{"id":"W4398411981","doi":"10.7910/dvn/jcvnxg","title":"Replication Data for: The impact of entrepreneurship training and credit on labour market outcomes of disadvantaged youth","year":2022,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Entrepreneurship Studies and Influences","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute on Governance","funders":"","keywords":"Disadvantaged; Replication (statistics); Entrepreneurship; Business; Labour economics; Economics; Demographic economics; Economic growth; Finance; Biology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001127191,0.0003221024,0.0005647339,0.0001737485,0.000258926,0.0001171432,0.00165632,0.00007512925,0.01538909],"category_scores_gemma":[0.002521385,0.0002151264,0.0001640624,0.0002195485,0.0001605722,0.0006618248,0.001768548,0.0002319283,0.00005415101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002374647,"about_ca_system_score_gemma":0.00003524819,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002643378,"about_ca_topic_score_gemma":0.000175442,"domain_scores_codex":[0.9980363,0.00004309037,0.0005120932,0.0007460463,0.0003924542,0.0002700179],"domain_scores_gemma":[0.9944473,0.0007180994,0.001005504,0.003722331,0.0000905451,0.00001621552],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002181969,0.00009627021,0.01706537,0.000291684,0.000359504,0.000001898943,0.0000959969,0.00005625676,0.000002881683,0.0001031121,0.9802783,0.00143051],"study_design_scores_gemma":[0.000516219,0.00005199899,0.02580162,0.00006127596,0.0005268131,6.784223e-7,0.00213684,0.0001166457,0.000001093423,0.00006045067,0.970519,0.0002073398],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.005272039,0.00001655885,0.000004815834,0.00004939765,0.0003591655,0.0005740488,0.9935907,0.00002115764,0.0001121818],"genre_scores_gemma":[0.01038207,0.0007286929,0.00001498409,0.0002837162,0.0003234632,0.00004296476,0.9881492,0.0000238574,0.0000510194],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01533494,"threshold_uncertainty_score":0.985511,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06503531524447409,"score_gpt":0.3046313746029451,"score_spread":0.239596059358471,"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."}}