{"id":"W2911791687","doi":"10.1109/mwscas.2018.8624045","title":"Multiplatform Spectrum Sensing Prototype","year":2018,"lang":"en","type":"article","venue":"","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"White spaces; Computer science; Ultra high frequency; Cognitive radio; Usability; Spectrum (functional analysis); Channel (broadcasting); Radio spectrum; Real-time computing; Telecommunications; Wireless; Human–computer interaction","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":[0.0001565871,0.0001180024,0.0001198818,0.00007515896,0.0002181493,0.0001919898,0.0002287316,0.00004061106,0.00005854654],"category_scores_gemma":[0.00001851935,0.00009902599,0.00004827463,0.0003672888,0.00007280348,0.0003451005,0.0001355463,0.0001001255,0.0003002979],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003606873,"about_ca_system_score_gemma":0.00003354381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004653716,"about_ca_topic_score_gemma":0.0001872477,"domain_scores_codex":[0.9989851,0.00001618096,0.0001410724,0.0003283342,0.0001630349,0.000366324],"domain_scores_gemma":[0.999404,0.00004688189,0.00003826577,0.00035454,0.00006973102,0.00008661812],"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":[0.00004727137,0.00005710974,0.0007191569,0.000007667845,0.00004857508,0.0001206307,0.001031566,0.00001075798,0.003107121,0.2712378,0.001932718,0.7216797],"study_design_scores_gemma":[0.0004443101,0.0004167767,0.002944326,0.00003665151,0.000005003537,0.000218291,0.00002805906,0.9319847,0.02599264,0.02299579,0.01454203,0.0003914017],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02824955,0.00001676626,0.8668543,0.000968033,0.0004477288,0.0002531101,1.346023e-7,0.0003730582,0.1028374],"genre_scores_gemma":[0.9153637,0.000002900624,0.08308368,0.000550208,0.0005887664,6.695265e-7,3.643488e-7,0.000008625213,0.0004010951],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.931974,"threshold_uncertainty_score":0.4038163,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01630790325768192,"score_gpt":0.2426580809291322,"score_spread":0.2263501776714502,"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."}}