{"id":"W2256148366","doi":"10.34989/swp-2015-6","title":"A New Data Set of Quarterly Total Factor Productivity in the Canadian Business Sector","year":2021,"lang":"en","type":"preprint","venue":"Econstor (Econstor)","topic":"Economic Growth and Productivity","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bank of Canada","funders":"","keywords":"Total factor productivity; Productivity; Factor (programming language); Data set; Set (abstract data type); Business sector; Econometrics; Growth accounting; Economics; Agricultural economics; Industrial organization; Business; Computer science; Statistics; Macroeconomics; Mathematics; Economy","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0009222584,0.00131915,0.0008346444,0.0139687,0.002019464,0.002063655,0.001383813,0.0005388028,0.01105953],"category_scores_gemma":[0.008080881,0.00037807,0.0007292507,0.02051057,0.0003471684,0.0008574022,0.0009322331,0.001312,0.004228892],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01327959,"about_ca_system_score_gemma":0.0304612,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9731081,"about_ca_topic_score_gemma":0.9680185,"domain_scores_codex":[0.997957,0.00005154187,0.0001105219,0.0002466939,0.001348062,0.0002861102],"domain_scores_gemma":[0.9881593,0.0005105286,0.0005776634,0.0006404174,0.009417896,0.0006941719],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004665969,0.0004211188,0.1081175,0.001146188,0.0002344521,0.0004159666,0.001267564,0.01144446,0.005075661,0.01153371,0.6131427,0.2467341],"study_design_scores_gemma":[0.0000669892,0.00004590234,0.4127871,0.0001592567,0.00009569112,0.0001393491,0.0005735806,0.004575171,0.003210111,0.0009347231,0.5772332,0.0001788325],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.03559535,0.0005160658,0.003637888,0.0002997062,0.0001674437,0.0002916113,0.9427348,0.000811061,0.01594599],"genre_scores_gemma":[0.05124927,0.0008116983,0.008412622,0.00009694797,0.00005307692,0.0004283971,0.9276391,0.0001582967,0.01115065],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02689195,"threshold_uncertainty_score":0.09635067,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0583531223074812,"score_gpt":0.2329018435204265,"score_spread":0.1745487212129453,"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."}}