{"id":"W2962825110","doi":"","title":"부산 연안해역의 잔류성 유기오염물질과 중금속 오염평가","year":2016,"lang":"ko","type":"article","venue":"Ocean and Polar Research","topic":"Marine and Coastal Research","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sediment; Environmental chemistry; Pollutant; Contamination; Total organic carbon; Heavy metals; Environmental science; Environmental engineering; Chemistry; Geology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003142779,0.0002164345,0.0001697408,0.0007542806,0.0006995398,0.0007858172,0.0001875714,0.0001718435,0.006299673],"category_scores_gemma":[0.0003195455,0.0001149704,0.0001827239,0.0008817746,0.000225292,0.0002360122,0.0002719972,0.0002202972,0.001505037],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007602796,"about_ca_system_score_gemma":0.0008145366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01830903,"about_ca_topic_score_gemma":0.03812447,"domain_scores_codex":[0.9997514,0.00003416176,0.00001659154,0.00005583894,0.00009567006,0.00004633809],"domain_scores_gemma":[0.9997029,0.00001640083,0.00005842681,0.00001097347,0.0001827142,0.00002858629],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004031988,0.0001827433,0.6504037,0.0005254729,0.0001497656,0.001128039,0.002499588,0.00234434,0.06266298,0.003175975,0.007852843,0.2686714],"study_design_scores_gemma":[0.00001833579,0.0005341278,0.894504,0.00007536637,0.00007679775,0.0007561655,0.002902619,0.003248821,0.01761537,0.001449843,0.07876849,0.00005016596],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9486296,0.0008804245,0.005440574,0.0006296822,0.00003927872,0.0001757725,0.001535045,0.0001281736,0.04254163],"genre_scores_gemma":[0.9504098,0.0007318142,0.008791143,0.0001800593,0.00002179574,0.0001181305,0.002440216,0.00001651363,0.03729057],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01830903,"threshold_uncertainty_score":0.03640491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04985291981159742,"score_gpt":0.3377132091278264,"score_spread":0.287860289316229,"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."}}