{"id":"W2004525898","doi":"10.1016/j.jedc.2014.04.006","title":"Barriers to capital accumulation in a model of technology adoption and schooling","year":2014,"lang":"en","type":"article","venue":"Journal of Economic Dynamics and Control","topic":"Economic Growth and Productivity","field":"Economics, Econometrics and Finance","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Economics; Productivity; Per capita income; Total factor productivity; Growth model; Per capita; Capital (architecture); Human capital; Growth accounting; Aggregate (composite); Capital accumulation; Econometrics; Demographic economics; Labour economics; Macroeconomics; Economic growth","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":[0.001937557,0.0009144633,0.002157575,0.001307575,0.001492557,0.005212438,0.002394308,0.005349225,0.02317567],"category_scores_gemma":[0.008305007,0.001192102,0.001599982,0.001533348,0.003053401,0.004753634,0.003117156,0.00352711,0.001792043],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002571024,"about_ca_system_score_gemma":0.002779483,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03494605,"about_ca_topic_score_gemma":0.01856659,"domain_scores_codex":[0.9992645,0.0002389025,0.00003158435,0.000113205,0.00004880365,0.000302946],"domain_scores_gemma":[0.9913623,0.005575787,0.001222532,0.0002853224,0.0003184805,0.001235623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005323413,0.0004160317,0.0105204,0.0001265226,0.000128288,0.0008610439,0.0007045952,0.5268949,0.0008734198,0.4490953,0.004037381,0.005809858],"study_design_scores_gemma":[0.0005383476,0.000230107,0.005753964,0.00009312024,0.0001660654,0.0002706184,0.0009357186,0.7710097,0.0002948687,0.2176906,0.002903356,0.0001134699],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8672544,0.00108812,0.06828796,0.01593499,0.0001390531,0.0001205421,0.001469875,0.0003720876,0.0453329],"genre_scores_gemma":[0.9570283,0.0006100801,0.002353244,0.0003241358,0.00009195849,0.00007385332,0.0002258104,0.00005800508,0.03923465],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03494605,"threshold_uncertainty_score":0.07753038,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01143304968140967,"score_gpt":0.2101953028247941,"score_spread":0.1987622531433844,"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."}}