{"id":"W2968700299","doi":"10.1109/rose.2019.8790408","title":"Intelligent Sensing for Automated Spectrum Assignment","year":2019,"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":"Communications Research Centre Canada","funders":"","keywords":"Computer science; Cognitive radio; Wireless; Real-time computing; Wireless sensor network; Point (geometry); Reading (process); Computer network; Embedded system; Telecommunications","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":[0.0009038622,0.0005309453,0.0005779738,0.000381507,0.0007845351,0.001140204,0.001150351,0.0007501764,0.002287582],"category_scores_gemma":[0.003399258,0.0003516828,0.0003380431,0.0003861125,0.001002002,0.001465848,0.001084351,0.0009170714,0.000470872],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007695019,"about_ca_system_score_gemma":0.001090632,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002599991,"about_ca_topic_score_gemma":0.003099125,"domain_scores_codex":[0.9988841,0.0002907152,0.00004865591,0.0002532435,0.000401854,0.0001212762],"domain_scores_gemma":[0.9981822,0.000864605,0.0001645876,0.0004720241,0.0002541437,0.000062511],"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":[0.0006039037,0.000561126,0.002760747,0.0001866701,0.00007510518,0.0003405252,0.0006356081,0.4102744,0.1463698,0.0633181,0.006874194,0.3679998],"study_design_scores_gemma":[0.00003872442,0.00009069643,0.0005844311,0.00001156784,0.00001594912,0.0001041345,0.00008107529,0.9622038,0.01340323,0.01915441,0.004291059,0.00002093685],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03637839,0.0001651077,0.9544674,0.0003896987,0.00006967173,0.0001022689,0.00003114641,0.001454932,0.006941312],"genre_scores_gemma":[0.7738068,0.00009969265,0.2233563,0.000199502,0.00004665714,0.0001099187,0.00004706409,0.00007196044,0.002262051],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002599991,"threshold_uncertainty_score":0.00765276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01463753113947691,"score_gpt":0.248786020795465,"score_spread":0.2341484896559881,"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."}}