{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007486964,0.0002648027,0.0003278512,0.0002315708,0.0006074163,0.0003228283,0.001230286,0.0002050944,0.00000127345],"category_scores_gemma":[0.00001834579,0.0002853019,0.00004519481,0.0005712584,0.00017178,0.0003245816,0.001602101,0.0007982235,0.000001752078],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003361256,"about_ca_system_score_gemma":0.00003649148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001900665,"about_ca_topic_score_gemma":0.0003500971,"domain_scores_codex":[0.9980159,0.0002112514,0.0005321251,0.0005850696,0.0001918764,0.0004637848],"domain_scores_gemma":[0.9973734,0.0004571668,0.0001959097,0.001693133,0.0001319255,0.0001484736],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000005330124,0.0001909126,0.001477731,0.00002983104,0.00001851118,0.00000846825,0.001910439,0.2913277,0.004274664,0.265209,0.000004767192,0.4355426],"study_design_scores_gemma":[0.0003830703,0.00003026381,0.0001688114,0.0001413273,0.000006035016,0.00004807715,0.0002084001,0.9977577,0.0001652048,0.0006226574,0.0001582993,0.0003101965],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5881832,0.0005631309,0.4103838,0.0001809296,0.0001831991,0.0002208121,7.15825e-7,0.0001510166,0.0001331822],"genre_scores_gemma":[0.9228904,0.001319534,0.07551675,0.00009971236,0.00007028451,0.00004555817,0.00001314841,0.00002845922,0.00001621299],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.70643,"threshold_uncertainty_score":0.9999599,"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."}}