{"id":"W3181414762","doi":"10.3390/engproc2021005049","title":"Automatic Hierarchical Time-Series Forecasting Using Gaussian Processes","year":2021,"lang":"en","type":"article","venue":"","topic":"Forecasting Techniques and Applications","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Overfitting; Computer science; Gaussian process; Series (stratigraphy); Hyperparameter; Bayesian probability; Time series; Hierarchy; Constraint (computer-aided design); Algorithm; Gaussian; Data mining; Artificial intelligence; Machine learning; Mathematics; Artificial neural 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002145348,0.001113477,0.001394754,0.001699445,0.0005813492,0.00115901,0.001883354,0.001133748,0.001387773],"category_scores_gemma":[0.005986751,0.0006717617,0.00144576,0.001860838,0.0005318343,0.001783596,0.001300032,0.002179162,0.0007786315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000898104,"about_ca_system_score_gemma":0.001323585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0126659,"about_ca_topic_score_gemma":0.01310019,"domain_scores_codex":[0.9991267,0.0002108348,0.00005171057,0.0002755527,0.0002218404,0.0001133317],"domain_scores_gemma":[0.9978353,0.00135604,0.0002351215,0.0002021712,0.0002839614,0.00008738186],"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":[0.0001388531,0.00007548967,0.002675646,0.00008285078,0.0001149011,0.0001247078,0.0002050758,0.7087807,0.004553583,0.01401237,0.003576172,0.2656597],"study_design_scores_gemma":[0.000003260237,0.000004291881,0.0001340148,0.000002842626,0.00000436685,0.000005096336,0.000005230903,0.9941163,0.0003489796,0.005098629,0.0002726497,0.000004222345],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008981014,0.0001399352,0.9892467,0.00009082485,0.00002319516,0.00001625722,0.0000736193,0.001103687,0.0003247486],"genre_scores_gemma":[0.4627674,0.0003628509,0.5330895,0.0001783729,0.000164869,0.0001358429,0.00106384,0.0003623875,0.001874962],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0126659,"threshold_uncertainty_score":0.02518433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1805018551811075,"score_gpt":0.3897435748926834,"score_spread":0.2092417197115759,"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."}}