{"id":"W4389508435","doi":"10.1007/978-3-031-43759-5_3","title":"A Benchmark InSAR Simulator for Phase Filtering and Coherence Estimation","year":2023,"lang":"en","type":"book-chapter","venue":"Advances in Science, Technology & Innovation/Advances in science, technology & innovation","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"3v Geomatics (Canada); University of Alberta","funders":"","keywords":"Interferometric synthetic aperture radar; Computer science; Coherence (philosophical gambling strategy); Benchmark (surveying); Key (lock); Interferometry; Synthetic aperture radar; A priori and a posteriori; Ground truth; Real-time computing; Remote sensing; Simulation; Artificial intelligence; Geography; Geodesy","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":[0.0004931103,0.0005327178,0.0004687917,0.0003015757,0.0003554427,0.0005565865,0.001086907,0.0009010869,0.009898951],"category_scores_gemma":[0.001697932,0.0002618319,0.0003057524,0.0006841459,0.0001985296,0.0007325009,0.0004057679,0.0008013784,0.00427302],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003741746,"about_ca_system_score_gemma":0.0009638169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005548159,"about_ca_topic_score_gemma":0.00663882,"domain_scores_codex":[0.9997633,0.00006254998,0.00001131012,0.00003002795,0.0001051378,0.00002768503],"domain_scores_gemma":[0.9993212,0.0002488061,0.00002713193,0.0001318152,0.0002422703,0.00002868492],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004081266,0.0002022995,0.001047373,0.0001730908,0.00008946587,0.000120534,0.00007318131,0.8388039,0.01223481,0.01387188,0.03616251,0.09681272],"study_design_scores_gemma":[0.00003314716,0.00003834994,0.0001519472,0.000005748819,0.000006871051,0.00002091782,0.00001008748,0.9863946,0.005143759,0.001788892,0.006396641,0.000009018511],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07038601,0.0005875564,0.8547654,0.000516643,0.000455427,0.0002428258,0.009771692,0.02400417,0.03927036],"genre_scores_gemma":[0.4241603,0.000492265,0.5273294,0.0003735468,0.00009401737,0.0004327248,0.01706916,0.003040891,0.02700768],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009898951,"threshold_uncertainty_score":0.03311533,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01351343643216854,"score_gpt":0.3136746776863213,"score_spread":0.3001612412541528,"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."}}