{"id":"W6969053401","doi":"10.5683/sp3/nw1doe","title":"Replication Data and Code for: Allocative Efficiency and the Productivity Slowdown","year":2025,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bank of Canada","funders":"","keywords":"Allocative efficiency; Replicate; Slowdown; Replication (statistics); Productivity; Code (set theory)","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":[0.003319628,0.003317541,0.001946948,0.0038561,0.001528339,0.004323015,0.004276188,0.002266235,0.118048],"category_scores_gemma":[0.02731262,0.001517783,0.002841602,0.007363256,0.0008852519,0.00305085,0.002138856,0.00353652,0.124193],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002861575,"about_ca_system_score_gemma":0.004302218,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04513229,"about_ca_topic_score_gemma":0.06199585,"domain_scores_codex":[0.996442,0.0006516656,0.0003717309,0.001220911,0.0008724716,0.0004412404],"domain_scores_gemma":[0.9858788,0.004770636,0.0009412502,0.00446384,0.003317014,0.0006284322],"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":[0.00007662271,0.00001691402,0.0009009215,0.0003679148,0.00003908813,0.000008090505,0.00003059475,0.0004234697,0.00007129072,0.0006974448,0.9956036,0.001764063],"study_design_scores_gemma":[0.0007541369,0.00003873732,0.008527126,0.0003608638,0.000108742,0.00009296615,0.0001746662,0.001986664,0.001002639,0.007715409,0.9791291,0.0001090849],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002562209,0.00007578947,0.0003279176,0.0001360638,0.00007609496,0.00002234574,0.9959805,0.00184279,0.001282268],"genre_scores_gemma":[0.001748203,0.00006475877,0.001238834,0.0001214541,0.0000280818,0.0002068199,0.9936665,0.001248763,0.001676658],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.118048,"threshold_uncertainty_score":0.3949099,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03666886916382987,"score_gpt":0.3302698715653029,"score_spread":0.293601002401473,"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."}}