{"id":"W2990750272","doi":"10.1017/s0140525x19000086","title":"The wealth→life history→innovation account of the Industrial Revolution is largely inconsistent with empirical time series data","year":2019,"lang":"en","type":"letter","venue":"Behavioral and Brain Sciences","topic":"Historical Economic and Social Studies","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Industrial Revolution; Standard of living; Time series; Series (stratigraphy); Economics; Econometrics; Test (biology); Political science; Computer science; Market economy; Machine learning","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":[0.006399593,0.0003660709,0.0008450461,0.000811647,0.001306967,0.001875828,0.00128487,0.00998959,0.00600614],"category_scores_gemma":[0.04443745,0.0002731447,0.000448465,0.001271642,0.004197934,0.003927262,0.001059935,0.01483258,0.005265323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002040287,"about_ca_system_score_gemma":0.001287553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004751083,"about_ca_topic_score_gemma":0.005079237,"domain_scores_codex":[0.9977889,0.000943944,0.0002103287,0.0004224422,0.0004625249,0.0001717617],"domain_scores_gemma":[0.9637073,0.02946486,0.002072682,0.001931367,0.002203894,0.0006197859],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0003446483,0.00008840008,0.01227173,0.0002272254,0.00009138417,0.00330322,0.0006021241,0.0006839024,0.0002806984,0.2341537,0.6527036,0.09524944],"study_design_scores_gemma":[0.0001842568,0.00009472796,0.009542854,0.0004039092,0.00005535718,0.003093516,0.0006574756,0.007545594,0.000560979,0.4841854,0.4935559,0.0001200385],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.002773413,0.002571257,0.002378348,0.9786127,0.003607201,0.00001168267,0.0002341731,0.00005656913,0.009754692],"genre_scores_gemma":[0.1267449,0.008078847,0.002614979,0.8078694,0.04067445,0.00009343408,0.0002463985,0.00007591661,0.01360173],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.00998959,"threshold_uncertainty_score":0.03384465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2688456033119269,"score_gpt":0.2996488628550601,"score_spread":0.03080325954313323,"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."}}