{"id":"W4206661796","doi":"10.1007/s11053-021-10003-w","title":"Combination of Machine Learning and Kriging for Spatial Estimation of Geological Attributes","year":2022,"lang":"en","type":"article","venue":"Natural Resources Research","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":77,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Kriging; Mean squared error; Gaussian; Weighting; Variance (accounting); Statistics; Gaussian process; Algorithm; Variogram; Mathematics; Gaussian network model; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001134786,0.00004140756,0.00009103671,0.00007343462,0.000310338,0.00001049004,0.0001070645,0.00002083515,0.0002751825],"category_scores_gemma":[0.001016681,0.00003667033,0.00001844306,0.0002088311,0.0001783258,0.0000333487,0.0003891764,0.0002765069,9.456136e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004727127,"about_ca_system_score_gemma":0.000005142263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001099386,"about_ca_topic_score_gemma":0.00003167295,"domain_scores_codex":[0.9988842,0.0001552396,0.0001351217,0.0001361009,0.0005283203,0.0001610174],"domain_scores_gemma":[0.9990833,0.0007432696,0.00006749665,0.00004654739,0.00003296798,0.00002638222],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005783824,0.0001995467,0.3290673,0.0001880842,0.000027055,0.00000489613,0.002988331,0.05653406,0.03583224,0.003565629,0.0007817415,0.5702327],"study_design_scores_gemma":[0.0005247009,0.0005442453,0.0963824,0.000009199579,0.000004237107,0.000003087085,0.0004125507,0.8883145,0.00151721,0.00292778,0.009294005,0.00006609385],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975957,0.0002586444,0.001207497,0.0002104515,0.00002287991,0.0002081202,0.00001955055,0.000006869771,0.000470299],"genre_scores_gemma":[0.9982169,0.00001340879,0.001374897,0.000005118593,0.000006551042,0.00002121253,0.00004248379,0.000003818204,0.0003156545],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8317804,"threshold_uncertainty_score":0.3013056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0343605955401966,"score_gpt":0.3361096519158392,"score_spread":0.3017490563756426,"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."}}