{"id":"W2944414485","doi":"10.5430/jms.v10n3p27","title":"The Impact of HR Analytics on the Training and Development Strategy - Private Sector Case Study in Lebanon","year":2019,"lang":"en","type":"article","venue":"Journal of Management and Strategy","topic":"AI and HR Technologies","field":"Business, Management and Accounting","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Analytics; Training and development; Private sector; Business; Data science; Management; Computer science; Political 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009493188,0.0001571585,0.000247721,0.0002706326,0.0001496402,0.0002835176,0.0002202662,0.00003682384,0.00002988483],"category_scores_gemma":[0.00001173152,0.00007833035,0.00004897,0.0002438182,0.00005672971,0.0003108848,0.0001214117,0.0002131189,0.000002346363],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002737319,"about_ca_system_score_gemma":0.00002528312,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001019556,"about_ca_topic_score_gemma":0.0001486796,"domain_scores_codex":[0.9989818,0.00002015836,0.0004491389,0.0001241752,0.0002218271,0.0002029283],"domain_scores_gemma":[0.9992772,0.00008632727,0.0004220803,0.0001480988,0.00005613422,0.00001014113],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005514837,0.0007970387,0.6939852,0.0003591698,0.001706039,0.002495267,0.002202435,0.005480881,0.0001114539,0.03575281,0.001440714,0.2551175],"study_design_scores_gemma":[0.00321712,0.001344075,0.8238666,0.0002267152,0.0001943925,0.0001324628,0.1582666,0.004260961,0.00002941566,0.005417272,0.002625831,0.0004185213],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952412,0.0001586794,0.00001329564,0.0001750964,0.00004645713,0.0003551883,2.957522e-7,0.000009027851,0.004000713],"genre_scores_gemma":[0.9996393,0.00008879552,0.00002491195,0.00003129375,0.00006094938,0.000002871454,3.227043e-7,0.000008830121,0.0001426691],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.254699,"threshold_uncertainty_score":0.3194219,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06882119962639427,"score_gpt":0.2831429872503479,"score_spread":0.2143217876239537,"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."}}