{"id":"W2157932537","doi":"10.1109/tgrs.2002.805070","title":"Characterization of target symmetric scattering using polarimetric SARs","year":2002,"lang":"en","type":"article","venue":"IEEE Transactions on Geoscience and Remote Sensing","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":181,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Scattering; Synthetic aperture radar; Computer science; Scattering amplitude; Scattering theory; Context (archaeology); Rayleigh scattering; Physics; Remote sensing; Optics; Artificial intelligence; Geology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009742127,0.0001290069,0.0001511688,0.0005779927,0.0001885426,0.00003127698,0.00006888119,0.00007685956,0.00001102839],"category_scores_gemma":[0.000003954766,0.0001257626,0.00004529395,0.001276019,0.00009839826,0.0001453635,0.000001247841,0.0001264637,0.000003151208],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004392622,"about_ca_system_score_gemma":0.000005585049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001416734,"about_ca_topic_score_gemma":0.000001893253,"domain_scores_codex":[0.9992437,0.00001395577,0.0002071034,0.0001920876,0.0001546688,0.0001884813],"domain_scores_gemma":[0.9996462,0.00003760315,0.00004461358,0.0001838141,0.00003581109,0.00005193192],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[6.552772e-7,0.00001027001,9.349482e-7,0.00001572707,0.000005356091,7.044338e-7,0.00006567124,0.00004328617,0.2264403,0.000003739962,7.95205e-7,0.7734125],"study_design_scores_gemma":[0.00005116019,0.00001762586,0.0001758395,0.00005843585,0.00001611342,0.00005194438,0.00001536355,0.6476694,0.35051,0.00003085284,0.001279087,0.0001241084],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2095604,0.00005836471,0.7897221,0.00003617778,0.0001564288,0.0001004129,0.000007875553,0.0001246195,0.0002336303],"genre_scores_gemma":[0.6251297,0.0002005748,0.3745966,0.00002246401,0.00001362458,5.794412e-8,5.145137e-7,0.00001376748,0.00002273223],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7732884,"threshold_uncertainty_score":0.5128449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01665023370348135,"score_gpt":0.2170362880660577,"score_spread":0.2003860543625763,"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."}}