{"id":"W1995064357","doi":"10.1117/12.477042","title":"&lt;title&gt;Synthetic aperture radar for search and rescue: evaluation of advanced capabilities in preparation for RADARSAT-2&lt;/title&gt;","year":2002,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"Canadian Space Agency; Goddard Space Flight Center","keywords":"Synthetic aperture radar; Search and rescue; Remote sensing; Inverse synthetic aperture radar; Computer science; Radar; Radar imaging; Geography; Telecommunications; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0009653176,0.0002867611,0.0002631073,0.0007709695,0.0003401906,0.0008815406,0.0003768668,0.0002826659,0.02902629],"category_scores_gemma":[0.0006719746,0.00008944865,0.000100298,0.0007332255,0.0002859884,0.0005973419,0.0003239787,0.0003236826,0.01082271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001024831,"about_ca_system_score_gemma":0.0009408852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01524914,"about_ca_topic_score_gemma":0.02975689,"domain_scores_codex":[0.9996655,0.00003096429,0.00000777943,0.00002238234,0.0002250118,0.00004848193],"domain_scores_gemma":[0.9987355,0.00009482366,0.00003967322,0.00004827321,0.0009179623,0.0001638081],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00113804,0.0002553964,0.006993202,0.00027519,0.00002858733,0.0002544394,0.00009160805,0.00364184,0.03153286,0.005969923,0.5048639,0.444955],"study_design_scores_gemma":[0.0002221797,0.001261087,0.02785293,0.0001242472,0.00003219774,0.0003306312,0.0002183349,0.01189904,0.06283122,0.002124971,0.8930566,0.00004658578],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1131219,0.009804468,0.04728898,0.009788259,0.007548204,0.001946166,0.02608646,0.005721738,0.7786939],"genre_scores_gemma":[0.378685,0.008904573,0.05041695,0.001217191,0.001081183,0.0002918025,0.03580062,0.001467982,0.5221347],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02902629,"threshold_uncertainty_score":0.09710264,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01453151936205466,"score_gpt":0.2496145433027427,"score_spread":0.235083023940688,"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."}}