{"id":"W4394744622","doi":"10.1109/jrfid.2024.3387996","title":"Digital Twin Models: Functions, Challenges, and Industry Applications","year":2024,"lang":"en","type":"article","venue":"IEEE Journal of Radio Frequency Identification","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"National Research Council Canada","keywords":"Computer science; Industrial engineering; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00287578,0.0006920419,0.0006008922,0.002174681,0.001348396,0.007348773,0.001871648,0.001845178,0.007902524],"category_scores_gemma":[0.005329813,0.0003655179,0.0005887648,0.002838127,0.004187021,0.01331656,0.004886015,0.002386895,0.002415581],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002081137,"about_ca_system_score_gemma":0.002262065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00153602,"about_ca_topic_score_gemma":0.001447705,"domain_scores_codex":[0.997892,0.0005916157,0.0001397902,0.0002557921,0.0009532108,0.0001676511],"domain_scores_gemma":[0.9980197,0.0007584098,0.0001535499,0.0003610968,0.0005464194,0.0001607391],"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":[0.00003339169,0.00001923137,0.0004799669,0.0004085031,0.000009529501,0.0001236789,0.000611809,0.001831381,0.000936607,0.8814127,0.004205766,0.1099275],"study_design_scores_gemma":[0.00001037123,0.0001063216,0.0005711454,0.001131013,0.00004019742,0.0009697867,0.002401296,0.01443735,0.003870229,0.4124633,0.5639251,0.00007389947],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.03710481,0.0616084,0.5509881,0.01379163,0.002669208,0.0002319909,0.0002989986,0.00113306,0.3321739],"genre_scores_gemma":[0.5871226,0.106448,0.2181319,0.003708466,0.001145813,0.0003694908,0.0007147495,0.0006435525,0.08171532],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.007902524,"threshold_uncertainty_score":0.02643663,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03226270485462468,"score_gpt":0.2370151127791138,"score_spread":0.2047524079244891,"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."}}