{"id":"W1494209541","doi":"10.1007/978-3-540-77024-4_37","title":"A Study on the Binary Exponential Backoff in Noisy and Heterogeneous Environment","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Wireless Networks and Protocols","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Exponential backoff; Computer science; Transmission (telecommunications); Binary number; Throughput; Network packet; Computer network; Collision; Exponential function; Channel (broadcasting); Packet loss; Real-time computing; Algorithm; Computer security; Wireless; Telecommunications; Mathematics; Arithmetic","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":[0.001476742,0.0004900635,0.0004214837,0.0004993753,0.0002430496,0.0004267485,0.002320602,0.000219428,0.00002101902],"category_scores_gemma":[0.0000139382,0.0003507121,0.0000760477,0.0003214325,0.0004839275,0.000196249,0.001716919,0.0008674418,0.0000302772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001861895,"about_ca_system_score_gemma":0.0001065241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001989073,"about_ca_topic_score_gemma":0.00006072449,"domain_scores_codex":[0.9964169,0.00009643989,0.0004790761,0.001438878,0.000943243,0.0006254388],"domain_scores_gemma":[0.9977024,0.0006306454,0.0001861836,0.001326871,0.00002722078,0.0001267097],"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":[0.0000624197,0.0004108152,0.0007183899,0.00002564086,0.00002677001,0.001702622,0.003907254,0.1455766,0.0001082514,0.006273891,0.00002568842,0.8411617],"study_design_scores_gemma":[0.002541967,0.005710223,0.007834466,0.001465035,0.00002263561,0.0003644988,0.000004370869,0.9039285,0.001561695,0.06809048,0.005522768,0.002953356],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009353047,0.0002638254,0.9830542,0.000586812,0.0006000465,0.005415075,0.000002172309,0.00005306263,0.000671819],"genre_scores_gemma":[0.9720332,0.00004699585,0.02485966,0.00195032,0.0005265921,0.0004184791,0.00000138257,0.00004485752,0.0001185111],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9626802,"threshold_uncertainty_score":0.9998945,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03408448399659316,"score_gpt":0.2615534175286175,"score_spread":0.2274689335320244,"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."}}