{"id":"W2104265766","doi":"10.1109/ccnc.2009.4784896","title":"A Distributed Energy-Efficient Cluster Formation Protocol for Wireless Sensor Networks","year":2009,"lang":"en","type":"article","venue":"","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Wireless sensor network; Computer science; Cluster analysis; Energy consumption; Computer network; Routing protocol; Distributed computing; Bandwidth (computing); Efficient energy use; Distributed algorithm; Routing (electronic design automation); Engineering","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":[0.0003356678,0.0003279291,0.0002914578,0.0001357309,0.0003003852,0.0003315765,0.0008530251,0.0001994686,0.000008349135],"category_scores_gemma":[0.00002052915,0.0002740028,0.0001773928,0.0007077117,0.00003808955,0.0003857123,0.0001378856,0.0001477642,0.000007709221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001358956,"about_ca_system_score_gemma":0.00003662339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007047096,"about_ca_topic_score_gemma":0.00001035736,"domain_scores_codex":[0.9975132,0.0001073555,0.0005729873,0.0006063657,0.000407284,0.0007928446],"domain_scores_gemma":[0.9983151,0.0001880127,0.0002431721,0.0007859549,0.0002734086,0.000194354],"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":[0.00006406914,0.0002215591,0.000003746117,0.00001095936,0.000006750955,0.000003356026,0.00005038063,0.888283,0.0001054388,0.07949819,0.007327442,0.02442509],"study_design_scores_gemma":[0.001622538,0.0002236817,0.00006268943,0.00004953295,0.000004959362,0.00002151415,0.00001069947,0.9782729,0.002296851,0.0002288833,0.01683536,0.0003703933],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0003474103,0.000003332172,0.9587571,0.001271311,0.0001866511,0.03749966,0.000004074329,0.0006580397,0.001272395],"genre_scores_gemma":[0.6858258,0.000001999777,0.1324602,0.004862989,0.0006754996,0.1748783,0.0001413311,0.00005734396,0.001096549],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.826297,"threshold_uncertainty_score":0.9999712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01400886536188783,"score_gpt":0.2563385913182232,"score_spread":0.2423297259563354,"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."}}