{"id":"W3125995405","doi":"10.1109/globecom42002.2020.9322133","title":"Learning-Based Cooperative Spectrum Sensing in Hybrid Underlay-Interweave Secondary Networks","year":2020,"lang":"en","type":"article","venue":"","topic":"Sparse and Compressive Sensing Techniques","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Support vector machine; Computer science; Kernel (algebra); Artificial intelligence; Pattern recognition (psychology); Machine learning; Algorithm; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005054338,0.0001829336,0.0002221723,0.00006654071,0.0000397998,0.00005718443,0.00008518362,0.00005576874,0.0001415971],"category_scores_gemma":[0.00001890105,0.0001867963,0.0000512827,0.0001813912,0.00003021643,0.00007348411,0.00003477106,0.0005524434,0.00002530725],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005412497,"about_ca_system_score_gemma":0.00002170738,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003487873,"about_ca_topic_score_gemma":0.00006929065,"domain_scores_codex":[0.9992004,0.00005136382,0.0001929291,0.0002117885,0.0000776548,0.0002658486],"domain_scores_gemma":[0.9996953,0.00006567386,0.0000203065,0.0001176178,0.00002180269,0.00007928856],"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":[0.00002059678,0.000006091153,0.0001085779,0.000008320502,0.00002263646,0.0001615354,0.0001813278,0.9881719,0.001740104,0.00006179892,0.00533993,0.004177216],"study_design_scores_gemma":[0.0002374903,0.00009380597,0.00009066625,0.00005081356,0.000004493147,0.000007989462,0.0001070657,0.8999217,0.09776282,0.00007148425,0.001442313,0.000209414],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1044509,0.0001711284,0.8712734,0.0008789339,0.000162917,0.0001979102,0.000001447336,0.002154154,0.02070919],"genre_scores_gemma":[0.9971634,0.00001491942,0.001433609,0.001157778,0.0001298984,0.000001281563,0.00001144264,0.00004492003,0.00004276094],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8927124,"threshold_uncertainty_score":0.761733,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01199871862472172,"score_gpt":0.2028622264611691,"score_spread":0.1908635078364474,"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."}}