{"id":"W2321804829","doi":"10.1061/40976(316)168","title":"Real-Time Water Quality Monitoring as a Regulatory Tool for Mining Sites — The Newfoundland and Labrador Experience","year":2008,"lang":"en","type":"article","venue":"World Environmental and Water Resources Congress 2008","topic":"Mine drainage and remediation techniques","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Department of Environment and Conservation; Government of Newfoundland and Labrador","funders":"","keywords":"Quality (philosophy); Copper mine; Water quality; Quality assurance; Process (computing); Environmental resource management; Computer science; Engineering; Environmental science; Operations management","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.000229757,0.0002117788,0.0001908876,0.00003706931,0.0006649666,0.00005730021,0.0001660122,0.00005624964,0.00071575],"category_scores_gemma":[0.000005677161,0.000114717,0.00004967411,0.00003078729,0.0008571197,0.0002447587,0.0003228475,0.00007878628,0.00007118419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005993788,"about_ca_system_score_gemma":9.443616e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004468814,"about_ca_topic_score_gemma":0.00004213,"domain_scores_codex":[0.9986687,0.00006984292,0.0002652906,0.0003985146,0.0002405041,0.0003571187],"domain_scores_gemma":[0.9995257,0.00007147268,0.00005684803,0.0002425312,0.000001911864,0.0001015777],"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":[0.00007478373,0.00004257324,0.336865,0.00001378158,0.00001622504,0.00001908091,0.02335793,0.00001449568,0.6370047,0.000003030525,0.000648498,0.001939846],"study_design_scores_gemma":[0.0009840742,0.0001567099,0.3138435,0.00003109682,0.0000316448,0.0001260378,0.001312497,0.000176096,0.5704358,0.0002072056,0.1120055,0.0006898722],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982978,0.0001394494,0.000003516517,0.0002608683,0.00004730554,0.0003521706,0.000008656052,0.00005306956,0.00083721],"genre_scores_gemma":[0.9750343,0.0002736672,0.0003945401,0.0001101255,0.0001048609,0.00009833097,0.00002046733,0.00002124152,0.02394246],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.111357,"threshold_uncertainty_score":0.7836961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01312026721098077,"score_gpt":0.2327250468601046,"score_spread":0.2196047796491238,"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."}}