{"id":"W2153134928","doi":"10.1080/15320383.2013.750268","title":"Metal Speciation and Contamination in Dredged Harbor Sediments from Kaohsiung Harbor, Taiwan","year":2013,"lang":"en","type":"article","venue":"Soil and Sediment Contamination An International Journal","topic":"Heavy metals in environment","field":"Environmental Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Research Council Canada","keywords":"Contamination; Environmental chemistry; Sediment; Genetic algorithm; Environmental science; Enrichment factor; Organic matter; Metal; Extraction (chemistry); Carbonate; Heavy metals; Metallurgy; Chemistry; Geology; Ecology; Materials science; Biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007353156,0.0002169527,0.0002049984,0.0001547725,0.0001532706,0.0002470131,0.0002286147,0.0001051787,0.003691381],"category_scores_gemma":[0.00009179045,0.0002102299,0.00004321791,0.00008501095,0.0001395432,0.00201112,0.0001496504,0.0002751254,0.0001407225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006659628,"about_ca_system_score_gemma":0.00001784292,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006132949,"about_ca_topic_score_gemma":0.0001819796,"domain_scores_codex":[0.9976254,0.0002268699,0.0005532099,0.0004047503,0.0009322219,0.0002575797],"domain_scores_gemma":[0.9992166,0.00006958808,0.0002860377,0.0001322579,0.00005767959,0.0002379067],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001071252,0.0008797294,0.6717986,0.000006173938,0.0002220797,0.0000636249,0.00432806,0.0003541671,0.07847657,0.001672221,0.0005787192,0.2415129],"study_design_scores_gemma":[0.002094893,0.0001291093,0.9772266,0.00002881768,0.00002609883,0.00001571639,0.0004819219,0.01292309,0.003242421,0.000778891,0.002816708,0.0002356975],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939789,0.00008576976,0.001295771,0.002033166,0.0007792441,0.0003168249,0.00001391293,0.00002043751,0.00147602],"genre_scores_gemma":[0.997142,0.0002317913,0.001179193,0.0007149552,0.0002586288,0.00004459476,0.00005459696,0.0000187014,0.0003555953],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3054281,"threshold_uncertainty_score":0.9972194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008944885967435796,"score_gpt":0.2332110577251926,"score_spread":0.2242661717577568,"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."}}