{"id":"W2514791050","doi":"","title":"Response of Terrestrial Ecosystems Biogeochemistry to Dynamic Hydrological and Climatic Drivers I","year":2015,"lang":"en","type":"article","venue":"2015 AGU Fall Meeting","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Biogeochemistry; Environmental science; Ecosystem; Terrestrial ecosystem; Earth science; Hydrology (agriculture); Oceanography; Ecology; Geology; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000413919,0.0001384952,0.0001842144,0.0002546303,0.0002335635,0.001022858,0.0002019156,0.0004338064,0.002525117],"category_scores_gemma":[0.00200338,0.0001627996,0.0003660839,0.000363562,0.000322246,0.0004549829,0.000628159,0.0004198762,0.0002646814],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000926703,"about_ca_system_score_gemma":0.0003869592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01255994,"about_ca_topic_score_gemma":0.01098546,"domain_scores_codex":[0.9998268,0.00005327407,0.00001018592,0.0000512363,0.00001787384,0.00004060731],"domain_scores_gemma":[0.9994586,0.0002105359,0.0001034506,0.00004861574,0.00009296797,0.00008589993],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000658487,0.0001605011,0.8772563,0.0001312174,0.0004605225,0.0002484406,0.0003450222,0.04248498,0.04953822,0.002627989,0.00430586,0.02178243],"study_design_scores_gemma":[0.0000189567,0.00008982158,0.9549795,0.00001051864,0.00004810119,0.00005803467,0.0004963233,0.0387653,0.002101824,0.001238427,0.002171866,0.00002123965],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970204,0.0001054683,0.0004292208,0.0005527635,0.00001923764,0.000006829901,0.0004761977,0.00002365129,0.001366151],"genre_scores_gemma":[0.9992931,0.0000688062,0.0001067989,0.00005743953,0.00001103095,0.000002650848,0.0002000454,0.000007594086,0.0002524023],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01255994,"threshold_uncertainty_score":0.02497369,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01750651873673001,"score_gpt":0.25192108849094,"score_spread":0.23441456975421,"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."}}