{"id":"W2060835324","doi":"10.1002/eco.230","title":"The DigiBog peatland development model 1: rationale, conceptual model, and hydrological basis","year":2011,"lang":"en","type":"article","venue":"Ecohydrology","topic":"Peatlands and Wetlands Ecology","field":"Environmental Science","cited_by":108,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Queen Mary University of London","keywords":"Peat; Ecohydrology; Environmental science; Hydrology (agriculture); Water table; Groundwater; Ecology; Geology; Ecosystem","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002865682,0.0001580046,0.0001757059,0.00002275653,0.0004519836,0.00001469807,0.000243574,0.0001528873,0.0004998323],"category_scores_gemma":[0.00002391378,0.0001024393,0.00003275703,0.00005517006,0.0007017082,0.00009424886,0.0002948812,0.0001407689,0.0001508295],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005658064,"about_ca_system_score_gemma":0.0000254527,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002541819,"about_ca_topic_score_gemma":0.000523047,"domain_scores_codex":[0.9987902,0.0000597088,0.0002418038,0.0003717964,0.0001209922,0.0004154769],"domain_scores_gemma":[0.9995232,0.00009949214,0.00006811017,0.0001802484,0.000006284845,0.0001226793],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007799729,0.0004232189,0.6934015,0.000007716483,0.000175475,0.00009793991,0.01048483,0.2287045,0.001868915,0.04492283,0.009824587,0.009308432],"study_design_scores_gemma":[0.0007256035,0.0001776871,0.04996126,9.207266e-7,0.00001830007,0.0000699523,0.00002426963,0.931106,0.0001792264,0.008839956,0.008649674,0.0002470963],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9549747,0.0000450592,0.00195757,0.0004328149,0.0000557934,0.0001489447,0.000003925456,0.00004697567,0.04233429],"genre_scores_gemma":[0.9957067,0.000040933,0.002516751,0.0006867234,0.00002419945,0.00007224824,0.00001694819,0.000009248476,0.0009262052],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7024015,"threshold_uncertainty_score":0.5472814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03105050307792799,"score_gpt":0.2109125043247869,"score_spread":0.1798620012468589,"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."}}