{"id":"W2037628836","doi":"10.1109/igarss.2007.4423066","title":"Ship signatures in synthetic aperture radar imagery","year":2007,"lang":"en","type":"article","venue":"","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Synthetic aperture radar; Inverse synthetic aperture radar; Automatic Identification System; Radar imaging; Side looking airborne radar; Remote sensing; Computer science; Radar cross-section; Signature (topology); Early-warning radar; Radar; Geology; Identification (biology); Bistatic radar; Telecommunications; Real-time computing; Mathematics","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":[0.0003314122,0.0001790771,0.0001357744,0.0009241866,0.0000934183,0.0005366005,0.0001491906,0.0002108161,0.00096522],"category_scores_gemma":[0.001618402,0.0001711529,0.0001565334,0.00112845,0.0002533768,0.0005481254,0.0003312363,0.0002161037,0.0006741803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001565348,"about_ca_system_score_gemma":0.0001643424,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008269496,"about_ca_topic_score_gemma":0.0006447275,"domain_scores_codex":[0.9997806,0.00005118362,0.00001144957,0.00002863695,0.0001093652,0.00001870662],"domain_scores_gemma":[0.999649,0.0001086759,0.00007198635,0.00005723882,0.00008957017,0.00002349912],"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":[0.00048065,0.00009854488,0.0196382,0.0003132867,0.0000845726,0.0007738333,0.0004034264,0.1905707,0.2714273,0.02911511,0.005629795,0.4814646],"study_design_scores_gemma":[0.00003317674,0.0001355565,0.04006617,0.00004816726,0.0000350133,0.001272682,0.0002264496,0.8577602,0.07128776,0.01150043,0.01758573,0.00004872821],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.523892,0.001257398,0.4651735,0.0002917807,0.0001114819,0.00005093837,0.001282241,0.001059039,0.006881549],"genre_scores_gemma":[0.8662586,0.001022507,0.126319,0.00006873416,0.00007525365,0.000025614,0.001848637,0.0001809128,0.004200716],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00096522,"threshold_uncertainty_score":0.003228962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006055533905179716,"score_gpt":0.2191436923013941,"score_spread":0.2130881583962144,"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."}}