{"id":"W2102933901","doi":"","title":"Computer Simulations of Canada's RADARSAT2 GMTI","year":2000,"lang":"en","type":"article","venue":"Defense Technical Information Center (DTIC)","topic":"Advanced SAR Imaging Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Moving target indication; Clutter; Computer science; Stationary target indication; Computer vision; Visibility; Synthetic aperture radar; Artificial intelligence; Radar; Context (archaeology); Interferometry; Remote sensing; Radar imaging; Bistatic radar; Continuous-wave radar; Geology; Physics; Optics; Telecommunications","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0002681564,0.0006218158,0.0005332489,0.0004135561,0.0007416978,0.0007149435,0.001054378,0.001024012,0.005855313],"category_scores_gemma":[0.00185809,0.0002794802,0.0003829665,0.0008116822,0.0005250528,0.0004128424,0.0003405343,0.000697649,0.0004918859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002321079,"about_ca_system_score_gemma":0.002019261,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3623569,"about_ca_topic_score_gemma":0.3113245,"domain_scores_codex":[0.9998347,0.000030147,0.00000483691,0.00002208965,0.0000545416,0.00005366058],"domain_scores_gemma":[0.9987001,0.0007115652,0.00005533205,0.00004219199,0.0004066091,0.00008412528],"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":[0.00006337539,0.00003410591,0.001369134,0.0000258383,0.00001009213,0.00004221819,0.00003371239,0.9935411,0.0003136141,0.001544233,0.001642392,0.001380027],"study_design_scores_gemma":[0.00002043664,0.00001371958,0.0006882026,0.000003723888,0.000004076821,0.00000744268,0.00003055048,0.9981074,0.0001962525,0.000294983,0.0006273821,0.000005774054],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9214744,0.0004371984,0.01360199,0.000910114,0.00008897586,0.00008895846,0.006003509,0.0008007628,0.05659411],"genre_scores_gemma":[0.9853793,0.0001966591,0.005576585,0.0001183295,0.00001226111,0.00008264491,0.00309828,0.00009617289,0.005439713],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6376431,"threshold_uncertainty_score":0.7204955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006963991997329763,"score_gpt":0.2120725815540161,"score_spread":0.2051085895566863,"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."}}