{"id":"W3184275331","doi":"","title":"원저 : 부산 남항 퇴적물의 오염도 평가 연구","year":2013,"lang":"ko","type":"article","venue":"한국폐기물자원순환학회지","topic":"Agriculture, Soil, Plant Science","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Dredging; Sediment; Environmental science; Environmental chemistry; Loss on ignition; Contamination; Pollution; Heavy metals; Geology; Chemistry; Oceanography; Ecology","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":[0.0005149335,0.0006836037,0.0006151826,0.00004290462,0.0009336101,0.0007838692,0.001842554,0.000556875,0.004647553],"category_scores_gemma":[0.0002135513,0.0002597021,0.0003511122,0.001417639,0.0005487443,0.001052529,0.0005398086,0.0006327021,0.01797946],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000116067,"about_ca_system_score_gemma":0.00004980168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003022194,"about_ca_topic_score_gemma":0.0008354367,"domain_scores_codex":[0.9951024,0.0002336168,0.0007119234,0.001320937,0.001055518,0.001575621],"domain_scores_gemma":[0.9977905,0.0004266748,0.0003753645,0.0003297437,0.0003103978,0.0007673448],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00004019104,0.0008903798,0.1824677,0.00007990323,0.000108701,0.0000823139,0.00122635,0.000036297,0.04684856,0.004807476,0.6649378,0.09847438],"study_design_scores_gemma":[0.0003401064,0.0005816768,0.8631182,0.0001411373,0.00005777067,0.0001170913,0.001914085,0.0005036711,0.003076485,0.002550828,0.1263207,0.001278209],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.956278,0.0007190723,0.00000721426,0.01135419,0.001451025,0.0008925896,0.0001458948,0.0002775936,0.02887437],"genre_scores_gemma":[0.9520723,0.0003601646,0.0001847091,0.001423715,0.001776328,0.00007359578,0.0001227824,0.000005285607,0.04398118],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6806505,"threshold_uncertainty_score":0.9999855,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01454525471140843,"score_gpt":0.1919809313573285,"score_spread":0.17743567664592,"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."}}