{"id":"W2040429377","doi":"10.1002/wcm.1000","title":"MAX–MIN aggregation in wireless sensor networks: mechanism and modeling","year":2010,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Data aggregator; Computer science; Wireless sensor network; Aggregate (composite); Redundancy (engineering); Data redundancy; Function (biology); Computer network; Distributed computing","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":[0.003072018,0.001064103,0.001021045,0.001046003,0.0006821547,0.001943001,0.00238268,0.001610928,0.001974398],"category_scores_gemma":[0.004623925,0.0008129649,0.0009913429,0.001813257,0.001515986,0.003583436,0.001252753,0.001337046,0.000495267],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001594579,"about_ca_system_score_gemma":0.0009797189,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003182113,"about_ca_topic_score_gemma":0.002006019,"domain_scores_codex":[0.9989331,0.0004402197,0.00006051824,0.0001581833,0.0003028527,0.0001051694],"domain_scores_gemma":[0.9977227,0.001374352,0.000377068,0.0001602429,0.0003043287,0.00006134252],"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":[0.00004715428,0.00004040696,0.0004639487,0.00009180723,0.0000316325,0.00008400004,0.00009336146,0.8769689,0.001102254,0.1104117,0.001197565,0.009467284],"study_design_scores_gemma":[0.000004007492,0.00001444223,0.00005939333,0.000007165169,0.000006568304,0.00002423439,0.000007126428,0.9807344,0.0001759068,0.0181824,0.0007783844,0.00000589596],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01382719,0.002352692,0.9766633,0.0006714972,0.0001079823,0.00007767435,0.00008471408,0.0001859086,0.006028929],"genre_scores_gemma":[0.8395658,0.007294947,0.1393647,0.0003064038,0.0004480317,0.0006179034,0.0001678655,0.0001190223,0.0121153],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003182113,"threshold_uncertainty_score":0.01624662,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01608516159875224,"score_gpt":0.2521895445194763,"score_spread":0.2361043829207241,"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."}}