{"id":"W2341426508","doi":"10.3808/jei.201500300","title":"Assessing Lead Contamination in Buffalo River Sediments","year":2015,"lang":"en","type":"article","venue":"Journal of Environmental Informatics","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Dredging; Kriging; Contamination; Environmental science; Sediment; Hydrology (agriculture); Pollution; Watershed; Water quality; Geology; Oceanography; Geomorphology; Geotechnical engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002643253,0.0001556721,0.0002729367,0.0007848518,0.0003445931,0.0006790772,0.0001717934,0.0001631449,0.0006521589],"category_scores_gemma":[0.0005525711,0.0001295882,0.0001268145,0.000740113,0.0001859772,0.0002456518,0.0003823586,0.0001302131,0.0001104458],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006021665,"about_ca_system_score_gemma":0.0008848403,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08477633,"about_ca_topic_score_gemma":0.1546174,"domain_scores_codex":[0.9998055,0.00002411098,0.00001140259,0.00003803191,0.00009569914,0.00002527455],"domain_scores_gemma":[0.9997885,0.00004183367,0.00004366494,0.000007400219,0.0001004094,0.00001829519],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002453512,0.0001014389,0.8163978,0.0001058072,0.0001043505,0.000344972,0.0006949831,0.01260622,0.1287781,0.0003192181,0.000283494,0.04001835],"study_design_scores_gemma":[0.00001827104,0.0004346443,0.8915623,0.00003210744,0.0001424758,0.0001556777,0.001618027,0.04023776,0.06162374,0.000466371,0.003664375,0.00004417949],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997547,0.00005844366,0.001463385,0.000006181702,8.201848e-7,0.00001206841,0.0001657764,0.00001731286,0.0007290059],"genre_scores_gemma":[0.9960657,0.0001541586,0.002597007,0.000004708512,9.726882e-7,0.00001068811,0.0002798678,0.000007480985,0.000879524],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08477633,"threshold_uncertainty_score":0.1685658,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02492335311260677,"score_gpt":0.2611684827405994,"score_spread":0.2362451296279926,"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."}}