{"id":"W4398255883","doi":"10.5539/ijef.v16n7p13","title":"Export Intensity and Total Factor Productivity in Kenya’s Manufacturing Sector","year":2024,"lang":"en","type":"article","venue":"International Journal of Economics and Finance","topic":"Global trade and economics","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Manufacturing sector; Productivity; Total factor productivity; Agricultural economics; Intensity (physics); Factor (programming language); Business; Economics; International trade; Economic growth; Labour economics; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0003731,0.0001691952,0.0001342457,0.001176524,0.0003202671,0.0007574625,0.0001553407,0.000176774,0.003629657],"category_scores_gemma":[0.001623454,0.0001135122,0.000295776,0.002629406,0.0002845963,0.0004569368,0.0003303599,0.0002816799,0.0003816821],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007200601,"about_ca_system_score_gemma":0.0004748873,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03593188,"about_ca_topic_score_gemma":0.04422682,"domain_scores_codex":[0.9998153,0.00003064914,0.00001952333,0.00003231118,0.00004711761,0.00005517013],"domain_scores_gemma":[0.9989051,0.0002449333,0.0006159667,0.00003741124,0.0001115471,0.00008504293],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003147288,0.00003131283,0.9944844,0.00002751016,0.00004618531,0.0001329034,0.0003721468,0.000327131,0.0001756132,0.0005357948,0.0003405939,0.003495042],"study_design_scores_gemma":[0.000001151992,0.00001350423,0.9981905,0.00001968427,0.00001208582,0.00005020676,0.0005205015,0.0003371727,0.00006267394,0.00009697163,0.0006927288,0.000002850519],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944578,0.0003498804,0.0001253025,0.00009336961,0.000002701311,0.000007994407,0.00103792,0.000002068968,0.003922845],"genre_scores_gemma":[0.9981845,0.0002505389,0.00009666101,0.00001147157,0.000003563277,0.000005667933,0.0005687139,0.000001152435,0.0008776909],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03593188,"threshold_uncertainty_score":0.07144547,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04292104920161582,"score_gpt":0.2157633229041817,"score_spread":0.1728422737025658,"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."}}