{"id":"W3198197522","doi":"10.1080/07038992.2021.1964944","title":"Land Subsidence in Beijing’s Sub-Administrative Center and Its Relationship with Urban Expansion Inferred from Sentinel-1/2 Observations","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Remote Sensing","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Beijing; Subsidence; Interferometric synthetic aperture radar; Index (typography); Groundwater-related subsidence; Geography; Physical geography; Geology; Environmental science; Remote sensing; Geomorphology; China; Synthetic aperture radar","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008636888,0.0001021406,0.0001528012,0.0001392683,0.00008095037,0.00005562207,0.00004412314,0.00006955545,0.000005138491],"category_scores_gemma":[0.0001406724,0.00009859839,0.00002405409,0.0002395476,0.00002912159,0.0001393214,0.00000461757,0.0002300372,7.468921e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009923227,"about_ca_system_score_gemma":0.0003528971,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000540371,"about_ca_topic_score_gemma":0.04750099,"domain_scores_codex":[0.9993828,0.00003176085,0.000245392,0.0001046284,0.000085801,0.0001496292],"domain_scores_gemma":[0.9993312,0.0001457077,0.00006818821,0.0001139388,0.0001580348,0.0001829302],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003724698,0.00002922607,0.6448348,0.0001163978,0.00020846,0.003893477,0.007093168,0.0001699468,0.01312377,0.0009550035,0.00156803,0.3279705],"study_design_scores_gemma":[0.001268034,0.00005939277,0.8437737,0.002967752,0.0001133266,0.00230801,0.001351066,0.07467995,0.02879417,0.002074434,0.04188458,0.0007256086],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9298531,0.0007589107,0.06818294,0.0006948243,0.00005714037,0.00006244749,0.000009840163,0.00001748301,0.0003633148],"genre_scores_gemma":[0.8478618,0.00005428804,0.1519444,0.00004986108,0.00005023406,4.400704e-8,0.00001082984,0.00001571566,0.00001288416],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3272449,"threshold_uncertainty_score":0.9698796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03308874954962453,"score_gpt":0.231083026766353,"score_spread":0.1979942772167285,"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."}}