{"id":"W1984794230","doi":"10.1016/j.trac.2006.11.009","title":"Emerging tools and sustainability of water-quality monitoring","year":2007,"lang":"en","type":"article","venue":"TrAC Trends in Analytical Chemistry","topic":"Water Quality and Pollution Assessment","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Sustainability; Quality (philosophy); Water quality; Sampling (signal processing); Complement (music); Sustainable development; Risk analysis (engineering); Environmental resource management; Business; Computer science; Environmental economics; Environmental planning; Environmental science; Economics","routes":{"ca_aff":true,"ca_fund":true,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001252475,0.000103133,0.0001814825,0.00002583381,0.00003602573,0.00001455906,0.0001068605,0.00008478801,0.001310331],"category_scores_gemma":[0.00006479608,0.00008540681,0.00005442761,0.0001985092,0.0002424357,0.0001104896,0.0001059265,0.0001717387,0.00000420498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002327645,"about_ca_system_score_gemma":0.000004975491,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002197759,"about_ca_topic_score_gemma":0.00001609629,"domain_scores_codex":[0.9987298,0.0000347438,0.0004307276,0.0002471246,0.0002442221,0.0003133524],"domain_scores_gemma":[0.9995521,0.00008050348,0.00004386481,0.0001937512,0.000008630343,0.0001210907],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001114451,0.0004867545,0.8481103,0.0002537416,0.00002161305,0.00002807906,0.0015886,0.0005569038,0.06938639,0.0003930939,0.00005592254,0.0790072],"study_design_scores_gemma":[0.0003025754,0.00001185366,0.7167255,0.00001009901,0.00001078903,0.000002267858,0.0005686547,0.0001924759,0.2804045,0.000764863,0.000855936,0.0001504051],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9796835,0.000009495478,0.0003327536,0.0004580645,0.00001761342,0.00002329424,0.00000590197,0.00001553098,0.01945386],"genre_scores_gemma":[0.9984877,0.000002580402,0.0001846997,0.000009292949,0.00002651488,0.000001512183,0.00000623562,0.000004005485,0.001277433],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2110181,"threshold_uncertainty_score":0.9996026,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03911474410227819,"score_gpt":0.36600225780527,"score_spread":0.3268875137029917,"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."}}