{"id":"W3202146269","doi":"10.1016/j.cmpbup.2021.100029","title":"Forecasting COVID-19 pandemic in Alberta, Canada using modified ARIMA models","year":2021,"lang":"en","type":"article","venue":"Computer Methods and Programs in Biomedicine Update","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; University of Calgary","funders":"","keywords":"Autoregressive integrated moving average; Heteroscedasticity; Confidence interval; Time series; Statistics; Series (stratigraphy); Prediction interval; Econometrics; Moving average; Variance (accounting); Interval (graph theory); Coronavirus disease 2019 (COVID-19); Mathematics; Economics; Accounting","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003542756,0.0002930242,0.0009070486,0.0001385091,0.0001127163,0.0000322551,0.0001990435,0.0001423292,0.00001076804],"category_scores_gemma":[0.002383717,0.0002278239,0.00005593647,0.0007565494,0.0001798545,0.00007124728,0.0005018823,0.0003541231,1.086826e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004532804,"about_ca_system_score_gemma":0.0004839494,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.3522883,"about_ca_topic_score_gemma":0.3883004,"domain_scores_codex":[0.9967638,0.0009712146,0.0008481879,0.0006476922,0.0001986359,0.0005704864],"domain_scores_gemma":[0.9938157,0.00535462,0.0001980292,0.0003107262,0.0000666304,0.0002542515],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008503495,0.0002106548,0.1156604,0.00120813,0.0001476121,0.000673457,0.002254096,0.006538447,0.0001006883,0.01157667,0.000831436,0.8607134],"study_design_scores_gemma":[0.001108658,0.00005825915,0.0004693787,0.0002143869,0.00003301003,0.0001004424,0.0001541587,0.7653055,0.00000808251,0.2252508,0.007020538,0.0002768245],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1736994,0.001158908,0.8208086,0.003501846,0.0002996577,0.0004129927,0.000004403522,0.00004694802,0.00006727361],"genre_scores_gemma":[0.1829006,0.0001873319,0.8113644,0.005306442,0.0001423286,0.00003537138,0.00002440043,0.00002099898,0.00001816147],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8604366,"threshold_uncertainty_score":0.9290389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5509120551413422,"score_gpt":0.4894202154909617,"score_spread":0.06149183965038052,"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."}}