{"id":"W2792092426","doi":"10.1038/sdata.2018.40","title":"A suite of global, cross-scale topographic variables for environmental and biodiversity modeling","year":2018,"lang":"en","type":"article","venue":"Scientific Data","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":858,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"McGill University; Deutsche Forschungsgemeinschaft; Yale University; National Aeronautics and Space Administration; National Science Foundation","keywords":"Digital elevation model; Landform; Scale (ratio); Terrain; Elevation (ballistics); Physical geography; Topographic Wetness Index; Variable (mathematics); Spatial analysis; Geography; Spatial variability; Cartography; Environmental science; Geology; Remote sensing; Statistics; Mathematics; Geometry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000575215,0.0007992317,0.0004911351,0.001484707,0.0003602318,0.001035563,0.0009655034,0.0005633603,0.005615673],"category_scores_gemma":[0.001919859,0.0003786903,0.00113202,0.003291909,0.0002193184,0.001015346,0.0009001576,0.001221753,0.001796893],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004584702,"about_ca_system_score_gemma":0.0007479517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01848332,"about_ca_topic_score_gemma":0.02722775,"domain_scores_codex":[0.9998234,0.00003813785,0.00001709018,0.00004330017,0.00005899447,0.00001914718],"domain_scores_gemma":[0.9996315,0.00009538785,0.0000406928,0.00009983547,0.0001074308,0.00002509216],"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":[0.00006401205,0.0002947132,0.04635299,0.0002168244,0.0004202061,0.0001989525,0.0001856225,0.7628767,0.005082801,0.01304672,0.03968402,0.1315764],"study_design_scores_gemma":[0.00003255205,0.00003031323,0.02062595,0.00002609461,0.0000423477,0.00006259575,0.00009220409,0.9448622,0.002060119,0.008049197,0.0240713,0.00004503368],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"dataset","genre_scores_codex":[0.1561459,0.0006394559,0.717315,0.0005679755,0.0002427736,0.0003139437,0.09394109,0.01701859,0.01381523],"genre_scores_gemma":[0.5435704,0.0007777413,0.3629174,0.0001688119,0.0001054072,0.0006398642,0.08622245,0.001567839,0.004029999],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.01848332,"threshold_uncertainty_score":0.03675145,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.058784412206377,"score_gpt":0.284479141665156,"score_spread":0.225694729458779,"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."}}