{"id":"W4391610497","doi":"10.18282/hrms.v6i2.3420","title":"Examining the impact of generative artificial intelligence on work dynamics","year":2024,"lang":"en","type":"article","venue":"Human Resources Management and Services","topic":"AI and HR Technologies","field":"Business, Management and Accounting","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trent University","funders":"","keywords":"Generative grammar; Dynamics (music); Artificial intelligence; Work (physics); Computer science; Psychology; Engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.0002273943,0.0001831538,0.0001530358,0.0003125941,0.0003015838,0.0007011289,0.0003902874,0.00004908333,0.00009946928],"category_scores_gemma":[0.000002974508,0.0001116055,0.00006949709,0.0005006267,0.0001255245,0.0002757525,0.0003685105,0.0001342739,0.00004754356],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002028826,"about_ca_system_score_gemma":0.0000014004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002154624,"about_ca_topic_score_gemma":0.0001573603,"domain_scores_codex":[0.9991106,0.00000893158,0.0002248835,0.000277981,0.0001818528,0.0001956872],"domain_scores_gemma":[0.9995829,0.00004578997,0.0001066656,0.0002326119,0.00002587496,0.000006095473],"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":[0.00007179663,0.00008091576,0.01637946,0.001064937,0.0003737839,0.00003766538,0.00175085,0.001597696,0.0000431215,0.8125046,0.00120834,0.1648868],"study_design_scores_gemma":[0.0002806403,0.000479786,0.2730404,0.002466957,0.0006383316,0.000002207474,0.0703579,0.2335422,0.0001669991,0.3920428,0.0254989,0.00148299],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9658228,0.0005781269,0.0002145784,0.0004580486,0.00007984789,0.0002085113,0.000001792661,0.0002223418,0.03241396],"genre_scores_gemma":[0.9987938,0.00005120878,0.00004677103,0.0001771609,0.0003027532,0.00001624264,0.00001538925,0.0000176716,0.0005790317],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4204619,"threshold_uncertainty_score":0.6761001,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04533786967693289,"score_gpt":0.2712199040038518,"score_spread":0.2258820343269189,"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."}}