{"id":"W1969504503","doi":"10.5589/m07-023","title":"Polarimetric SAR image filtering with trace-based partial differential equations","year":2007,"lang":"en","type":"article","venue":"Canadian Journal of Remote Sensing","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Jet Propulsion Laboratory","keywords":"Speckle noise; Smoothing; Synthetic aperture radar; Regularization (linguistics); Speckle pattern; Partial differential equation; Computer vision; Artificial intelligence; Computer science; Mathematics; Algorithm; Mathematical analysis","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002149326,0.0001437669,0.0001868082,0.0005627413,0.0001388739,0.00007304859,0.0001056639,0.0000814675,0.00003508321],"category_scores_gemma":[0.00006597435,0.000131084,0.00007878397,0.0003826068,0.00006136012,0.00008598335,0.000002919933,0.0002760641,0.000003104622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002233852,"about_ca_system_score_gemma":0.0002257059,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002095802,"about_ca_topic_score_gemma":0.004447154,"domain_scores_codex":[0.9990897,0.00001504579,0.0003157267,0.00009303272,0.0001526793,0.0003338667],"domain_scores_gemma":[0.9991152,0.0001082573,0.00009324666,0.0001763315,0.0001238859,0.000383135],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000008094916,0.000003248325,0.00001918954,0.00001187614,0.0000354693,0.0001563366,0.000104548,0.00005002956,0.00577658,0.00005194319,0.0001270256,0.9936557],"study_design_scores_gemma":[0.000979063,0.0001917205,0.002520024,0.0004939731,0.0002270691,0.001210752,0.0002320408,0.2682433,0.2622345,0.0002150475,0.4626896,0.0007629424],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04750693,0.0002433263,0.9508411,0.0001466294,0.0001594165,0.00008497157,0.000006038495,0.00005354635,0.0009579884],"genre_scores_gemma":[0.528457,0.000002140554,0.471351,0.00001941464,0.0001392763,6.173011e-9,0.000001625285,0.00002365089,0.000005842247],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9928927,"threshold_uncertainty_score":0.5345451,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01072681667703531,"score_gpt":0.2143589942099993,"score_spread":0.203632177532964,"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."}}