{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001287492,0.0001810876,0.0001574079,0.0003039958,0.0003102952,0.000127547,0.00004981238,0.0000595185,0.000002806833],"category_scores_gemma":[0.000005396472,0.0001525697,0.00002507521,0.0004872548,0.0001152162,0.0002083921,0.000001119651,0.0002138287,0.000002677681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002173272,"about_ca_system_score_gemma":0.00004371492,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005003121,"about_ca_topic_score_gemma":0.00006044416,"domain_scores_codex":[0.9990559,0.0000145549,0.0001681048,0.0003145375,0.000174971,0.0002718875],"domain_scores_gemma":[0.999588,0.00002851385,0.0000230651,0.0001456469,0.00003969167,0.0001751566],"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":[0.00001598645,0.000008246905,0.000009710692,0.00002179591,0.000009464363,0.00001431531,0.000708311,0.003587733,0.002682897,9.559546e-8,0.000002383964,0.9929391],"study_design_scores_gemma":[0.0002243688,0.00008335966,0.00005262828,0.00006858858,0.00004404504,0.0004807456,0.00007544756,0.9607992,0.03783899,0.00006473331,0.00004784075,0.0002200895],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.364877,0.0001638546,0.6345103,0.000009172286,0.0001664629,0.00005515166,0.000001350319,0.0001013232,0.0001154407],"genre_scores_gemma":[0.7962145,0.0002403574,0.2033601,0.00006775154,0.0000416676,5.105926e-8,5.251546e-7,0.00002014365,0.00005485689],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.992719,"threshold_uncertainty_score":0.6221613,"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."}}