{"id":"W2028642863","doi":"10.5539/cis.v2n4p89","title":"Enhancement of Hierarchy Cluster-Tree Routing for Wireless Sensor Network","year":2009,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Wireless sensor network; Energy consumption; Cluster analysis; Computer network; Routing protocol; Hierarchical routing; Cluster (spacecraft); Hierarchy; Tree (set theory); Routing (electronic design automation); Energy (signal processing); Distributed computing; Wireless Routing Protocol; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004743399,0.0002737546,0.0001960802,0.0004297542,0.0003382531,0.0003664769,0.0006074894,0.0003401278,0.0008010185],"category_scores_gemma":[0.001107201,0.0001193707,0.000261614,0.0009010419,0.0002442882,0.0008838628,0.0005108563,0.0004379272,0.0003197092],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004777129,"about_ca_system_score_gemma":0.0006487052,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002149223,"about_ca_topic_score_gemma":0.002839167,"domain_scores_codex":[0.9995876,0.00009373693,0.0000208566,0.00004184514,0.0002169994,0.0000389686],"domain_scores_gemma":[0.999602,0.0001016022,0.00005272447,0.00005099248,0.0001703064,0.00002247636],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001825918,0.00009969819,0.002581298,0.0008355221,0.0001081047,0.0002556583,0.0003097552,0.1075825,0.07118017,0.07715083,0.01952698,0.7201869],"study_design_scores_gemma":[0.00006468981,0.0006495381,0.004095463,0.00009230526,0.0001749906,0.001497113,0.0001949681,0.6905702,0.05462356,0.04808342,0.1998573,0.00009635014],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02960609,0.007739183,0.9473949,0.001165918,0.000288683,0.0001535722,0.0001453559,0.001331501,0.01217473],"genre_scores_gemma":[0.5961152,0.007907741,0.3860931,0.0004765661,0.0002413274,0.0001548898,0.0005063345,0.0001402616,0.008364582],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002149223,"threshold_uncertainty_score":0.004273415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009373995298222845,"score_gpt":0.2344902169936875,"score_spread":0.2251162216954647,"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."}}