{"id":"W7100517113","doi":"","title":"Neural networks for macroeconomic forecasting: a complementary approach to linear regression models. Working Paper 2000-07","year":2000,"lang":"en","type":"article","venue":"","topic":"Legal Studies and Reforms","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial neural network; Linear regression; Set (abstract data type); Linear model; Parallels; Work (physics); Data set","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":[],"consensus_categories":[],"category_scores_codex":[0.0003437267,0.000145077,0.0002027305,0.00002459431,0.001168641,0.00007145678,0.0002461035,0.0000748237,0.0007544949],"category_scores_gemma":[0.00000545598,0.00009196436,0.000116349,0.0001325136,0.00007641127,0.000219331,0.0000785121,0.0001105989,0.00001709306],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001555774,"about_ca_system_score_gemma":0.00002818992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003590898,"about_ca_topic_score_gemma":0.00213009,"domain_scores_codex":[0.9986817,0.00002322051,0.0002490182,0.0003036687,0.000140595,0.0006018342],"domain_scores_gemma":[0.9995956,0.00004866177,0.00004629096,0.0001193053,0.00002786035,0.0001622217],"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":[0.0004194501,0.0001536954,0.00108118,0.00001726861,0.00008171621,0.000002004315,0.01552904,0.2142953,0.000002007121,0.009360051,0.04347549,0.7155827],"study_design_scores_gemma":[0.0004241144,0.00005526187,0.00005670464,0.00001864644,0.00001100104,9.905557e-7,0.002407418,0.6086987,0.000001156922,0.0009855701,0.3871341,0.000206289],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1375534,0.000887354,0.02063973,0.009961084,0.000999207,0.002979774,0.00001976766,0.0003165464,0.8266431],"genre_scores_gemma":[0.9715215,0.0001800339,0.01033863,0.002890022,0.001403186,0.0001031998,0.00002536026,0.0000241496,0.01351393],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.833968,"threshold_uncertainty_score":0.8988361,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0794548524780862,"score_gpt":0.2990272452450094,"score_spread":0.2195723927669232,"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."}}