{"id":"W1502666521","doi":"10.34989/swp-2007-7","title":"Technology Shocks and Business Cycles: The Role of Processing Stages and Nominal Rigidities","year":2021,"lang":"en","type":"preprint","venue":"Econstor (Econstor)","topic":"Economic Growth and Productivity","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bank of Canada; Université du Québec à Montréal","funders":"","keywords":"Linkage (software); Economics; Business cycle; Face (sociological concept); General equilibrium theory; Econometrics; Stage (stratigraphy); Macroeconomics; Monetary economics","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":[0.0006568801,0.0005822218,0.0007446901,0.0006238751,0.0003513668,0.003072132,0.0006797192,0.001486491,0.003448945],"category_scores_gemma":[0.003774857,0.0005835153,0.0007114313,0.001263357,0.0009133923,0.002264982,0.0008286222,0.001092668,0.0006655707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001069066,"about_ca_system_score_gemma":0.0008539736,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008953377,"about_ca_topic_score_gemma":0.004093809,"domain_scores_codex":[0.9997481,0.00007630957,0.00001245311,0.00005860289,0.00003955032,0.00006512398],"domain_scores_gemma":[0.999062,0.0004582861,0.0002985807,0.00007455701,0.00004393753,0.00006259713],"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":[0.0001271549,0.00005752515,0.01196765,0.00004665283,0.00004440852,0.0001711997,0.0001311417,0.8421651,0.001184796,0.1321308,0.0007734256,0.0112001],"study_design_scores_gemma":[0.00007168883,0.00007588859,0.010685,0.00003787439,0.00004308693,0.00007605661,0.0001061831,0.823624,0.0006606744,0.1596357,0.004924367,0.00005946841],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7573946,0.001640538,0.212435,0.003011121,0.00007805891,0.00009146782,0.001020047,0.0001990409,0.02413015],"genre_scores_gemma":[0.9854456,0.001297645,0.00502621,0.00009989518,0.00004470401,0.00003198376,0.0003110151,0.00004192639,0.00770092],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008953377,"threshold_uncertainty_score":0.01780248,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01494512314398806,"score_gpt":0.2061468517511973,"score_spread":0.1912017286072093,"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."}}