{"id":"W4400275556","doi":"10.1109/tccn.2024.3414394","title":"Cooperative NOMA Empowered Integrated Sensing and Communication: Joint Beamforming and User Pairing","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Cognitive Communications and Networking","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; Concordia University","keywords":"Noma; Pairing; Beamforming; Joint (building); Computer science; Telecommunications; Engineering; Physics; Telecommunications link","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":[0.0001975705,0.0002098059,0.0001972638,0.0002286323,0.000766953,0.0002592872,0.0001120103,0.000121077,0.000008813222],"category_scores_gemma":[0.000007161988,0.0002084196,0.00003483435,0.0004033075,0.000359387,0.0002555113,0.00002004488,0.0005639711,0.000003398658],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004827139,"about_ca_system_score_gemma":0.00001730807,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003410524,"about_ca_topic_score_gemma":0.000219476,"domain_scores_codex":[0.9991707,0.00008856296,0.0002701964,0.0002096471,0.00007063496,0.0001902179],"domain_scores_gemma":[0.9989293,0.0005329069,0.00002619342,0.0003487072,0.0001053986,0.00005748721],"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":[0.00001692656,0.00002883294,0.00005954056,0.0001177806,0.0002553343,0.000005094467,0.003241702,0.001341572,0.001015856,0.0008550195,0.00007832293,0.992984],"study_design_scores_gemma":[0.0004960897,0.00008842671,0.0001018502,0.00245815,0.0001531413,0.0001012184,0.005656912,0.9712705,0.007009235,0.0003432842,0.01182813,0.0004930546],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03566936,0.01995701,0.9411687,0.0003472061,0.0002238293,0.000330015,0.00003643791,0.0008895251,0.001377878],"genre_scores_gemma":[0.9655403,0.03026733,0.003949529,0.00007880273,0.00001958623,0.00003482724,0.0000211053,0.00003966475,0.00004880673],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9924909,"threshold_uncertainty_score":0.8499104,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0263219002527972,"score_gpt":0.2455912837638039,"score_spread":0.2192693835110067,"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."}}