{"id":"W2083490075","doi":"10.5539/mas.v7n7p10","title":"A Forecasting Model for Thailand’s Unemployment Rate","year":2013,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Mahasarakham University","keywords":"Unemployment rate; Unemployment; Box–Jenkins; Econometrics; Statistics; Economics; Computer science; Mathematics; Time series; Macroeconomics; Autoregressive integrated moving average","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003325692,0.0001567395,0.0001305266,0.00008926771,0.0002418512,0.0001437611,0.0003218494,0.00003888384,0.0000124789],"category_scores_gemma":[0.00001639752,0.0001406527,0.00003559751,0.0002237158,0.00009891216,0.0002390547,0.00006083242,0.00008551532,0.00002179867],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006362898,"about_ca_system_score_gemma":0.00003897942,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006417288,"about_ca_topic_score_gemma":0.000007395043,"domain_scores_codex":[0.9987888,0.000002158273,0.0001822746,0.0002877023,0.0001913078,0.0005476967],"domain_scores_gemma":[0.9995365,0.00004681634,0.00002838721,0.0002100894,0.00004672445,0.0001315059],"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":[0.000002332289,0.000005964294,0.00002233506,0.00002134051,0.000003723618,1.902845e-7,0.0006927613,0.7943218,0.184314,0.00153002,0.0002564277,0.01882919],"study_design_scores_gemma":[0.0001896484,0.000008034349,0.00001390245,0.00001361427,0.000003505138,0.000001408986,0.00002017364,0.976049,0.01337321,0.01000466,0.0001365691,0.0001862443],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1907604,0.00003170081,0.7873606,0.00002774989,0.0001549978,0.0003360028,0.000004739046,0.0002721988,0.02105155],"genre_scores_gemma":[0.9825419,0.000002549909,0.01662986,0.00009444181,0.00005470313,0.000293693,0.000003075018,0.00003090261,0.0003489227],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7917814,"threshold_uncertainty_score":0.573565,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03329416298919206,"score_gpt":0.2207362472151329,"score_spread":0.1874420842259408,"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."}}