{"id":"W2339024370","doi":"10.3997/2214-4609.201600354","title":"A Novel Workflow for Building Multiple Point Statistics Training Images from Virtual Outcrops","year":2016,"lang":"en","type":"article","venue":"Proceedings","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Suncor Energy Incorporated; ConocoPhillips","keywords":"Outcrop; Workflow; Facies; Photogrammetry; Lidar; Geology; Scale (ratio); Data mining; Computer science; Remote sensing; Structural basin; Geomorphology; Cartography; Geography; Database","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002735248,0.0002010927,0.0002322703,0.00009587609,0.0000655273,0.00008711247,0.0001607542,0.00008978793,0.00002866377],"category_scores_gemma":[0.00100291,0.000163678,0.00006124959,0.0001120699,0.0000240374,0.0002689113,0.00002744659,0.0001039177,0.000008624701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007000228,"about_ca_system_score_gemma":0.000009946811,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007595183,"about_ca_topic_score_gemma":8.747407e-7,"domain_scores_codex":[0.9989714,0.000002506621,0.0002759322,0.0002359927,0.0001553395,0.0003588316],"domain_scores_gemma":[0.999027,0.000606405,0.0000393852,0.00008575666,0.0001250246,0.0001164075],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004713476,0.00001777996,0.001116702,0.0001041728,0.00009398007,0.000001025559,0.001496712,0.09812045,0.8008403,0.002707006,0.002484277,0.0929705],"study_design_scores_gemma":[0.002477083,0.00006037902,0.001270227,0.0002340577,0.0000315066,0.000003374642,0.000197162,0.9267003,0.05457934,0.003293297,0.01063544,0.0005178346],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1621958,0.00005019696,0.8363573,0.00008892651,0.000309653,0.0001594642,0.0002406155,0.0004605752,0.0001374094],"genre_scores_gemma":[0.5128512,0.000009515186,0.4867056,0.00001080827,0.000202922,0.00004139054,0.00000519935,0.00005133703,0.0001219956],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8285798,"threshold_uncertainty_score":0.6674596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03194735566623171,"score_gpt":0.2698988190489264,"score_spread":0.2379514633826947,"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."}}