{"id":"W2968392249","doi":"10.1002/etc.4568","title":"Context-Dependent Responses of Aquatic Insects to Metals and Metal Mixtures: A Quantitative Analysis Summarizing 24 Yr of Stream Mesocosm Experiments","year":2019,"lang":"en","type":"article","venue":"Environmental Toxicology and Chemistry","topic":"Freshwater macroinvertebrate diversity and ecology","field":"Environmental Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. Geological Survey; Colorado Parks and Wildlife; Colorado State University; Rio Tinto; National Institute of Environmental Health Sciences; International Zinc Association; U.S. Environmental Protection Agency","keywords":"Mesocosm; Abiotic component; Context (archaeology); Cadmium; Environmental chemistry; Ecology; Aquatic ecosystem; Chironomidae; Community structure; Aquatic insect; STREAMS; Biology; Environmental science; Chemistry; Ecosystem; Larva","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":[0.001191892,0.0003720534,0.0005714556,0.0005135725,0.0004398842,0.0003878917,0.0002238336,0.0002591412,0.0003719502],"category_scores_gemma":[0.0009371771,0.0001745938,0.0005022963,0.0003436895,0.0003236444,0.0002702168,0.0005425378,0.0003980024,0.0001034608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004672278,"about_ca_system_score_gemma":0.0002237361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002014264,"about_ca_topic_score_gemma":0.00584483,"domain_scores_codex":[0.9993744,0.0001084756,0.00006828451,0.0002194115,0.0001846369,0.00004474954],"domain_scores_gemma":[0.9986969,0.0004231503,0.000360215,0.0001638483,0.0002363429,0.0001196456],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.001347717,0.0003554923,0.4130989,0.000203666,0.0004557852,0.0001680951,0.0003323878,0.0009004521,0.5607166,0.00003535737,0.0001733346,0.02221208],"study_design_scores_gemma":[0.000009884525,0.0009309317,0.9767398,0.000006332783,0.0001375428,0.00007233946,0.0001439645,0.0009024965,0.0204118,0.00002774543,0.0006055583,0.00001160413],"study_design_candidate":"meta_analysis","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974604,0.0004624416,0.001148933,0.00001021862,0.000005302462,0.00006796763,0.0005733012,0.00001337294,0.0002580436],"genre_scores_gemma":[0.9935629,0.0004856536,0.002980597,0.00006026992,0.00001557805,0.0003890957,0.001791088,0.00001074527,0.0007039706],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002014264,"threshold_uncertainty_score":0.00630343,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01374077045507214,"score_gpt":0.229568713047344,"score_spread":0.2158279425922719,"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."}}