{"id":"W3041189593","doi":"","title":"하천 퇴적물 내 중금속 오염도 평가에 관한 연구 (낙동강 수계 표층 퇴적물을 대상으로)","year":2017,"lang":"ko","type":"article","venue":"한국물환경학회지","topic":"Ecology and Conservation Studies","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sediment; Environmental chemistry; Heavy metals; Contamination; Pollution; Environmental science; Silt; Grain size; Tributary; Mineralogy; Chemistry; Metallurgy; Geology; Geography; Geomorphology; Materials science","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":[0.0003114019,0.0001590214,0.0001271567,0.0003903336,0.0003911775,0.0005551126,0.0001396562,0.000206807,0.004580529],"category_scores_gemma":[0.0001754074,0.000107202,0.000223906,0.0003419745,0.0001628011,0.0002485396,0.0003681061,0.0002153113,0.001292102],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003674809,"about_ca_system_score_gemma":0.0005288487,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005592232,"about_ca_topic_score_gemma":0.01228254,"domain_scores_codex":[0.9998323,0.00001738724,0.00001931751,0.00005034097,0.00005663875,0.00002401735],"domain_scores_gemma":[0.9998567,0.00001090165,0.0000475587,0.00001103252,0.00005531883,0.00001842187],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005060874,0.0002518861,0.6228617,0.0006846811,0.00009703825,0.001160725,0.00132021,0.0008017545,0.1309155,0.0008673242,0.004605152,0.235928],"study_design_scores_gemma":[0.00002499152,0.0007415798,0.9044535,0.00005271968,0.00009186683,0.001493227,0.0009636623,0.002157007,0.03990887,0.0004435477,0.04962765,0.00004135443],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9838274,0.001003852,0.004326093,0.0003701964,0.00009333352,0.00007921385,0.0008199565,0.00007547373,0.00940443],"genre_scores_gemma":[0.9562526,0.0009462577,0.01001048,0.0001704152,0.00005054618,0.00008357429,0.001217645,0.00001894229,0.03124965],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005592232,"threshold_uncertainty_score":0.0153234,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06675601078622782,"score_gpt":0.2741095792806407,"score_spread":0.2073535684944128,"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."}}