{"id":"W2141083740","doi":"10.1109/iwcmc.2011.5982675","title":"Comparison of ns2.34's ZigBee/802.15.4 implementation to Memsic's IRIS Motes","year":2011,"lang":"en","type":"article","venue":"","topic":"Wireless Networks and Protocols","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Throughput; Computer science; Wireless sensor network; Wireless; NeuRFon; Channel (broadcasting); IRIS (biosensor); Computer network; Divergence (linguistics); Set (abstract data type); Wireless network; Service set; Wireless lan; Wi-Fi; Key distribution in wireless sensor networks; Telecommunications; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001320169,0.0004630684,0.0003028238,0.0004086794,0.0004278788,0.0005830767,0.00100172,0.0002513123,0.002170552],"category_scores_gemma":[0.004328603,0.00020723,0.0001793949,0.0004863822,0.0003022798,0.001039196,0.0002538585,0.0004736909,0.0004058209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008731863,"about_ca_system_score_gemma":0.0009082863,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009888395,"about_ca_topic_score_gemma":0.01292235,"domain_scores_codex":[0.9993303,0.0001767303,0.00005515867,0.00005454851,0.0003012097,0.00008215625],"domain_scores_gemma":[0.9982597,0.0007124791,0.00009439711,0.0002680554,0.0005998892,0.00006553024],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002493665,0.0007612086,0.01760836,0.0008555169,0.0003623409,0.0003118382,0.000642151,0.6705214,0.08933878,0.0177814,0.02256727,0.176756],"study_design_scores_gemma":[0.00008667504,0.0004662127,0.004568761,0.00003617974,0.0000464301,0.0001120606,0.0003554258,0.9220917,0.0585051,0.001248278,0.01242888,0.0000541538],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7949158,0.0005759605,0.1604596,0.001379363,0.0004823617,0.0002943354,0.001796711,0.01488684,0.02520906],"genre_scores_gemma":[0.9475694,0.0003382431,0.04687934,0.00016465,0.00001238706,0.0001361518,0.001648335,0.0003475945,0.002903963],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009888395,"threshold_uncertainty_score":0.01966166,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09288813700532975,"score_gpt":0.3829798603543567,"score_spread":0.2900917233490269,"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."}}