{"id":"W2182940581","doi":"","title":"Inference of 2D and 3D Locally Varying Anisotropy Fields","year":2013,"lang":"en","type":"article","venue":"","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Focus (optics); Kriging; Anisotropy; Inference; Field (mathematics); Orientation (vector space); Algorithm; Computer science; Mathematics; Data mining; Artificial intelligence; Geometry; Machine learning; Physics","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":[0.0009301073,0.0004651541,0.0004590139,0.002189892,0.0002621121,0.001234259,0.0005664455,0.0005594293,0.000907116],"category_scores_gemma":[0.004064383,0.0004961875,0.0008003921,0.001349744,0.0004808094,0.0008022219,0.0007344899,0.0007419898,0.0004082285],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004542917,"about_ca_system_score_gemma":0.0006963056,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007901892,"about_ca_topic_score_gemma":0.01221593,"domain_scores_codex":[0.999642,0.00009269117,0.0000181856,0.0001105844,0.00008894569,0.00004760507],"domain_scores_gemma":[0.9988315,0.0006654967,0.0001604283,0.0001685877,0.0001231618,0.00005092286],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001577437,0.00008178517,0.0273899,0.0001820015,0.0001362085,0.0002047692,0.0002484293,0.6965501,0.02225593,0.01834622,0.002083156,0.2323638],"study_design_scores_gemma":[0.000009028118,0.00001222075,0.007718636,0.00001645229,0.00001412461,0.00006184963,0.00007155434,0.9764467,0.003608378,0.01039779,0.001611937,0.00003122364],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.09736505,0.0002212635,0.8983375,0.0001448634,0.00002161383,0.00003335324,0.00107342,0.001213342,0.001589644],"genre_scores_gemma":[0.7121016,0.0003329739,0.2844877,0.00004879055,0.00003512362,0.00006349092,0.001851339,0.0001683232,0.0009106075],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007901892,"threshold_uncertainty_score":0.01571184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0102933196281274,"score_gpt":0.2212203149187583,"score_spread":0.2109269952906309,"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."}}