{"id":"W3084328393","doi":"10.1109/access.2020.3022569","title":"Eliciting Truthful Data From Crowdsourced Wireless Monitoring Modules in Cloud Managed Networks","year":2020,"lang":"en","type":"article","venue":"IEEE Access","topic":"Mobile Crowdsensing and Crowdsourcing","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Infotech Oulu; Academy of Finland","keywords":"Computer science; Crowdsourcing; Cloud computing; Wireless; Payment; Data collection; Metric (unit); Key (lock); Computer network; Data mining; Computer security; Telecommunications; World Wide Web","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":[0.00945752,0.0008901305,0.001056071,0.0006661955,0.001027662,0.002030946,0.002274209,0.001624298,0.00110776],"category_scores_gemma":[0.03634649,0.0005989096,0.0004492131,0.00107967,0.001606317,0.002408315,0.002752436,0.001339682,0.0002770905],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00209795,"about_ca_system_score_gemma":0.001981156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003464681,"about_ca_topic_score_gemma":0.004006001,"domain_scores_codex":[0.9918391,0.004290248,0.0004125364,0.00124463,0.001622773,0.0005907721],"domain_scores_gemma":[0.9723025,0.01727189,0.003850549,0.003740805,0.00189228,0.000941952],"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":[0.001617834,0.0005302872,0.01931388,0.0004048642,0.0001917273,0.0007966392,0.001499342,0.7270781,0.01914999,0.0693208,0.003831249,0.1562652],"study_design_scores_gemma":[0.00006121342,0.0001573348,0.002254754,0.00003310231,0.00002037706,0.00007807431,0.0002643037,0.9442374,0.00544405,0.0459444,0.001469784,0.00003508673],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1891073,0.0001875356,0.8035873,0.001559092,0.0000724358,0.0004123713,0.0003467707,0.0005396071,0.004187536],"genre_scores_gemma":[0.9515179,0.00004980162,0.04707213,0.0001544794,0.00002775081,0.0001311071,0.00009202105,0.00002680411,0.0009280074],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00945752,"threshold_uncertainty_score":0.0500167,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08521545187985106,"score_gpt":0.3006890594212276,"score_spread":0.2154736075413765,"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."}}