{"id":"W1540501767","doi":"10.1029/2010gl046484","title":"Using multiple RADARSAT InSAR pairs to estimate a full three-dimensional solution for glacial ice movement","year":2011,"lang":"en","type":"article","venue":"Geophysical Research Letters","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":128,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Agency for Natural Resources and Energy; Canadian Space Agency; Natural Resources Canada; U.S. Geological Survey","keywords":"Geology; Geodesy; Interferometric synthetic aperture radar; Azimuth; Glacier; Displacement (psychology); Synthetic aperture radar; Terrain; Latitude; Remote sensing; Geomorphology; Optics; Geography; Physics; Cartography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004141194,0.0001286145,0.0001580485,0.00005200675,0.0006878486,0.00004296415,0.0002043835,0.00003448402,0.0002215961],"category_scores_gemma":[0.0002455083,0.0001100793,0.00009012684,0.0003812212,0.0001481578,0.000151889,0.00007515914,0.0001723122,0.0001585987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003223532,"about_ca_system_score_gemma":0.00005622106,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02288884,"about_ca_topic_score_gemma":0.009696929,"domain_scores_codex":[0.9980749,0.00006183558,0.0001797251,0.0003497459,0.0006205526,0.0007132374],"domain_scores_gemma":[0.9990309,0.0004141823,0.00003266272,0.0001789121,0.0001379916,0.0002053442],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.006313799,0.0009499692,0.475862,0.0002611619,0.0004889765,0.0001220271,0.00539672,0.04463329,0.1081015,0.001575849,0.06960011,0.2866946],"study_design_scores_gemma":[0.0005713119,0.0003864269,0.6098964,0.0000264888,0.00001326485,6.707858e-7,0.00009015245,0.3829651,0.0002158707,0.001421549,0.004192523,0.0002202418],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9731489,0.00003777859,0.02329596,0.002456278,0.0002523514,0.0006391207,0.00007215529,0.00003131615,0.00006617919],"genre_scores_gemma":[0.9235726,0.000001614749,0.0738829,0.001964456,0.0004553345,0.00001615432,0.00005989683,0.000009532354,0.00003751373],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3383318,"threshold_uncertainty_score":0.9836178,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1409380229345485,"score_gpt":0.3283803785155722,"score_spread":0.1874423555810237,"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."}}