{"id":"W4254278515","doi":"10.4095/219697","title":"Calibrated Polarimetric SAR Data for Ship Detection","year":2000,"lang":"en","type":"report","venue":"","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Remote sensing; Polarimetry; Computer science; Geology; Physics; Optics","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":[0.0006666585,0.0005156762,0.0002796809,0.0008797034,0.000204636,0.0005410659,0.0004770945,0.0003623743,0.008474811],"category_scores_gemma":[0.002699798,0.0002327629,0.0002595697,0.001093182,0.0002219353,0.0005839242,0.0003398409,0.0004628444,0.002681087],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000232415,"about_ca_system_score_gemma":0.0004528914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006693281,"about_ca_topic_score_gemma":0.001163391,"domain_scores_codex":[0.999317,0.0001958793,0.00002630343,0.00008277236,0.0003306133,0.00004735155],"domain_scores_gemma":[0.9988415,0.0002930946,0.00008024591,0.0003777667,0.0003794963,0.0000279099],"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":[0.001481141,0.0004594086,0.0435479,0.001071926,0.0003569569,0.0004547532,0.000150577,0.1227268,0.3587298,0.01634252,0.02328536,0.4313929],"study_design_scores_gemma":[0.0001586628,0.0006757581,0.1109884,0.0001734545,0.0002938761,0.001518928,0.0002009147,0.2270188,0.5921785,0.007941241,0.05867318,0.0001781339],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5487347,0.001737042,0.3580995,0.0004263934,0.0002538268,0.0004595839,0.01856805,0.002987913,0.06873298],"genre_scores_gemma":[0.8431191,0.0009066341,0.1247239,0.0001944903,0.00003313357,0.0001997832,0.02487621,0.0003557254,0.005590956],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008474811,"threshold_uncertainty_score":0.02835101,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05390981090796101,"score_gpt":0.2924227295702042,"score_spread":0.2385129186622432,"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."}}