{"id":"W2889667995","doi":"10.2134/jeq2018.07.0277","title":"Microbial Water Quality: Monitoring and Modeling","year":2018,"lang":"en","type":"article","venue":"Journal of Environmental Quality","topic":"Fecal contamination and water quality","field":"Environmental Science","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Water quality; Quality (philosophy); Nexus (standard); Environmental monitoring; Environmental science; Multidisciplinary approach; Metaproteomics; Environmental planning; Environmental resource management; Computer science; Ecology; Environmental engineering; Biology; Metagenomics","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002145468,0.0001534988,0.00026027,0.00003379225,0.0001753798,0.00004450101,0.0001869408,0.00007808161,0.00139312],"category_scores_gemma":[0.00003930588,0.0001113383,0.0001025694,0.0000352703,0.000352785,0.0004529874,0.0002488954,0.0002032099,0.0002177878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002455317,"about_ca_system_score_gemma":0.000004096386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001267231,"about_ca_topic_score_gemma":0.000009557453,"domain_scores_codex":[0.9979402,0.0003301569,0.0007740585,0.0002199339,0.0004754014,0.0002602692],"domain_scores_gemma":[0.9993699,0.00004586832,0.0002184985,0.0001762001,0.000008318969,0.0001811689],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001546335,0.0001992102,0.1210555,0.00001308474,0.00002896251,0.000006780584,0.002503024,0.00007032431,0.8674689,0.00004120661,0.0000711325,0.00838718],"study_design_scores_gemma":[0.001964464,0.0004757764,0.6509772,0.00003834286,0.00005015763,0.00009071428,0.001464588,0.0004460935,0.3358046,0.001823632,0.006271875,0.0005925813],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975395,0.00003714951,0.001053907,0.0003237146,0.000290885,0.00006842732,0.000007061017,0.000009024802,0.000670398],"genre_scores_gemma":[0.9980541,0.00002637712,0.001129559,0.0001739369,0.0002861544,8.192629e-7,0.000001528712,0.0000119367,0.0003155782],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5316644,"threshold_uncertainty_score":0.9995198,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05162533208229993,"score_gpt":0.3098682512767637,"score_spread":0.2582429191944637,"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."}}