{"id":"W1962466166","doi":"","title":"부산시 도심하천 퇴적물의 유기물 및 중금속 오염도 평가","year":2010,"lang":"ko","type":"article","venue":"한국지반환경공학회 논문집","topic":"Ecology and Conservation Studies","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sediment; Total organic carbon; Environmental science; Environmental chemistry; STREAMS; Chemistry; Geology","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":[0.0001685727,0.0002090654,0.0001930579,0.001031962,0.0009609222,0.000931683,0.0001859307,0.0001460134,0.002754074],"category_scores_gemma":[0.0003148729,0.0001472797,0.00013407,0.001829422,0.0002873038,0.0002974646,0.0002249316,0.0001299654,0.0004559868],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001035679,"about_ca_system_score_gemma":0.001333354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02885078,"about_ca_topic_score_gemma":0.1249664,"domain_scores_codex":[0.9997945,0.00002490221,0.00001497154,0.00003120171,0.00009032553,0.00004406176],"domain_scores_gemma":[0.9996991,0.00002395263,0.0001113946,0.00001087151,0.0001249074,0.00002981618],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004296991,0.0001480324,0.880554,0.0004619121,0.00005939063,0.0009312928,0.001614889,0.001249811,0.03764516,0.0005698881,0.001016285,0.07531974],"study_design_scores_gemma":[0.000007513269,0.0001914219,0.9758069,0.0000190434,0.00003573042,0.0005175899,0.002729322,0.0005662172,0.009157507,0.0002422866,0.01070768,0.00001882312],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962189,0.0003423583,0.0005533611,0.00008090369,0.000004104872,0.00001329481,0.0003635337,0.00001407451,0.002409431],"genre_scores_gemma":[0.9924873,0.0005413287,0.001838057,0.00002881138,0.00001218193,0.00001929536,0.001161614,0.000007193613,0.00390406],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02885078,"threshold_uncertainty_score":0.05736572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02315138868722124,"score_gpt":0.2301783282793542,"score_spread":0.207026939592133,"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."}}