{"id":"W4406829136","doi":"10.4236/oalib.1112669","title":"Skill Selection and Productivity Growth","year":2025,"lang":"en","type":"article","venue":"OALib","topic":"Firm Innovation and Growth","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Selection (genetic algorithm); Productivity; Computer science; Economics; Artificial intelligence; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001880659,0.00005011438,0.0001007479,0.0001525513,0.00006269649,0.00003354342,0.0000380595,0.00003799744,0.00007797145],"category_scores_gemma":[0.00009850904,0.00005896754,0.00001585428,0.0003930218,0.00001813787,0.0001254775,0.00002003348,0.00006116725,0.00007437873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002459448,"about_ca_system_score_gemma":0.000007664248,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008314721,"about_ca_topic_score_gemma":0.00001416714,"domain_scores_codex":[0.9995544,0.000004533529,0.0001492726,0.0001971165,0.000009513451,0.00008514926],"domain_scores_gemma":[0.9998211,0.000009457718,0.00005358498,0.00007707986,0.00002528905,0.00001346027],"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":[0.000002990349,0.00002315037,0.1570149,0.00001728965,0.000009339414,1.042267e-7,0.00004200495,5.487128e-7,0.00003955832,0.838064,0.003937664,0.0008485154],"study_design_scores_gemma":[0.0003460521,0.00002385414,0.5635971,0.00000759453,0.000002370757,0.000001940023,0.00001101063,0.0004777907,0.001642405,0.2966564,0.1370946,0.0001389446],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7780929,0.0004329377,0.005067316,0.008587706,0.0005502339,0.0001692947,0.0000156546,0.00008977954,0.2069942],"genre_scores_gemma":[0.9918893,0.00002078944,0.000334886,0.0004516418,0.00004534891,0.000008741403,0.000003803061,0.000004668563,0.007240812],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5414076,"threshold_uncertainty_score":0.2404626,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01177679341125626,"score_gpt":0.2052297058285823,"score_spread":0.1934529124173261,"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."}}