{"id":"W1968921164","doi":"10.1021/es040614u","title":"Peer Reviewed: Experimenting with Hydroelectric Reservoirs","year":2004,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada","funders":"Fisheries and Oceans Canada; University of Waterloo; Manitoba Hydro; Hydro-Québec; Canadian Foundation for Climate and Atmospheric Sciences; University of Alberta; University of Pennsylvania","keywords":"Hydroelectricity; Peer review; Environmental science; Petroleum engineering; Water resource management; Geology; Engineering; Chemistry","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"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":[0.004815016,0.0004757377,0.0006953978,0.0006784493,0.002676377,0.002115132,0.001521847,0.001137791,0.1773609],"category_scores_gemma":[0.01588686,0.0004872223,0.0003665041,0.0005809956,0.0006552643,0.002321064,0.002024191,0.001513028,0.06414605],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009142094,"about_ca_system_score_gemma":0.003759328,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005427577,"about_ca_topic_score_gemma":0.01704744,"domain_scores_codex":[0.9968555,0.0006552714,0.0001132968,0.000480377,0.001565386,0.0003301356],"domain_scores_gemma":[0.9856526,0.002805548,0.0003059631,0.001552655,0.006556025,0.003127336],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00202774,0.003297905,0.01207041,0.0007770851,0.00005372955,0.0005110014,0.002473607,0.0008265413,0.03466085,0.002809853,0.6029407,0.3375506],"study_design_scores_gemma":[0.0009735911,0.004575036,0.01776072,0.0002503327,0.0000926005,0.0001895755,0.004221932,0.005107452,0.02790844,0.005017509,0.933738,0.000164947],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4744214,0.001355761,0.02268337,0.02674014,0.0134483,0.01777147,0.01460574,0.009321941,0.4196519],"genre_scores_gemma":[0.4197793,0.001737753,0.03700402,0.003469843,0.0009233943,0.00743617,0.009701444,0.00227278,0.5176754],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1773609,"threshold_uncertainty_score":0.5933315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009601833291416189,"score_gpt":0.2466561032869755,"score_spread":0.2370542699955593,"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."}}