{"id":"W2089577646","doi":"10.1007/s11004-012-9402-9","title":"Multivariate Block-Support Simulation of the Yandi Iron Ore Deposit, Western Australia","year":2012,"lang":"en","type":"article","venue":"Mathematical Geosciences","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"AngloGold Ashanti","keywords":"Joint (building); Block (permutation group theory); Multivariate statistics; Scale (ratio); Geology; Iron ore; Geostatistics; Mineral exploration; Algorithm; Computer science; Mineralogy; Statistics; Mathematics; Geochemistry; Spatial variability; Engineering; Metallurgy; Materials science; Geography","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":[0.0003650278,0.0002216439,0.0002755354,0.0003259302,0.0003128842,0.0003631867,0.0007775471,0.0004938029,0.00113581],"category_scores_gemma":[0.001299226,0.0002203549,0.000314924,0.0003546081,0.0003595806,0.0002571837,0.0005200402,0.0002829417,0.0001114234],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001243258,"about_ca_system_score_gemma":0.001012307,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.134972,"about_ca_topic_score_gemma":0.09984049,"domain_scores_codex":[0.9999021,0.00002832137,0.000006397111,0.00001848747,0.0000246698,0.00001989983],"domain_scores_gemma":[0.9995667,0.0001948722,0.00004005546,0.00004532122,0.0001118123,0.00004131631],"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":[0.00008668638,0.00008292113,0.02134882,0.00001443373,0.00001760511,0.0001374986,0.0001041901,0.9715993,0.001594543,0.0008065405,0.0001259474,0.004081457],"study_design_scores_gemma":[0.000008263482,0.00001559396,0.003748117,9.8143e-7,0.000002644419,0.000005690235,0.0000276955,0.995625,0.0003544582,0.0001360387,0.00007267875,0.000002819117],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966074,0.000005115904,0.002468987,0.00002644262,0.000001408252,0.00001157797,0.00008291179,0.0000343735,0.000761729],"genre_scores_gemma":[0.9972197,0.000005773921,0.002172228,0.00000407849,5.053811e-7,0.0000100487,0.00009743335,0.000006000854,0.0004842742],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.134972,"threshold_uncertainty_score":0.2683727,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03715899103572258,"score_gpt":0.2981492179378288,"score_spread":0.2609902269021063,"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."}}