{"id":"W4394938856","doi":"10.5267/j.ijdns.2024.3.017","title":"Investigating electronic human resource management systems, sustainable innovation, and organizational agility on sustainable competitive advantage in the manufacturing industries","year":2024,"lang":"en","type":"article","venue":"International Journal of Data and Network Science","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Business; Competitive advantage; Human resource management; Knowledge management; Industrial organization; Human resource management system; Process management; Marketing; Computer 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":[0.001805725,0.00008463752,0.00007919746,0.0003361403,0.0001609206,0.0008276358,0.0006559383,0.00002818618,0.000004936944],"category_scores_gemma":[0.00005918684,0.00006706017,0.000005099771,0.000775888,0.000181694,0.002044912,0.0001684792,0.0003522395,5.358875e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001972202,"about_ca_system_score_gemma":0.00009865355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003981407,"about_ca_topic_score_gemma":0.000001413986,"domain_scores_codex":[0.9987484,0.00002559863,0.0003513962,0.0001393469,0.0004977091,0.0002375225],"domain_scores_gemma":[0.9994721,0.0001259126,0.00006546363,0.0001153822,0.0001906426,0.00003043457],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000004317967,0.00001035803,0.001531495,0.0001139744,0.00003710836,0.00007246773,0.0004146195,0.01737949,0.00001370887,0.9767197,0.001961659,0.001741131],"study_design_scores_gemma":[0.001902887,0.0003598779,0.03169586,0.004160975,0.00008297669,0.001371473,0.197767,0.05039616,0.001539581,0.09729211,0.6124131,0.001018045],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9414423,0.001129698,0.00481014,0.001395378,0.0004511578,0.0003983543,0.00005080013,0.00006627185,0.05025589],"genre_scores_gemma":[0.9994057,0.00007700599,0.000082774,0.00008225958,0.0001619198,0.000002428199,0.00003937023,0.000006602761,0.0001419157],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8794276,"threshold_uncertainty_score":0.7980911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01530112505916322,"score_gpt":0.2704024852847966,"score_spread":0.2551013602256334,"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."}}