{"id":"W7084131201","doi":"10.64628/aam.gs5rjs6ug","title":"Breeding young men for export in poor countries","year":2019,"lang":"en","type":"article","venue":"","topic":"Economic and Technological Innovation","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"","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":[0.0003674225,0.00006642628,0.0002050418,0.0001651737,0.00002220812,0.00003265037,0.0001108385,0.00009687521,0.0008813601],"category_scores_gemma":[0.00003547658,0.00007126921,0.00003418375,0.0001159564,0.00001712432,0.0002079581,0.00002689672,0.00005725121,0.00097564],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007909591,"about_ca_system_score_gemma":0.00000509692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000897277,"about_ca_topic_score_gemma":0.00001714291,"domain_scores_codex":[0.9992011,7.105813e-7,0.0004005948,0.0002225871,0.000008409582,0.0001666264],"domain_scores_gemma":[0.9997066,0.00002355841,0.0001306333,0.000111881,0.00001482451,0.00001251474],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000004174879,0.000008310752,0.2976899,0.000006446442,0.000004094852,1.140902e-7,0.00001693367,0.000002112214,0.00002306735,0.7006462,0.001477357,0.0001213969],"study_design_scores_gemma":[0.001998241,0.0001684471,0.1381038,0.00001635954,0.00000192101,0.000003121911,0.0005226865,0.01576741,0.001042224,0.6511754,0.1906801,0.000520319],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7301231,0.00008173337,0.003047433,0.0009246601,0.0002280354,0.0002780024,0.00002121211,0.00005389636,0.265242],"genre_scores_gemma":[0.9893442,0.00001998809,0.001054523,0.0003196468,0.00003018009,0.00004163702,0.00001158697,0.00000851306,0.009169676],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2592212,"threshold_uncertainty_score":0.9998022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04127359100925986,"score_gpt":0.2207280903498569,"score_spread":0.179454499340597,"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."}}