{"id":"W2411234846","doi":"","title":"Inference of 2D and 3D locally varying anisotropy fields for complex geological formations","year":2012,"lang":"en","type":"article","venue":"","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Inference; Anisotropy; Interpolation (computer graphics); Field (mathematics); Kriging; Computer science; Tensor (intrinsic definition); Algorithm; Focus (optics); Geology; Data mining; Mathematics; Geometry; Artificial intelligence; Machine learning; Physics; Image (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":[0.001367778,0.0004637718,0.0004527317,0.003589773,0.0004579679,0.001480037,0.0006895724,0.0005554183,0.000988433],"category_scores_gemma":[0.005983574,0.0005725354,0.0009200655,0.001582512,0.0007748116,0.0009130721,0.0008497532,0.0006875166,0.0004137213],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000885934,"about_ca_system_score_gemma":0.0009640088,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0120518,"about_ca_topic_score_gemma":0.0184595,"domain_scores_codex":[0.9994363,0.0001190737,0.00003564408,0.0001775269,0.000160472,0.00007095774],"domain_scores_gemma":[0.9980546,0.000971241,0.000330922,0.0002808643,0.000276327,0.00008606927],"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":[0.0001360036,0.00009314926,0.08034801,0.0002116111,0.0001457709,0.0003358489,0.000491867,0.6259296,0.01529772,0.02065076,0.003326078,0.2530335],"study_design_scores_gemma":[0.000009344554,0.00001031189,0.01580352,0.00002137622,0.00001345458,0.0001148084,0.000117078,0.9680854,0.002606222,0.01130955,0.001875849,0.00003315088],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1390895,0.0002219509,0.8557234,0.0001712411,0.0000177284,0.0000538118,0.001191046,0.001845065,0.001686277],"genre_scores_gemma":[0.7136733,0.0002321595,0.2831264,0.00004446859,0.00003096584,0.00005920729,0.001925563,0.000201211,0.0007067116],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0120518,"threshold_uncertainty_score":0.02396327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04419549509336952,"score_gpt":0.2792772256065958,"score_spread":0.2350817305132263,"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."}}