{"id":"W4220679352","doi":"10.1093/jeea/jvac014","title":"Engineering Growth","year":2022,"lang":"en","type":"article","venue":"Journal of the European Economic Association","topic":"Economic Growth and Productivity","field":"Economics, Econometrics and Finance","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"University of British Columbia","keywords":"Great Divergence; Human capital; Construct (python library); Quarter (Canadian coin); Order (exchange); Divergence (linguistics); Economics; Political science; Economic growth; China; Geography; Finance; Law; Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.004603162,0.00008058691,0.000232627,0.0001210711,0.0001777331,0.00004569541,0.0004601819,0.00001696882,0.0003279225],"category_scores_gemma":[0.0003579814,0.00008508888,0.0002228459,0.00007029579,0.000006912744,0.0002524623,0.0001676734,0.0003451769,0.000306394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001453185,"about_ca_system_score_gemma":0.00002905958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001613729,"about_ca_topic_score_gemma":0.000001242967,"domain_scores_codex":[0.998861,0.0001349418,0.000673872,0.0001356241,0.00003282551,0.0001617494],"domain_scores_gemma":[0.9978272,0.00007018468,0.001871186,0.0001708975,0.00001909746,0.00004147269],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002823747,0.0001000784,0.8495629,0.00001448981,0.0003607823,0.000005785069,0.0009296421,0.02491795,0.0001279329,0.058362,0.06478806,0.0008021099],"study_design_scores_gemma":[0.001444607,0.0001156083,0.590421,0.000008182957,0.0000310662,0.00009105667,0.000114273,0.002540424,0.0001805499,0.02559076,0.3790467,0.0004157387],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9118109,0.0004339321,0.0003201191,0.004936176,0.00682361,0.0001071322,0.00009729242,0.00001788054,0.07545291],"genre_scores_gemma":[0.9968198,0.0000229443,0.00009685201,0.0002049964,0.0007557936,0.000001299277,0.000001121795,0.00002338425,0.002073812],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3142587,"threshold_uncertainty_score":0.3938177,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01112971547330022,"score_gpt":0.1592818549887951,"score_spread":0.1481521395154949,"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."}}