{"id":"W7092203821","doi":"10.5281/zenodo.17368249","title":"FORECASTING NIGERIA'S INFLATION RATES (2009–2024) USING SARIMA MODELS","year":2025,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Forecasting Techniques and Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Autoregressive integrated moving average; Inflation (cosmology); Economic forecasting; Forecast period; Quarter (Canadian coin); Inflation rate; Time series","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001442507,0.000506188,0.0004706279,0.0005997007,0.0002342464,0.0006939294,0.0003119201,0.0005151817,0.0005914964],"category_scores_gemma":[0.003557208,0.0002773064,0.0004100603,0.0005789707,0.0001374713,0.0007242206,0.0003103367,0.0006870777,0.0001851664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005329146,"about_ca_system_score_gemma":0.0009061568,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01221522,"about_ca_topic_score_gemma":0.0141958,"domain_scores_codex":[0.9996634,0.000132475,0.00003083944,0.00005404888,0.00006408041,0.00005518264],"domain_scores_gemma":[0.9987059,0.0008294248,0.0001562908,0.00003848796,0.0002386621,0.00003113476],"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":[0.0004086414,0.0002023943,0.07292509,0.0001903568,0.0001104456,0.0002937694,0.0002816388,0.8570919,0.002000548,0.003894588,0.001239693,0.06136084],"study_design_scores_gemma":[0.00001261877,0.0001149754,0.008525907,0.00002605083,0.00002542388,0.00003411685,0.0001342058,0.9885456,0.001021769,0.0009500182,0.0005957867,0.00001352124],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9457767,0.000795297,0.04742502,0.0004792729,0.00008512066,0.00006868601,0.0006280078,0.0001829418,0.004558965],"genre_scores_gemma":[0.9878037,0.0004179439,0.01057252,0.00002050896,0.0000153446,0.00002747519,0.0004031527,0.000006376233,0.0007330427],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01221522,"threshold_uncertainty_score":0.02428824,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2203627906200567,"score_gpt":0.3712095592769649,"score_spread":0.1508467686569082,"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."}}