{"id":"W4388680316","doi":"10.22617/wps230478-2","title":"Demography, Growth, and Robots in Advanced and Emerging Economies","year":2023,"lang":"en","type":"report","venue":"","topic":"Economic Growth and Productivity","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact","funders":"","keywords":"Productivity; Economics; Population ageing; Population; Emerging markets; Population growth; Demographic economics; Panel data; Demographic change; Economic geography; Economy; Economic growth; Demography; Macroeconomics; Econometrics; Sociology","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":[0.0003884203,0.0002075648,0.0002144295,0.001388199,0.0002395799,0.0006690335,0.0001114979,0.0001840085,0.001812047],"category_scores_gemma":[0.00123457,0.0001155183,0.0003339304,0.002094812,0.0003122643,0.0009306073,0.0007388385,0.0004798538,0.0003396688],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005593366,"about_ca_system_score_gemma":0.0003798914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03494352,"about_ca_topic_score_gemma":0.03674681,"domain_scores_codex":[0.9998995,0.00002306696,0.000007689013,0.0000198321,0.00001763043,0.00003219842],"domain_scores_gemma":[0.9993727,0.0001370509,0.0002782852,0.0000333824,0.0001014398,0.00007721373],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006343247,0.00004247055,0.9631926,0.00004414689,0.00006498418,0.0001665216,0.0007504126,0.009761387,0.0001526429,0.005196839,0.001947795,0.01861681],"study_design_scores_gemma":[0.000006110037,0.00005197188,0.9816309,0.00004649892,0.0000219931,0.00009248861,0.001478581,0.004407298,0.0001885744,0.001823183,0.01024291,0.000009500413],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.9883441,0.001143629,0.001010715,0.0004815267,0.00001189639,0.00001272977,0.00356855,0.0000125917,0.005414237],"genre_scores_gemma":[0.9924488,0.002188988,0.0003402169,0.00004323679,0.00001990626,0.00001604221,0.003283055,0.000004540839,0.00165525],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.03494352,"threshold_uncertainty_score":0.06948024,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05941332859673029,"score_gpt":0.2621481579928299,"score_spread":0.2027348293960996,"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."}}