{"id":"W2320685541","doi":"10.2514/6.2003-2820","title":"Canadian Experience on Radarsat 1 and Radarsat 2/GMTI for Surveillance","year":2003,"lang":"en","type":"article","venue":"AIAA International Air and Space Symposium and Exposition: The Next 100 Years","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Moving target indication; Remote sensing; Synthetic aperture radar; Computer science; Environmental science; Geology; Radar imaging; Radar; Telecommunications","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001134426,0.0001380865,0.0001107966,0.00006993621,0.0001784209,0.00008876584,0.000100654,0.00006740248,0.00002548352],"category_scores_gemma":[0.00001130787,0.0001156816,0.00003047826,0.00005933297,0.00008757931,0.000111876,0.00001426747,0.00008222182,0.000003194943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000638993,"about_ca_system_score_gemma":0.00001760031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001300408,"about_ca_topic_score_gemma":0.0005780721,"domain_scores_codex":[0.9993704,0.00001717436,0.0001197627,0.0002038723,0.0001124415,0.0001763236],"domain_scores_gemma":[0.9995782,0.0001136615,0.00002179554,0.0001426439,0.00003523012,0.0001084454],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002192053,0.0001672823,0.009431646,0.0001844298,0.0004799397,0.00003429169,0.01207542,0.0002777019,0.02050286,0.5646702,0.03767599,0.354281],"study_design_scores_gemma":[0.0003557228,0.00008738269,0.0030709,0.00003855227,0.00001115219,0.0001125056,0.0004250401,0.002431459,0.006891951,0.002171799,0.9841505,0.0002530923],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8805132,0.003181237,0.04813475,0.02963397,0.001104912,0.001358854,0.000208741,0.0003520183,0.03551232],"genre_scores_gemma":[0.9889772,0.001280285,0.008700037,0.0005645581,0.0000902562,0.00002768051,0.000014877,0.00002081203,0.0003243243],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9464744,"threshold_uncertainty_score":0.4717357,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00808445884110431,"score_gpt":0.2166105033220965,"score_spread":0.2085260444809922,"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."}}