{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005931988,0.0001008403,0.0001539598,0.00007462601,0.00003462539,0.00005259172,0.0001459567,0.00004854884,0.000175035],"category_scores_gemma":[0.00005354173,0.00009055611,0.00003660498,0.00008259936,0.0001154886,0.001467673,0.0001141303,0.0001720247,0.0001761936],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000574345,"about_ca_system_score_gemma":0.00001456523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003038995,"about_ca_topic_score_gemma":0.000005632502,"domain_scores_codex":[0.9986031,0.00002932874,0.0006235105,0.00004556203,0.0005269824,0.0001715013],"domain_scores_gemma":[0.9992869,0.00003761293,0.0004637717,0.00008406343,0.000005063521,0.0001225692],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007238115,0.0007513079,0.7611175,0.00003499415,0.00005768971,0.0001416599,0.0275604,0.02338265,0.004348811,0.0001093561,0.01039357,0.1720296],"study_design_scores_gemma":[0.00350069,0.0003875861,0.9239805,0.0001026312,0.00004246194,0.0002154896,0.01755117,0.02781997,0.0009934112,0.001434647,0.02359246,0.000378924],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9872215,0.00003637001,0.004440132,0.00003830114,0.0002352978,0.00007738157,0.000004874705,0.000003300534,0.007942825],"genre_scores_gemma":[0.986883,0.00003436184,0.01272264,0.0002266488,0.00002845249,8.833064e-7,0.000005892629,0.000006836357,0.00009122788],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1716507,"threshold_uncertainty_score":0.3692771,"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."}}