{"id":"W2039449808","doi":"10.1049/el:20040038","title":"Performance bound of dynamic forward link adaptation in cellular WCDMA networks using high-order modulation and multicode formats","year":2004,"lang":"en","type":"article","venue":"Electronics Letters","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Link adaptation; Computer science; Throughput; Modulation (music); Transmission (telecommunications); W-CDMA; Link (geometry); Adaptation (eye); Code division multiple access; Computer network; Electronic engineering; Telecommunications; Wireless; Engineering; Channel (broadcasting); Fading; Physics","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":[0.003253431,0.001323017,0.001225953,0.0008880262,0.000619123,0.002509231,0.0007675304,0.001648236,0.003178094],"category_scores_gemma":[0.01437179,0.0004722204,0.0003847894,0.001291236,0.001706649,0.001807695,0.001690021,0.001595723,0.000538218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002058561,"about_ca_system_score_gemma":0.001483991,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003485352,"about_ca_topic_score_gemma":0.002229819,"domain_scores_codex":[0.9980041,0.0006177085,0.00004778767,0.0001705384,0.0007002879,0.0004595041],"domain_scores_gemma":[0.9900874,0.008163247,0.0003816535,0.000307197,0.0009065865,0.0001538236],"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":[0.0001906387,0.00003639073,0.0002995292,0.0001187499,0.00003398462,0.00007082908,0.00005163339,0.9584492,0.005256462,0.0213545,0.0008134852,0.0133246],"study_design_scores_gemma":[0.00001260611,0.00006584193,0.0003157984,0.00003075164,0.00001293469,0.00003412578,0.00002198849,0.9888732,0.002688269,0.007612437,0.0003186798,0.00001330428],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1515615,0.004708563,0.8040287,0.002038218,0.000131332,0.00007880622,0.000313415,0.0006573812,0.0364822],"genre_scores_gemma":[0.9664742,0.00175334,0.02664573,0.0002616033,0.0001144763,0.0001412833,0.000253738,0.0001428709,0.004212638],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003485352,"threshold_uncertainty_score":0.01720601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01271042149932421,"score_gpt":0.2419986266518364,"score_spread":0.2292882051525121,"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."}}