{"id":"W2093827238","doi":"10.1016/j.procs.2014.07.073","title":"Determining Fuzzy Link Quality Membership Functions in Wireless Sensor Networks","year":2014,"lang":"en","type":"article","venue":"Procedia Computer Science","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Computer science; Link (geometry); Wireless sensor network; Fuzzy logic; Quality (philosophy); Wireless; Computer network; Data mining; Artificial intelligence; Telecommunications","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":[0.002546986,0.00041938,0.0003587941,0.0009680727,0.0004154724,0.0007362174,0.000601156,0.0006613652,0.000371661],"category_scores_gemma":[0.01171172,0.0002728348,0.0003178574,0.0004129703,0.0005852004,0.0008460343,0.0004364773,0.0004674138,0.00009191611],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007248306,"about_ca_system_score_gemma":0.0003077102,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001650721,"about_ca_topic_score_gemma":0.001056744,"domain_scores_codex":[0.9991385,0.0002466108,0.00004392213,0.0001100029,0.0004007591,0.00006014457],"domain_scores_gemma":[0.996066,0.002762548,0.0003240385,0.000192161,0.0005950853,0.00006007581],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000208078,0.0001205975,0.003450916,0.00009584409,0.00003553541,0.0001075265,0.0002793046,0.8715245,0.02947266,0.005131787,0.0001528383,0.08942046],"study_design_scores_gemma":[0.000006291661,0.0000501356,0.0008057947,0.000008140802,0.000005250396,0.00002590154,0.00003072826,0.9882221,0.008972657,0.001756451,0.0001053915,0.00001118091],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2323396,0.0001097927,0.7666071,0.00004695788,0.000009514732,0.00004554227,0.0000156496,0.0002138687,0.0006119777],"genre_scores_gemma":[0.9176196,0.00005192833,0.08206472,0.00001327469,0.000003909857,0.00003683696,0.00002444782,0.00001260034,0.0001726109],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002546986,"threshold_uncertainty_score":0.01346987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02021399265694943,"score_gpt":0.2542004213519967,"score_spread":0.2339864286950473,"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."}}