{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001648752,0.000134546,0.0004433748,0.00001284704,0.00004342557,0.000002207898,0.0003320209,0.00009600525,0.002537893],"category_scores_gemma":[0.00007113923,0.00007363855,0.0001254433,0.0001253409,0.0003743917,0.00005496935,0.0003517507,0.0001999751,0.0004551368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001599402,"about_ca_system_score_gemma":0.000004166634,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004111752,"about_ca_topic_score_gemma":0.00004010451,"domain_scores_codex":[0.9981346,0.0007578221,0.0004056188,0.0002312935,0.0002612378,0.0002094605],"domain_scores_gemma":[0.9992508,0.0000889958,0.0001438528,0.0004499707,0.000002165577,0.00006422296],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001253357,0.0006688076,0.8289621,0.001408818,0.00004495946,0.000009033156,0.0002382203,0.0006444491,0.1430592,0.0005644383,0.01710762,0.007167094],"study_design_scores_gemma":[0.002011504,0.003086202,0.6923885,0.001138795,0.0001128034,0.00001874109,0.0000347876,0.00006786668,0.1673118,0.0002450723,0.1331292,0.0004546988],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.947939,0.0004370083,4.824599e-7,0.0006242564,0.0001023106,0.0005478915,0.000003375982,0.000006771411,0.05033888],"genre_scores_gemma":[0.9969487,0.0008494403,0.00006272364,0.001827531,0.000005677285,0.0000151169,0.000001458895,0.00001200789,0.0002774076],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1365736,"threshold_uncertainty_score":0.9983739,"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."}}