{"id":"W4407351697","doi":"10.1109/ojcoms.2025.3540287","title":"The Role of Digital Twin in 6G-Based URLLCs: Current Contributions, Research Challenges, and Next Directions","year":2025,"lang":"en","type":"article","venue":"IEEE Open Journal of the Communications Society","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Türkiye Bilimsel ve Teknolojik Araştırma Kurumu; Engineering and Physical Sciences Research Council; Canada Excellence Research Chairs, Government of Canada","keywords":"Current (fluid); Twin study; Data science; Computer science; Engineering; Electrical engineering; Biology; Evolutionary biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001390677,0.0000716017,0.000140734,0.00006383674,0.0004056623,0.0002771612,0.001855404,0.00006103952,0.000001578756],"category_scores_gemma":[0.0001743132,0.00005034377,0.000116015,0.0004827846,0.0003433028,0.0005986694,0.0002495612,0.0008829658,0.000001298991],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002020716,"about_ca_system_score_gemma":0.0002037235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007722583,"about_ca_topic_score_gemma":0.00003156058,"domain_scores_codex":[0.9989688,0.0001700218,0.0004745951,0.00004810464,0.0001923193,0.0001460991],"domain_scores_gemma":[0.9977807,0.0009956084,0.00009987527,0.0007278436,0.0003588971,0.00003709681],"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":[0.00008149874,0.001423208,0.004035602,0.0002763555,0.0009375224,3.641801e-7,0.01677885,0.0183723,0.001309268,0.1019614,0.03636368,0.81846],"study_design_scores_gemma":[0.001289275,0.00003745889,0.003396507,0.001115187,0.00004056055,0.000009914082,0.01876619,0.01532529,0.002216581,0.01886065,0.9387866,0.0001557371],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.07905958,0.5551435,0.001987151,0.1009949,0.00251415,0.003329961,0.0005136614,0.0001121438,0.256345],"genre_scores_gemma":[0.9775252,0.02216948,0.0001810809,0.00001206239,0.0000141638,0.00003183663,0.000002176414,0.000007212805,0.00005677872],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.902423,"threshold_uncertainty_score":0.3836096,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1018526547825813,"score_gpt":0.3736816066678986,"score_spread":0.2718289518853173,"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."}}