{"id":"W4237255168","doi":"10.32920/ryerson.14644716","title":"The generation of digital elevation models using open source images","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Satellite Image Processing and Photogrammetry","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Ministry of Economy, Trade and Industry; U.S. Geological Survey; National Aeronautics and Space Administration","keywords":"Digital elevation model; Remote sensing; Advanced Spaceborne Thermal Emission and Reflection Radiometer; Elevation (ballistics); Satellite; Ranging; Geology; Geography; Cartography; Geodesy; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0008373496,0.001068761,0.0004798645,0.002707587,0.0003852641,0.00188571,0.001500776,0.0007102343,0.006672755],"category_scores_gemma":[0.00426328,0.0006524234,0.001223318,0.002793958,0.0002911962,0.001659468,0.001557809,0.001121451,0.006242945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006162167,"about_ca_system_score_gemma":0.0007975181,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006222484,"about_ca_topic_score_gemma":0.008580414,"domain_scores_codex":[0.9993286,0.00006639856,0.00006796952,0.000133037,0.0003483275,0.00005567259],"domain_scores_gemma":[0.9986095,0.0002108306,0.00008435254,0.0003831432,0.0006595167,0.00005258052],"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":[0.0002562049,0.0004285112,0.009129797,0.0006609132,0.0002611105,0.0009625686,0.0006244458,0.2174068,0.01753157,0.01602925,0.1130921,0.6236167],"study_design_scores_gemma":[0.00009048564,0.00005438754,0.006987683,0.0001344042,0.00006360597,0.0003182474,0.0003484808,0.7847478,0.02801759,0.01482512,0.1642734,0.0001388405],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02593855,0.0001786016,0.8737392,0.0002561228,0.0003726362,0.0006478418,0.02845004,0.05245645,0.01796047],"genre_scores_gemma":[0.1868533,0.0005655795,0.70204,0.0001067706,0.00007182045,0.0008777805,0.09329239,0.006034298,0.01015805],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006672755,"threshold_uncertainty_score":0.02232265,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08440939087359643,"score_gpt":0.2885525334883393,"score_spread":0.2041431426147429,"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."}}