{"id":"W4382182526","doi":"10.2196/46357","title":"Vector Autoregression for Forecasting the Number of COVID-19 Cases and Analyzing Behavioral Indicators in the Philippines: Ecologic Time-Trend Study","year":2023,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Google","keywords":"Vector autoregression; Econometrics; Granger causality; Statistics; Computer science; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005854932,0.0008042215,0.0005930971,0.001852123,0.0002898258,0.000657004,0.0007365015,0.0005519408,0.0009678566],"category_scores_gemma":[0.009751946,0.000312003,0.001013014,0.001477372,0.0003038997,0.0009114349,0.0005158276,0.0008934993,0.0001609512],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007923315,"about_ca_system_score_gemma":0.001241075,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04765938,"about_ca_topic_score_gemma":0.01824363,"domain_scores_codex":[0.9985099,0.001015282,0.00005597693,0.0001975206,0.00009213294,0.0001291404],"domain_scores_gemma":[0.9945532,0.003666986,0.0007622711,0.0002801425,0.0005425828,0.0001948505],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002571754,0.0004779586,0.665293,0.00008562652,0.0004680552,0.000300799,0.0003842553,0.3002429,0.001055704,0.001721725,0.0008275189,0.02888525],"study_design_scores_gemma":[0.00001285414,0.0002326156,0.07208955,0.00001165813,0.00005324102,0.00002404191,0.0002054925,0.9264412,0.000241591,0.0004452983,0.0002265299,0.00001599083],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.983489,0.0001197542,0.01541109,0.0002092588,0.00001188056,0.00004057747,0.0003584549,0.00007425102,0.0002857369],"genre_scores_gemma":[0.9925629,0.00009921454,0.006411096,0.00001407208,0.00001277223,0.00004725694,0.0005221096,0.00001042109,0.000320008],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04765938,"threshold_uncertainty_score":0.09476399,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.527513496824299,"score_gpt":0.5856886947046683,"score_spread":0.05817519788036929,"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."}}