{"id":"W3016537303","doi":"","title":"Seasonal Variation in Water Chemistry Parameters in the Clayburn - Willband Watershed, Abbotsford, British Columbia.","year":2017,"lang":"en","type":"article","venue":"AGU Fall Meeting Abstracts","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Watershed; Water chemistry; Variation (astronomy); Seasonality; Environmental science; Hydrology (agriculture); Chemistry; Environmental chemistry; Geology; Mathematics; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009504469,0.0001241013,0.0001463554,0.000009695653,0.0003217437,0.0008004046,0.0005742799,0.0001300948,0.00001577586],"category_scores_gemma":[0.0001277644,0.0001188967,0.00004863771,0.00004941741,0.0001545724,0.0003874496,0.000150881,0.0002850385,0.0000702059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001229998,"about_ca_system_score_gemma":0.000006741556,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.2662393,"about_ca_topic_score_gemma":0.1433223,"domain_scores_codex":[0.9984235,0.00005189776,0.0003123536,0.0003739395,0.0003499268,0.0004884377],"domain_scores_gemma":[0.9993567,0.0000611439,0.0001280775,0.0003783985,0.000006807927,0.00006880446],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001024275,0.00008897243,0.9926527,0.00001324162,0.000004202313,0.0001258434,0.0008715302,0.00420856,0.0006727511,1.2325e-7,0.000253824,0.001098047],"study_design_scores_gemma":[0.0006400437,0.00001391729,0.9953159,0.00007789895,0.000008015612,0.00003306335,0.0001027661,0.001376306,0.000379416,0.001323133,0.000530636,0.0001989099],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9916587,0.000007334861,0.000001539116,0.0005029809,0.0001125415,0.0001765091,0.000004763259,0.00001976528,0.007515821],"genre_scores_gemma":[0.9991747,0.00001683099,0.0001869588,0.0001889878,0.00004206141,0.00002653016,0.00003283699,0.000014668,0.0003164138],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.122917,"threshold_uncertainty_score":0.8723098,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00955092307959123,"score_gpt":0.2046871917379062,"score_spread":0.1951362686583149,"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."}}