{"id":"W4388651529","doi":"10.36227/techrxiv.24527455","title":"Semantic Communication: A Survey on Research Landscape, Challenges, and Future Directions","year":2023,"lang":"en","type":"preprint","venue":"","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"National Institute of Standards and Technology; U.S. Department of Commerce","keywords":"Computer science; Data science; Paradigm shift; Status quo; Semantic integration; Context (archaeology); World Wide Web; Semantic computing; Semantic Web; Geography","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":[0.006411602,0.001337651,0.001750464,0.00848337,0.001705369,0.008536922,0.002609136,0.003076085,0.008487189],"category_scores_gemma":[0.01191265,0.0008576122,0.00125966,0.01159625,0.005572773,0.02508898,0.003526467,0.004623376,0.002484545],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003051226,"about_ca_system_score_gemma":0.004497908,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003735333,"about_ca_topic_score_gemma":0.003052277,"domain_scores_codex":[0.9972386,0.00108455,0.0002745581,0.0004205559,0.0007657713,0.0002158368],"domain_scores_gemma":[0.9844213,0.01253519,0.0003397916,0.0006856766,0.00168118,0.0003369733],"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":[0.00006781461,0.00009298367,0.0012465,0.006002372,0.00006856931,0.0002087111,0.001343697,0.00167512,0.000445125,0.364564,0.03184987,0.5924353],"study_design_scores_gemma":[0.00001459918,0.00008923675,0.001044028,0.007808717,0.0000731885,0.001029924,0.004207286,0.006664312,0.0005481051,0.2867169,0.6917036,0.0001001093],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.002376299,0.9222662,0.0270872,0.0236187,0.001643441,0.00006059454,0.0001668306,0.0001720071,0.0226087],"genre_scores_gemma":[0.01547483,0.9652552,0.01213882,0.002283075,0.00246708,0.00006504191,0.0002337046,0.00006148931,0.002020726],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.008536922,"threshold_uncertainty_score":0.03390819,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2335033143011106,"score_gpt":0.3763190243992491,"score_spread":0.1428157100981385,"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."}}