{"id":"W2593229429","doi":"10.1149/2.f06164if","title":"Rapid Water Quality Monitoring for Microbial Contamination","year":2016,"lang":"en","type":"article","venue":"The Electrochemical Society Interface","topic":"Biosensors and Analytical Detection","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Contamination; Environmental science; Water quality; Water contamination; Indicator organism; Environmental engineering; Biology; Ecology","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":[],"consensus_categories":[],"category_scores_codex":[0.0001778782,0.0001046403,0.0001075297,0.000004646055,0.00005681339,0.00002060185,0.0001133152,0.0001023674,0.00003088954],"category_scores_gemma":[0.00002513715,0.00005134485,0.0001659598,0.00003668467,0.00004905983,0.00005037674,0.00001787686,0.0001244309,0.00002683553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001379645,"about_ca_system_score_gemma":0.000002034224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001646841,"about_ca_topic_score_gemma":2.672003e-7,"domain_scores_codex":[0.9993495,0.00001399309,0.0001547748,0.0001218721,0.00007253524,0.0002873219],"domain_scores_gemma":[0.9996814,0.0001219474,0.0000133806,0.0001071074,0.00004277586,0.00003345869],"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":[0.00001866251,0.000006498931,0.000004666746,0.0000175795,0.00004232266,1.044771e-8,0.0001682822,0.00000243373,0.9944329,0.00002994248,0.0007724864,0.004504214],"study_design_scores_gemma":[0.0002755789,0.00003136848,0.00003363114,0.00001712776,0.00001441655,0.000001192001,0.00003650373,0.001009684,0.9921665,0.0003477548,0.005958721,0.0001075075],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7125767,0.0001617281,0.2852771,0.001363479,0.00020851,0.0001418268,0.000004251185,0.000187633,0.00007870596],"genre_scores_gemma":[0.9987569,0.00007676514,0.0003521389,0.00003145527,0.0003140302,0.00001803815,0.000001798399,0.00001715708,0.0004317303],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2861801,"threshold_uncertainty_score":0.2093782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01308263420841372,"score_gpt":0.2472254057793419,"score_spread":0.2341427715709282,"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."}}