{"id":"W2921414615","doi":"10.5194/bg-16-3491-2019","title":"Assessing the peatland hummock–hollow classification framework using high-resolution elevation models: implications for appropriate complexity ecosystem modeling","year":2019,"lang":"en","type":"article","venue":"Biogeosciences","topic":"Peatlands and Wetlands Ecology","field":"Environmental Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Forest Service; University of Alberta; Natural Resources Canada; McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Peat; Environmental science; Transect; Digital elevation model; Elevation (ballistics); Biogeochemical cycle; Geology; Soil science; Hydrology (agriculture); Physical geography; Atmospheric sciences; Remote sensing; Ecology; Geography; Geometry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007668027,0.0006017373,0.0009982479,0.001519969,0.000615234,0.0028045,0.001556303,0.0009153202,0.0006558176],"category_scores_gemma":[0.02059752,0.0004026422,0.0009852082,0.001082212,0.0006969828,0.002190459,0.001496247,0.000821818,0.0001318678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001883125,"about_ca_system_score_gemma":0.001735159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03248699,"about_ca_topic_score_gemma":0.04019864,"domain_scores_codex":[0.9982327,0.001134949,0.00008112787,0.0002523021,0.0001940487,0.0001048072],"domain_scores_gemma":[0.9911583,0.005856015,0.0009285982,0.000607473,0.0009042883,0.0005454204],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008925721,0.0001328569,0.1080781,0.00007940123,0.0002625455,0.00006220529,0.0001868427,0.857426,0.001191234,0.00697981,0.0005448798,0.0249669],"study_design_scores_gemma":[0.000004605098,0.00001278878,0.009390427,0.00001591535,0.000007176038,0.000007750089,0.0000639755,0.9873725,0.00008381702,0.00286238,0.0001672304,0.00001138687],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6310998,0.0004438463,0.3636246,0.001101307,0.00004246144,0.0001887799,0.0008842293,0.0006040709,0.002010838],"genre_scores_gemma":[0.9054151,0.00008824308,0.09369573,0.0000604206,0.00002082964,0.00007096429,0.0004344578,0.00004529689,0.0001689585],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03248699,"threshold_uncertainty_score":0.06459576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.11700366404436,"score_gpt":0.318675961786641,"score_spread":0.201672297742281,"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."}}