{"id":"W3034416095","doi":"10.1016/j.envpol.2020.114984","title":"Validation of the micro-EROD assay with H4IIE cells for assessing sediment contamination with dioxin-like chemicals","year":2020,"lang":"en","type":"article","venue":"Environmental Pollution","topic":"Toxic Organic Pollutants Impact","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Global Institute for Water Security; University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; Global Water Futures; Canada First Research Excellence Fund; Bundesministerium für Verkehr und Digitale Infrastruktur","keywords":"Environmental chemistry; Sediment; Contamination; Bioassay; Chemistry; Environmental science; Mean squared error; Mathematics; Statistics; Ecology; Geology; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.002289201,0.001438671,0.0008318892,0.0006949817,0.0004843218,0.0008081822,0.001163754,0.001278388,0.001009695],"category_scores_gemma":[0.001641782,0.0005191542,0.0007990135,0.0006345354,0.000727147,0.0005623445,0.0009991475,0.0008760848,0.001331524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004168518,"about_ca_system_score_gemma":0.0006633499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0023463,"about_ca_topic_score_gemma":0.00327622,"domain_scores_codex":[0.9967063,0.001008581,0.0003337677,0.0005482574,0.001177505,0.0002256981],"domain_scores_gemma":[0.9986738,0.0003913563,0.0001276055,0.0002375063,0.0005076244,0.00006207763],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000545293,0.00007261769,0.001319027,0.00004971881,0.00001104938,0.00001902616,0.00002737077,0.0001301198,0.9966774,0.00003890364,0.00003101143,0.001569227],"study_design_scores_gemma":[0.00000706852,0.000468142,0.003259805,0.000009149875,0.00002574215,0.00006856355,0.00004339638,0.001275856,0.9939228,0.0000295558,0.000881361,0.000008597463],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.756869,0.001586355,0.2322292,0.0004137377,0.0003541758,0.001139452,0.003289487,0.000668266,0.003450464],"genre_scores_gemma":[0.7284069,0.002223993,0.2501667,0.0003403938,0.00008113869,0.001336139,0.006946938,0.000137211,0.01036062],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0023463,"threshold_uncertainty_score":0.0121066,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008011445685531084,"score_gpt":0.2043786805795629,"score_spread":0.1963672348940318,"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."}}