{"id":"W37141553","doi":"","title":"Potential of dual-pol TerraSAR-X data for Land Cover Classification in Arctic Tundra Landscapes","year":2013,"lang":"en","type":"article","venue":"Helmholtz-Zentrum für Polar-und Meeresforschung (Alfred-Wegener-Institut)","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Tundra; Permafrost; Arctic; Arctic vegetation; Vegetation (pathology); Land cover; Physical geography; Thermokarst; Environmental science; River delta; Geology; Delta; Remote sensing; Land use; Geography; Oceanography; Ecology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002532147,0.0006525111,0.000479638,0.004261829,0.0003815559,0.002069458,0.0008560508,0.0008081171,0.001341011],"category_scores_gemma":[0.003638695,0.0002374133,0.000422845,0.002614497,0.0001839866,0.001164611,0.0009738132,0.0004270896,0.001218634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008054441,"about_ca_system_score_gemma":0.000647801,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04071183,"about_ca_topic_score_gemma":0.05023063,"domain_scores_codex":[0.9990821,0.0002895188,0.00007298197,0.0002335098,0.0001914537,0.0001303483],"domain_scores_gemma":[0.9975272,0.0004905128,0.0002258302,0.0003826542,0.001053562,0.0003202774],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001038643,0.0005037958,0.5151721,0.0002268954,0.0002661652,0.0003057533,0.0003446047,0.01628451,0.01221244,0.0007042477,0.01118106,0.4417598],"study_design_scores_gemma":[0.0001213892,0.000281936,0.6272082,0.0003104621,0.0003097209,0.0002056142,0.00212087,0.3394957,0.006510204,0.001774604,0.02153137,0.0001297951],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9233998,0.002190545,0.01880747,0.001472723,0.0002462892,0.0003566727,0.03575189,0.002318547,0.01545619],"genre_scores_gemma":[0.9287531,0.0007033029,0.04341592,0.0002905999,0.0001052421,0.0001148465,0.02450006,0.00008996719,0.002026894],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04071183,"threshold_uncertainty_score":0.08094972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04512416123985039,"score_gpt":0.27831846914673,"score_spread":0.2331943079068796,"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."}}