{"id":"W2765801076","doi":"10.1007/978-3-319-70096-0_91","title":"Ten-Quarter Projection for Spanish Central Government Debt via WASD Neuronet","year":2017,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Projection (relational algebra); Debt; Government (linguistics); Government debt; Debt ratio; Debt crisis; Financial crisis; Debt-to-GDP ratio; Financial system; Economy; Economics; External debt; Finance; Computer science; Geography; Macroeconomics; Algorithm","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000179408,0.0003575546,0.0002914358,0.0001000421,0.0002134217,0.0002418819,0.0006085368,0.0002108639,0.00001256094],"category_scores_gemma":[0.00002565389,0.0003329613,0.0001034401,0.0000415628,0.0001549302,0.0002176535,0.0001149668,0.0003928464,0.000005817581],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002828742,"about_ca_system_score_gemma":0.00005547468,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001269309,"about_ca_topic_score_gemma":0.0001387547,"domain_scores_codex":[0.9981818,0.000005340207,0.0002566743,0.0005548491,0.0004384585,0.0005629348],"domain_scores_gemma":[0.9991884,0.0001045463,0.0000975163,0.000474554,0.00003910889,0.00009583376],"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":[0.00001418306,0.00001432501,0.0001458872,0.0001585976,0.00002583755,0.00002856214,0.0005210573,0.242753,0.0009396414,0.0006621113,0.0002101076,0.7545266],"study_design_scores_gemma":[0.0002889218,0.0001967711,0.00027131,0.0003376624,0.00002055151,0.00005397069,1.499325e-7,0.9708024,0.004123585,0.007113008,0.01616775,0.0006239527],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0003253876,0.0001246161,0.9863693,0.00006253261,0.004365381,0.0003367685,0.00001982269,0.0001405747,0.008255672],"genre_scores_gemma":[0.9198076,0.00006211834,0.07537779,0.0004088004,0.003090086,0.00003969864,0.00002616855,0.0001502555,0.001037506],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9194822,"threshold_uncertainty_score":0.9999123,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01109962421114725,"score_gpt":0.207008269204749,"score_spread":0.1959086449936017,"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."}}