{"id":"W2963253923","doi":"10.1002/wics.1443","title":"Spatial modeling with R‐INLA: A review","year":2018,"lang":"en","type":"review","venue":"Wiley Interdisciplinary Reviews Computational Statistics","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":410,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Inference; Code (set theory); Gaussian; Bayesian inference; Bayesian probability; Random field; Algorithm; Theoretical computer science; Mathematics; Artificial intelligence; Statistics","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007940757,0.0009537903,0.002755923,0.0001048119,0.000431412,0.00009792398,0.0007577608,0.0001714603,0.002327765],"category_scores_gemma":[0.000164483,0.0006933707,0.000407364,0.0005850505,0.0003591781,0.0001456344,0.001521373,0.0005581361,0.00490017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004475441,"about_ca_system_score_gemma":0.0001734907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007130361,"about_ca_topic_score_gemma":0.0001362531,"domain_scores_codex":[0.9950935,0.0004220287,0.001995032,0.001114837,0.0007988308,0.0005757512],"domain_scores_gemma":[0.9973828,0.000419565,0.00116576,0.0006399528,0.0001051892,0.0002867506],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000006340798,0.0000676593,0.00000381429,0.02784004,0.00009228869,0.0000606932,0.00004989972,0.0009176409,3.00182e-9,0.0002681725,0.1447557,0.8259377],"study_design_scores_gemma":[0.0001189568,0.0002143853,0.000002078337,0.1166148,0.001066506,0.0002406054,0.000004254219,0.04189641,1.583973e-9,0.002979752,0.8360888,0.000773426],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[5.643641e-8,0.570216,0.4263841,0.00003067179,0.0002142926,0.001363058,0.0006046395,0.00003627618,0.001150924],"genre_scores_gemma":[7.767147e-7,0.888755,0.1071039,0.0002935374,0.0002887909,0.0004076039,0.002759358,0.0001117685,0.0002792377],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.8251643,"threshold_uncertainty_score":0.9995518,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05299260366295971,"score_gpt":0.346729488693779,"score_spread":0.2937368850308192,"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."}}