{"id":"W4399741855","doi":"10.1002/opfl.1980","title":"Multiparameter Monitoring Enhances Water Quality Insights","year":2024,"lang":"en","type":"article","venue":"Opflow","topic":"Water Quality Monitoring Technologies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quality (philosophy); Water quality; Environmental science; Computer science; Biology; Ecology; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008742299,0.0007168954,0.0006462726,0.001694858,0.0004361745,0.001811891,0.0006348868,0.0009996659,0.003149208],"category_scores_gemma":[0.002055656,0.000318424,0.0004138495,0.001292284,0.0003969474,0.003129361,0.001698718,0.0009399407,0.0004149432],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001014768,"about_ca_system_score_gemma":0.0006515479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009584433,"about_ca_topic_score_gemma":0.0141621,"domain_scores_codex":[0.9994189,0.00011656,0.0000269688,0.0001779615,0.0001991207,0.00006060879],"domain_scores_gemma":[0.9990861,0.0002476108,0.0001637456,0.0002250702,0.0002268097,0.0000505994],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005766151,0.0005023719,0.08605104,0.0004136897,0.0002351114,0.0006011995,0.0007547499,0.07395785,0.2537073,0.01761955,0.006866023,0.5587146],"study_design_scores_gemma":[0.00008605026,0.0004193443,0.1616313,0.0001839084,0.0003001276,0.0008254906,0.001041307,0.6306245,0.0726847,0.06642304,0.0655105,0.000269842],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3925686,0.002979403,0.5495861,0.002663003,0.0001948902,0.0002229534,0.002614763,0.0029866,0.04618359],"genre_scores_gemma":[0.9069611,0.001120623,0.08800908,0.0004611961,0.0001373204,0.00007645349,0.000520488,0.0002229225,0.002490827],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009584433,"threshold_uncertainty_score":0.01905727,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04795477635685971,"score_gpt":0.3091602874061827,"score_spread":0.261205511049323,"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."}}