{"id":"W2544462376","doi":"","title":"Characterization and Modeling of Selected Antiandrogens and Pharmaceuticals in Highly Impacted Reaches of Grand River Watershed in Southern Ontario","year":2013,"lang":"en","type":"dissertation","venue":"UWSpace (University of Waterloo)","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Antiandrogens; Watershed; Geography; Environmental science; Medicine; Antiandrogen; Computer science","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":[0.000111567,0.0003802655,0.0002106341,0.0004361155,0.0008083773,0.00103191,0.0007237007,0.0005127816,0.0009507567],"category_scores_gemma":[0.0003979558,0.0003589764,0.0004265647,0.000829977,0.0003968482,0.0002826424,0.0003836138,0.0002073547,0.0001087159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007905201,"about_ca_system_score_gemma":0.005266787,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9135985,"about_ca_topic_score_gemma":0.9224517,"domain_scores_codex":[0.9998825,0.000008753521,0.000005625188,0.00003807098,0.00002350535,0.00004163644],"domain_scores_gemma":[0.9998572,0.00002951932,0.00003410483,0.000007367018,0.00005159379,0.00002026124],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001565947,0.000180971,0.512017,0.0000942097,0.0001004028,0.000837186,0.0006057685,0.4548057,0.01718215,0.0006288943,0.001098523,0.01229261],"study_design_scores_gemma":[0.00003654402,0.00007588978,0.2737607,0.00001075784,0.00005626756,0.00007262007,0.001374359,0.7205756,0.002068155,0.0002806989,0.001658494,0.000029801],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976256,0.00003602717,0.0007104073,0.00004993932,0.000001149341,0.00001957081,0.0004949347,0.00003594491,0.001026306],"genre_scores_gemma":[0.9968861,0.00005957363,0.001005555,0.00001097926,7.749854e-7,0.0000189286,0.000709092,0.000009439887,0.001299588],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08640146,"threshold_uncertainty_score":0.1738206,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01133037799639663,"score_gpt":0.1931830931603221,"score_spread":0.1818527151639255,"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."}}