{"id":"W2169728719","doi":"10.1109/igarss.2012.6352487","title":"All optical Synthetic Aperture Lidar sensing-to-processing chain based on SAR technology","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Optical Sensing Technologies","field":"Physics and Astronomy","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National d'Optique","funders":"","keywords":"Synthetic aperture radar; Lidar; Payload (computing); Computer science; Remote sensing; 3D optical data storage; Aperture (computer memory); Data processing; Image resolution; Computer vision; Artificial intelligence; Optics; Geology; Engineering; Physics","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":[0.000478739,0.0004535634,0.0004710237,0.0005650354,0.0005074322,0.001290897,0.000736987,0.0003967836,0.005304654],"category_scores_gemma":[0.0006124758,0.00035139,0.0002565552,0.0006280587,0.0003653585,0.00127133,0.001023367,0.0005970562,0.002344764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003547311,"about_ca_system_score_gemma":0.0008940464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006246337,"about_ca_topic_score_gemma":0.0009635859,"domain_scores_codex":[0.9993913,0.00005055846,0.0000344961,0.000119676,0.0003416778,0.00006214232],"domain_scores_gemma":[0.9994472,0.00009407147,0.00005422463,0.00008667799,0.0002842287,0.00003354938],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00053228,0.000379258,0.00373897,0.0005073888,0.00008889678,0.000508003,0.0004541583,0.009873413,0.5554076,0.01573624,0.007341521,0.4054322],"study_design_scores_gemma":[0.0001596958,0.00157615,0.007412945,0.0001738633,0.0001302235,0.001609598,0.0002686083,0.2109811,0.6482913,0.01119475,0.1180734,0.0001282999],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.107317,0.0008936906,0.8540568,0.0007365571,0.0003468307,0.0007354895,0.0005022668,0.008108456,0.02730296],"genre_scores_gemma":[0.4851673,0.001264556,0.4867078,0.001090107,0.0004068869,0.00038629,0.001115132,0.0003157679,0.02354616],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005304654,"threshold_uncertainty_score":0.01774585,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01174061888557731,"score_gpt":0.2592532348371254,"score_spread":0.2475126159515481,"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."}}