{"id":"W3034403930","doi":"10.1002/env.2644","title":"A joint Bayesian space–time model to integrate spatially misaligned air pollution data in R‐INLA","year":2020,"lang":"en","type":"article","venue":"Environmetrics","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Medical Research Council; Medical Research Council Canada","keywords":"Bayesian probability; Dispersion (optics); Calibration; Grid; Spatial analysis; Bayesian inference; Atmospheric dispersion modeling; Bilinear interpolation","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004009382,0.000210989,0.0002406592,0.0001592285,0.00007246329,0.00003336964,0.000574852,0.00009034695,0.0005435846],"category_scores_gemma":[0.0007866102,0.0002166073,0.00003656963,0.001204924,0.00007579762,0.0002056918,0.0009861679,0.0001936183,0.001889425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002320264,"about_ca_system_score_gemma":0.00002105675,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007000102,"about_ca_topic_score_gemma":0.0001490128,"domain_scores_codex":[0.9980699,0.00006132379,0.0003316402,0.0006878646,0.0004541546,0.0003951057],"domain_scores_gemma":[0.998893,0.00005131408,0.00009031576,0.0006204622,0.000002723713,0.0003421631],"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":[0.00007478116,0.0002454158,0.01190092,0.00002244269,0.00002075375,0.00011038,0.00206751,0.8604069,0.03962258,0.0003690592,0.03893353,0.0462257],"study_design_scores_gemma":[0.0004091484,0.0001124718,0.04893482,0.00001320232,0.00001644222,0.000002251006,0.00005704984,0.9296618,0.0007691059,0.0005008018,0.01913903,0.000383855],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1386504,0.000054633,0.8400107,0.01383016,0.0001063462,0.0006028541,0.0003288636,0.0000881507,0.006327828],"genre_scores_gemma":[0.9325275,0.00003629113,0.06258853,0.004219677,0.00004397722,0.000009194489,0.0001027005,0.00003323522,0.0004389111],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7938771,"threshold_uncertainty_score":0.9988877,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03519326169219058,"score_gpt":0.2343943617395649,"score_spread":0.1992011000473743,"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."}}