{"id":"W2050583385","doi":"10.1007/s11004-012-9428-z","title":"Non-stationary Geostatistical Modeling Based on Distance Weighted Statistics and Distributions","year":2012,"lang":"en","type":"article","venue":"Mathematical Geosciences","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":51,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; University of Alberta","funders":"","keywords":"Variogram; Geostatistics; Covariance; Mathematics; Gaussian; Kriging; Spatial analysis; Weighting; Covariance function; Transformation (genetics); Range (aeronautics); Statistics; Gaussian process; Histogram; Spatial variability; Computer science; Artificial intelligence","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":[0.004465146,0.0009566589,0.001605063,0.001680603,0.0005397322,0.002093236,0.00245874,0.001115961,0.001203941],"category_scores_gemma":[0.01888551,0.0008803395,0.001418852,0.00229186,0.001718773,0.003320745,0.001555823,0.001743429,0.0004101373],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001298782,"about_ca_system_score_gemma":0.001630019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006645354,"about_ca_topic_score_gemma":0.005043605,"domain_scores_codex":[0.9977251,0.001239868,0.0001143886,0.0003331193,0.000475953,0.0001114923],"domain_scores_gemma":[0.9875754,0.009537646,0.001030788,0.0006615698,0.001019211,0.0001752924],"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":[0.00002470329,0.00002347428,0.0005907868,0.00004013643,0.00004677465,0.00004049121,0.00005080072,0.8754773,0.0003283044,0.1115226,0.0003876764,0.01146694],"study_design_scores_gemma":[0.000001552731,0.000004291145,0.0000480632,0.000002130963,0.000003504469,0.000007150419,0.00000296515,0.9816524,0.00006321652,0.01808846,0.0001220066,0.000004139478],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005602878,0.00009125217,0.9938583,0.00008092471,0.00001830346,0.00001060417,0.00002796782,0.00004956495,0.000260315],"genre_scores_gemma":[0.6293526,0.001477853,0.3570983,0.0001553279,0.0002551638,0.0003547897,0.000619079,0.0003396866,0.01034723],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006645354,"threshold_uncertainty_score":0.02361423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01594433308531435,"score_gpt":0.2537960446753275,"score_spread":0.2378517115900132,"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."}}