{"id":"W2021496467","doi":"10.1039/c0em00727g","title":"A statistical approach for the assessment and redesign of the Nile Delta drainage system water-quality-monitoring locations","year":2011,"lang":"en","type":"article","venue":"Journal of Environmental Monitoring","topic":"Water Quality and Pollution Assessment","field":"Environmental Science","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydro-Québec; Institut National de la Recherche Scientifique","funders":"National Water Center, United Arab Emirates University; Royal Society of Chemistry; Royal Society; National Research Centre","keywords":"Water quality; Multivariate statistics; Variance (accounting); Drainage; Identification (biology); Structural basin; Artificial neural network; Sampling (signal processing); Data mining; Hydrology (agriculture); Environmental science; Statistics; Computer science; Engineering; Mathematics; Artificial intelligence; Geology","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":[0.0048112,0.0006812227,0.0009011294,0.003768286,0.0004845172,0.001164556,0.001025836,0.0005315319,0.0008778889],"category_scores_gemma":[0.01892103,0.0005278664,0.0007004454,0.002556807,0.0009058158,0.001284977,0.001309798,0.0007816796,0.0001653648],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001589441,"about_ca_system_score_gemma":0.002724239,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006338234,"about_ca_topic_score_gemma":0.007498261,"domain_scores_codex":[0.9952553,0.001663749,0.0003828189,0.0009076223,0.00164875,0.0001416846],"domain_scores_gemma":[0.9914669,0.003813324,0.001530572,0.0007499298,0.002300442,0.0001388046],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0001545104,0.0001185852,0.02292235,0.0002216447,0.0002665091,0.0001377824,0.0002791721,0.6113474,0.006469007,0.01738736,0.0008656,0.33983],"study_design_scores_gemma":[0.0000186109,0.0002740371,0.01169728,0.00002943691,0.00006402205,0.00007600278,0.0001751562,0.9756216,0.003170457,0.006329036,0.002501012,0.00004338444],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02910902,0.00009560745,0.9694716,0.0000797578,0.00001366321,0.000112478,0.0001288909,0.0002609161,0.000728168],"genre_scores_gemma":[0.373928,0.0001310514,0.6245183,0.00005152434,0.00002460018,0.000331297,0.000372604,0.00003470296,0.0006079064],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006338234,"threshold_uncertainty_score":0.02544433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06902998886863974,"score_gpt":0.3061525206576201,"score_spread":0.2371225317889804,"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."}}