{"id":"W3125899499","doi":"10.2308/accr-51939","title":"Aggregate Cost Stickiness in GAAP Financial Statements and Future Unemployment Rate","year":2017,"lang":"en","type":"article","venue":"The Accounting Review","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":100,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economics; Econometrics; Unemployment; Predictive power; Macro; Percentage point; Aggregate (composite); Quarter (Canadian coin); Explanatory power; Point (geometry); Sample (material); Regression analysis; Regression; Statistics; Mathematics; Macroeconomics; Computer science; Finance","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":[0.0021559,0.0001664172,0.0004877456,0.00005323067,0.000328739,0.0002129839,0.0004502969,0.00004400559,0.0002011887],"category_scores_gemma":[0.0002703989,0.0001370335,0.00006029743,0.00005502215,0.00006770899,0.0005399475,0.0001540836,0.0001582371,0.0003433845],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005065908,"about_ca_system_score_gemma":0.00001252516,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008702432,"about_ca_topic_score_gemma":0.0001039876,"domain_scores_codex":[0.998732,0.00002639165,0.0006068831,0.0002806491,0.00002160559,0.0003324339],"domain_scores_gemma":[0.9985031,0.00003836104,0.000762389,0.0006439253,0.000008409362,0.00004377454],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008464075,0.0001820573,0.6652016,0.004663553,0.0001748137,0.00003584856,0.001139487,0.0001784098,0.000006112823,0.04523626,0.02146572,0.2616315],"study_design_scores_gemma":[0.0007265607,0.00001721232,0.3992957,0.001006186,0.00002047348,0.000005509778,0.00001146774,0.001050518,0.000004788061,0.008982045,0.588572,0.0003075199],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8900878,0.08780325,0.00002461258,0.01591885,0.0007440511,0.0009407816,0.00008956219,0.00001799879,0.004373088],"genre_scores_gemma":[0.8299168,0.1649839,0.0000387877,0.004072531,0.0004937919,0.00005599693,0.00001077131,0.00002165378,0.0004057528],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5671063,"threshold_uncertainty_score":0.5588064,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08754602061341558,"score_gpt":0.3102315725802207,"score_spread":0.2226855519668051,"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."}}