{"id":"W2063815472","doi":"10.5194/isprsarchives-xxxviii-4-w19-359-2011","title":"EVALUATION OF INSAR DEM FROM HIGH-RESOLUTION SPACEBORNE SAR DATA","year":2012,"lang":"en","type":"article","venue":"˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Deutsches Zentrum für Luft- und Raumfahrt","keywords":"Remote sensing; Interferometric synthetic aperture radar; Digital elevation model; Interferometry; Synthetic aperture radar; Satellite; Shuttle Radar Topography Mission; Computer science; Geology; Engineering","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":[0.0009514014,0.0004506072,0.0002943795,0.001292686,0.0002193868,0.0005776085,0.0002842983,0.000252383,0.002198333],"category_scores_gemma":[0.001562229,0.0001556132,0.0002812763,0.001007212,0.0001773302,0.0004127729,0.0002857173,0.0002170625,0.0008619492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004581194,"about_ca_system_score_gemma":0.0003342573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00836247,"about_ca_topic_score_gemma":0.01251409,"domain_scores_codex":[0.9996253,0.0001194414,0.00002317561,0.00005836058,0.0001400187,0.00003367096],"domain_scores_gemma":[0.999077,0.0001731969,0.00006100499,0.0001909731,0.0004555518,0.00004225921],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.001239148,0.0004574911,0.05214689,0.000551682,0.0005380203,0.0007608674,0.0002828509,0.6944361,0.03782591,0.001897465,0.01158,0.1982836],"study_design_scores_gemma":[0.0001353189,0.0002268412,0.1357257,0.00004723408,0.0001075602,0.0001979148,0.0003255264,0.8279491,0.02514134,0.0006081776,0.00949058,0.00004490152],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9471698,0.0003566841,0.02996755,0.0001736212,0.0001393724,0.0001473528,0.01220004,0.002772236,0.007073439],"genre_scores_gemma":[0.9655063,0.00009659555,0.02147868,0.00001447799,0.000007942986,0.00002746993,0.01185595,0.0001164238,0.0008962318],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00836247,"threshold_uncertainty_score":0.01662761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03225630355305884,"score_gpt":0.2734000786854878,"score_spread":0.241143775132429,"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."}}