{"id":"W2406562495","doi":"10.1021/acs.est.5b00979","title":"Who Smells? Forecasting Taste and Odor in a Drinking Water Reservoir","year":2015,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Aquatic Ecosystems and Phytoplankton Dynamics","field":"Environmental Science","cited_by":89,"is_retracted":false,"has_abstract":true,"ca_institutions":"Global Institute for Water Security; University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; Government of Canada","keywords":"Odor; Random forest; Environmental science; Linear regression; Statistics; Mathematics; Ecology; Biology; Computer science; Machine learning","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009867358,0.0001702786,0.0001966826,0.0002315677,0.0002157942,0.00004249261,0.0005193101,0.0001220555,0.0002219023],"category_scores_gemma":[0.00004563591,0.0001340226,0.00001795863,0.0005476798,0.001574777,0.0004394036,0.001230181,0.0002305569,0.0002794135],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005684831,"about_ca_system_score_gemma":0.00001177868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001835211,"about_ca_topic_score_gemma":0.000555538,"domain_scores_codex":[0.9980488,0.00002797069,0.000276777,0.0005739283,0.0004237371,0.0006488116],"domain_scores_gemma":[0.9994069,0.00001845499,0.00007139573,0.0003332554,0.000001687204,0.0001682748],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001027331,0.00005927937,0.9503673,0.000004203684,0.000002194201,0.0000534239,0.001475975,0.002238982,0.03623807,0.0004023749,0.00006094467,0.009087021],"study_design_scores_gemma":[0.005285923,0.001884479,0.2806746,0.0003532408,0.00004257682,0.001700213,0.01722386,0.4437691,0.112577,0.05312856,0.08017267,0.003187814],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931279,0.00005205504,0.0001643212,0.000428434,0.00009156473,0.0002379907,0.000002693631,0.00004426597,0.005850764],"genre_scores_gemma":[0.9981107,0.0000111206,0.001367453,0.00006657715,0.00001407303,0.00002201702,0.000002560911,0.00001293596,0.0003925778],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6696927,"threshold_uncertainty_score":0.5802332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01503602758940999,"score_gpt":0.2107820700332294,"score_spread":0.1957460424438194,"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."}}