{"id":"W2982055038","doi":"10.4095/220068","title":"DEM Extraction from High Resolution Imagery","year":2003,"lang":"en","type":"report","venue":"","topic":"Image Processing and 3D Reconstruction","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Extraction (chemistry); Computer science; High resolution; Resolution (logic); Artificial intelligence; Remote sensing; Computer vision; Geology; Chromatography; Chemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002442945,0.0009191504,0.0004974849,0.003330682,0.0002144771,0.0006708346,0.0005503391,0.0004709045,0.006482555],"category_scores_gemma":[0.0009355659,0.0003507441,0.0007388904,0.003225084,0.0001169766,0.0005837879,0.0005225029,0.0005345853,0.004872221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003010205,"about_ca_system_score_gemma":0.0005175713,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004469422,"about_ca_topic_score_gemma":0.004592078,"domain_scores_codex":[0.999826,0.00001651201,0.00001863265,0.00003877916,0.00007433093,0.00002580324],"domain_scores_gemma":[0.9996861,0.00003503813,0.00002401712,0.00006948165,0.0001723251,0.00001300934],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000373849,0.0002104248,0.009898906,0.001683433,0.0001798571,0.001454872,0.0003412072,0.1578452,0.0790988,0.005371376,0.06127956,0.6822625],"study_design_scores_gemma":[0.0001840419,0.0002230663,0.08458416,0.0002937292,0.0002718467,0.001246865,0.0007269293,0.6303508,0.0877008,0.009589196,0.1845981,0.000230501],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.1656068,0.001077501,0.5969935,0.000281028,0.0003246693,0.002120614,0.1732343,0.02651742,0.03384418],"genre_scores_gemma":[0.3627729,0.001288529,0.4740468,0.00008157039,0.00006129369,0.0008668193,0.1515939,0.0007791979,0.008509015],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.006482555,"threshold_uncertainty_score":0.02168626,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02674551852875313,"score_gpt":0.2782262238273753,"score_spread":0.2514807052986222,"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."}}