{"id":"W2334829834","doi":"10.5721/eujrs20164901","title":"3D displacement field retrieved by integrating Sentinel-1 InSAR and GPS data: the 2014 South Napa earthquake","year":2016,"lang":"en","type":"article","venue":"European Journal of Remote Sensing","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"Ministerio de Economía y Competitividad; European Space Agency","keywords":"Interferometric synthetic aperture radar; Global Positioning System; Geology; Geodesy; Remote sensing; Satellite; Seismology; Synthetic aperture radar; Computer science; Telecommunications","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0001231756,0.0004601686,0.0002730398,0.001179957,0.0002370273,0.0004229402,0.0002636477,0.0003829935,0.0006276566],"category_scores_gemma":[0.0003208689,0.0002336677,0.0002766494,0.0008394371,0.0001496325,0.0003341209,0.0002628586,0.0002079604,0.000336676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003379759,"about_ca_system_score_gemma":0.0003624413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03123199,"about_ca_topic_score_gemma":0.06218385,"domain_scores_codex":[0.9999191,0.000007287706,0.000003694448,0.00002201765,0.00003209115,0.00001582944],"domain_scores_gemma":[0.999922,0.000009805941,0.00001506754,0.000009991558,0.00003422473,0.000008915044],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0011635,0.0004487182,0.3378119,0.0003997605,0.0004817472,0.002733863,0.001200074,0.1424043,0.2947067,0.0007923045,0.004035603,0.2138214],"study_design_scores_gemma":[0.00003270939,0.00008560684,0.7789006,0.00002999843,0.0001128158,0.0003114926,0.0006945853,0.2024482,0.01485544,0.0001840893,0.002280335,0.00006403291],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9936177,0.0001572718,0.003365464,0.00006852735,0.0000155453,0.00001743287,0.001268444,0.0001424417,0.001347282],"genre_scores_gemma":[0.9910957,0.0001601136,0.005603979,0.00001627864,0.00001086875,0.00001380552,0.00240158,0.0000199324,0.0006776804],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03123199,"threshold_uncertainty_score":0.06210041,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01158065231613289,"score_gpt":0.2157452469140308,"score_spread":0.2041645945978979,"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."}}