{"id":"W4383913712","doi":"10.1111/1748-8583.12524","title":"Human resource management in the age of generative artificial intelligence: Perspectives and research directions on ChatGPT","year":2023,"lang":"en","type":"article","venue":"Human Resource Management Journal","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":765,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; Western University","funders":"Economic and Social Research Council","keywords":"Generative grammar; Context (archaeology); Stakeholder; Scholarship; Realm; Knowledge management; Sociology; Engineering ethics; Political science; Artificial intelligence; Public relations; Computer science; Engineering; Law","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":[0.00967033,0.0003154595,0.0005902281,0.001555317,0.004644557,0.01321625,0.001316777,0.00429757,0.006437828],"category_scores_gemma":[0.01537479,0.0002197052,0.0004466959,0.001678517,0.01486041,0.01033641,0.003800753,0.007624691,0.0008165074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004668503,"about_ca_system_score_gemma":0.005950533,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001954331,"about_ca_topic_score_gemma":0.003790379,"domain_scores_codex":[0.9933637,0.004537487,0.0001621587,0.0003758873,0.001147268,0.0004135588],"domain_scores_gemma":[0.9414717,0.05296352,0.0008989107,0.0006365824,0.002307859,0.001721518],"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":[0.00004807741,0.0000390089,0.000331102,0.0009598355,0.00001143655,0.0004959411,0.03473899,0.0002892685,0.0002246551,0.8029231,0.1119956,0.04794287],"study_design_scores_gemma":[0.0000111064,0.00003513869,0.0006553679,0.002287243,0.00001212144,0.0003033532,0.02801335,0.0006453107,0.0002389976,0.1477872,0.8199763,0.00003435827],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"review","genre_scores_codex":[0.008941795,0.174687,0.0105508,0.6272115,0.04995944,0.00005652118,0.000059775,0.0000792803,0.1284539],"genre_scores_gemma":[0.4966779,0.2335622,0.007950265,0.1078463,0.108199,0.0002845127,0.000105211,0.0003050446,0.04506958],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.01321625,"threshold_uncertainty_score":0.05114222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3244641556378462,"score_gpt":0.4965829114004847,"score_spread":0.1721187557626385,"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."}}