{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005551821,0.0002683316,0.0003110233,0.0002272207,0.0002198822,0.0004447492,0.0003867348,0.0004438073,0.0001677254],"category_scores_gemma":[0.0001541138,0.0002469725,0.0001300329,0.0002860436,0.00005320099,0.0009656553,0.00008153822,0.0005246718,0.0002083441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003302609,"about_ca_system_score_gemma":0.001526991,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001537464,"about_ca_topic_score_gemma":0.00003203113,"domain_scores_codex":[0.9976858,0.00009927023,0.0004477586,0.0007505149,0.0007269725,0.0002897228],"domain_scores_gemma":[0.9982671,0.0000708996,0.0004429261,0.0006406984,0.0004996707,0.00007877019],"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":[0.000004973051,0.0000669112,0.0001555515,0.00008638917,0.00006976433,0.00005518075,0.00004000389,0.00002285659,0.000751205,0.000710032,0.2247562,0.773281],"study_design_scores_gemma":[0.0007424518,0.00009487881,0.004968118,0.0007435552,0.0002228874,0.002889749,0.00005348656,0.01825571,0.02087343,0.03403854,0.9148054,0.00231183],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0002525942,0.001428877,0.8034127,0.0001846143,0.009872006,0.00008899488,0.000007012857,0.0004436275,0.1843095],"genre_scores_gemma":[0.02016733,0.002467521,0.8308139,0.0002783539,0.002801301,0.00004775174,0.0002555271,0.00007804017,0.1430903],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7709692,"threshold_uncertainty_score":0.9999983,"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."}}