{"id":"W2067258979","doi":"10.1109/iwcmc.2013.6583650","title":"Reciprocal public sensing for integrated RFID-Sensor Networks","year":2013,"lang":"en","type":"article","venue":"","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Reciprocal; Wireless sensor network; Network packet; Scheme (mathematics); Data exchange; Cloud computing; Computer network; Energy consumption; Distributed computing; Real-time computing; Database; 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":[],"consensus_categories":[],"category_scores_codex":[0.0003051988,0.0002676606,0.000271683,0.0001575563,0.0002398191,0.000742583,0.000815879,0.000207598,0.00006525331],"category_scores_gemma":[0.0001301804,0.0002173431,0.0001303553,0.0008595411,0.00007940517,0.0006575752,0.0002250347,0.0002556097,0.0001114449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000837558,"about_ca_system_score_gemma":0.00005068813,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001189113,"about_ca_topic_score_gemma":0.00004883882,"domain_scores_codex":[0.9977194,0.0001015949,0.0003939532,0.0006639729,0.0002564977,0.0008645572],"domain_scores_gemma":[0.9978903,0.0004379261,0.0001161666,0.0007642064,0.0005318103,0.0002596248],"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":[0.00001237126,0.0001445274,0.0002548771,0.00001361842,0.00007100944,0.00001285141,0.0001616547,0.2046658,0.001148732,0.1232289,0.04373353,0.6265522],"study_design_scores_gemma":[0.0003094611,0.00006285356,0.0001328918,0.00001864824,0.000003468164,0.00002172188,0.00004974728,0.9830535,0.0005573137,0.000342292,0.01514676,0.0003013204],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01252844,0.00007083861,0.978246,0.002761098,0.001002508,0.00049212,5.188718e-7,0.0008451175,0.004053389],"genre_scores_gemma":[0.5908028,0.00001081037,0.4050467,0.001403873,0.0002658062,0.00003259974,0.00001412349,0.00003228248,0.002390987],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7783878,"threshold_uncertainty_score":0.8862996,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0190046864908466,"score_gpt":0.2212116305598478,"score_spread":0.2022069440690012,"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."}}