{"id":"W158782428","doi":"10.1007/978-0-387-09441-0_7","title":"Extending Network Life by Using Mobile Actors in Cluster-based Wireless Sensor and Actor Networks","year":2008,"lang":"en","type":"book-chapter","venue":"","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Wireless sensor network; Energy consumption; Computer science; Cluster (spacecraft); Computer network; Resource (disambiguation); Energy (signal processing); Key distribution in wireless sensor networks; Distributed computing; Topology (electrical circuits); Position (finance); Resource consumption; Wireless; Wireless network; Telecommunications; Engineering; Mathematics; Electrical engineering; Business","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":[0.0004562189,0.0004156655,0.0002237884,0.0004921258,0.0004867783,0.001052237,0.000687591,0.0005935873,0.001948935],"category_scores_gemma":[0.0007817895,0.0002618538,0.0002954023,0.000911781,0.001102352,0.002673062,0.001116535,0.0009747437,0.001085864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004458349,"about_ca_system_score_gemma":0.0003993277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003640094,"about_ca_topic_score_gemma":0.0006961749,"domain_scores_codex":[0.9998106,0.00005802285,0.000008281122,0.00003967886,0.00006876218,0.00001464419],"domain_scores_gemma":[0.9997155,0.0001510681,0.00002032959,0.00005202575,0.00003084082,0.00003014065],"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":[0.00004856727,0.00004162296,0.00043668,0.0004146067,0.00002503937,0.0003029639,0.001150255,0.03070986,0.009023399,0.5744474,0.01535774,0.3680418],"study_design_scores_gemma":[0.00001405624,0.0001094917,0.0003364117,0.0002378422,0.00003844206,0.0009953354,0.0002656874,0.07713018,0.004888802,0.1978888,0.7180614,0.00003347004],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01829841,0.02026363,0.8131187,0.002667928,0.0008892851,0.0001089157,0.00004729004,0.0007522671,0.1438536],"genre_scores_gemma":[0.2652962,0.03827685,0.5985697,0.00095317,0.0008230148,0.0003037482,0.0001660587,0.0004197313,0.09519152],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001948935,"threshold_uncertainty_score":0.006519794,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01668187587391045,"score_gpt":0.2219428809943537,"score_spread":0.2052610051204433,"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."}}