{"meta":{"query_hash":"460218ca1f9e","filters":{"venue":"2022 IEEE 19th International Conference on Mobile Ad Hoc and Smart Systems (MASS)"},"cohort_total":2,"direct_labels_cover":0,"predictions_cover":2,"exported":2,"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/460218ca1f9e","api":"https://metacan.xera.ac/api/v1/cohort?venue=2022+IEEE+19th+International+Conference+on+Mobile+Ad+Hoc+and+Smart+Systems+%28MASS%29"},"results":[{"id":"W4312579541","doi":"10.1109/mass56207.2022.00071","title":"PRE-SLAM: Persistence Reasoning in Edge-assisted Visual SLAM","year":2022,"lang":"en","type":"article","venue":"2022 IEEE 19th International Conference on Mobile Ad Hoc and Smart Systems (MASS)","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"National Science Foundation","keywords":"Computer science; Leverage (statistics); Enhanced Data Rates for GSM Evolution; Computer vision; Simultaneous localization and mapping; Artificial intelligence; Feature (linguistics); Filter (signal processing); Overhead (engineering); Mobile robot; Robot","score_opus":0.02350010394943466,"score_gpt":0.25176848298454857,"score_spread":0.2282683790351139,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312579541","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008909052,0.00013051656,0.986465,0.00013812762,0.000048977105,0.000032488148,0.00010835405,0.0031299763,0.0010375669],"genre_scores_gemma":[0.49925083,0.00022134783,0.49655673,0.00033048456,0.00012425361,0.00011287296,0.00067416334,0.0004982963,0.0022309662],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990772,0.00010824233,0.00006467675,0.0002628146,0.0003437917,0.00014324376],"domain_scores_gemma":[0.9984425,0.0004356421,0.0001736543,0.00051518163,0.00034290817,0.00009018187],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010172093,0.00082055974,0.00082520285,0.00074688543,0.0008909921,0.0017454969,0.003176206,0.0011208843,0.0026556032],"category_scores_gemma":[0.0033411423,0.0006028705,0.0006980963,0.0009926306,0.0010262091,0.0033148464,0.003214763,0.002385233,0.00075762067],"study_design_candidate":"bench_or_experimental","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":[0.00050368026,0.00022331798,0.0046773204,0.00028603093,0.00012393498,0.00035326136,0.00044799826,0.45550326,0.022480259,0.017141132,0.013819967,0.48443985],"study_design_scores_gemma":[0.000032801432,0.00006222921,0.00067687454,0.000017286195,0.000015608497,0.000067945984,0.00007397982,0.9758691,0.007211084,0.011339641,0.004605103,0.000028332317],"about_ca_topic_score_codex":0.007682451,"about_ca_topic_score_gemma":0.010349713,"teacher_disagreement_score":0.007682451,"about_ca_system_score_codex":0.00057791127,"about_ca_system_score_gemma":0.0013852193,"threshold_uncertainty_score":0.015275478},"labels":[],"label_agreement":null},{"id":"W4312998458","doi":"10.1109/mass56207.2022.00070","title":"An Accurate and Energy-Efficient Anomaly Detection in Edge-Cloud Networks","year":2022,"lang":"en","type":"article","venue":"2022 IEEE 19th International Conference on Mobile Ad Hoc and Smart Systems (MASS)","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","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":"Ontario Tech University","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Cloud computing; Computer science; Anomaly detection; Anomaly (physics); Enhanced Data Rates for GSM Evolution; Boundary (topology); Data mining; Edge computing; Artificial intelligence; Mathematics","score_opus":0.016857927010611302,"score_gpt":0.2559509576161777,"score_spread":0.2390930306055664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312998458","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06687376,0.00045938962,0.9301701,0.00017042086,0.0000783789,0.00005481365,0.0001639015,0.0007615186,0.0012676873],"genre_scores_gemma":[0.76002526,0.00044390743,0.23748286,0.00013320168,0.000050337316,0.0000589722,0.00054367905,0.00006681215,0.0011949298],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99942005,0.00006825885,0.000027078777,0.00014692762,0.00024517765,0.00009254148],"domain_scores_gemma":[0.99938893,0.00016910562,0.00009078518,0.00009367899,0.00021611969,0.00004136167],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043153728,0.0007076184,0.0007707499,0.0007639348,0.0006795028,0.0008991898,0.0017546746,0.00061792077,0.00036630922],"category_scores_gemma":[0.0018017164,0.00023237799,0.00052710925,0.0010320039,0.00040125183,0.001600472,0.0011604114,0.0007613371,0.0001888176],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005956543,0.00017382568,0.01106674,0.00013033328,0.00006795242,0.000677695,0.00024124104,0.5991654,0.036922395,0.008384593,0.0050858064,0.33748844],"study_design_scores_gemma":[0.0000029318019,0.000016461161,0.0005443149,0.0000031928464,0.000004427062,0.00006743273,0.000030480956,0.99431956,0.003230164,0.0012883767,0.0004870486,0.00000556828],"about_ca_topic_score_codex":0.009266354,"about_ca_topic_score_gemma":0.00674924,"teacher_disagreement_score":0.009266354,"about_ca_system_score_codex":0.000697936,"about_ca_system_score_gemma":0.0007510884,"threshold_uncertainty_score":0.018424809},"labels":[],"label_agreement":null}]}