{"id":"W2005015105","doi":"10.1007/s11284-009-0630-5","title":"A revaluation of lake‐phosphorus loading models using a Bayesian hierarchical framework","year":2009,"lang":"en","type":"article","venue":"Ecological Research","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"University of Toronto Scarborough","keywords":"Hierarchical database model; Phosphorus; Bayesian hierarchical modeling; Environmental science; Bayesian inference; Trophic level; Statistics; Predictability; Bayesian probability; Inflow; Limnology; Ecology; Mathematics; Hydrology (agriculture); Econometrics; Computer science; Biology; Meteorology; Data mining; Geography; Geology; Chemistry","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00177865,0.00009773949,0.0001770445,0.0000726103,0.0002133604,0.00003320609,0.0003375139,0.0002025856,0.0007032421],"category_scores_gemma":[0.0008811757,0.00007583505,0.00006579004,0.0006625857,0.0003217435,0.0001485415,0.0002386085,0.000571139,0.00007417354],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002706135,"about_ca_system_score_gemma":0.00002855832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004010824,"about_ca_topic_score_gemma":0.00001099451,"domain_scores_codex":[0.9974942,0.0003174514,0.0002641666,0.0003552634,0.0009298232,0.0006391032],"domain_scores_gemma":[0.9990512,0.000428015,0.00004397989,0.0002392763,0.00003489441,0.0002027103],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006486271,0.002167445,0.7736223,0.00002613676,0.00002466738,0.0001342233,0.001836898,0.08286332,0.003870548,0.03475612,0.001066499,0.09898323],"study_design_scores_gemma":[0.0001444461,0.0003875087,0.09325203,0.00002283642,0.000003265842,0.000003135395,0.00002542746,0.3499592,0.0001707895,0.5558211,0.0001267421,0.00008349794],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9754188,0.00002711912,0.01696176,0.000731697,0.00004021619,0.0002846796,0.00000322315,0.00002691628,0.006505602],"genre_scores_gemma":[0.9871266,0.00006371521,0.01253172,0.0001264834,0.00003685253,0.000009419437,0.000003803538,0.000006077318,0.00009532023],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6803703,"threshold_uncertainty_score":0.7700008,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1106773043350717,"score_gpt":0.3794782564844102,"score_spread":0.2688009521493386,"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."}}