{"id":"W4309706969","doi":"10.3389/feart.2022.918901","title":"Response of a large deep-seated gravitational slope deformation to meteorological, seismic, and deglaciation drivers as measured by InSAR","year":2022,"lang":"en","type":"article","venue":"Frontiers in Earth Science","topic":"Landslides and related hazards","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"BGC Engineering (Canada); Simon Fraser University","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Geology; Geodesy; Deformation (meteorology); Interferometric synthetic aperture radar; Displacement (psychology); Smoothing; Sensitivity (control systems); Seismology; Glacier; Magnitude (astronomy); Remote sensing; Synthetic aperture radar; Geomorphology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002647074,0.0003276511,0.0001958333,0.0005097963,0.0001670132,0.0003826458,0.0001381347,0.0001840443,0.00069733],"category_scores_gemma":[0.0008493816,0.00020509,0.0002870472,0.0005268732,0.000222696,0.0001934825,0.0002953519,0.000206906,0.0001232431],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002313335,"about_ca_system_score_gemma":0.0001646731,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007666785,"about_ca_topic_score_gemma":0.009118788,"domain_scores_codex":[0.9998839,0.00001708455,0.000008162428,0.00004331093,0.00002404699,0.00002355655],"domain_scores_gemma":[0.999607,0.0001182303,0.0001183225,0.00005443815,0.00004487172,0.00005704367],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003118635,0.00008664505,0.9426012,0.00001952034,0.0002255256,0.0001984174,0.0001146225,0.01812674,0.02861901,0.00009757292,0.0001782867,0.00942056],"study_design_scores_gemma":[0.000003318129,0.00005461368,0.9832715,0.000001661694,0.0000187698,0.00005059719,0.00005358122,0.01506594,0.001350467,0.00002841498,0.00009474144,0.000006327874],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995463,0.00001069334,0.0001429328,0.000006396634,0.000001157087,0.000002144474,0.0001211043,0.00001014157,0.0001589731],"genre_scores_gemma":[0.9995579,0.000008698535,0.0001044377,0.000003329556,0.000001564473,0.000001417202,0.0002649041,0.000001854158,0.00005590149],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007666785,"threshold_uncertainty_score":0.01524436,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004656755725419343,"score_gpt":0.2088895182345823,"score_spread":0.2042327625091629,"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."}}