{"id":"W3164505946","doi":"10.1002/env.2684","title":"Generalized least‐squares in dimension expansion method for nonstationary processes","year":2021,"lang":"en","type":"article","venue":"Environmetrics","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Covariance; Dimension (graph theory); Least-squares function approximation; Applied mathematics; Mathematics; Projection (relational algebra); Mathematical optimization; Variogram; Algorithm; Computer science; Estimator; Statistics; Kriging","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001542417,0.0007451689,0.0008555672,0.0004726176,0.0002925701,0.0004871594,0.0008029703,0.0008637794,0.001099959],"category_scores_gemma":[0.00290678,0.00034997,0.0007979156,0.0006848645,0.0006401144,0.0007074411,0.0007931541,0.001308966,0.0003099041],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003925025,"about_ca_system_score_gemma":0.0006279506,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002558519,"about_ca_topic_score_gemma":0.002405271,"domain_scores_codex":[0.9989008,0.0006499224,0.00002856807,0.000206978,0.0001716905,0.0000420559],"domain_scores_gemma":[0.9987747,0.0008795807,0.000104068,0.00009452347,0.0001219365,0.0000251404],"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":[0.00009123305,0.00004631701,0.001060338,0.0001633761,0.0001579432,0.0001147094,0.0001054589,0.8731012,0.007532831,0.03101155,0.002361602,0.08425336],"study_design_scores_gemma":[0.000002774996,0.000007145634,0.0001244462,0.000003011606,0.000003680243,0.00001084525,0.000003264734,0.9957761,0.0002744404,0.003325918,0.0004627819,0.000005489584],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005723072,0.0001704108,0.993643,0.00006185475,0.00001578747,0.00001237729,0.00003215008,0.0001159163,0.0002254583],"genre_scores_gemma":[0.2942928,0.0004749313,0.7015361,0.0001517041,0.00008011294,0.0002336413,0.0003924427,0.0001624268,0.002675829],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002558519,"threshold_uncertainty_score":0.008157194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02107157194968918,"score_gpt":0.2761899130915095,"score_spread":0.2551183411418203,"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."}}