{"id":"W4235806207","doi":"10.32920/ryerson.14644860.v1","title":"Accommodating Machine-To-Machine Traffic In IEEE 802.15.4: The Prioritized Wait Time Approach","year":2021,"lang":"en","type":"preprint","venue":"","topic":"IoT Networks and Protocols","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Automation; Machine to machine; Computer science; Wireless; Computer network; Smart grid; Embedded system; Telecommunications; Engineering","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":[0.0009098123,0.0006332162,0.0008439439,0.0001691134,0.0001078858,0.0004065628,0.000986789,0.0004904206,0.00071833],"category_scores_gemma":[0.00003636694,0.0004855335,0.0002622367,0.0004453135,0.0000264466,0.00008479967,0.0006117448,0.002256731,0.00007987396],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001631779,"about_ca_system_score_gemma":0.00007606031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001611844,"about_ca_topic_score_gemma":0.0002248367,"domain_scores_codex":[0.9974336,0.0002183872,0.0007474419,0.0006446135,0.0002969629,0.0006589639],"domain_scores_gemma":[0.9984401,0.0002197864,0.00008148276,0.001071366,0.00004692822,0.00014027],"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":[0.00001993875,0.00005880063,0.00005953317,0.0003996084,0.00009101376,0.00001676761,0.0007325024,0.971435,0.0002482396,0.00003870315,0.002253373,0.02464649],"study_design_scores_gemma":[0.000587089,0.00001401864,0.0002112298,0.0003403281,0.00002655696,0.00001305553,0.00005064123,0.9953575,0.0001687387,0.00007197823,0.002515829,0.0006430174],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4345763,0.006511804,0.1863521,0.002020729,0.005510328,0.1037021,0.0003204478,0.006156154,0.25485],"genre_scores_gemma":[0.9572875,0.00008418,0.02512169,0.0004724817,0.001143561,0.01331525,0.0005354139,0.0003145674,0.001725296],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5227113,"threshold_uncertainty_score":0.9997596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01538588926539382,"score_gpt":0.2419710110205058,"score_spread":0.2265851217551119,"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."}}