{"id":"W2025679903","doi":"10.1109/isspit.2007.4458206","title":"Placement of multiple mobile base stations in wireless sensor networks","year":2007,"lang":"en","type":"article","venue":"","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Base station; Wireless sensor network; Computer science; Computer network; Integer programming; Efficient energy use; Routing protocol; Key distribution in wireless sensor networks; Routing (electronic design automation); Solver; Network topology; Base (topology); Energy (signal processing); Energy consumption; Linear programming; Distributed computing; Wireless; Wireless network; Engineering; Telecommunications; Electrical engineering; Algorithm; Mathematics","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":[0.001070701,0.00154339,0.0008335408,0.0005462952,0.001189459,0.0008350303,0.00202894,0.001832162,0.001195422],"category_scores_gemma":[0.002964272,0.0008590909,0.0005970986,0.001338691,0.001292327,0.0014829,0.001124391,0.000998743,0.0007022654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006921745,"about_ca_system_score_gemma":0.0007961828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002493575,"about_ca_topic_score_gemma":0.002164792,"domain_scores_codex":[0.998691,0.0005280374,0.00006224926,0.0003086098,0.0003147314,0.00009527303],"domain_scores_gemma":[0.9991834,0.0003583005,0.0002023573,0.0001149826,0.00008759726,0.00005347742],"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":[0.0001880086,0.000086985,0.001380349,0.0003208686,0.00005262049,0.0006005389,0.0001871917,0.8703215,0.01190391,0.01490937,0.001683876,0.0983648],"study_design_scores_gemma":[0.00005118836,0.0004055503,0.0003428002,0.00004667942,0.00005587296,0.0003817233,0.000135304,0.9677784,0.007687435,0.01300278,0.01008228,0.00002986776],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02142816,0.001361799,0.9735415,0.0002798538,0.0001627467,0.0001801624,0.00003572684,0.0005098691,0.002500198],"genre_scores_gemma":[0.4775832,0.002235562,0.5158346,0.0002198926,0.0002390872,0.0003433121,0.000160068,0.00009768898,0.003286507],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002493575,"threshold_uncertainty_score":0.005662441,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01088397290249143,"score_gpt":0.2398316594448565,"score_spread":0.228947686542365,"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."}}