{"id":"W4407129048","doi":"10.1109/tcomm.2025.3538830","title":"QoE-Oriented Hybrid Semantic and Bit Communications Under Mismatched Knowledge","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Robotics and Automated Systems","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Computer science; Bit (key); Electronic engineering; Bit error rate; Computer network; Computer architecture; Engineering; Channel (broadcasting)","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":[0.001327156,0.0009369597,0.001093825,0.0005574078,0.0006487853,0.001132794,0.001376266,0.000910849,0.001606426],"category_scores_gemma":[0.004370255,0.0002714104,0.0003832015,0.0007982437,0.0008342162,0.002165816,0.001690235,0.0009306787,0.0002553619],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008428981,"about_ca_system_score_gemma":0.001336107,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003256442,"about_ca_topic_score_gemma":0.003097596,"domain_scores_codex":[0.9989929,0.0003289272,0.00004253001,0.000181299,0.000235344,0.0002191021],"domain_scores_gemma":[0.9979923,0.001152848,0.0001786318,0.0001476724,0.0004033416,0.0001253559],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004682076,0.000195234,0.001523449,0.0002247239,0.00006518773,0.0002923337,0.0002784128,0.8207939,0.01404687,0.0378516,0.003091476,0.1211687],"study_design_scores_gemma":[0.00001443013,0.00006267872,0.0001221535,0.000005339878,0.00001041166,0.00004854049,0.00002923227,0.9917902,0.001001744,0.006523883,0.0003818492,0.000009615374],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03854662,0.0003899003,0.9571791,0.0003073427,0.00005376173,0.00004714939,0.00005983033,0.0002377911,0.00317849],"genre_scores_gemma":[0.9512155,0.0002639744,0.0465709,0.0001714045,0.00005253786,0.00006853379,0.0000713356,0.00003300298,0.001552862],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003256442,"threshold_uncertainty_score":0.007018745,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02362569454684672,"score_gpt":0.2747310683697688,"score_spread":0.2511053738229221,"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."}}