{"id":"W2989625480","doi":"","title":"The Stylized Facts about Slower Productivity Growth in Canada","year":2018,"lang":"en","type":"article","venue":"International productivity monitor","topic":"Economic Growth and Productivity","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Total factor productivity; Stylized fact; Economics; Slowdown; Productivity; Multifactor productivity; Growth accounting; Labour economics; Technological change; Technical progress; Macroeconomics; Economic growth","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.001514953,0.0002646995,0.0003849489,0.0001748258,0.0003041879,0.0001568828,0.0007331517,0.00006951212,0.0001668007],"category_scores_gemma":[0.001959221,0.0002561106,0.00008507054,0.0002932408,0.0002525565,0.0007865047,0.0001821992,0.0003847078,0.0003137169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00118318,"about_ca_system_score_gemma":0.0003752501,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5224054,"about_ca_topic_score_gemma":0.5414857,"domain_scores_codex":[0.997537,0.00007383403,0.0006776301,0.001019262,0.0001424262,0.0005498867],"domain_scores_gemma":[0.9984091,0.0001764468,0.000426446,0.0006481131,0.0002283735,0.0001115032],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002989224,0.0002780817,0.9494339,0.00002380789,0.0001663578,0.000009148244,0.0003847952,0.00002709865,0.0004150841,0.03288904,0.006771635,0.009302139],"study_design_scores_gemma":[0.0007580071,0.0000637357,0.8280367,0.00001773921,0.000004133685,0.00001321726,0.00008714922,0.000475415,0.01244864,0.03729645,0.1202537,0.0005451453],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.958147,0.0005319835,0.0001024061,0.01487658,0.009693848,0.0004671891,0.0001577796,0.00003850896,0.01598474],"genre_scores_gemma":[0.9943404,0.0000596198,0.0001263052,0.0001123157,0.002995339,0.00007778392,0.00001091077,0.00003244268,0.00224492],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1213972,"threshold_uncertainty_score":0.9999891,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01898698980256359,"score_gpt":0.21713602340397,"score_spread":0.1981490336014064,"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."}}