{"id":"W2217362142","doi":"10.1080/2150704x.2015.1126683","title":"Large deformation monitoring over a coal mining region using pixel-tracking method with high-resolution Radarsat-2 imagery","year":2015,"lang":"en","type":"article","venue":"Remote Sensing Letters","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities; Canadian Space Agency; Priority Academic Program Development of Jiangsu Higher Education Institutions","keywords":"Deformation monitoring; Remote sensing; Tracking (education); Pixel; Deformation (meteorology); Coal; Coal mining; High resolution; Geology; Resolution (logic); Mining engineering; Environmental science; Computer science; Computer vision; Artificial intelligence; Geography; Archaeology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002251551,0.0002501918,0.0002186217,0.000683531,0.0001977668,0.0002571167,0.0002692426,0.0003396007,0.0004343017],"category_scores_gemma":[0.0001896863,0.0001498833,0.0002438342,0.0006548623,0.0001131769,0.0003767514,0.0002343799,0.0001797842,0.0001742091],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001290083,"about_ca_system_score_gemma":0.000251285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001181163,"about_ca_topic_score_gemma":0.00323394,"domain_scores_codex":[0.9998771,0.00001511473,0.000006031829,0.00004810289,0.00004099552,0.00001263951],"domain_scores_gemma":[0.9999003,0.000014708,0.00002514884,0.00001820889,0.00002739883,0.00001410736],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000337766,0.0004996511,0.09211192,0.0002134518,0.0001897133,0.000516132,0.0003563864,0.06357189,0.5220446,0.0005593191,0.001255692,0.3183435],"study_design_scores_gemma":[0.00003897608,0.000308314,0.279115,0.00002091151,0.0001166839,0.0007032817,0.0001583694,0.6432606,0.07399426,0.0004616264,0.001756226,0.00006579292],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.908699,0.0001947078,0.08852874,0.00005810394,0.00002316008,0.00003830388,0.0002934659,0.0004398201,0.001724681],"genre_scores_gemma":[0.9272932,0.00008391868,0.07170998,0.00002136917,0.000009299121,0.00001691891,0.0003229027,0.00002006569,0.0005223232],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001181163,"threshold_uncertainty_score":0.002348602,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02444688269877866,"score_gpt":0.2580892089819126,"score_spread":0.233642326283134,"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."}}