{"id":"W2330073205","doi":"10.5721/eujrs20154803","title":"Game Theoretic Classification of Polarimetric SAR images","year":2015,"lang":"en","type":"article","venue":"European Journal of Remote Sensing","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Space Agency","keywords":"Pattern recognition (psychology); Computer science; Artificial intelligence; Cluster analysis; Polarimetry; Measure (data warehouse); Similarity measure; Similarity (geometry); Synthetic aperture radar; Image (mathematics); Data mining","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0009379665,0.0001093567,0.0001894314,0.0002543218,0.00001988094,0.00002320693,0.0001512389,0.00002585089,0.000003535932],"category_scores_gemma":[0.0001653405,0.00009269667,0.0000806344,0.0002977212,0.00006832376,0.00007177448,0.00001854151,0.0002025634,0.0000127436],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000547141,"about_ca_system_score_gemma":0.00002226107,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004687814,"about_ca_topic_score_gemma":1.270809e-7,"domain_scores_codex":[0.9990272,0.0001409908,0.0004310901,0.00007645468,0.0002071025,0.0001171409],"domain_scores_gemma":[0.9991397,0.00006805934,0.0002264901,0.000233705,0.0002372859,0.00009472001],"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":[0.000007170143,0.000006642107,0.00001118431,0.00001487705,0.00002258083,0.0000225126,0.0001974128,0.00001426089,0.01269975,0.0001678489,0.0005567231,0.986279],"study_design_scores_gemma":[0.001102371,0.0003974008,0.007656249,0.0007658009,0.000228855,0.002340205,0.0008207969,0.06320903,0.2208889,0.004887348,0.6970916,0.0006113804],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04261083,0.0009679069,0.9256049,0.0001334784,0.0001346107,0.00005532017,0.000001454835,0.00007974809,0.03041179],"genre_scores_gemma":[0.5674672,0.00007810789,0.4323064,0.00001075175,0.00009623141,9.235894e-10,6.476851e-7,0.00002761351,0.00001299551],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9856676,"threshold_uncertainty_score":0.3780061,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02091852170454824,"score_gpt":0.2336423506007936,"score_spread":0.2127238288962454,"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."}}