{"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":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0005017089,0.0002083767,0.0001893335,0.0002375261,0.0007239706,0.00003645859,0.000630384,0.00007222436,0.001201037],"category_scores_gemma":[0.00008843502,0.0001623499,0.00003471106,0.001900645,0.003291977,0.0005613679,0.0005486242,0.000208233,0.001269484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007600649,"about_ca_system_score_gemma":0.00002435773,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005117844,"about_ca_topic_score_gemma":0.00001733087,"domain_scores_codex":[0.9974876,0.00001417955,0.0002247463,0.0006004722,0.0009759356,0.0006970432],"domain_scores_gemma":[0.9992735,0.00001020462,0.0001162914,0.0004492872,0.000005546766,0.0001451416],"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":[0.00001790798,0.000283956,0.1233066,0.00000449412,0.00001619697,0.0000437741,0.001605373,0.001334427,0.8484469,0.001261752,0.0007364021,0.02294222],"study_design_scores_gemma":[0.001554104,0.0009895497,0.05968443,0.00006003774,0.00003964031,0.0003125428,0.004526519,0.00006151716,0.8245478,0.004451048,0.1027695,0.001003324],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9774573,0.0003550989,0.0003678079,0.003223084,0.0000595509,0.0002946543,0.000001814652,0.0001402453,0.01810038],"genre_scores_gemma":[0.9952179,0.0001174828,0.002982391,0.0002711501,0.00001501696,0.00005843373,0.000002077639,0.00001488349,0.001320726],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1020331,"threshold_uncertainty_score":0.999712,"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."}}