{"id":"W2063755869","doi":"10.1190/tle33080882.1","title":"Using InSAR to detect active deformation associated with faults in Suban field, South Sumatra Basin, Indonesia","year":2014,"lang":"en","type":"article","venue":"The Leading Edge","topic":"Geological and Geophysical Studies","field":"Earth and Planetary Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"ConocoPhillips (Canada)","funders":"","keywords":"Geology; Seismology; Tectonics; Subsidence; Active fault; Fault (geology); Deformation (meteorology); Subduction; Interferometric synthetic aperture radar; Block (permutation group theory); Structural basin; Geomorphology; Remote sensing; Synthetic aperture radar; Oceanography","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":[0.0001867172,0.0003880698,0.0002141371,0.001107392,0.0002967703,0.0005227542,0.0002437589,0.0001620563,0.0005836944],"category_scores_gemma":[0.0002568563,0.0001735326,0.0001116651,0.001055893,0.0002210449,0.000266784,0.0002665633,0.0001751116,0.0002193186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004199709,"about_ca_system_score_gemma":0.0004219969,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03056013,"about_ca_topic_score_gemma":0.06791347,"domain_scores_codex":[0.9999205,0.00001123091,0.000007516558,0.00002221573,0.00001909548,0.00001943747],"domain_scores_gemma":[0.9998226,0.00002274246,0.0000477894,0.00002093411,0.00004840038,0.00003766802],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003277607,0.00034376,0.8862958,0.0001021276,0.0001248272,0.001260476,0.0009662158,0.008920832,0.0346237,0.0001804401,0.001638129,0.0652159],"study_design_scores_gemma":[0.00001334191,0.0000294753,0.9831468,0.00001025749,0.00002872362,0.000101909,0.0006191885,0.01336285,0.001819682,0.00005438323,0.0008057855,0.000007687905],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977986,0.0000541573,0.0002867821,0.00003119812,0.000004994709,0.000009603822,0.0006237442,0.00003561674,0.001155267],"genre_scores_gemma":[0.9979106,0.00006494579,0.0008001099,0.00001493017,0.000004119449,0.000007662063,0.0007953991,0.000004715168,0.0003975181],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03056013,"threshold_uncertainty_score":0.06076449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02822401088502683,"score_gpt":0.2229067945017279,"score_spread":0.194682783616701,"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."}}