{"id":"W2103752966","doi":"10.1109/wimob.2008.78","title":"Power-Efficient Clustering in Wireless Sensor Networks under Coverage Constraint","year":2008,"lang":"en","type":"article","venue":"","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Wireless sensor network; Computer science; Heuristic; Integer programming; Energy consumption; Routing (electronic design automation); Cluster analysis; Greedy algorithm; Key distribution in wireless sensor networks; Constraint (computer-aided design); Topology (electrical circuits); Linear programming; Distributed computing; Computer network; Wireless network; Wireless; Algorithm; Mathematics; 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":[0.0003234074,0.0003328648,0.0003719851,0.0002335812,0.0002146467,0.0001167885,0.0008583465,0.0001956686,0.00006501945],"category_scores_gemma":[0.00001352271,0.0003185598,0.0001173914,0.0008974598,0.000209529,0.0001776796,0.0004767182,0.0004295697,0.00004715113],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001928865,"about_ca_system_score_gemma":0.0000855481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006984581,"about_ca_topic_score_gemma":0.00006792642,"domain_scores_codex":[0.997147,0.0001526117,0.0005403523,0.0007866318,0.0004782434,0.0008952098],"domain_scores_gemma":[0.9984753,0.0002721011,0.0001248373,0.0008358131,0.00008031914,0.0002116587],"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":[0.000008059545,0.0001432789,0.0006760807,0.000003036365,0.000009574834,0.0003240288,0.0002533069,0.9692965,0.0001868734,0.02776319,0.0001264506,0.001209684],"study_design_scores_gemma":[0.0006982954,0.00004701532,0.003893015,0.00004468574,0.000001428622,0.0002898691,0.00006659208,0.9940827,0.0002699451,0.00002402764,0.0001702458,0.0004121341],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3367223,0.00005063682,0.6500774,0.000241527,0.0005820491,0.0001549374,5.631564e-7,0.0002879768,0.01188259],"genre_scores_gemma":[0.9869785,0.00005845357,0.01143228,0.0009570396,0.0000682851,0.00001118051,0.000002710421,0.00002900996,0.0004625457],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6502562,"threshold_uncertainty_score":0.9999266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01394772232818877,"score_gpt":0.2160827036261993,"score_spread":0.2021349812980105,"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."}}