{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001487362,0.001021943,0.001042301,0.0003154853,0.0006273899,0.001201871,0.0009027473,0.001083333,0.0009022128],"category_scores_gemma":[0.00210906,0.0003739747,0.0004768289,0.0008505195,0.001019353,0.001351414,0.002057242,0.0009493835,0.0003885998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004224529,"about_ca_system_score_gemma":0.0008787736,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008851906,"about_ca_topic_score_gemma":0.001225347,"domain_scores_codex":[0.9981477,0.0009892618,0.0000512137,0.0002538931,0.00031662,0.000241389],"domain_scores_gemma":[0.9990149,0.0004525218,0.0001313651,0.0001626073,0.000151943,0.00008663745],"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":[0.0004993404,0.0003035624,0.002057876,0.0002043855,0.0001191728,0.0008496763,0.0003138548,0.7796776,0.02724192,0.1006218,0.001798369,0.08631235],"study_design_scores_gemma":[0.00001371543,0.000134838,0.0001389884,0.000006538104,0.000011313,0.0001559402,0.00005167719,0.9890918,0.002433076,0.006882553,0.00106256,0.00001699863],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0334358,0.0003420348,0.9619141,0.0001527549,0.00006891134,0.00005533951,0.00002214793,0.0001096947,0.003899296],"genre_scores_gemma":[0.8889124,0.0002658741,0.1080805,0.0001409843,0.0000752925,0.0001085574,0.00003367045,0.00001314398,0.00236951],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001487362,"threshold_uncertainty_score":0.007866025,"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."}}