{"id":"W2089555454","doi":"10.1007/s00244-012-9752-9","title":"Laboratory Toxicity and Benthic Invertebrate Field Colonization of Upper Columbia River Sediments: Finding Adverse Effects Using Multiple Lines of Evidence","year":2012,"lang":"en","type":"article","venue":"Archives of Environmental Contamination and Toxicology","topic":"Environmental Toxicology and Ecotoxicology","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Canada Excellence Research Chairs, Government of Canada; U.S. Environmental Protection Agency","keywords":"Hyalella azteca; Midge; Sediment; Benthic zone; Environmental science; Ecotoxicology; Environmental chemistry; Total organic carbon; Effluent; Pollution; Hydrology (agriculture); Geology; Environmental engineering; Amphipoda; Ecology; Oceanography; Chemistry; Biology; Geotechnical engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006444873,0.0004542187,0.0002374231,0.0006286018,0.001036528,0.0008319788,0.0004093924,0.0005026909,0.001110435],"category_scores_gemma":[0.001478561,0.0003191373,0.0002300364,0.000392239,0.001201925,0.0003099142,0.0004005024,0.0005575845,0.0001105405],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001878316,"about_ca_system_score_gemma":0.002161634,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1462073,"about_ca_topic_score_gemma":0.3856611,"domain_scores_codex":[0.9993018,0.0001584365,0.00004442535,0.0001502916,0.0002387595,0.0001062538],"domain_scores_gemma":[0.9983342,0.0003553685,0.0004552511,0.0001906195,0.0003896621,0.0002749098],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002627152,0.001221315,0.8633172,0.00008026918,0.0003112629,0.0002841562,0.0004554677,0.0003381072,0.1205718,0.0001114236,0.0003083066,0.0103735],"study_design_scores_gemma":[0.00002384521,0.001668934,0.9839459,0.00001146236,0.0001053498,0.0001720587,0.0004012619,0.0001946376,0.01308888,0.00004848754,0.0003277377,0.00001147727],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991564,0.0001177482,0.0001175749,0.00001982249,0.000002155939,0.000008803771,0.00005136485,0.00000325156,0.0005229902],"genre_scores_gemma":[0.9984323,0.0001398407,0.0002007034,0.00004899571,0.000003240246,0.00001334198,0.0001387278,0.000002210737,0.001020671],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1462073,"threshold_uncertainty_score":0.2907125,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01920147245646394,"score_gpt":0.2474786032840197,"score_spread":0.2282771308275557,"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."}}