{"id":"W2063697750","doi":"10.2166/wst.2008.135","title":"monEAU: a platform for water quality monitoring networks","year":2008,"lang":"en","type":"article","venue":"Water Science & Technology","topic":"Water Quality Monitoring and Analysis","field":"Environmental Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Flexibility (engineering); Standardization; Environmental monitoring; Quality (philosophy); Set (abstract data type); Computer science; Network monitoring; Data quality; Continuous monitoring; Risk analysis (engineering); Systems engineering; Engineering; Operations management; Environmental engineering; Business","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001193713,0.0002107322,0.0002809887,0.0003094399,0.001173127,0.00006017093,0.001068906,0.0001853416,0.00006518309],"category_scores_gemma":[0.00004095226,0.0001282698,0.0001046264,0.000774509,0.001927337,0.000534051,0.0007149521,0.0002186963,0.0003026749],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002451173,"about_ca_system_score_gemma":0.00001042986,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003490548,"about_ca_topic_score_gemma":0.000003469097,"domain_scores_codex":[0.997209,0.00001946377,0.000390997,0.000734973,0.0004708589,0.001174698],"domain_scores_gemma":[0.999086,0.00002011143,0.00005189807,0.000666712,0.00003685653,0.0001384097],"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":[0.00002006022,0.00008718747,0.1111429,0.00000684955,0.00001270546,0.00001443039,0.002157101,0.005092933,0.8780671,0.0001197908,0.00008538775,0.003193646],"study_design_scores_gemma":[0.0002297087,0.00007935802,0.002694521,0.000006028588,0.00001092633,0.00002549419,0.000221176,0.001089393,0.9900305,0.002047175,0.003285627,0.0002800955],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908762,0.0000154562,0.006840903,0.0010442,0.0004481204,0.000177638,0.00000144707,0.0003146913,0.0002813297],"genre_scores_gemma":[0.9957886,0.00001169853,0.002916752,0.0000242471,0.0001321086,0.00008384109,0.000003585799,0.00001516787,0.001023989],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1119634,"threshold_uncertainty_score":0.9022866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04170946477361172,"score_gpt":0.2838906356827898,"score_spread":0.242181170909178,"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."}}