{"id":"W2167925360","doi":"10.1080/00036846.2010.522522","title":"What affects MFP in the long-run? Evidence from Canadian industries","year":2011,"lang":"en","type":"article","venue":"Applied Economics","topic":"Economic Growth and Productivity","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bank of Canada; Statistics Canada","funders":"Infrastructure Canada","keywords":"Openness to experience; Outsourcing; Economics; Productivity; Information and Communications Technology; Investment (military); Error correction model; Panel data; Capital equipment; Short run; Econometrics; Industrial organization; International trade; International economics; Macroeconomics; Cointegration; Business","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001121053,0.000248286,0.0004487592,0.0002593471,0.0001411069,0.0002792827,0.0007522015,0.0002339749,0.0006709999],"category_scores_gemma":[0.00008026784,0.0002728887,0.00007288146,0.0001946011,0.0001208845,0.001141398,0.00007244147,0.0003841404,0.001769076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003085881,"about_ca_system_score_gemma":0.0001414602,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.09661616,"about_ca_topic_score_gemma":0.2477048,"domain_scores_codex":[0.9981527,0.00002365668,0.0005352704,0.0007136905,0.00001467215,0.000559981],"domain_scores_gemma":[0.9984894,0.0002142646,0.0002860477,0.0008176023,0.000007895071,0.000184755],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006234663,0.00008205875,0.7302863,0.00001673377,0.00007906642,0.000009332107,0.008825789,0.0001258436,0.000003625203,0.2500425,0.001914948,0.008551426],"study_design_scores_gemma":[0.0006285346,0.00005595531,0.8048489,0.00003620196,0.0000127782,0.000006032272,0.001660934,0.0002009955,0.0007746035,0.1760498,0.01495261,0.0007726498],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9542299,0.001898871,0.00004400837,0.001290012,0.001045591,0.0004606886,0.0000835723,0.00002218608,0.04092517],"genre_scores_gemma":[0.996506,0.001306669,0.0001605788,0.001476374,0.0002613172,0.0001003344,0.00002876928,0.00003155689,0.000128353],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1510886,"threshold_uncertainty_score":0.9999723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06795399380192417,"score_gpt":0.1988098010643141,"score_spread":0.1308558072623899,"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."}}