{"meta":{"query_hash":"d4ac5bce7033","filters":{"venue":"2018 Annual IEEE International Systems Conference (SysCon)"},"cohort_total":12,"direct_labels_cover":0,"predictions_cover":12,"exported":12,"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/d4ac5bce7033","api":"https://metacan.xera.ac/api/v1/cohort?venue=2018+Annual+IEEE+International+Systems+Conference+%28SysCon%29"},"results":[{"id":"W2805269058","doi":"10.1109/syscon.2018.8369613","title":"High latency cause detection using multilevel dynamic analysis","year":2018,"lang":"en","type":"article","venue":"2018 Annual IEEE International Systems Conference (SysCon)","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; User space; Latency (audio); Synchronizing; Root cause; Interrupt; System call; Tracing; Operating system; Distributed computing; Address space; Kernel (algebra); Embedded system; Real-time computing; Reliability engineering","score_opus":0.035663074553681284,"score_gpt":0.30523724556070264,"score_spread":0.26957417100702136,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2805269058","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":[0.18106623,0.00074614177,0.79578906,0.00036115345,0.000055184595,0.00028876303,0.001213957,0.016556054,0.0039234073],"genre_scores_gemma":[0.7608372,0.00021817385,0.2349208,0.00012540206,0.000043085387,0.00028598364,0.0010431786,0.0006256019,0.0019005741],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978776,0.0002616795,0.00014309974,0.00046978355,0.000992191,0.0002556908],"domain_scores_gemma":[0.9935735,0.0027159154,0.001120403,0.00094463344,0.0014122056,0.00023336051],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011910746,0.0010899839,0.000796613,0.007875928,0.0009943584,0.0018436366,0.0013045216,0.0006322857,0.0024209437],"category_scores_gemma":[0.007640952,0.0005733802,0.0010530666,0.0031188694,0.0005934363,0.001731734,0.0022355926,0.0011452994,0.00059904694],"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":[0.0005924306,0.0006479795,0.16731828,0.00068739016,0.0005377918,0.0014360743,0.0025527957,0.118235536,0.08217829,0.019190438,0.007869105,0.5987539],"study_design_scores_gemma":[0.000035597506,0.00020893481,0.027924875,0.000067790534,0.00020880037,0.00048447825,0.00044535965,0.9185041,0.027354605,0.017950479,0.0067127896,0.000102184495],"about_ca_topic_score_codex":0.010408575,"about_ca_topic_score_gemma":0.011078292,"teacher_disagreement_score":0.010408575,"about_ca_system_score_codex":0.0011745559,"about_ca_system_score_gemma":0.0022352864,"threshold_uncertainty_score":0.020695984},"labels":[],"label_agreement":null},{"id":"W2805423212","doi":"10.1109/syscon.2018.8369500","title":"Integration of artificial intelligence in an injection molding process for on-line process parameter adjustment","year":2018,"lang":"en","type":"article","venue":"2018 Annual IEEE International Systems Conference (SysCon)","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":25,"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 New Brunswick","funders":"","keywords":"Adaptability; Process (computing); Cloud computing; Computer science; Controller (irrigation); Artificial intelligence; Big data; Molding (decorative); Assembly line; Factory (object-oriented programming); Industrial Revolution; Process control; Manufacturing engineering; Industrial engineering; Machine learning; Control engineering; Engineering; Mechanical engineering; Data mining; Operating system","score_opus":0.10621732674454341,"score_gpt":0.3546920538956369,"score_spread":0.24847472715109348,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2805423212","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":[0.19793569,0.0008451853,0.7808459,0.00050053705,0.0002027901,0.00029372852,0.00014622688,0.0038098232,0.015420142],"genre_scores_gemma":[0.90894175,0.00020457077,0.08876922,0.00007459065,0.00002075088,0.00005145452,0.00006491936,0.00005589449,0.0018167774],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995814,0.000063162435,0.0000295823,0.00008544035,0.00020843236,0.000031994638],"domain_scores_gemma":[0.9994542,0.00026104698,0.00008187577,0.00009119331,0.000094551884,0.000017088112],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050437875,0.00045263505,0.0004184649,0.00053449743,0.0003558989,0.0010144782,0.0007420382,0.0005146941,0.0015390598],"category_scores_gemma":[0.0010865207,0.0002412144,0.00039565854,0.00046396576,0.00038837123,0.0006399884,0.00048718494,0.0006554514,0.00029899826],"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":[0.00083275203,0.000755206,0.0043807346,0.0005033686,0.00008135256,0.0007548269,0.00038721782,0.25795496,0.28463897,0.0056413603,0.001268312,0.442801],"study_design_scores_gemma":[0.000023942253,0.00049407827,0.0020735192,0.00002920581,0.000040734445,0.00016726705,0.000037600734,0.8469411,0.14306466,0.0020693575,0.0050259354,0.000032493743],"about_ca_topic_score_codex":0.0010355173,"about_ca_topic_score_gemma":0.0014207256,"teacher_disagreement_score":0.0015390598,"about_ca_system_score_codex":0.00040428643,"about_ca_system_score_gemma":0.00054433255,"threshold_uncertainty_score":0.005148649},"labels":[],"label_agreement":null},{"id":"W2805620467","doi":"10.1109/syscon.2018.8369523","title":"A robust adaptive control scheme for under-actuated non-linear systems","year":2018,"lang":"en","type":"article","venue":"2018 Annual IEEE International Systems Conference (SysCon)","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada; New Brunswick Innovation Foundation","keywords":"Inverted pendulum; Control theory (sociology); Adaptive control; Computer science; Robust control; Scheme (mathematics); Mobile robot; Control engineering; Linear system; Control system; Planar; Robustness (evolution); Control (management); Robot; Engineering; Nonlinear system; Mathematics; Artificial intelligence","score_opus":0.06829300103698431,"score_gpt":0.279702432451006,"score_spread":0.2114094314140217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2805620467","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":[0.012402281,0.0002743377,0.984584,0.00007611249,0.000101763355,0.000043803786,0.000019566589,0.00040481315,0.0020932932],"genre_scores_gemma":[0.9172506,0.0003446675,0.076191545,0.0001029986,0.00011472652,0.00021632311,0.00007459938,0.000037465878,0.005667161],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997167,0.000046681642,0.000026284506,0.00007077413,0.00010702556,0.00003249705],"domain_scores_gemma":[0.9997768,0.00006049315,0.000052704523,0.00002470713,0.0000717976,0.0000135442415],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043461248,0.00066613546,0.00055383204,0.00021277898,0.00030955367,0.0006119673,0.00095750927,0.0004996805,0.0018402027],"category_scores_gemma":[0.0006792157,0.00019221503,0.00033295073,0.00021641691,0.0004527455,0.00042587242,0.00069535075,0.0009372396,0.00032249553],"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":[0.00022205028,0.00005732314,0.00032473696,0.0004281636,0.00009136508,0.00035680062,0.00028283114,0.68152636,0.10062199,0.02451881,0.001691245,0.1898783],"study_design_scores_gemma":[0.00002041954,0.00018021547,0.00014191255,0.000009456196,0.000013867719,0.000032949225,0.0000061391493,0.99342865,0.003223714,0.0011821531,0.0017497927,0.000010843619],"about_ca_topic_score_codex":0.0023424702,"about_ca_topic_score_gemma":0.001729924,"teacher_disagreement_score":0.0023424702,"about_ca_system_score_codex":0.00026324784,"about_ca_system_score_gemma":0.0005268548,"threshold_uncertainty_score":0.006156087},"labels":[],"label_agreement":null},{"id":"W2805646502","doi":"10.1109/syscon.2018.8369536","title":"Applying expectation-maximization evaluation on approximate optimal control","year":2018,"lang":"en","type":"article","venue":"2018 Annual IEEE International Systems Conference (SysCon)","topic":"Adaptive Dynamic Programming Control","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 New Brunswick","funders":"","keywords":"Maximization; Iterative learning control; Reinforcement learning; Computer science; Frame (networking); Optimal control; Trajectory; Convergence (economics); Tracking (education); Task (project management); Generator (circuit theory); Artificial intelligence; Mathematical optimization; Expectation–maximization algorithm; Control theory (sociology); Control (management); Mathematics; Power (physics); Engineering; Maximum likelihood","score_opus":0.035015107107010036,"score_gpt":0.3010516916635031,"score_spread":0.26603658455649304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2805646502","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003003718,0.000117103744,0.99545646,0.000106902124,0.000014787474,0.00002203386,0.0000069170546,0.00010267068,0.0011694499],"genre_scores_gemma":[0.6522849,0.0003745944,0.34236157,0.00030932124,0.00010985279,0.00035696628,0.0001233919,0.0002594492,0.0038198899],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99737823,0.0015936574,0.00011177435,0.00024523906,0.00051352323,0.00015760276],"domain_scores_gemma":[0.99471927,0.003972937,0.00024122313,0.00027484907,0.000684206,0.00010748587],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0072863903,0.0014006364,0.0019431832,0.0008148231,0.00043765677,0.0015633203,0.0015960627,0.0016076326,0.002412819],"category_scores_gemma":[0.017570024,0.00068117597,0.0006232713,0.0007458812,0.00193935,0.0020499278,0.0019849874,0.0016028419,0.00041581076],"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":[0.000060860908,0.000027580349,0.0002266774,0.00007600855,0.000034428554,0.00003415281,0.000046719568,0.9354173,0.00049430685,0.042474907,0.00043257538,0.02067456],"study_design_scores_gemma":[0.0000036701206,0.00001696728,0.000019043468,0.000006829279,0.0000020818472,0.0000044293083,0.000002400693,0.9924825,0.00016607434,0.0071590953,0.00013407707,0.0000027663816],"about_ca_topic_score_codex":0.004090538,"about_ca_topic_score_gemma":0.0022068773,"teacher_disagreement_score":0.0072863903,"about_ca_system_score_codex":0.0019804442,"about_ca_system_score_gemma":0.0016267534,"threshold_uncertainty_score":0.038534522},"labels":[],"label_agreement":null},{"id":"W2805872043","doi":"10.1109/syscon.2018.8369499","title":"Out-of-sample mapping of a two-link robotic manipulator","year":2018,"lang":"en","type":"article","venue":"2018 Annual IEEE International Systems Conference (SysCon)","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":1,"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 New Brunswick","funders":"","keywords":"Dimension (graph theory); Link (geometry); Extension (predicate logic); Artificial neural network; Computer science; Sample (material); Set (abstract data type); MIMO; Identification (biology); Manifold (fluid mechanics); Robot; Manipulator (device); Control theory (sociology); Artificial intelligence; Algorithm; Control (management); Mathematics; Engineering","score_opus":0.04349244217157956,"score_gpt":0.28042245411914024,"score_spread":0.2369300119475607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2805872043","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":[0.33932903,0.000060326485,0.6558448,0.00012202788,0.000031153228,0.00010868962,0.0000712666,0.00130978,0.0031229039],"genre_scores_gemma":[0.92192554,0.000017617116,0.07687709,0.000013621762,0.0000043823447,0.00004965358,0.00006636555,0.000031740703,0.0010139231],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99980503,0.000062250154,0.000009481479,0.00003401087,0.00007219994,0.000017015454],"domain_scores_gemma":[0.9992176,0.00038272463,0.00008718488,0.00014804307,0.00013685742,0.000027562282],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005122962,0.00057400187,0.00034197886,0.00028420237,0.00034161244,0.00033884082,0.00046631857,0.000400424,0.0019436642],"category_scores_gemma":[0.0019458502,0.00024095096,0.00029605476,0.00019988992,0.0003445612,0.00051212293,0.0005114565,0.0005535748,0.00020738953],"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":[0.00043714765,0.00018460055,0.002550739,0.00016472461,0.000042756004,0.00029066193,0.00034338317,0.79479206,0.042442553,0.0034878203,0.0005105021,0.1547531],"study_design_scores_gemma":[0.0000067297306,0.00016134897,0.0007892781,0.0000033373346,0.0000024087626,0.000036187772,0.000018585159,0.99180764,0.0061897407,0.00065063,0.0003272448,0.00000679287],"about_ca_topic_score_codex":0.0023400732,"about_ca_topic_score_gemma":0.0024283368,"teacher_disagreement_score":0.0023400732,"about_ca_system_score_codex":0.00023960324,"about_ca_system_score_gemma":0.0005370959,"threshold_uncertainty_score":0.0065022707},"labels":[],"label_agreement":null},{"id":"W2806117508","doi":"10.1109/syscon.2018.8369532","title":"ORGODEX: Authorization as a service (AaaS)","year":2018,"lang":"en","type":"article","venue":"2018 Annual IEEE International Systems Conference (SysCon)","topic":"Access Control and Trust","field":"Social Sciences","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":"Royal Military College of Canada","funders":"","keywords":"Computer science; Cloud computing; Role-based access control; Computer security; Access control; Scalability; Context (archaeology); Implementation; Software deployment; Cloud computing security; Information security; Software engineering; Database","score_opus":0.048501206460825015,"score_gpt":0.35431765887531574,"score_spread":0.30581645241449074,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2806117508","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016312202,0.00032214916,0.9153354,0.0012931762,0.00045153016,0.0005702336,0.0010561927,0.014966192,0.049692955],"genre_scores_gemma":[0.35395962,0.00076320133,0.5964195,0.00092660234,0.00023367403,0.0007599642,0.0036774657,0.0018730497,0.041386932],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99585295,0.0014439726,0.00044098857,0.00045573356,0.0013874661,0.0004189455],"domain_scores_gemma":[0.9962192,0.0008157053,0.00034363082,0.0013871698,0.00086636876,0.00036793711],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005284348,0.00067590794,0.0004893771,0.0012288064,0.0016031013,0.005644547,0.0021279743,0.0015492832,0.0076845596],"category_scores_gemma":[0.0056358604,0.0005335463,0.000968996,0.00094658136,0.0013157198,0.006163346,0.0032196965,0.002425559,0.00352704],"study_design_candidate":"not_applicable","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":[0.00033883678,0.0003591655,0.0052524935,0.00036323743,0.000081445636,0.00048252087,0.00084719056,0.017509814,0.0075155953,0.79539084,0.0448619,0.12699693],"study_design_scores_gemma":[0.00009785324,0.00022029415,0.0018115347,0.00019624352,0.0000705146,0.00094323873,0.00045877177,0.21412987,0.02033876,0.1140131,0.6475964,0.00012338893],"about_ca_topic_score_codex":0.0041211653,"about_ca_topic_score_gemma":0.003968348,"teacher_disagreement_score":0.0076845596,"about_ca_system_score_codex":0.001650868,"about_ca_system_score_gemma":0.003500041,"threshold_uncertainty_score":0.027946651},"labels":[],"label_agreement":null},{"id":"W2806305228","doi":"10.1109/syscon.2018.8369571","title":"Localization of specific body part by multiple depth sensors network","year":2018,"lang":"en","type":"article","venue":"2018 Annual IEEE International Systems Conference (SysCon)","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":1,"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":"","keywords":"Computer vision; Point cloud; Artificial intelligence; Computer science; Geodesic; RGB color model; Body surface; Depth map; Wearable computer; Image (mathematics); Mathematics; Geometry","score_opus":0.024956362496787475,"score_gpt":0.24160944977955387,"score_spread":0.2166530872827664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2806305228","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":[0.10400335,0.0009066915,0.88881516,0.00017685925,0.000096643686,0.00009256018,0.0003934068,0.0016017684,0.00391353],"genre_scores_gemma":[0.833209,0.0008181539,0.16098161,0.00011804106,0.000045383586,0.00011505641,0.00052037823,0.000049238097,0.0041430676],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996904,0.00004141686,0.000013439716,0.00009065508,0.00012733226,0.00003684648],"domain_scores_gemma":[0.9998604,0.00002344501,0.000030817355,0.000022633321,0.000049126425,0.000013542713],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016664802,0.00059257774,0.00047272642,0.0007814997,0.00023183491,0.00039767308,0.00065338134,0.0004071904,0.0012955028],"category_scores_gemma":[0.0005129957,0.00023826826,0.00029229044,0.00058639894,0.00015868478,0.0007631537,0.00088705367,0.00025092156,0.00043178545],"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":[0.0006158272,0.0001378463,0.01574093,0.0003111615,0.00012075844,0.0005320557,0.00034490856,0.14316021,0.18109088,0.0034224077,0.00427042,0.6502526],"study_design_scores_gemma":[0.000026592765,0.00029438862,0.013072802,0.000046398378,0.0000612905,0.00056749437,0.00021062091,0.9156294,0.058797963,0.0030195976,0.008240432,0.000033073582],"about_ca_topic_score_codex":0.0039729453,"about_ca_topic_score_gemma":0.0053318716,"teacher_disagreement_score":0.0039729453,"about_ca_system_score_codex":0.0003827678,"about_ca_system_score_gemma":0.00038821096,"threshold_uncertainty_score":0.007899642},"labels":[],"label_agreement":null},{"id":"W2806383563","doi":"10.1109/syscon.2018.8369554","title":"Roof report from automatically generated 3D building models by straight skeleton computation","year":2018,"lang":"en","type":"article","venue":"2018 Annual IEEE International Systems Conference (SysCon)","topic":"3D Modeling in Geospatial Applications","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":"Okanagan College","funders":"","keywords":"Polygon (computer graphics); Roof; Computation; Point in polygon; Computer science; Monotone polygon; Skeleton (computer programming); Process (computing); Geometry; Computer graphics (images); Algorithm; Mathematics; Structural engineering; Engineering; Polygon mesh","score_opus":0.02639759471721785,"score_gpt":0.2733309358947222,"score_spread":0.24693334117750432,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2806383563","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":[0.014421457,0.00007465841,0.9669316,0.000038918068,0.000055552417,0.00013269883,0.0009265971,0.013180235,0.0042382814],"genre_scores_gemma":[0.16966286,0.00026030015,0.8145653,0.00002695075,0.000028133654,0.00021967142,0.00740369,0.0026233008,0.005209733],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994381,0.000051898343,0.000032879856,0.00009375982,0.00034507024,0.000038306138],"domain_scores_gemma":[0.99925214,0.00015871563,0.00007517801,0.0002424132,0.00022964686,0.00004188894],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039471537,0.0012936828,0.00061364676,0.0019530533,0.00043976327,0.0011362826,0.0011287922,0.0006858596,0.012096055],"category_scores_gemma":[0.0016612104,0.0007768779,0.0014769153,0.0010024403,0.0004636872,0.0008400768,0.0015915888,0.0006071884,0.0045473827],"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":[0.0004121079,0.00013108958,0.0035652744,0.00048260842,0.00010502389,0.0012868674,0.00043627966,0.3843099,0.048661783,0.017881377,0.028262917,0.51446486],"study_design_scores_gemma":[0.00002977803,0.00007293667,0.0007657714,0.000038363072,0.000029278644,0.00024128433,0.00010181371,0.9520197,0.024315013,0.005135802,0.017212996,0.000037303173],"about_ca_topic_score_codex":0.0024713955,"about_ca_topic_score_gemma":0.0042917742,"teacher_disagreement_score":0.012096055,"about_ca_system_score_codex":0.00033533064,"about_ca_system_score_gemma":0.000908817,"threshold_uncertainty_score":0.040465295},"labels":[],"label_agreement":null},{"id":"W2806794575","doi":"10.1109/syscon.2018.8369551","title":"Architecture for testing learning-based autonomous vehicle control design","year":2018,"lang":"en","type":"article","venue":"2018 Annual IEEE International Systems Conference (SysCon)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Controller (irrigation); Robot; Process (computing); Offline learning; Computer science; Control engineering; Mobile robot; Differential (mechanical device); Vehicle dynamics; Artificial intelligence; Control theory (sociology); Control (management); Engineering; Online learning; Automotive engineering","score_opus":0.06291224565056276,"score_gpt":0.2947151798646511,"score_spread":0.23180293421408837,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2806794575","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":[0.053423744,0.000090790214,0.94020283,0.00010899544,0.000034213663,0.00020558546,0.00003693337,0.0023288967,0.0035679739],"genre_scores_gemma":[0.84033626,0.00005431768,0.15731938,0.00006010848,0.000013384734,0.00034264952,0.00010037766,0.00009146719,0.0016819829],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989542,0.00026538107,0.000060201757,0.00018361016,0.0004497096,0.00008690028],"domain_scores_gemma":[0.9983834,0.0005422132,0.000134675,0.00036492496,0.0005196165,0.000055089073],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009372007,0.0006615329,0.00043603795,0.0004112608,0.00031084247,0.0007756737,0.0017558174,0.0008154693,0.0020054204],"category_scores_gemma":[0.003197905,0.00031433936,0.0003938768,0.00016291185,0.0008987902,0.000751966,0.0008408465,0.0013391515,0.00039464465],"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":[0.000132662,0.00018733568,0.0020047983,0.00015558707,0.0000577733,0.00013663709,0.00013470565,0.85363555,0.03594428,0.013311559,0.0006360481,0.09366312],"study_design_scores_gemma":[0.000015299382,0.00016183064,0.00031572543,0.000011333063,0.000008747205,0.000037582762,0.000011776051,0.9821154,0.01269263,0.0034269562,0.0011962814,0.0000064755773],"about_ca_topic_score_codex":0.002496812,"about_ca_topic_score_gemma":0.0018584154,"teacher_disagreement_score":0.002496812,"about_ca_system_score_codex":0.0010111227,"about_ca_system_score_gemma":0.0009486552,"threshold_uncertainty_score":0.0073361993},"labels":[],"label_agreement":null},{"id":"W2807215337","doi":"10.1109/syscon.2018.8369612","title":"VM processes state detection by hypervisor tracing","year":2018,"lang":"en","type":"article","venue":"2018 Annual IEEE International Systems Conference (SysCon)","topic":"Software System Performance and Reliability","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":"Polytechnique Montréal","funders":"","keywords":"Computer science; Virtualization; Tracing; Virtual machine; Hypervisor; Host (biology); TRACE (psycholinguistics); Operating system; Cloud computing; Kernel (algebra); Software deployment; Workload; Overhead (engineering); Distributed computing; Rootkit; Process (computing); Malware","score_opus":0.02150451725627705,"score_gpt":0.26423567579207075,"score_spread":0.2427311585357937,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2807215337","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":[0.22571151,0.0005709884,0.7505484,0.000121497185,0.00007525845,0.00014875163,0.00027479467,0.020292208,0.0022565976],"genre_scores_gemma":[0.8987316,0.0001937278,0.09922504,0.00002918594,0.000014850757,0.000045281042,0.0002966463,0.00031118817,0.0011524509],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989188,0.00015255908,0.0000770291,0.0002384925,0.0005008014,0.00011226206],"domain_scores_gemma":[0.9971209,0.0007912376,0.00058355805,0.0008344308,0.0005452749,0.00012469299],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063802046,0.0007011129,0.00049157726,0.0020163052,0.000357452,0.0014239657,0.0009026423,0.0004063389,0.00094893685],"category_scores_gemma":[0.004518821,0.000278712,0.00036225613,0.0007899029,0.00034133848,0.00095707824,0.0008722703,0.00061626104,0.0004260336],"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":[0.0008561241,0.000280902,0.0579968,0.0004242424,0.00017813344,0.0005615471,0.0011680488,0.05177819,0.15496281,0.006675801,0.0030361845,0.72208107],"study_design_scores_gemma":[0.00002627934,0.00019231539,0.014072262,0.00005721392,0.000058518006,0.00060122897,0.00022725777,0.82376593,0.14960134,0.005780372,0.0055692396,0.000047945283],"about_ca_topic_score_codex":0.0019048252,"about_ca_topic_score_gemma":0.0017245805,"teacher_disagreement_score":0.0020163052,"about_ca_system_score_codex":0.00045388436,"about_ca_system_score_gemma":0.0009818358,"threshold_uncertainty_score":0.0037875175},"labels":[],"label_agreement":null},{"id":"W2807391671","doi":"10.1109/syscon.2018.8369548","title":"Velocity and position trajectory tracking through sliding mode control of two-wheeled self-balancing mobile robot","year":2018,"lang":"en","type":"article","venue":"2018 Annual IEEE International Systems Conference (SysCon)","topic":"Control and Dynamics of Mobile Robots","field":"Engineering","cited_by":8,"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 New Brunswick","funders":"","keywords":"Control theory (sociology); Mobile robot; Trajectory; Controller (irrigation); Sliding mode control; Tracking (education); Robot; Nonlinear system; Position (finance); Computer science; Mode (computer interface); Track (disk drive); Position tracking; Stability (learning theory); Control engineering; Engineering; Control (management); Artificial intelligence; Actuator; Physics","score_opus":0.01274547698250304,"score_gpt":0.2596284644888245,"score_spread":0.24688298750632146,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2807391671","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6388567,0.00023135678,0.35471708,0.00011308716,0.00009191098,0.00007948091,0.00003501607,0.0008757784,0.0049995524],"genre_scores_gemma":[0.99405503,0.0000270951,0.0050211395,0.0000073983665,0.0000029385674,0.00002128945,0.000011136469,0.0000049290134,0.0008490763],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999062,0.000013600205,0.000007182761,0.000017684955,0.00004291103,0.0000124464095],"domain_scores_gemma":[0.9997826,0.000035863508,0.00005294261,0.000027461341,0.00008362501,0.00001748141],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021995424,0.00031649214,0.00019236025,0.00023257615,0.00022109172,0.0003320435,0.00039155025,0.00024704955,0.00063970854],"category_scores_gemma":[0.0003764044,0.00013905276,0.00012322784,0.00013575424,0.00021281876,0.00026044901,0.00028695175,0.00018623588,0.00010222194],"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":[0.00063686655,0.00018967927,0.0023615393,0.00028866116,0.00006487866,0.0004571495,0.00062426407,0.4866051,0.3592553,0.0044032615,0.000854828,0.14425845],"study_design_scores_gemma":[0.000027333155,0.00031724846,0.0008664641,0.000006984889,0.000008422508,0.000025263706,0.000018208015,0.984502,0.013375351,0.00028096768,0.00056349154,0.000008253555],"about_ca_topic_score_codex":0.0028334511,"about_ca_topic_score_gemma":0.0019719996,"teacher_disagreement_score":0.0028334511,"about_ca_system_score_codex":0.0001607376,"about_ca_system_score_gemma":0.00027408754,"threshold_uncertainty_score":0.0056338906},"labels":[],"label_agreement":null},{"id":"W2807652414","doi":"10.1109/syscon.2018.8369566","title":"A novel human posture estimation using single depth image from Kinect v2 sensor","year":2018,"lang":"en","type":"article","venue":"2018 Annual IEEE International Systems Conference (SysCon)","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":9,"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":"","keywords":"Computer science; Artificial intelligence; Fast Fourier transform; Computer vision; Field (mathematics); Image (mathematics); Artificial neural network; Carry (investment); Deep learning; Pattern recognition (psychology); Mathematics; Algorithm","score_opus":0.07415307089174916,"score_gpt":0.3195987724166757,"score_spread":0.24544570152492656,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2807652414","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":[0.03112686,0.0017261824,0.95900637,0.00013009847,0.00041136055,0.00013708051,0.0010113146,0.0029401293,0.0035106197],"genre_scores_gemma":[0.39783102,0.0028856425,0.5866074,0.0003575812,0.00025954773,0.0002856955,0.0020128756,0.00018857556,0.009571573],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999569,0.00003568194,0.000019230723,0.00014921156,0.00017813922,0.000048758036],"domain_scores_gemma":[0.9998642,0.000011363049,0.000021888443,0.000019870406,0.000063571475,0.000019029345],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018451642,0.0012367647,0.0007483823,0.0011828312,0.00016836835,0.00050634146,0.00071210664,0.000749289,0.0023508205],"category_scores_gemma":[0.00041995887,0.00039745928,0.0005193826,0.0008249922,0.00015157722,0.0008018849,0.00072768383,0.0004891908,0.0016212751],"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":[0.00036625893,0.00016628782,0.0072040474,0.0005723691,0.00018400417,0.00032510288,0.00011041529,0.009568355,0.18429804,0.0012103149,0.009482628,0.78651214],"study_design_scores_gemma":[0.000093939496,0.0006378553,0.05479024,0.00023898185,0.00020586615,0.0030568666,0.0001925507,0.7586009,0.15436192,0.0027460984,0.024853248,0.00022147405],"about_ca_topic_score_codex":0.0022694385,"about_ca_topic_score_gemma":0.004748746,"teacher_disagreement_score":0.0023508205,"about_ca_system_score_codex":0.00016641855,"about_ca_system_score_gemma":0.00042063338,"threshold_uncertainty_score":0.007864237},"labels":[],"label_agreement":null}]}