.9971905,0.000344699,0.0004959617,0.0005072241,0.000076622,0.001384994],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008516538,0.001872526,0.41427,0.0007307991,0.002078854,0.001563584,0.1486434,0.0003503257,0.196377,0.001762897,0.1996475,0.03185151],"study_design_scores_gemma":[0.004225646,0.001017419,0.7035406,0.0002018109,0.0006849566,0.0001694004,0.007532651,0.0009910088,0.0244312,0.0001867951,0.2550498,0.001968689],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9537016,0.001592641,0.0000572388,0.01313802,0.001452634,0.0007612646,0.0002586123,0.0001537354,0.0288843],"genre_scores_gemma":[0.9886917,0.001787756,0.0001802053,0.004104998,0.001153757,0.00003192985,0.00006983909,0.00008933518,0.003890475],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2892707,"threshold_uncertainty_score":0.9995584,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02695703851605668,"score_gpt":0.2435784943437691,"score_spread":0.2166214558277124,"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."}}