{"id":"W2600974057","doi":"","title":"Using geostatistical Bayesian Updating to integrate airborne radiometrics and soil geochemistry to improve mapping for mineral exploration","year":2014,"lang":"en","type":"article","venue":"Research Portal (Queen's University Belfast)","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Geostatistics; Sampling (signal processing); Bayesian inference; Bayesian probability; Mineral exploration; Remote sensing; Data mining; Digital soil mapping; Geology; Computer science; Soil map; Spatial variability; Soil science; Statistics; Artificial intelligence; Soil water; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.002810016,0.0004624125,0.0004423612,0.001005647,0.000330898,0.00104729,0.001089791,0.0005910711,0.0009465294],"category_scores_gemma":[0.01128934,0.0004485469,0.0006092245,0.001551598,0.0006510334,0.001255283,0.001021672,0.0008589317,0.0003577234],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009235607,"about_ca_system_score_gemma":0.00154671,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03190785,"about_ca_topic_score_gemma":0.0544127,"domain_scores_codex":[0.9988251,0.0004525942,0.00005767363,0.0002069564,0.0003986435,0.00005908289],"domain_scores_gemma":[0.9976914,0.001226996,0.0003201258,0.0002498407,0.0004744971,0.00003702475],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006041921,0.0001204531,0.01066562,0.00009855037,0.0001387284,0.0001104553,0.0004271486,0.5781661,0.00416626,0.02414784,0.001524902,0.3803735],"study_design_scores_gemma":[0.00001130655,0.00003505361,0.003417993,0.00002210673,0.00003324808,0.00006475216,0.00005259761,0.9779375,0.001303471,0.01350201,0.003591251,0.00002873741],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01463505,0.0000873528,0.9832268,0.0001143378,0.00001278271,0.0000309445,0.00004315983,0.0003293804,0.001520165],"genre_scores_gemma":[0.3868333,0.0003361273,0.6094312,0.000139617,0.00004846304,0.0001002479,0.0004105821,0.0001654348,0.002535002],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03190785,"threshold_uncertainty_score":0.06344426,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03701351096393123,"score_gpt":0.2862222161335353,"score_spread":0.249208705169604,"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."}}