{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002855915,0.0001560087,0.0001379803,0.00004364817,0.0001039258,0.0001530705,0.0003493872,0.0001082721,0.0002978629],"category_scores_gemma":[0.00003920477,0.0001005096,0.00006736722,0.0001362751,0.0001754603,0.0003914228,0.0003737436,0.0002000884,0.00387098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001478615,"about_ca_system_score_gemma":0.000002856595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003885528,"about_ca_topic_score_gemma":0.00001173499,"domain_scores_codex":[0.9986442,0.00006366905,0.0002243888,0.000423338,0.0003112006,0.000333177],"domain_scores_gemma":[0.9994502,0.00007958664,0.00001552013,0.0003987601,0.000004066605,0.00005183242],"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":[0.000009626317,0.00005304255,0.02498733,0.00006078174,0.00003254856,0.00004721919,0.003695083,0.0002161518,0.9349161,0.0001385597,0.000968912,0.03487466],"study_design_scores_gemma":[0.00005134969,0.00002393056,0.009635719,0.0000407537,0.000005991144,0.000001885146,0.0001228904,0.0001556923,0.9561598,0.003475186,0.03012437,0.0002023828],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949166,0.0001546849,0.000315576,0.0004846384,0.001554218,0.0001031179,0.000001723263,0.0007601342,0.001709278],"genre_scores_gemma":[0.9915218,0.00002713626,0.006151885,0.00001394005,0.0001811932,0.00003738785,0.000002051613,0.00001841573,0.002046235],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03467228,"threshold_uncertainty_score":0.9969046,"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."}}