{"id":"W2279344620","doi":"10.29252/jgit.2.4.53","title":"An Automatic Algorithm based on Angular Histogram for Corregistartion of Synthetic Aperture Radar Images","year":2015,"lang":"en","type":"article","venue":"Journal of Geospatial Information Technology","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Histogram; Synthetic aperture radar; Artificial intelligence; Computer vision; Computer science; Radar; Radar imaging; Inverse synthetic aperture radar; Remote sensing; Geology; Image (mathematics); Telecommunications","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003480773,0.0001466263,0.0002999709,0.0006245577,0.00004084585,0.00002058914,0.0002662432,0.0002360008,0.00001507159],"category_scores_gemma":[0.0002294835,0.0001257407,0.00009230371,0.0002653848,0.00008761547,0.0003783452,0.000009183865,0.0001899985,0.000004281218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001356369,"about_ca_system_score_gemma":0.00007246956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000912719,"about_ca_topic_score_gemma":0.000001496752,"domain_scores_codex":[0.9988508,0.00001673283,0.0006788849,0.0000610133,0.0002446835,0.0001478944],"domain_scores_gemma":[0.9986598,0.00008832954,0.000434326,0.0003072743,0.0004364906,0.00007377735],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002335637,0.00007611011,0.00001458007,0.00005886359,0.00002103288,8.003761e-7,0.0001333829,0.0004798264,0.0003604287,0.0007944151,0.00263755,0.9953997],"study_design_scores_gemma":[0.0008106373,0.00129486,0.00004892368,0.0001030492,0.00005438534,0.00007016075,0.0003956325,0.6780943,0.02790965,0.002887942,0.2881399,0.0001904922],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002515141,0.0001035753,0.9955507,0.0007574101,0.0001867642,0.0003340829,0.00004053714,0.0003083246,0.0002034985],"genre_scores_gemma":[0.3553862,0.00001374697,0.6444001,0.00008722672,0.00003805643,0.00002593348,0.00003066585,0.00001559603,0.000002416157],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9952092,"threshold_uncertainty_score":0.5127559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005859815897216151,"score_gpt":0.2273288414381915,"score_spread":0.2214690255409753,"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."}}