{"id":"W2047300650","doi":"10.1002/ett.1137","title":"Performance of collaborative codes in CSMA/CD environment","year":2006,"lang":"en","type":"article","venue":"European Transactions on Telecommunications","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Carrier sense multiple access with collision avoidance; Computer science; Throughput; Network packet; Markov chain; Computer network; Channel (broadcasting); Distributed coordination function; Access control; Channel access method; Protocol (science); Collision; Scheme (mathematics); Wireless; Computer security; Mathematics; IEEE 802.11; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002925131,0.0001345517,0.0001489135,0.0002302246,0.0002246194,0.00003328539,0.001088702,0.0000305949,0.0000277252],"category_scores_gemma":[0.000003447597,0.0001435692,0.00005195981,0.0007654683,0.0001285445,0.0001939941,0.00002644555,0.0002642134,0.00008508516],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007738457,"about_ca_system_score_gemma":0.00002982218,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004232824,"about_ca_topic_score_gemma":0.0001197712,"domain_scores_codex":[0.9985383,0.0004410754,0.0004055198,0.0002422095,0.0001736791,0.0001992105],"domain_scores_gemma":[0.9982927,0.0001940824,0.0001338533,0.001294184,0.00004914369,0.00003604041],"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":[0.00000651824,0.0006347466,0.0003604834,0.000004369561,0.000009540719,0.00000155535,0.0002950937,0.9817302,0.0007097955,0.004159888,0.00007085699,0.01201692],"study_design_scores_gemma":[0.001977368,0.0007234599,0.1630808,0.0002664281,0.00003655522,0.00001794679,0.0002756485,0.7666385,0.03155915,0.0001386395,0.03424124,0.001044248],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2531301,0.0003307961,0.6598148,0.0009632403,0.0001168166,0.0003332437,0.00002265616,0.0002159993,0.08507231],"genre_scores_gemma":[0.9416153,0.0005373968,0.05722098,0.00003624241,0.000009085691,0.00002001718,0.00001119944,0.00001723044,0.0005325329],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6884852,"threshold_uncertainty_score":0.5854583,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007750151187723384,"score_gpt":0.1959455362840515,"score_spread":0.1881953850963281,"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."}}