{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002890992,0.0008403134,0.0008073135,0.002173807,0.0009532252,0.002185906,0.002728286,0.0013163,0.009223294],"category_scores_gemma":[0.005046235,0.0005671384,0.0006618242,0.001719877,0.0006309082,0.004005126,0.003649361,0.001705212,0.003518593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001064104,"about_ca_system_score_gemma":0.001627675,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004338016,"about_ca_topic_score_gemma":0.003889699,"domain_scores_codex":[0.9986184,0.000380327,0.00007003504,0.0002091504,0.0005260895,0.0001961086],"domain_scores_gemma":[0.9979838,0.0004363322,0.0002007776,0.0006632897,0.0003181519,0.0003975909],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002113962,0.0004435853,0.007990844,0.0007200282,0.0002619965,0.0008619418,0.0009572173,0.04521241,0.03890046,0.1440441,0.1837744,0.574719],"study_design_scores_gemma":[0.0002854411,0.0003284348,0.005525065,0.0001545865,0.00008567016,0.0005192509,0.0001319754,0.3629265,0.02036221,0.04260195,0.5668725,0.0002063516],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01690884,0.0008011024,0.8049747,0.001247992,0.0003830346,0.000809231,0.004832637,0.1416339,0.02840853],"genre_scores_gemma":[0.2202005,0.001111038,0.7154282,0.0009393078,0.0004897431,0.002368735,0.02025382,0.00589473,0.03331395],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009223294,"threshold_uncertainty_score":0.03085494,"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."}}