{"id":"W4400275910","doi":"10.1109/lwc.2024.3422841","title":"Content-Aware Cross-Modal Stream Transmission","year":2024,"lang":"en","type":"article","venue":"IEEE Wireless Communications Letters","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Priority Academic Program Development of Jiangsu Higher Education Institutions; China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Computer science; Transmission (telecommunications); Modal; Computer network; Telecommunications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007192275,0.0007088238,0.0006128312,0.0005533366,0.0005729601,0.0006002883,0.001128308,0.0004266078,0.00175701],"category_scores_gemma":[0.002092645,0.0002386338,0.0003731396,0.0005812687,0.0004742293,0.001147298,0.001434045,0.0007710423,0.0003649032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005286703,"about_ca_system_score_gemma":0.0007794652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009543006,"about_ca_topic_score_gemma":0.001344115,"domain_scores_codex":[0.9994211,0.0001212676,0.0000331605,0.0001136953,0.0002221177,0.00008876428],"domain_scores_gemma":[0.9985996,0.0004520508,0.000175265,0.0002672233,0.0004155822,0.00009035422],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001293607,0.0006083461,0.002633552,0.0003146434,0.0001207548,0.0007092286,0.0005118332,0.3390497,0.231682,0.02263814,0.006844779,0.3935934],"study_design_scores_gemma":[0.00002345486,0.0001108483,0.0003065538,0.000007497154,0.0000161817,0.0001815064,0.00004437689,0.9705006,0.02475284,0.002664461,0.001375912,0.00001578953],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05094739,0.0003455226,0.9454951,0.000134194,0.00008045206,0.0000663752,0.00003984736,0.0007865786,0.002104548],"genre_scores_gemma":[0.8717242,0.0002710937,0.1249614,0.0001561301,0.00009268875,0.00008020808,0.0001159151,0.00009245852,0.002506009],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00175701,"threshold_uncertainty_score":0.005877733,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05226353412076621,"score_gpt":0.3322398580495018,"score_spread":0.2799763239287356,"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."}}