{"id":"W2062309559","doi":"10.5539/nct.v1n1p7","title":"New Approach Construction for Wireless ZigBee Sensor Based on Embedding Pancake Graphs","year":2012,"lang":"en","type":"article","venue":"Network and Communication Technologies","topic":"Interconnection Networks and Systems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Wireless sensor network; Topology control; Hypercube; NeuRFon; Distributed computing; Network topology; Computer network; Embedding; Topology (electrical circuits); Scheduling (production processes); Wireless network; Logical topology; Key distribution in wireless sensor networks; Wireless; Parallel computing; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004903692,0.0001442264,0.0001914966,0.0001121002,0.0004460007,0.0001385664,0.0006669669,0.000192974,0.000002283481],"category_scores_gemma":[0.00003293376,0.0001273081,0.00005464966,0.0003759982,0.00009395197,0.0002737065,0.0001770934,0.0002131652,0.000003738537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002874461,"about_ca_system_score_gemma":0.00001668287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001175233,"about_ca_topic_score_gemma":0.000002612591,"domain_scores_codex":[0.9990135,0.00009588029,0.0002372676,0.0002298568,0.0001096519,0.0003138127],"domain_scores_gemma":[0.9984279,0.0002957571,0.000166578,0.001002323,0.00006448031,0.00004293732],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001642782,0.00003370846,0.001865734,0.00001811377,0.00001793677,5.269536e-8,0.0001532105,0.002803567,0.00002259965,0.6551861,0.008399596,0.3314829],"study_design_scores_gemma":[0.0006411975,0.0001341466,0.0003670162,0.0001423333,0.00001612628,0.00003072165,0.001618178,0.9183834,0.0003942998,0.0311895,0.04670428,0.0003788668],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002943066,0.001133795,0.9899752,0.001220562,0.0004112289,0.0003534371,0.000001038745,0.00101526,0.002946408],"genre_scores_gemma":[0.7294145,0.0002136421,0.2699842,0.000119205,0.00007222388,0.0000996836,0.000006877212,0.000008008498,0.00008168817],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9155798,"threshold_uncertainty_score":0.5191475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02396202903471166,"score_gpt":0.2537846073790579,"score_spread":0.2298225783443462,"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."}}