{"id":"W92173118","doi":"","title":"DENSIFICATION OF DTM GRID DATA USING SINGLE SATELLITE IMAGERY","year":2002,"lang":"en","type":"article","venue":"","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Remote sensing; Digital elevation model; Photogrammetry; Terrain; Grid; Satellite; Elevation (ballistics); Computer science; Satellite imagery; Photometric stereo; Triangulated irregular network; Geology; Computer vision; Geography; Artificial intelligence; Geodesy; Cartography; Image (mathematics); Mathematics","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":[0.0009264886,0.0003397582,0.0005246131,0.001568256,0.0003091932,0.0008739533,0.0004924982,0.0002821669,0.001011389],"category_scores_gemma":[0.005367457,0.0002940012,0.0004757133,0.001292466,0.0003505086,0.001176453,0.000841367,0.0005057676,0.0002481227],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000767811,"about_ca_system_score_gemma":0.0003214813,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01029184,"about_ca_topic_score_gemma":0.01250207,"domain_scores_codex":[0.9996769,0.00004779999,0.00003676728,0.00007851164,0.000130616,0.00002938397],"domain_scores_gemma":[0.997995,0.0007293047,0.0001447172,0.0007354743,0.0003480956,0.00004748096],"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":[0.000164526,0.00005278775,0.01474491,0.00009968808,0.00005027971,0.0001878276,0.0005043063,0.7135811,0.007362521,0.008544128,0.002359021,0.2523489],"study_design_scores_gemma":[0.00001602488,0.00002436189,0.004845246,0.00001507391,0.00001272281,0.00008886328,0.0001387784,0.9789218,0.005751873,0.005767357,0.004399194,0.00001871593],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3986944,0.0003739988,0.5930979,0.0002439691,0.0001272879,0.0001606913,0.001146252,0.002306605,0.003848976],"genre_scores_gemma":[0.7150218,0.0002093828,0.281258,0.00004221312,0.0000251694,0.0001009263,0.002157689,0.0002137922,0.0009709654],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01029184,"threshold_uncertainty_score":0.02046388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1111948029032979,"score_gpt":0.2662753938919248,"score_spread":0.1550805909886269,"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."}}