{"id":"W4317781640","doi":"10.1109/bigdata55660.2022.10020852","title":"The Lannion report on Big Data and Security Monitoring Research","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Conference on Big Data (Big Data)","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bell (Canada)","funders":"Engineering and Physical Sciences Research Council; Institut national de recherche en informatique et en automatique (INRIA)","keywords":"Big data; Computer science; Data science; Analytics; Data management; Computer security; Computation; Data mining","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":["sts","scholarly_communication","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.006323639,0.0002257379,0.0001910974,0.0003004352,0.001626937,0.001174352,0.01452562,0.00007633848,0.00006749957],"category_scores_gemma":[0.0008471241,0.0001981631,0.00002343361,0.0006375522,0.0001815482,0.001289463,0.02098801,0.001513417,0.00006459544],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001625718,"about_ca_system_score_gemma":0.0003432218,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005850984,"about_ca_topic_score_gemma":0.0005129561,"domain_scores_codex":[0.9939569,0.0006606187,0.0005108489,0.001872155,0.002542232,0.0004571989],"domain_scores_gemma":[0.9909055,0.0006305561,0.0002767557,0.007760413,0.0002791932,0.0001476327],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000231484,0.0002663766,0.0004857028,0.00001286551,0.00009857707,0.0003303636,0.000265541,0.00003231722,0.0005937731,0.01908787,0.1940445,0.7845506],"study_design_scores_gemma":[0.0003458173,0.0002315394,0.000653927,0.00007188039,0.000007645434,0.0001960701,0.0002702376,0.1952924,0.0003590492,0.00557441,0.7967233,0.0002737304],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"editorial","genre_gemma":"empirical","genre_scores_codex":[0.3060119,0.002794597,0.1062693,0.1100787,0.3350344,0.004638353,0.08207164,0.001601193,0.05149991],"genre_scores_gemma":[0.9832289,0.001971796,0.0002174133,0.0002532153,0.004444456,0.00005744135,0.009040474,0.00002121113,0.0007650642],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7842768,"threshold_uncertainty_score":0.9998626,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4622280971601727,"score_gpt":0.414755484398714,"score_spread":0.0474726127614587,"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."}}