{"id":"W3124901408","doi":"","title":"Wages, Human Capital, and Structural Transformation","year":2017,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Firm Innovation and Growth","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Human capital; Wage; Economics; Labour economics; Agriculture; Economic growth; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004157216,0.0001017274,0.0001433494,0.0004978459,0.0005099711,0.001195007,0.0002483863,0.0003280471,0.006286109],"category_scores_gemma":[0.004167754,0.00007920471,0.0001454427,0.0008926156,0.001569006,0.0009074593,0.0006945606,0.0004718257,0.0002872769],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001287583,"about_ca_system_score_gemma":0.0005790479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005099117,"about_ca_topic_score_gemma":0.00724841,"domain_scores_codex":[0.9997689,0.00005283772,0.000009456186,0.00004613641,0.00004129359,0.00008143813],"domain_scores_gemma":[0.998076,0.0006207678,0.0007874506,0.0001868999,0.0001063827,0.0002225591],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0002239521,0.0003111261,0.3433517,0.0001085802,0.00008953026,0.0004383884,0.001616098,0.06266898,0.001752211,0.5043403,0.003165324,0.08193387],"study_design_scores_gemma":[0.0000353092,0.000108609,0.320778,0.00004793526,0.000018931,0.000197441,0.001183788,0.02361519,0.0007461656,0.646133,0.00711779,0.00001784203],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.960359,0.0004311852,0.006447323,0.00154368,0.00001591564,0.00001710594,0.000301818,0.00003273638,0.03085115],"genre_scores_gemma":[0.9988735,0.0000599302,0.0001769405,0.00001992921,0.000005009851,0.000002670924,0.00003704417,0.000001483704,0.0008234217],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006286109,"threshold_uncertainty_score":0.02102917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01874082737085776,"score_gpt":0.2376276028383614,"score_spread":0.2188867754675037,"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."}}