{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000673213,0.0004807175,0.0003870667,0.002139276,0.002368032,0.002823438,0.0005685315,0.0005222131,0.008643712],"category_scores_gemma":[0.004802074,0.0002396185,0.000569985,0.00754432,0.00116909,0.0009620526,0.0009641144,0.001442411,0.0007347896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02773819,"about_ca_system_score_gemma":0.02241277,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.986421,"about_ca_topic_score_gemma":0.9868895,"domain_scores_codex":[0.9989028,0.00003940349,0.00004835161,0.0001571057,0.0004335451,0.0004187969],"domain_scores_gemma":[0.9979472,0.0004086067,0.0004326925,0.0001185703,0.000976319,0.0001166373],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0003409842,0.00003862883,0.2126269,0.001011675,0.0001981932,0.002292212,0.005719374,0.03942718,0.002642281,0.4088213,0.1958418,0.1310393],"study_design_scores_gemma":[0.00007102839,0.00005273309,0.6244434,0.0004417378,0.0001244126,0.0008042214,0.003068096,0.02247626,0.002292258,0.04669747,0.2993427,0.0001856361],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.343307,0.01604673,0.01440714,0.04747435,0.0005637401,0.000206271,0.101008,0.001161826,0.475825],"genre_scores_gemma":[0.9377917,0.01055292,0.003064886,0.001330074,0.000106938,0.00005247095,0.01187814,0.00009904542,0.03512368],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02773819,"threshold_uncertainty_score":0.2012556,"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."}}