{"id":"W2082888220","doi":"10.1046/j.1440-1703.2002.00507.x","title":"Vegetation gradients in relation to temporal fluctuation of environmental factors in Bekanbeushi peatland, Hokkaido, Japan","year":2002,"lang":"en","type":"article","venue":"Ecological Research","topic":"Peatlands and Wetlands Ecology","field":"Environmental Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Peat; Swamp; Water table; Bog; Environmental science; Vegetation (pathology); Groundwater; Marsh; Hydrology (agriculture); Soil science; Ecology; Sampling (signal processing); Physical geography; Wetland; Geology; Geography; 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":[0.0001953896,0.0001292689,0.0001837236,0.000552766,0.0003461138,0.0003527131,0.0001159109,0.0001735433,0.0003451439],"category_scores_gemma":[0.0004075193,0.0001712499,0.0001049511,0.0005223005,0.0003718696,0.000221526,0.0002968608,0.0001502287,0.00006429919],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004474532,"about_ca_system_score_gemma":0.0002940841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04298458,"about_ca_topic_score_gemma":0.1358187,"domain_scores_codex":[0.9999113,0.00001436823,0.000008469847,0.00002721888,0.000009392556,0.00002927437],"domain_scores_gemma":[0.9996266,0.00005981944,0.0001205439,0.00001558223,0.00006015032,0.0001171529],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001070153,0.00002473371,0.9917926,0.00001648491,0.00004197439,0.0002114176,0.001315306,0.0001557892,0.003867096,0.00002547687,0.00006216222,0.002379935],"study_design_scores_gemma":[5.86051e-7,0.000005002914,0.9995846,8.91471e-7,0.000002865025,0.00001874515,0.00026999,0.00006385015,0.00002290522,0.000004199759,0.0000250978,0.000001187335],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9998748,0.00002690489,0.00001634606,0.000004821473,5.89375e-7,6.919894e-7,0.00002679788,5.591847e-7,0.00004839543],"genre_scores_gemma":[0.9997906,0.00002555489,0.00003612647,0.000003467316,0.00000127516,0.000002645375,0.00006648331,6.891146e-7,0.00007317386],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04298458,"threshold_uncertainty_score":0.08546877,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0551255077939265,"score_gpt":0.3022666457729881,"score_spread":0.2471411379790616,"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."}}