{"id":"W2037886680","doi":"10.1109/tgrs.2011.2170693","title":"Radarsat-2 DSM Generation With New Hybrid, Deterministic, and Empirical Geometric Modeling Without GCP","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Geoscience and Remote Sensing","topic":"Satellite Image Processing and Photogrammetry","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"Canadian Space Agency","keywords":"Digital elevation model; Computer science; Polynomial; Lidar; Elevation (ballistics); Digital surface; Function (biology); Remote sensing; Algorithm; Mathematics; Geometry; Geography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0007721455,0.001012953,0.0005968511,0.001038163,0.0002706711,0.0007973581,0.0009187934,0.0004612127,0.001271794],"category_scores_gemma":[0.001310518,0.0003513939,0.0008272925,0.001169417,0.0002223019,0.000804164,0.0006588048,0.0003387606,0.000435653],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009188797,"about_ca_system_score_gemma":0.0007522646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01427216,"about_ca_topic_score_gemma":0.01520235,"domain_scores_codex":[0.999585,0.00007362516,0.00002877879,0.00007532995,0.0001787609,0.00005855568],"domain_scores_gemma":[0.9993902,0.0001154269,0.00005440122,0.0001622461,0.0002535664,0.00002410708],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005894271,0.0002157628,0.00977215,0.0001866676,0.000167805,0.0001190757,0.00006826407,0.8558936,0.0108322,0.001144219,0.001355444,0.1196554],"study_design_scores_gemma":[0.00006724679,0.0000992498,0.004141891,0.000007316906,0.00004363588,0.0000388914,0.0000391767,0.9876224,0.006678668,0.0002871784,0.0009476459,0.00002655144],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7748577,0.0004274208,0.2079539,0.0001649076,0.0001009774,0.0002890823,0.003554089,0.005203232,0.007448699],"genre_scores_gemma":[0.8879468,0.0001217228,0.1066802,0.00003334464,0.00001082436,0.00010884,0.003962822,0.0002229689,0.000912517],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01427216,"threshold_uncertainty_score":0.02837819,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05503364907465035,"score_gpt":0.2530802136045916,"score_spread":0.1980465645299412,"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."}}