{"id":"W7083291342","doi":"10.1214/25-ba1552","title":"Bayesian Time-Varying Tensor Vector Autoregressive Models for Dynamic Effective Connectivity","year":2025,"lang":"en","type":"article","venue":"Bayesian Analysis","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Università Bocconi","keywords":"Tensor (intrinsic definition); Autoregressive model; Rank (graph theory); Bayesian probability; Prior probability; Model selection; Ising model; Dynamic Bayesian network","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"],"consensus_categories":[],"category_scores_codex":[0.0004543918,0.0003057265,0.0006406594,0.0004555685,0.0003831352,0.0001738051,0.000825274,0.0001773123,0.00005684796],"category_scores_gemma":[0.0003890612,0.000286573,0.0005754918,0.001823066,0.00007692131,0.0003416372,0.0002327181,0.0001804541,0.00001287972],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001630082,"about_ca_system_score_gemma":0.0001080261,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005423967,"about_ca_topic_score_gemma":0.00002503258,"domain_scores_codex":[0.9978464,0.0001708144,0.0003277793,0.0009494287,0.0002029559,0.0005026151],"domain_scores_gemma":[0.9977821,0.0007286487,0.0002018006,0.0008818943,0.0002827419,0.0001228027],"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":[0.0003457107,0.001050078,0.008648929,0.0009611637,0.01813972,0.0002042391,0.003606772,0.6922454,0.01830073,0.1323559,0.005995939,0.1181454],"study_design_scores_gemma":[0.00039665,0.00003549859,0.00193896,0.00004201075,0.0005700766,0.000002632894,0.0000240953,0.9616833,0.001926369,0.03277766,0.0003103387,0.0002924227],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001281077,0.0001212717,0.9825276,0.002878732,0.0001091972,0.000513197,0.00002082417,0.0002603716,0.01228774],"genre_scores_gemma":[0.9692636,0.000002780053,0.02368854,0.0002401597,0.00003281746,0.0002023067,0.00003213744,0.000005514563,0.006532194],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9679825,"threshold_uncertainty_score":0.9999586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005864160067632578,"score_gpt":0.2405208010678671,"score_spread":0.2346566410002345,"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."}}