{"id":"W2131858722","doi":"10.1109/glocom.2009.5425620","title":"Feedback Based Real-Time MAC (RT-MAC) Protocol for Wireless Sensor Networks","year":2009,"lang":"en","type":"article","venue":"","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer network; Computer science; Network packet; Wireless sensor network; Multiple Access with Collision Avoidance for Wireless; Real-time computing; Media access control; Channel (broadcasting); Node (physics); Sink (geography); Wireless; Routing protocol; Engineering; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004963672,0.0004904053,0.000495811,0.0001687578,0.0003054292,0.0003669282,0.001494325,0.0003028981,0.0001205576],"category_scores_gemma":[0.00002445183,0.0004309055,0.0002643306,0.0008334273,0.00007868986,0.0003381993,0.000137984,0.0002608116,0.0001010027],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001144351,"about_ca_system_score_gemma":0.0001166618,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002656783,"about_ca_topic_score_gemma":0.000009858538,"domain_scores_codex":[0.9964509,0.0001633337,0.0006275843,0.001077151,0.0005263792,0.001154641],"domain_scores_gemma":[0.9972955,0.0004394493,0.0002612917,0.00138928,0.0002840219,0.0003304435],"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":[0.0002156823,0.0005226312,0.00007040091,0.00003974869,0.00002622461,0.0000298826,0.00004914481,0.8907096,0.003587198,0.02575842,0.03225854,0.04673246],"study_design_scores_gemma":[0.002113636,0.0003966379,0.000246037,0.00008904438,0.000008199516,0.000007886464,0.000004108947,0.9814638,0.005585583,0.0001693126,0.009330649,0.0005850996],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0007854389,0.000002455686,0.9112334,0.001610195,0.0002216675,0.06684984,0.000002742053,0.001317143,0.01797716],"genre_scores_gemma":[0.08228794,0.000005645144,0.7334315,0.007118612,0.001644736,0.1580623,0.00005870888,0.0001917765,0.01719875],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1778019,"threshold_uncertainty_score":0.9998143,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01487723314549263,"score_gpt":0.2679389619794599,"score_spread":0.2530617288339673,"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."}}