{"id":"W2578217697","doi":"10.1145/2899000","title":"Securely Reinforcing Synchronization for Embedded Online Contests","year":2017,"lang":"en","type":"article","venue":"ACM Transactions on Embedded Computing Systems","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Francis Xavier University","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Computer science; Eavesdropping; Computer security; CONTEST; Competitor analysis; Synchronization (alternating current); Asynchronous communication; Security analysis; Anonymity; Distributed computing; Computer network","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","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0007376272,0.0003135226,0.0003941238,0.0002374006,0.001751212,0.001257576,0.002395238,0.0001648978,0.000003102524],"category_scores_gemma":[0.0002741966,0.0003183412,0.0002322931,0.0002560755,0.00007926863,0.00109945,0.00006924571,0.0003328291,0.00001465878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008251196,"about_ca_system_score_gemma":0.000119614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000158861,"about_ca_topic_score_gemma":0.00007290563,"domain_scores_codex":[0.9977283,0.0001222333,0.0005869043,0.0007101453,0.0003712354,0.0004811788],"domain_scores_gemma":[0.9955955,0.0005766526,0.0005206641,0.002846351,0.0003052464,0.0001555893],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002340358,0.001312026,0.0003029661,0.001018871,0.0006629589,0.0000461882,0.01448058,0.3064002,0.001174752,0.394415,0.002060334,0.2778921],"study_design_scores_gemma":[0.001783091,0.0003537089,0.0003084273,0.0004860749,0.00004108822,0.0000613865,0.0004276714,0.99116,0.0005109766,0.002647951,0.001702674,0.0005169788],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01033827,0.00009699683,0.984946,0.0005373993,0.002341723,0.0007890121,0.0001057791,0.0005471654,0.0002976775],"genre_scores_gemma":[0.9004795,0.00001569811,0.09898095,0.0001840217,0.0001877349,0.0000357618,0.00005361607,0.00002764076,0.00003508772],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8901412,"threshold_uncertainty_score":0.9999269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03488650103070727,"score_gpt":0.3068612307702629,"score_spread":0.2719747297395556,"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."}}