{"id":"W2151353827","doi":"10.1109/igarss.2004.1369796","title":"Synthetic aperture radar for search and rescue: polarimetry and interferometry","year":2004,"lang":"en","type":"article","venue":"","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada; Natural Resources Canada","funders":"Defence Research and Development Canada","keywords":"Synthetic aperture radar; Search and rescue; Remote sensing; Interferometry; Polarimetry; Inverse synthetic aperture radar; Computer science; Radar imaging; Radar; Space-based radar; Early-warning radar; Side looking airborne radar; Interferometric synthetic aperture radar; Geology; Radar engineering details; Artificial intelligence; Telecommunications; Optics; Physics","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":[0.0006215285,0.0003861591,0.0003181145,0.0005176066,0.0002015417,0.0007500273,0.0002319935,0.0004553142,0.001589833],"category_scores_gemma":[0.001031645,0.0001267067,0.0001139558,0.0006902648,0.0005053301,0.000839184,0.0004090093,0.0004574385,0.0008424445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000171663,"about_ca_system_score_gemma":0.0004053473,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006590246,"about_ca_topic_score_gemma":0.0007612355,"domain_scores_codex":[0.9996432,0.0001302887,0.000008876939,0.00001915789,0.0001813741,0.00001714384],"domain_scores_gemma":[0.9996156,0.0001433747,0.00003675444,0.00003431099,0.0001532515,0.00001677709],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002589047,0.00009629718,0.004185454,0.0004835806,0.00005417806,0.0001328402,0.0001952911,0.02074617,0.09342963,0.02758041,0.01438682,0.8384505],"study_design_scores_gemma":[0.0002498816,0.00133291,0.02486538,0.0004876029,0.0001726495,0.003682574,0.0009426647,0.3455006,0.1437959,0.09087639,0.3878694,0.0002238513],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08191445,0.07405854,0.7962382,0.007548004,0.0008408237,0.0001829608,0.0004166645,0.001219564,0.03758087],"genre_scores_gemma":[0.5786689,0.034942,0.3711425,0.0009469563,0.0007506985,0.0001198713,0.0009070239,0.0001667413,0.01235529],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001589833,"threshold_uncertainty_score":0.005318522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008016948969160888,"score_gpt":0.2295961084117256,"score_spread":0.2215791594425647,"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."}}