{"meta":{"query_hash":"18f09df695c4","filters":{"venue":"Proceedings of the 17th International Conference on Availability, Reliability and Security"},"cohort_total":3,"direct_labels_cover":0,"predictions_cover":3,"exported":3,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/18f09df695c4","api":"https://metacan.xera.ac/api/v1/cohort?venue=Proceedings+of+the+17th+International+Conference+on+Availability%2C+Reliability+and+Security"},"results":[{"id":"W4298399705","doi":"10.1145/3538969.3544450","title":"Security of Social Networks: Lessons Learned on Twitter Bot Analysis in the Literature","year":2022,"lang":"en","type":"article","venue":"Proceedings of the 17th International Conference on Availability, Reliability and Security","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Disinformation; Misinformation; Computer science; Social media; Social network analysis; Data science; Microblogging; Social network (sociolinguistics); World Wide Web; Internet privacy; Computer security","score_opus":0.03674139946058441,"score_gpt":0.29501986659639307,"score_spread":0.25827846713580865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4298399705","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.967839,0.00003593401,0.000056032713,0.025297122,0.0003570626,0.00029500804,0.00006481968,0.000027846247,0.0060271877],"genre_scores_gemma":[0.99918896,0.00003167243,0.000036128888,0.00057419925,0.000053821725,0.00004080483,0.0000068527966,0.0000042992087,0.00006324146],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99754083,0.0002665696,0.00047396193,0.00062287174,0.0009011252,0.00019464165],"domain_scores_gemma":[0.9983962,0.00026651213,0.00036278414,0.00036962196,0.00056863856,0.00003621008],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028522823,0.00017923086,0.00031108633,0.00017759661,0.0003105408,0.00020277123,0.0016900597,0.00010492001,0.000087793785],"category_scores_gemma":[0.00053611305,0.00012714707,0.00025101536,0.0014066173,0.00024910973,0.0002699243,0.000732826,0.0009879743,8.264632e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000783722,0.0024684859,0.110658236,0.00025459917,0.00021653988,0.0000020352518,0.045662638,0.001073966,0.00048412918,0.8345062,0.0021900835,0.0016993305],"study_design_scores_gemma":[0.0008216607,0.0005178647,0.22782972,0.000084134655,0.00010689651,0.000010506573,0.001960765,0.14092684,0.0015460973,0.62408864,0.0017334297,0.00037341187],"about_ca_topic_score_codex":0.000094186114,"about_ca_topic_score_gemma":0.00004098862,"teacher_disagreement_score":0.21041757,"about_ca_system_score_codex":0.00012415834,"about_ca_system_score_gemma":0.00006256966,"threshold_uncertainty_score":0.51849073},"labels":[],"label_agreement":null},{"id":"W4301170153","doi":"10.1145/3538969.3544412","title":"Analysis and prediction of web proxies misbehavior","year":2022,"lang":"en","type":"article","venue":"Proceedings of the 17th International Conference on Availability, Reliability and Security","topic":"Internet Traffic Analysis and Secure E-voting","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Computer science; Leverage (statistics); The Internet; Proxy (statistics); World Wide Web; Server; Anonymity; Web content; Proxy server; Web server; Web analytics; Web development; Web application security; Computer security","score_opus":0.02004682605307545,"score_gpt":0.2467000942704499,"score_spread":0.22665326821737444,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4301170153","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.994917,0.000030473026,0.00023686304,0.0019909835,0.00019938925,0.00022002848,0.000120547986,0.000036187557,0.0022485708],"genre_scores_gemma":[0.9993187,0.000034831577,0.000383588,0.000056277953,0.000016820226,0.00002885609,0.000004998537,0.000004019117,0.0001519087],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99778926,0.00007642835,0.00059860066,0.00061403424,0.0007678641,0.0001538165],"domain_scores_gemma":[0.99829465,0.000099567245,0.00041837155,0.00021677585,0.0009095244,0.000061089544],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015051663,0.0001609258,0.0003514017,0.000183006,0.00020308873,0.00009906095,0.0009350318,0.00006026136,0.00014595258],"category_scores_gemma":[0.00039797506,0.00012865619,0.00021202909,0.00060694624,0.00033587456,0.0002807849,0.0011241826,0.00036445842,5.1178756e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000108890905,0.00077898917,0.4040639,0.0001869817,0.00030526088,4.131556e-7,0.0041824966,0.00017287661,0.0017086983,0.5871977,0.00017227001,0.001121487],"study_design_scores_gemma":[0.00047437003,0.00033297486,0.104892574,0.000043960375,0.00029011365,0.000012735851,0.0010605862,0.87575006,0.0036168504,0.012909663,0.00039786322,0.00021824425],"about_ca_topic_score_codex":0.000049491093,"about_ca_topic_score_gemma":0.00003299739,"teacher_disagreement_score":0.8755772,"about_ca_system_score_codex":0.000081473096,"about_ca_system_score_gemma":0.00008617674,"threshold_uncertainty_score":0.5246447},"labels":[],"label_agreement":null},{"id":"W4302602562","doi":"10.1145/3538969.3543788","title":"SAMM: Situation Awareness with Machine Learning for Misbehavior Detection in VANET","year":2022,"lang":"en","type":"article","venue":"Proceedings of the 17th International Conference on Availability, Reliability and Security","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Vehicular ad hoc network; Artificial intelligence; Machine learning; Telecommunications; Wireless ad hoc network; Wireless","score_opus":0.0171058685024525,"score_gpt":0.2379335088711036,"score_spread":0.2208276403686511,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4302602562","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9973448,0.000033277953,0.0001381024,0.0004952046,0.00028485124,0.0006289655,0.00006759249,0.00007711232,0.00093010254],"genre_scores_gemma":[0.9994547,0.000032746477,0.00014024581,0.000025804933,0.00002964345,0.00020769762,0.0000276665,0.000018405693,0.00006313854],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985667,0.000043965334,0.00035985836,0.00038825412,0.00043909752,0.0002021639],"domain_scores_gemma":[0.999172,0.00011995531,0.00012889634,0.00013343262,0.00039666222,0.0000490692],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010053786,0.00017827601,0.00022406649,0.00008252454,0.0001818683,0.000051422085,0.00031914524,0.0000728663,0.00009590423],"category_scores_gemma":[0.00033607002,0.00015469287,0.000066498775,0.00022180924,0.000111572874,0.00017822071,0.00017322839,0.0005963667,8.0944847e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016942128,0.00093369035,0.57390326,0.0011484408,0.00009751154,0.0000016188943,0.0034350625,0.3876587,0.015476942,0.008595366,0.00016618623,0.0068890215],"study_design_scores_gemma":[0.0009084859,0.00029457198,0.03336847,0.00006589187,0.000030195892,0.000016497153,0.00038880762,0.9391785,0.009579343,0.014785401,0.001142834,0.00024097606],"about_ca_topic_score_codex":0.000119756834,"about_ca_topic_score_gemma":0.0005216044,"teacher_disagreement_score":0.5515198,"about_ca_system_score_codex":0.0003092527,"about_ca_system_score_gemma":0.000050401155,"threshold_uncertainty_score":0.6308192},"labels":[],"label_agreement":null}]}