{"id":"W7001525429","doi":"","title":"2018 Kentucky River Watershed Watch: Annual Report","year":2019,"lang":"en","type":"article","venue":"UKnowledge (University of Kentucky)","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Watershed Watch Salmon Society","keywords":"Annual report; Watershed; Hydrology (agriculture); Water resources; Drainage basin","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002583464,0.000190084,0.0002823874,0.00006950387,0.0001408955,0.000009167806,0.0005424394,0.0001428884,0.002061879],"category_scores_gemma":[0.00001433528,0.0002025041,0.0001687771,0.0003232417,0.0003896182,0.0004995419,0.00062719,0.0001557958,0.005959845],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002325777,"about_ca_system_score_gemma":0.00001719528,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008137311,"about_ca_topic_score_gemma":0.0001001775,"domain_scores_codex":[0.9984561,0.00005729524,0.0001968576,0.0005373363,0.0003697768,0.0003825989],"domain_scores_gemma":[0.9989647,0.00002465222,0.0001751526,0.0006120551,0.00004632697,0.0001771611],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001351853,0.0002407888,0.9276617,0.00003615561,0.0000471717,0.0002077397,0.005763196,0.00007219658,0.0005027935,0.00009263319,0.06301442,0.00222602],"study_design_scores_gemma":[0.003156617,0.0004174928,0.3167476,0.00008692071,0.000133693,0.0001138349,0.004135651,0.002377556,0.0006968862,0.002906979,0.6682953,0.0009314006],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9490456,0.00001561545,0.0002270024,0.000432429,0.0006067027,0.0002384559,0.00002465453,0.00007916824,0.04933035],"genre_scores_gemma":[0.9096932,0.00004416689,0.001096791,0.00003552763,0.00003528941,2.716731e-7,0.00006666707,0.00001895905,0.08900908],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6109141,"threshold_uncertainty_score":0.9988503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005168307000851772,"score_gpt":0.1673091917591305,"score_spread":0.1621408847582787,"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."}}