{"id":"W2746013538","doi":"10.1515/picbe-2017-0047","title":"Human talent forecasting","year":2017,"lang":"en","type":"article","venue":"Proceedings of the ... International Conference on Business Excellence","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Human resources; Economic shortage; Order (exchange); Face (sociological concept); Computer science; Data science; Visibility; Resource (disambiguation); Sign (mathematics); Human resource management; Operations research; Data mining; Knowledge management; Marketing; Business; Engineering; Government (linguistics); Management; Economics; Geography; Mathematics; Finance","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":[0.0007771624,0.0006637131,0.0003602466,0.002850914,0.0003193269,0.0008430161,0.0006528069,0.0006866503,0.009487846],"category_scores_gemma":[0.003639378,0.000129864,0.0004276522,0.002819892,0.0001698356,0.0006813977,0.0003780979,0.0006877647,0.00346201],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009972194,"about_ca_system_score_gemma":0.0004128204,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01394311,"about_ca_topic_score_gemma":0.008652071,"domain_scores_codex":[0.9995604,0.00008351479,0.00001996278,0.00012157,0.0001549552,0.00005956574],"domain_scores_gemma":[0.9982602,0.0008473727,0.0001512341,0.0001563931,0.0004503496,0.0001344371],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000576318,0.0005311098,0.1329898,0.000281361,0.0001211982,0.0002074477,0.0002474078,0.4748686,0.002592469,0.004549086,0.0257274,0.3573079],"study_design_scores_gemma":[0.00001539137,0.0001486609,0.03908869,0.00004544207,0.00002162837,0.00003278802,0.0001432147,0.9502364,0.00220739,0.002742545,0.005289063,0.00002878681],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7653709,0.001177304,0.123114,0.001853203,0.0004978157,0.0006701855,0.03059805,0.004221707,0.0724969],"genre_scores_gemma":[0.964017,0.0003457183,0.01943459,0.00008867254,0.00006089709,0.0002070257,0.006611655,0.00004476703,0.009189629],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01394311,"threshold_uncertainty_score":0.03173995,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09963786675806313,"score_gpt":0.3022768333407212,"score_spread":0.2026389665826581,"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."}}