{"id":"W2021883703","doi":"10.1080/13658810600894364","title":"DEM resolution dependencies of terrain attributes across a landscape","year":2007,"lang":"en","type":"article","venue":"International Journal of Geographical Information Systems","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":144,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Landform; Terrain; Sample (material); Cluster analysis; Resampling; Curvature; Topographic Wetness Index; Orientation (vector space); Sampling (signal processing); Geography; Cartography; Geology; Remote sensing; Mathematics; Digital elevation model; Statistics; Computer science; Geometry; Computer vision","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":[0.001294015,0.0002133482,0.0002823144,0.0009683514,0.0002087075,0.0005069702,0.0001998924,0.0001847934,0.0007652916],"category_scores_gemma":[0.01342388,0.0002357406,0.0002217056,0.0009731941,0.0003279596,0.0005458939,0.0003950344,0.0004511033,0.0001543154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002247071,"about_ca_system_score_gemma":0.00008998335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001712425,"about_ca_topic_score_gemma":0.003045788,"domain_scores_codex":[0.9990147,0.0003540541,0.00005857365,0.0001889043,0.000310265,0.00007348758],"domain_scores_gemma":[0.9898863,0.006908048,0.0009564509,0.001108944,0.001039075,0.0001013347],"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":[0.001196611,0.0001666983,0.5737976,0.0003918129,0.0004435344,0.0007511915,0.001706815,0.07527837,0.1980581,0.002270486,0.001321613,0.1446171],"study_design_scores_gemma":[0.000008394196,0.0001489723,0.9446391,0.00001431776,0.00007023825,0.0005153465,0.0003282564,0.03201461,0.02007427,0.0009124493,0.001231418,0.00004271568],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9777191,0.0001922103,0.01888915,0.00005339014,0.000006308839,0.00003500476,0.000587134,0.000126682,0.002391051],"genre_scores_gemma":[0.9952061,0.00006021739,0.00412829,0.00001412138,0.000003900649,0.000007916963,0.0003948255,0.00002685635,0.000157824],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001712425,"threshold_uncertainty_score":0.006843507,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01204847211418065,"score_gpt":0.2686715728666286,"score_spread":0.256623100752448,"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."}}