{"id":"W2261538152","doi":"","title":"원저 : 통영 수산물 양식 지역의 퇴적물 중금속 함량 측정 연구","year":2013,"lang":"ko","type":"article","venue":"한국폐기물자원순환학회지","topic":"Materials Engineering and Processing","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sediment; Contamination; Environmental science; Loss on ignition; Environmental chemistry; Enrichment factor; Heavy metals; 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":[0.0001815629,0.0001699066,0.0001514943,0.000378591,0.0006436914,0.0005605157,0.0001549831,0.0001951271,0.001869519],"category_scores_gemma":[0.0001748195,0.00010655,0.0001396976,0.0006894269,0.0002735596,0.0002351435,0.0002060045,0.0001201782,0.0007293379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005640938,"about_ca_system_score_gemma":0.0009872491,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01281243,"about_ca_topic_score_gemma":0.03066348,"domain_scores_codex":[0.9998345,0.0000101345,0.00001185066,0.00003431481,0.00007189281,0.00003734163],"domain_scores_gemma":[0.9998449,0.000007632864,0.00004169897,0.000006192516,0.00008396507,0.00001556249],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004320224,0.0001065488,0.6589867,0.0002930812,0.00005597474,0.001278474,0.001491704,0.0007358419,0.2559806,0.0003527828,0.0009873348,0.07929882],"study_design_scores_gemma":[0.00001361176,0.0005346575,0.8912592,0.00001926518,0.00007260881,0.001517423,0.001816745,0.001039734,0.08639973,0.0002252674,0.01706903,0.00003286027],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965104,0.0002009776,0.0007474116,0.00004784994,0.000006375479,0.00001437853,0.0001544746,0.00001126332,0.002306891],"genre_scores_gemma":[0.9910019,0.0002601388,0.001998175,0.00003725411,0.000003780595,0.00001290972,0.0003494939,0.000005561139,0.006330781],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01281243,"threshold_uncertainty_score":0.02547574,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005857265751897003,"score_gpt":0.1822898219782182,"score_spread":0.1764325562263211,"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."}}