{"id":"W4405704914","doi":"10.1142/s1363919624400061","title":"ARTIFICIAL INTELLIGENCE IN TRANSFORMING HRM PROCESSES WITHIN ORGANIZATIONS","year":2024,"lang":"en","type":"article","venue":"International Journal of Innovation Management","topic":"AI and HR Technologies","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Knowledge management; Human resource management; Scopus; Systematic review; Computer science; Process management; Business; Political science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03301309,0.0005584647,0.001058389,0.006926124,0.0007068214,0.005659991,0.0009096785,0.00170686,0.001309019],"category_scores_gemma":[0.05972134,0.0004372892,0.001701012,0.006883761,0.002712789,0.005360827,0.002263074,0.001697418,0.0001722559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003052769,"about_ca_system_score_gemma":0.008912466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00393375,"about_ca_topic_score_gemma":0.005591025,"domain_scores_codex":[0.9605092,0.0297136,0.003373151,0.001173132,0.004807235,0.0004237114],"domain_scores_gemma":[0.8958811,0.09190228,0.006669722,0.001859449,0.003267087,0.0004205261],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001523315,0.0001484977,0.00677001,0.1446213,0.003107949,0.0001891268,0.006837331,0.002336129,0.0005960473,0.0358904,0.002225496,0.7971255],"study_design_scores_gemma":[0.0002581847,0.001365397,0.04494979,0.5315264,0.01013318,0.00122736,0.01461517,0.002767829,0.003257915,0.09293599,0.2966717,0.0002909935],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.01116278,0.9687007,0.005218131,0.006025034,0.0003885285,0.0002119195,0.00008038885,0.00002474021,0.008187766],"genre_scores_gemma":[0.2310654,0.7408532,0.02260892,0.003989609,0.0004549223,0.0004883241,0.00008448277,0.00001792232,0.000437258],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03301309,"threshold_uncertainty_score":0.174592,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02684287126911154,"score_gpt":0.2863984542195178,"score_spread":0.2595555829504062,"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."}}