{"id":"W2442365540","doi":"10.12943/anr.2015.00040","title":"ASSESSMENT OF THE EFFECT OF WATER QUALITY ON COPPER TOXICITY IN<i>HYALELLA AZTECA</i>","year":2015,"lang":"en","type":"article","venue":"AECL Nuclear Review","topic":"Environmental Toxicology and Ecotoxicology","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Nuclear Laboratories; University of Guelph","funders":"University of Waterloo","keywords":"Hyalella azteca; Sediment; Toxicity; Environmental chemistry; Copper; Water quality; Environmental science; Copper toxicity; Aquatic ecosystem; Chemistry; Toxicology; Ecology; Biology; Amphipoda","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.0001991588,0.0003991874,0.0003113291,0.0002005868,0.0002580659,0.0006091775,0.0003250297,0.0003096906,0.0006366725],"category_scores_gemma":[0.0003567136,0.0001277686,0.0002256632,0.000259359,0.000291194,0.0003305001,0.0003723296,0.0003613681,0.0001334526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008293893,"about_ca_system_score_gemma":0.0005246149,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01248023,"about_ca_topic_score_gemma":0.01774037,"domain_scores_codex":[0.9997161,0.00004090386,0.00003397186,0.0000684153,0.0001000725,0.00004052653],"domain_scores_gemma":[0.9996133,0.00005925744,0.0001269419,0.00002225093,0.0001296808,0.0000486082],"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":[0.000216808,0.00003497753,0.008020728,0.00008598914,0.00001773042,0.00005748584,0.00005518462,0.00009790961,0.9890516,0.00001764897,0.00002235628,0.002321571],"study_design_scores_gemma":[0.00001112798,0.002224541,0.1419034,0.00001138543,0.0000723292,0.0001196341,0.0004303537,0.0005813359,0.8535674,0.00003534999,0.001023856,0.00001927299],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988239,0.0001990454,0.0002871527,0.00002925744,0.000005106455,0.0000183684,0.0001938885,0.00001130514,0.0004318088],"genre_scores_gemma":[0.9975497,0.0002309107,0.0008421654,0.00005342676,0.000002611974,0.00001628655,0.0003917408,0.000005043548,0.0009081332],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01248023,"threshold_uncertainty_score":0.0248152,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02145527249394177,"score_gpt":0.3044111093624029,"score_spread":0.2829558368684612,"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."}}