{"id":"W2982003849","doi":"10.4095/219806","title":"Ship Detection Using Airborne Polarimetric SAR","year":2001,"lang":"en","type":"report","venue":"","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Remote sensing; Polarimetry; Environmental science; Geology; Computer science; Physics; Optics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003441034,0.0004066758,0.0002634412,0.001280405,0.0002173949,0.0008772317,0.0002065331,0.0002238774,0.001298752],"category_scores_gemma":[0.0007560844,0.0002591338,0.0001283858,0.001449326,0.0001644799,0.000593407,0.0005342726,0.0002335294,0.0008921194],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002286416,"about_ca_system_score_gemma":0.0007121837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02518101,"about_ca_topic_score_gemma":0.04908546,"domain_scores_codex":[0.9995543,0.00006137395,0.00001123824,0.00005902349,0.0002702438,0.00004377612],"domain_scores_gemma":[0.9996222,0.00005834709,0.00002166152,0.00005304378,0.000227693,0.00001697856],"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":[0.0003795938,0.0001200461,0.02279146,0.000322834,0.0001200972,0.0003723651,0.0002588497,0.04091375,0.2778492,0.003611617,0.01543785,0.6378223],"study_design_scores_gemma":[0.000169561,0.0006310103,0.199173,0.0001610101,0.0002375335,0.0019271,0.0005124616,0.3885162,0.2834965,0.005234177,0.119712,0.0002296101],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4826173,0.002752309,0.4174251,0.0004253235,0.0002090799,0.000368933,0.007317003,0.004658026,0.08422697],"genre_scores_gemma":[0.7331753,0.004037145,0.2304801,0.0001618885,0.0001291564,0.00008092471,0.01274484,0.0001819846,0.0190086],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02518101,"threshold_uncertainty_score":0.05006891,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03478221282477587,"score_gpt":0.2747449130628041,"score_spread":0.2399627002380282,"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."}}