{"id":"W4237586500","doi":"10.32920/ryerson.14653116.v1","title":"Adaptive Subcarrier Allocation for Orthogonal Frequency Code Division Multiplexing (OFCDM)","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Subcarrier; Computer science; Interference (communication); Code division multiple access; Orthogonal frequency-division multiplexing; Electronic engineering; Algorithm; Telecommunications; Engineering; Channel (broadcasting)","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001155107,0.0003584,0.0004249974,0.0002284286,0.0003487977,0.0007989028,0.003828324,0.0004175584,0.00005968821],"category_scores_gemma":[0.0002941915,0.0003599085,0.0002799625,0.0004396466,0.0000985774,0.0005660465,0.006007186,0.001029709,0.00001878644],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002780066,"about_ca_system_score_gemma":0.0009548414,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002346895,"about_ca_topic_score_gemma":0.0006509762,"domain_scores_codex":[0.9963212,0.0004601099,0.0006270881,0.001188544,0.0008464098,0.0005566589],"domain_scores_gemma":[0.9944269,0.0007318311,0.0003068906,0.002931413,0.001395121,0.0002078588],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005445568,0.0005556716,0.002334091,0.0003805613,0.0004537386,0.00002458198,0.003788637,0.1983875,0.003094249,0.4934369,0.002551348,0.2949382],"study_design_scores_gemma":[0.0003320662,0.00004629669,0.003140371,0.0002212392,0.000006037474,0.000002597387,0.00009199391,0.985672,0.000818972,0.008811273,0.0004303807,0.0004267926],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005094648,0.0008495887,0.9876527,0.002834534,0.0005707724,0.001130788,0.0000316622,0.0003050717,0.001530238],"genre_scores_gemma":[0.6682357,0.0001457355,0.3301907,0.0001338337,0.000121453,0.0004966037,0.0003162195,0.00002969666,0.0003301374],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7872844,"threshold_uncertainty_score":0.9998853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08773319860745304,"score_gpt":0.3379074466415276,"score_spread":0.2501742480340745,"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."}}