{"id":"W2894634227","doi":"10.1130/ges01688.1","title":"3-D stratigraphic mapping using a digital outcrop model derived from UAV images and structure-from-motion photogrammetry","year":2018,"lang":"en","type":"article","venue":"Geosphere","topic":"3D Surveying and Cultural Heritage","field":"Earth and Planetary Sciences","cited_by":68,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; University of Calgary","funders":"","keywords":"Geology; Outcrop; Facies; Photogrammetry; Fluvial; Channel (broadcasting); Digital elevation model; Structure from motion; Geomorphology; Paleontology; Remote sensing; Motion (physics); Artificial intelligence","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":[0.00008552655,0.000472378,0.0001855147,0.0009675482,0.0002113356,0.0004930118,0.0003665922,0.0002460737,0.001311753],"category_scores_gemma":[0.0002348067,0.0002348309,0.0003399748,0.0007011053,0.0002512361,0.0002557103,0.0003847122,0.0002026313,0.000427011],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006010661,"about_ca_system_score_gemma":0.001046447,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0506274,"about_ca_topic_score_gemma":0.1411399,"domain_scores_codex":[0.9999162,0.000003920116,0.000003256088,0.00002480982,0.00003983236,0.00001200823],"domain_scores_gemma":[0.9999275,0.000009099377,0.00001184518,0.00001546008,0.00002657176,0.000009590723],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001363919,0.0001768309,0.06601173,0.0004163728,0.00009043394,0.0008285261,0.0009619729,0.3329965,0.2120785,0.003013026,0.003701285,0.3795885],"study_design_scores_gemma":[0.00002495553,0.0001079127,0.08246008,0.00005936959,0.0000402021,0.0004891786,0.0005125633,0.8747598,0.03152824,0.00097183,0.008978574,0.00006732719],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5221235,0.0002157001,0.4642789,0.0001074245,0.00003637261,0.0003360927,0.002942498,0.002567205,0.007392274],"genre_scores_gemma":[0.7718896,0.0002047859,0.2241931,0.00002317327,0.000005370297,0.00009714783,0.001693495,0.00009955325,0.001793876],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0506274,"threshold_uncertainty_score":0.1006655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02383651176760718,"score_gpt":0.2102097597264563,"score_spread":0.1863732479588492,"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."}}