{"id":"W1965663463","doi":"10.1109/wimob.2010.5644982","title":"A lightweight dynamic optimization methodology for wireless sensor networks","year":2010,"lang":"en","type":"article","venue":"","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Wireless sensor network; Computer science; Reliability (semiconductor); Node (physics); Wireless; Sensor node; State (computer science); Resource allocation; Task (project management); Key distribution in wireless sensor networks; Real-time computing; Distributed computing; Embedded system; Wireless network; Engineering; Computer network; Telecommunications","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0006642375,0.000241431,0.0003050692,0.0001565215,0.0002165835,0.0001554206,0.0009793765,0.0003312677,0.00004414292],"category_scores_gemma":[0.00008195397,0.0002110608,0.00013111,0.0005052065,0.00008316669,0.0002659783,0.000198304,0.0003385411,0.0000101793],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002737731,"about_ca_system_score_gemma":0.00004069445,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001258328,"about_ca_topic_score_gemma":0.0001200766,"domain_scores_codex":[0.9980251,0.0001654512,0.0003513568,0.0006801801,0.0001835984,0.0005943202],"domain_scores_gemma":[0.9976315,0.0009878052,0.0001550738,0.0008581917,0.000215826,0.0001516117],"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":[0.00001048862,0.00004498048,0.00002396618,0.000004563434,0.00001640085,0.00000371761,0.0000521088,0.8750474,0.002137198,0.1093943,0.0003344102,0.01293045],"study_design_scores_gemma":[0.0003815298,0.00005687371,0.00003452722,0.000005736875,0.00001009306,0.00003414585,0.000007211365,0.9950893,0.001790234,0.0002803993,0.002028173,0.0002817954],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006882648,0.00003345869,0.9870308,0.001109039,0.002698439,0.000332344,0.000001180554,0.0005696607,0.001342401],"genre_scores_gemma":[0.1719335,0.00002136113,0.8260261,0.0004720503,0.000211536,0.00005288893,0.00001712169,0.0000309388,0.001234423],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1650509,"threshold_uncertainty_score":0.8606811,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01762749415070963,"score_gpt":0.2665603285066394,"score_spread":0.2489328343559298,"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."}}