{"meta":{"query_hash":"e1b794f1aaa0","filters":{"venue":"ACM Transactions on Modeling and Computer Simulation"},"cohort_total":41,"direct_labels_cover":1,"predictions_cover":41,"exported":41,"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/e1b794f1aaa0","api":"https://metacan.xera.ac/api/v1/cohort?venue=ACM+Transactions+on+Modeling+and+Computer+Simulation"},"results":[{"id":"W1984785310","doi":"10.1145/369534.369537","title":"Parallel shared-memory simulator performance for large ATM networks","year":2000,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":18,"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 Saskatchewan; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Parallel computing; Speedup; Kernel (algebra); Benchmark (surveying); Multiprocessing; Shared memory; Performance improvement","score_opus":0.023250719919683076,"score_gpt":0.2653314796262749,"score_spread":0.24208075970659182,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1984785310","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":[0.86491674,0.00023630072,0.11492549,0.0002396628,0.000080840895,0.00012340302,0.000591287,0.007264449,0.011621816],"genre_scores_gemma":[0.9739996,0.000065530076,0.024084669,0.000023897854,0.000006338627,0.00006480072,0.00043768948,0.00013170962,0.0011856381],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99965906,0.00009948304,0.00002227696,0.000040802963,0.00012722205,0.00005105534],"domain_scores_gemma":[0.9991466,0.0003455331,0.00004525057,0.00018873528,0.0002085721,0.0000653641],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00073212024,0.00042543685,0.0003764681,0.00027312053,0.0004941367,0.0006372377,0.0014106808,0.00036686068,0.0024587228],"category_scores_gemma":[0.0019892212,0.00025265434,0.00030490386,0.00050034944,0.00026847926,0.0008633524,0.00056287594,0.000560831,0.0003961231],"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":[0.0013692295,0.00030982608,0.008093411,0.00011604143,0.00010208832,0.00017631678,0.00018342053,0.9115741,0.024146603,0.0057522906,0.0032408366,0.044935822],"study_design_scores_gemma":[0.00004452661,0.000101269005,0.0005855305,0.000002743606,0.000015879266,0.000018484645,0.000025426982,0.98761183,0.009784777,0.0009276098,0.0008744874,0.0000074712357],"about_ca_topic_score_codex":0.0053152703,"about_ca_topic_score_gemma":0.0036671949,"teacher_disagreement_score":0.0053152703,"about_ca_system_score_codex":0.0008530039,"about_ca_system_score_gemma":0.001148801,"threshold_uncertainty_score":0.010568678},"labels":[],"label_agreement":null},{"id":"W1990674830","doi":"10.1145/1225275.1225280","title":"Rare events, splitting, and quasi-Monte Carlo","year":2007,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Probability and Risk Models","field":"Decision Sciences","cited_by":89,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Estimator; Monte Carlo method; Variance reduction; Importance sampling; Computer science; Rare events; Context (archaeology); Markov chain Monte Carlo; Disjoint sets; Markov chain; Algorithm; Sequence (biology); Measure (data warehouse); Sampling (signal processing); Mathematical optimization; Statistical physics; Mathematics; Statistics; Discrete mathematics; Physics; Machine learning","score_opus":0.10067338486188931,"score_gpt":0.36408016069703664,"score_spread":0.2634067758351473,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1990674830","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":[0.0060872277,0.0004955544,0.9914135,0.00022535633,0.00007431548,0.000050206072,0.00004637523,0.00028157266,0.0013259727],"genre_scores_gemma":[0.38496143,0.0010834365,0.60977185,0.00046656013,0.00023891259,0.00035934767,0.0003142743,0.00033000892,0.002474208],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99226123,0.0049021253,0.00026610916,0.00091048004,0.0013457858,0.00031434724],"domain_scores_gemma":[0.96232754,0.02846739,0.0020066067,0.005065562,0.0015096519,0.0006231467],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009459384,0.0008524217,0.0013656515,0.0013092103,0.00081180944,0.0016973102,0.0024353664,0.0017056722,0.0032038612],"category_scores_gemma":[0.03981859,0.00085279945,0.001347023,0.0012176823,0.00312308,0.0033432818,0.0022704806,0.0025330635,0.0005721928],"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":[0.00019786673,0.00007789155,0.0027602066,0.00027910588,0.00014488205,0.0001774846,0.00026909346,0.49136558,0.001444625,0.46111673,0.0015477479,0.040618703],"study_design_scores_gemma":[0.00002538195,0.000057525973,0.0002956351,0.000038983642,0.000024834753,0.000060861315,0.000018513741,0.87020504,0.0008186334,0.12624806,0.0021801542,0.000026361507],"about_ca_topic_score_codex":0.0042135506,"about_ca_topic_score_gemma":0.0031139795,"teacher_disagreement_score":0.009459384,"about_ca_system_score_codex":0.0012981583,"about_ca_system_score_gemma":0.0016425295,"threshold_uncertainty_score":0.050026655},"labels":[],"label_agreement":null},{"id":"W1990749876","doi":"10.1145/1596519.1596521","title":"FISTE","year":2009,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Network Traffic and Congestion Control","field":"Computer Science","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":"Carleton University","funders":"","keywords":"Computer science; Quality of service; Network traffic simulation; Distributed computing; Computer network; Traffic engineering; Traffic generation model; Network traffic control; Queue; Sampling (signal processing); Traffic classification","score_opus":0.021844129165387045,"score_gpt":0.2501052288329259,"score_spread":0.22826109966753885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1990749876","genre_codex":"other","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":[0.008665449,0.0018855558,0.3785542,0.0036132648,0.0038544247,0.00066467933,0.009388579,0.027768802,0.56560504],"genre_scores_gemma":[0.12905967,0.002931515,0.22604427,0.003189024,0.0010085289,0.0009975199,0.02543169,0.007196535,0.60414124],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99869245,0.00024076621,0.00008149363,0.0002589961,0.0005404958,0.00018580323],"domain_scores_gemma":[0.99779785,0.0004305562,0.00011234728,0.0007080524,0.00076244544,0.00018866557],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013517393,0.00083460775,0.0006697477,0.0014642956,0.0011282342,0.0031712714,0.0020152952,0.0017517639,0.21450335],"category_scores_gemma":[0.005094699,0.00045361317,0.0008521699,0.001423073,0.00053328375,0.003000549,0.0027906345,0.0014824633,0.11306737],"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":[0.000353244,0.00018581616,0.0012935443,0.0006070936,0.000054671673,0.0004060729,0.0002802446,0.008103313,0.009183764,0.13528147,0.38008815,0.46416253],"study_design_scores_gemma":[0.000036040015,0.00005860392,0.00041925473,0.00008686062,0.000015612986,0.00039861878,0.00006728803,0.013965759,0.005501631,0.022743762,0.9566743,0.000032275726],"about_ca_topic_score_codex":0.0013857723,"about_ca_topic_score_gemma":0.0016717638,"teacher_disagreement_score":0.21450335,"about_ca_system_score_codex":0.0009895581,"about_ca_system_score_gemma":0.0017073748,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W2000167291","doi":"10.1145/1870085.1870090","title":"Joint congestion control and distributed scheduling for throughput guarantees in wireless networks","year":2010,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Wireless Networks and Protocols","field":"Computer Science","cited_by":31,"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 Waterloo","funders":"Army Research Office; Air Force Office of Scientific Research; Division of Computer and Network Systems","keywords":"Computer science; Scheduling (production processes); Wireless network; Round-robin scheduling; Distributed computing; Computer network; Maximum throughput scheduling; Network congestion; Dynamic priority scheduling; Fair-share scheduling; Wireless; Mathematical optimization; Network packet; Quality of service; Telecommunications; Mathematics","score_opus":0.025908901390723743,"score_gpt":0.2718026307721484,"score_spread":0.24589372938142465,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2000167291","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":[0.013728475,0.00027025663,0.984463,0.00022882788,0.00004252737,0.000044272525,0.000011739176,0.00018041987,0.0010305385],"genre_scores_gemma":[0.8864517,0.00038187794,0.1116176,0.00012496488,0.0001416771,0.00017067142,0.000032825716,0.00007655315,0.0010019736],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976373,0.0010609856,0.00013356378,0.00030451742,0.0005616996,0.00030201743],"domain_scores_gemma":[0.9947054,0.0035758745,0.00048764638,0.0005129793,0.0005094525,0.00020879114],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0052636806,0.0010203734,0.0011863653,0.00060452987,0.0008893628,0.001625586,0.0017683064,0.00096489646,0.001218169],"category_scores_gemma":[0.012547857,0.0005880234,0.00056182564,0.00075849873,0.0019153046,0.0024679583,0.0017829931,0.0014304066,0.00016879433],"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":[0.000115194634,0.000052248583,0.00034549835,0.00007355755,0.000036993835,0.000045253488,0.00010278623,0.91018945,0.0025940542,0.06065663,0.0007408835,0.025047539],"study_design_scores_gemma":[0.000018386212,0.00003116025,0.000044498393,0.0000037359412,0.000007813402,0.000007869533,0.0000077789855,0.9861129,0.00059183355,0.012846306,0.00032310333,0.000004618391],"about_ca_topic_score_codex":0.0019561436,"about_ca_topic_score_gemma":0.0014532496,"teacher_disagreement_score":0.0052636806,"about_ca_system_score_codex":0.0016360981,"about_ca_system_score_gemma":0.0025460653,"threshold_uncertainty_score":0.027837396},"labels":[],"label_agreement":null},{"id":"W2010523529","doi":"10.1145/1113316.1113319","title":"On the xorshift random number generators","year":2005,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Chaos-based Image/Signal Encryption","field":"Computer Science","cited_by":106,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Random number generation; Modulo; Pseudorandom number generator; Mathematics; Simple (philosophy); Arithmetic; Class (philosophy); Computer science; Generator (circuit theory); Discrete mathematics; Algorithm; Artificial intelligence; Power (physics)","score_opus":0.026033544115530327,"score_gpt":0.2600723811718375,"score_spread":0.23403883705630718,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2010523529","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":[0.15063222,0.0019148522,0.8264456,0.0013273305,0.00021489827,0.00018944696,0.00021991976,0.00054317515,0.01851255],"genre_scores_gemma":[0.8364485,0.0013035728,0.15291022,0.00052955025,0.00041888875,0.0003988596,0.00031433607,0.00016386065,0.0075121857],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981982,0.0008973712,0.00006505671,0.00022055487,0.0004531454,0.00016567389],"domain_scores_gemma":[0.9899272,0.007971894,0.00043385528,0.000864188,0.00066501444,0.00013797749],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003358798,0.000570391,0.00073496776,0.0017966415,0.00068287697,0.00090293214,0.00065998913,0.0009197749,0.0030256736],"category_scores_gemma":[0.015503291,0.000365226,0.00053110806,0.0010394339,0.002343693,0.0026196686,0.001200854,0.0013158439,0.0006748649],"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":[0.0001412927,0.000028109953,0.00068992394,0.000042713134,0.00001311605,0.00012470238,0.00009089343,0.060389012,0.0026521543,0.9026622,0.0015874199,0.031578496],"study_design_scores_gemma":[0.000098220284,0.0001777463,0.00040545443,0.000047389996,0.0000121536605,0.00023206665,0.000026765647,0.40100047,0.0038320443,0.5881504,0.0059675747,0.00004976931],"about_ca_topic_score_codex":0.0004096555,"about_ca_topic_score_gemma":0.00028884318,"teacher_disagreement_score":0.003358798,"about_ca_system_score_codex":0.0006882977,"about_ca_system_score_gemma":0.00064083043,"threshold_uncertainty_score":0.017763197},"labels":[],"label_agreement":null},{"id":"W2021233452","doi":"10.1145/1734222.1734223","title":"Setwise and filtered gibbs samplers for teletraffic analysis","year":2010,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Gibbs sampling; Estimator; Markov chain; Computer science; Occupancy; Markov process; Applied mathematics; Markov chain Monte Carlo; Mathematical optimization; Algorithm; Mathematics; Statistics; Artificial intelligence; Bayesian probability; Machine learning; Engineering","score_opus":0.02660623500649122,"score_gpt":0.2626521806922541,"score_spread":0.23604594568576287,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2021233452","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":[0.0021431893,0.000054024385,0.9972825,0.000050007147,0.000016927035,0.000026865715,0.000038824306,0.00011240969,0.00027515658],"genre_scores_gemma":[0.2508557,0.00042280648,0.74256647,0.00023159932,0.00019679042,0.0009034283,0.0006946707,0.0003376507,0.0037907523],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975631,0.0015247684,0.00008869099,0.00024524337,0.00043244535,0.00014578865],"domain_scores_gemma":[0.9833725,0.013654538,0.00048283965,0.001192171,0.0009987376,0.00029917044],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00801265,0.00092966965,0.0011397924,0.0017296441,0.0010147566,0.0013468105,0.0030516554,0.0015104574,0.0046148896],"category_scores_gemma":[0.024789235,0.0008199442,0.0015797159,0.001512733,0.0024989126,0.002137725,0.0019901888,0.0027125492,0.0006991942],"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":[0.000077637844,0.000050348295,0.0013770505,0.000051273902,0.00007496095,0.00006953507,0.00011820228,0.57730234,0.00067326997,0.39118332,0.0013640234,0.027658008],"study_design_scores_gemma":[0.000007560725,0.000010425397,0.00008509915,0.0000068534755,0.0000055950145,0.000011623119,0.0000050006092,0.9512674,0.00019616127,0.047908414,0.0004871833,0.00000857564],"about_ca_topic_score_codex":0.00999846,"about_ca_topic_score_gemma":0.009089576,"teacher_disagreement_score":0.00999846,"about_ca_system_score_codex":0.0020127362,"about_ca_system_score_gemma":0.0023063582,"threshold_uncertainty_score":0.042375445},"labels":[],"label_agreement":null},{"id":"W2022664864","doi":"10.1145/1122012.1122016","title":"Perfect sampling for queues and network models","year":2006,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":13,"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; Western University","funders":"","keywords":"Computer science; Queue; Reservation; Queueing theory; Protocol (science); Poisson distribution; Construct (python library); Sampling (signal processing); Service (business); Fork–join queue; Computer network; Mathematics; Queue management system; Statistics; Telecommunications","score_opus":0.03553395263247132,"score_gpt":0.26086271129599664,"score_spread":0.2253287586635253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2022664864","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":[0.0011152466,0.0013539796,0.9950348,0.00025846675,0.0000856357,0.000044407854,0.00008935379,0.0002209944,0.0017971596],"genre_scores_gemma":[0.16155586,0.0070096464,0.8196323,0.0009751272,0.0012823332,0.00060383545,0.0007964994,0.0004611546,0.00768318],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99536043,0.002407223,0.0001879482,0.0005865324,0.0012645092,0.00019337692],"domain_scores_gemma":[0.9898352,0.007570133,0.0003537795,0.001156744,0.0008770912,0.00020706806],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0065732547,0.0014656298,0.0016418315,0.0022990787,0.0011550274,0.0024273552,0.0030867,0.002110023,0.0053775725],"category_scores_gemma":[0.032441255,0.0011359742,0.0015737916,0.0035096968,0.0026768784,0.0058528455,0.0024277845,0.003792477,0.0017099824],"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":[0.000038463975,0.000049338258,0.0007938073,0.0001781092,0.000048182563,0.000096346055,0.00013875116,0.08863151,0.0003340978,0.85157794,0.0057185236,0.052395012],"study_design_scores_gemma":[0.000019395924,0.000023551085,0.000105482526,0.000037966576,0.000013692756,0.00009288689,0.000015097006,0.31739908,0.00020571922,0.6736946,0.008376184,0.000016367965],"about_ca_topic_score_codex":0.005391687,"about_ca_topic_score_gemma":0.0034752355,"teacher_disagreement_score":0.0065732547,"about_ca_system_score_codex":0.0024250317,"about_ca_system_score_gemma":0.0017713425,"threshold_uncertainty_score":0.034763157},"labels":[],"label_agreement":null},{"id":"W2025952763","doi":"10.1145/1596519.1596523","title":"Random variate generation for exponentially and polynomially tilted stable distributions","year":2009,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":117,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Random variate; Mathematics; Exponential growth; Convolution random number generator; Representation (politics); Random variable; Applied mathematics; Distribution (mathematics); Exponential distribution; Variable (mathematics); Stability (learning theory); Key (lock); Combinatorics; Discrete mathematics; Mathematical analysis; Computer science; Statistics","score_opus":0.037730407018985355,"score_gpt":0.2846753339540069,"score_spread":0.24694492693502154,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2025952763","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":[0.0066167344,0.000036699348,0.9913326,0.00007873634,0.000017142405,0.000027238746,0.000024340767,0.000119903074,0.0017466146],"genre_scores_gemma":[0.53707266,0.00023731127,0.45123085,0.00021588097,0.000113074326,0.00035490424,0.00023148798,0.00035625033,0.010187637],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99810326,0.00070817326,0.000073359915,0.0002648992,0.00060961663,0.00024051174],"domain_scores_gemma":[0.99507374,0.003065206,0.00036539795,0.00081778824,0.0004959318,0.00018190072],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033786509,0.00046852365,0.00082177535,0.00084891234,0.000660012,0.001543891,0.0016971107,0.0009193676,0.01067104],"category_scores_gemma":[0.014732461,0.00038894292,0.0008301495,0.0008257929,0.0017656274,0.0032706202,0.0029572742,0.0019839779,0.0021615205],"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":[0.00009046075,0.000023482415,0.00029320354,0.000028489561,0.000008221277,0.00005963231,0.00008405944,0.03928001,0.0013856053,0.9315668,0.0008804697,0.026299635],"study_design_scores_gemma":[0.00003781048,0.000025894116,0.00007410724,0.000013531952,0.000005983365,0.00006572912,0.000016253294,0.53182083,0.0031430179,0.46304712,0.001726719,0.000023029057],"about_ca_topic_score_codex":0.00042507317,"about_ca_topic_score_gemma":0.00056067575,"teacher_disagreement_score":0.01067104,"about_ca_system_score_codex":0.0009833851,"about_ca_system_score_gemma":0.0008608527,"threshold_uncertainty_score":0.035698235},"labels":[],"label_agreement":null},{"id":"W2027801241","doi":"10.1145/502109.502112","title":"Fast simulation of broadband telecommunications networks carrying long-range dependent bursty traffic","year":2001,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":2,"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 Ottawa","funders":"","keywords":"Burstiness; Computer science; Broadband; Range (aeronautics); Sampling (signal processing); Noise (video); Broadband networks; Importance sampling; Algorithm; Telecommunications; Monte Carlo method; Mathematics; Computer network; Statistics; Engineering; Artificial intelligence","score_opus":0.027121675956178388,"score_gpt":0.26101102967122547,"score_spread":0.23388935371504707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2027801241","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":[0.2568162,0.00021413466,0.7377938,0.00027772278,0.00007097105,0.000088750974,0.00018367528,0.00066545524,0.0038892308],"genre_scores_gemma":[0.9261428,0.00016823313,0.07241755,0.000035252117,0.000018199822,0.00013655843,0.00016108772,0.00003961786,0.00088072574],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99968565,0.00012606045,0.000013132567,0.000022904149,0.000105703795,0.000046635694],"domain_scores_gemma":[0.99792576,0.0015553929,0.000121263685,0.00012018949,0.00019709487,0.00008025197],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00096418976,0.00056023186,0.00060892524,0.0005066676,0.0005373988,0.0005307589,0.00084161764,0.00081802206,0.0010818621],"category_scores_gemma":[0.0040216567,0.00033359506,0.00040514948,0.00047937807,0.0005639868,0.0007723343,0.00070881436,0.0009918611,0.0000925033],"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":[0.000025696005,0.000016439404,0.000500443,0.000009445651,0.000008292521,0.000024991763,0.000025882257,0.99121803,0.00064016454,0.0051934095,0.00008054241,0.002256696],"study_design_scores_gemma":[0.0000015678215,0.0000033457864,0.000030804746,5.613003e-7,7.278313e-7,0.0000022113222,0.000001731395,0.99921775,0.000107023065,0.00059401034,0.000039408176,8.4187417e-7],"about_ca_topic_score_codex":0.0064462945,"about_ca_topic_score_gemma":0.0035782668,"teacher_disagreement_score":0.0064462945,"about_ca_system_score_codex":0.0006188166,"about_ca_system_score_gemma":0.0005856312,"threshold_uncertainty_score":0.012817562},"labels":[],"label_agreement":null},{"id":"W2033803521","doi":"10.1145/945511.945515","title":"Empirical evidence concerning AES","year":2003,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Chaos-based Image/Signal Encryption","field":"Computer Science","cited_by":75,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Centre de Recherches Mathématiques","keywords":"Randomness; Computer science; Cryptography; Advanced Encryption Standard; Randomness tests; Statistical hypothesis testing; Theoretical computer science; Algorithm; Mathematics; Statistics","score_opus":0.1426649064882288,"score_gpt":0.3318136072770856,"score_spread":0.1891487007888568,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2033803521","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":[0.89082986,0.009970557,0.022196129,0.02773142,0.000387621,0.00015360775,0.0025068247,0.000055503155,0.04616862],"genre_scores_gemma":[0.9933001,0.0024621093,0.0010703374,0.0010929191,0.00030496655,0.00003938084,0.0006529082,0.000020368005,0.001056903],"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9770776,0.012486056,0.00244346,0.0024664227,0.004716431,0.0008101218],"domain_scores_gemma":[0.28864008,0.5820606,0.079552054,0.026000772,0.020187275,0.0035593014],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.028000478,0.00039711807,0.00063210464,0.0036784706,0.0010002294,0.0023000347,0.0014288389,0.0021776077,0.013932718],"category_scores_gemma":[0.35850874,0.00033975544,0.00047812084,0.0042366837,0.0058787605,0.0045045596,0.0021177742,0.002958921,0.0013462257],"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":[0.0013542646,0.00040786152,0.7867247,0.0008178327,0.00080328895,0.0010330175,0.0031619067,0.0031818983,0.00066136516,0.10418571,0.010189335,0.08747885],"study_design_scores_gemma":[0.0003256012,0.001966655,0.74397504,0.0013523591,0.0006230892,0.007318381,0.009391729,0.014913374,0.003342977,0.14391188,0.072689936,0.00018906264],"about_ca_topic_score_codex":0.0010387716,"about_ca_topic_score_gemma":0.00075422094,"teacher_disagreement_score":0.028000478,"about_ca_system_score_codex":0.00072639715,"about_ca_system_score_gemma":0.00085217395,"threshold_uncertainty_score":0.14808244},"labels":[],"label_agreement":null},{"id":"W2034644962","doi":"10.1145/1899396.1899399","title":"Modeling and simulation of SIP tandem server with finite buffer","year":2011,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Network Traffic and Congestion Control","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Server; Retransmission; Computer network; Distributed computing; Queueing theory; Upstream (networking); Real-time computing","score_opus":0.03960654247552595,"score_gpt":0.2371031194816948,"score_spread":0.19749657700616885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2034644962","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":[0.7751171,0.00037411676,0.20402484,0.00058467255,0.0001054146,0.00014264906,0.0005376352,0.0011955483,0.017918015],"genre_scores_gemma":[0.9871514,0.0001441518,0.009733792,0.000046807894,0.000010350579,0.00009084137,0.00011332444,0.00003182146,0.0026775766],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996859,0.00008328251,0.000019822462,0.0000477085,0.00007704989,0.00008623979],"domain_scores_gemma":[0.9993594,0.00029099063,0.000082632476,0.000045055476,0.00011798001,0.000103934755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005729806,0.00063093036,0.00071746274,0.0006449002,0.0007446074,0.0011074587,0.0016327292,0.001513385,0.0024292667],"category_scores_gemma":[0.0013566479,0.00039483054,0.0005247276,0.00059796876,0.0010997577,0.0011228187,0.0009400553,0.00079556124,0.0002625135],"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":[0.00003578727,0.000026706875,0.00056443876,0.000012041246,0.0000072083367,0.00009263922,0.00004364156,0.9936731,0.0013629055,0.003400251,0.00013170231,0.0006495266],"study_design_scores_gemma":[0.000003772676,0.000007708011,0.00003755433,0.0000011943987,0.000001636551,0.000005081607,0.0000072608873,0.9993511,0.00018682284,0.0003372343,0.000058453057,0.0000023187633],"about_ca_topic_score_codex":0.013243419,"about_ca_topic_score_gemma":0.004335413,"teacher_disagreement_score":0.013243419,"about_ca_system_score_codex":0.0013080369,"about_ca_system_score_gemma":0.0014771122,"threshold_uncertainty_score":0.026332617},"labels":[],"label_agreement":null},{"id":"W2051169247","doi":"10.1145/2611561","title":"Discrete Event Execution with One-Sided and Two-Sided GVT Algorithms on 216,000 Processor Cores","year":2014,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Simulation Techniques and Applications","field":"Decision Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Advanced Micro Devices (Canada)","funders":"","keywords":"Asynchronous communication; Computer science; Parallel computing; Computation; Synchronization (alternating current); Massively parallel; Distributed computing; Exploit; Event (particle physics); Supercomputer; Algorithm; Implementation; Parallel algorithm; Multi-core processor","score_opus":0.08701757572331453,"score_gpt":0.3748221742226232,"score_spread":0.2878045984993087,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2051169247","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":[0.380994,0.00020215962,0.6020848,0.0002872421,0.0001752722,0.00018853613,0.00036297576,0.003688768,0.01201625],"genre_scores_gemma":[0.7297721,0.00006271128,0.26696777,0.000063509586,0.00001876445,0.00018562088,0.00044415068,0.00023822467,0.0022472139],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995315,0.00011491332,0.000040321793,0.00009103943,0.00014893185,0.00007338395],"domain_scores_gemma":[0.99856037,0.0006194657,0.000096766045,0.0003709174,0.00023721717,0.00011522792],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000864406,0.000667138,0.0006364389,0.0003281069,0.000486905,0.0007040526,0.0013794493,0.0007340694,0.003052482],"category_scores_gemma":[0.003074665,0.00024569605,0.000498082,0.00055734144,0.00067354826,0.0008481847,0.000852719,0.0009181158,0.0004206945],"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":[0.000577034,0.00017352425,0.0037184749,0.00010183711,0.000057104142,0.00019513148,0.00019263609,0.907664,0.008299485,0.021383962,0.0019297984,0.055707052],"study_design_scores_gemma":[0.000044539647,0.000036368325,0.00014589205,0.0000019594772,0.0000032110408,0.000010960107,0.000014141049,0.99544513,0.0019772702,0.0018614056,0.0004549081,0.0000042585084],"about_ca_topic_score_codex":0.0051726806,"about_ca_topic_score_gemma":0.005152178,"teacher_disagreement_score":0.0051726806,"about_ca_system_score_codex":0.0007610915,"about_ca_system_score_gemma":0.001422328,"threshold_uncertainty_score":0.010285139},"labels":[],"label_agreement":null},{"id":"W2061086504","doi":"10.1145/1060576.1060578","title":"Simulating markov-reward processes with rare events","year":2005,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","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 Saskatchewan","funders":"","keywords":"Markov chain; Markov process; Computer science; Rare events; Mathematical optimization; Boundary (topology); Markov decision process; Mathematical economics; Markov renewal process; Markov model; Statistical physics; Applied mathematics; Mathematics; Variable-order Markov model; Statistics; Machine learning; Physics; Mathematical analysis","score_opus":0.019117381041608227,"score_gpt":0.24610024124230387,"score_spread":0.22698286020069564,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2061086504","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":[0.76734525,0.00021790712,0.22143601,0.0005896659,0.0000678923,0.00006583555,0.00020113964,0.00038558478,0.009690776],"genre_scores_gemma":[0.9847532,0.00006627909,0.013922213,0.000027172053,0.00000904001,0.000037022106,0.000055911896,0.000017076722,0.0011122245],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993562,0.00033025662,0.000026712329,0.00006210707,0.00009419056,0.00013053264],"domain_scores_gemma":[0.99358773,0.005344203,0.00031389756,0.00028452332,0.00023138158,0.0002383447],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016695227,0.0003963148,0.0006051343,0.000534446,0.0005237922,0.0009393454,0.0009289945,0.0011126788,0.002161278],"category_scores_gemma":[0.007907344,0.0004473453,0.0005627255,0.00047570077,0.00091390987,0.0013129959,0.0007927782,0.0009872604,0.00016113106],"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":[0.00003750017,0.000029266894,0.00076231465,0.0000090438525,0.000008452983,0.000038563798,0.000030860043,0.9844993,0.00022369977,0.013033704,0.00009053781,0.0012369235],"study_design_scores_gemma":[0.000010027464,0.000008231339,0.000080364174,0.0000014167563,0.0000022305014,0.00000406426,0.0000065909076,0.9954715,0.0001443489,0.0041898577,0.000078270874,0.0000030616707],"about_ca_topic_score_codex":0.014131207,"about_ca_topic_score_gemma":0.009233793,"teacher_disagreement_score":0.014131207,"about_ca_system_score_codex":0.0013972936,"about_ca_system_score_gemma":0.0012476186,"threshold_uncertainty_score":0.028097928},"labels":[],"label_agreement":null},{"id":"W2081195274","doi":"10.1145/1870085.1870088","title":"Optimal scheduling in high-speed downlink packet access networks","year":2010,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Telecommunications link; Computer science; Markov decision process; Scheduling (production processes); Heuristic; Network packet; Mathematical optimization; Dynamic programming; Dynamic priority scheduling; Markov process; Distributed computing; Computer network; Algorithm; Mathematics; Quality of service","score_opus":0.015504737510225365,"score_gpt":0.2523002044070183,"score_spread":0.23679546689679293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081195274","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":[0.04355331,0.00048842723,0.95069605,0.00028297777,0.000048008576,0.000049427865,0.00004907728,0.00015840029,0.0046744067],"genre_scores_gemma":[0.9064616,0.0006147189,0.09071698,0.00006745005,0.000042561474,0.00011844187,0.00007703815,0.000040791852,0.0018603258],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991178,0.00039703076,0.000022963952,0.00006616265,0.0002671394,0.00012883902],"domain_scores_gemma":[0.9986873,0.0008830205,0.00015141908,0.00005252923,0.00017670047,0.000048968934],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001233439,0.00050269597,0.0006783126,0.0005763826,0.0005825129,0.00101194,0.0006623659,0.0006275977,0.0010499096],"category_scores_gemma":[0.0044552796,0.0005546673,0.00034016283,0.0006160581,0.0012940094,0.0009340922,0.0005809543,0.00071161,0.00014303246],"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":[0.000010099566,0.0000094360585,0.000101693906,0.000010859594,0.000004437213,0.000013352752,0.000013010365,0.9807493,0.00020082676,0.01598468,0.00016895348,0.0027333882],"study_design_scores_gemma":[0.0000040321193,0.0000052712417,0.000021495502,0.000001541604,0.0000010059363,0.000002589036,0.000004800317,0.99394023,0.00010405987,0.005755568,0.00015804515,0.000001262384],"about_ca_topic_score_codex":0.008926524,"about_ca_topic_score_gemma":0.0036184401,"teacher_disagreement_score":0.008926524,"about_ca_system_score_codex":0.0019642576,"about_ca_system_score_gemma":0.0022839708,"threshold_uncertainty_score":0.01774913},"labels":[],"label_agreement":null},{"id":"W2100184918","doi":"10.1145/2133390.2133393","title":"Evolutionary optimization of low-discrepancy sequences","year":2012,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Mathematical Approximation and Integration","field":"Mathematics","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Curse of dimensionality; Sequence (biology); Latin hypercube sampling; Hypercube; Computer science; Algorithm; Pseudorandom number generator; Generator (circuit theory); Evolutionary algorithm; Mathematics; Theoretical computer science; Mathematical optimization; Combinatorics; Artificial intelligence; Power (physics); Monte Carlo method; Statistics","score_opus":0.06769827072555362,"score_gpt":0.3173805783833438,"score_spread":0.2496823076577902,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2100184918","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":[0.18497798,0.00034354773,0.8082637,0.000251574,0.00007237603,0.00009874034,0.000065543245,0.00027826556,0.005648312],"genre_scores_gemma":[0.78085643,0.00016593907,0.21394332,0.0001316923,0.00002820543,0.00022254136,0.00019365398,0.0001150002,0.004343182],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991868,0.00034755975,0.00004164014,0.00016216327,0.00018460045,0.00007716552],"domain_scores_gemma":[0.99748755,0.0015613426,0.00027016227,0.0002167782,0.0003511197,0.00011304069],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001331779,0.0005713394,0.00060976937,0.0006833864,0.00037938348,0.0006607818,0.0006153774,0.0006591364,0.002007502],"category_scores_gemma":[0.0064077424,0.00037872256,0.0003554376,0.00047810946,0.0008006854,0.00082758535,0.00079728774,0.00071244495,0.0003652124],"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":[0.00013868313,0.00007822151,0.0010126235,0.00007877818,0.000025985128,0.00012485143,0.00009124426,0.89331955,0.010269633,0.04106419,0.00068037293,0.053115908],"study_design_scores_gemma":[0.000023169152,0.00008370805,0.00014825875,0.000007251866,0.0000048251163,0.000033147222,0.000014459931,0.9842024,0.0020434922,0.01275073,0.00068033667,0.000008213186],"about_ca_topic_score_codex":0.0005953917,"about_ca_topic_score_gemma":0.0006209506,"teacher_disagreement_score":0.002007502,"about_ca_system_score_codex":0.0006260411,"about_ca_system_score_gemma":0.00054504204,"threshold_uncertainty_score":0.007043183},"labels":[],"label_agreement":null},{"id":"W2103255584","doi":"10.1145/1596519.1596520","title":"Generalized Halton sequences in 2008","year":2009,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Mathematical Approximation and Integration","field":"Mathematics","cited_by":74,"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 Waterloo","funders":"","keywords":"Sobol sequence; Computer science; Sequence (biology); Algorithm; Theoretical computer science; Mathematics; Statistics; Monte Carlo method","score_opus":0.08529437444045551,"score_gpt":0.3364752737771421,"score_spread":0.2511808993366866,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2103255584","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":[0.08697106,0.002961267,0.8672967,0.0011514883,0.00087526,0.00021568993,0.0004606781,0.00084505155,0.039222766],"genre_scores_gemma":[0.6114767,0.0029079965,0.33991465,0.0012448553,0.00035694285,0.0007488772,0.0012713003,0.0006157206,0.04146296],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9983266,0.00064255454,0.00011801048,0.0002453826,0.00050352846,0.00016382149],"domain_scores_gemma":[0.99665254,0.0014714657,0.0002046106,0.00058934954,0.0008467506,0.00023530351],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021147865,0.0009621273,0.0010402476,0.0011769717,0.0010935679,0.001960398,0.0011710168,0.0015744601,0.013655731],"category_scores_gemma":[0.010780524,0.00039906756,0.00087287306,0.001102888,0.0018186321,0.0032196748,0.0022665132,0.002351098,0.0025704156],"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":[0.00029205682,0.000036355985,0.0006064164,0.00022746317,0.000027148708,0.00016832976,0.00028095217,0.048929866,0.0040789293,0.87202513,0.006454672,0.06687264],"study_design_scores_gemma":[0.000086385044,0.00034359322,0.00043041084,0.00013499467,0.000021832293,0.00043704876,0.00021374674,0.27226728,0.011061252,0.663655,0.051254928,0.00009365416],"about_ca_topic_score_codex":0.00092505035,"about_ca_topic_score_gemma":0.0007236424,"teacher_disagreement_score":0.013655731,"about_ca_system_score_codex":0.0014840807,"about_ca_system_score_gemma":0.0014741907,"threshold_uncertainty_score":0.045682967},"labels":[],"label_agreement":null},{"id":"W2117513650","doi":"10.1145/502109.502110","title":"Packet delay in models of data networks","year":2001,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Interconnection Networks and Systems","field":"Computer Science","cited_by":20,"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 Guelph; Brock University","funders":"","keywords":"Routing table; Computer science; Network packet; Table (database); Routing (electronic design automation); Processing delay; Network delay; End-to-end delay; Computer network; Scalability; Source routing; Routing protocol; Transmission delay; Data mining","score_opus":0.08770757930442849,"score_gpt":0.2956826076131928,"score_spread":0.20797502830876433,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2117513650","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":[0.33259904,0.0037323255,0.6356395,0.002892235,0.00044941102,0.00023303997,0.0012111218,0.00057604123,0.022667302],"genre_scores_gemma":[0.9661973,0.0024057936,0.01975974,0.00025867773,0.0001793347,0.00023778659,0.0003187683,0.00012909778,0.010513562],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994685,0.00018361256,0.000020563228,0.00010136472,0.00011958488,0.00010633949],"domain_scores_gemma":[0.99694675,0.00214024,0.0003186811,0.00014742234,0.00026854483,0.00017838446],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010307742,0.0009550497,0.00083298347,0.00078246393,0.0007686463,0.0019047046,0.0014621094,0.0014108643,0.0021373772],"category_scores_gemma":[0.0074643833,0.00061118155,0.0005588812,0.001043722,0.0012702474,0.0031209057,0.0010549297,0.0010170382,0.0004054306],"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":[0.00009627005,0.000039127994,0.00058302406,0.000058224643,0.00001935689,0.00009025503,0.00008479727,0.9178781,0.0010547375,0.077238105,0.0009006298,0.0019574384],"study_design_scores_gemma":[0.000016395523,0.000032385116,0.00007228423,0.0000056447125,0.000009879022,0.00001929103,0.000021812475,0.9739328,0.00020802347,0.024836555,0.00083641725,0.0000083576415],"about_ca_topic_score_codex":0.0057003694,"about_ca_topic_score_gemma":0.0023452144,"teacher_disagreement_score":0.0057003694,"about_ca_system_score_codex":0.0024047957,"about_ca_system_score_gemma":0.0009657471,"threshold_uncertainty_score":0.017448068},"labels":[],"label_agreement":null},{"id":"W2118479715","doi":"10.1145/1667072.1667078","title":"Asymptotic robustness of estimators in rare-event simulation","year":2010,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Probability and Risk Models","field":"Decision Sciences","cited_by":101,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Division of Mathematical Sciences; Natural Sciences and Engineering Research Council of Canada; United States - Israel Binational Science Foundation","keywords":"Estimator; Mathematics; Robustness (evolution); Bounded function; Logarithm; Applied mathematics; Second moment of area; Delta method; Moment (physics); Statistics; Mathematical analysis","score_opus":0.08354774896116872,"score_gpt":0.3690416328269024,"score_spread":0.28549388386573366,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2118479715","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":[0.020561421,0.00041806579,0.9770896,0.00026073243,0.000020729325,0.000031071548,0.000051917275,0.0002814612,0.0012850225],"genre_scores_gemma":[0.8752198,0.00084190205,0.12094376,0.00027449924,0.00010632145,0.00024889494,0.00025656517,0.00021542057,0.0018929741],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9933297,0.004104125,0.00033074943,0.00079784455,0.001074801,0.00036268463],"domain_scores_gemma":[0.8850478,0.10097027,0.0061838366,0.004664423,0.0023894086,0.0007443196],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015906012,0.00091369264,0.001482169,0.0018405049,0.00051699986,0.0019025591,0.0018806692,0.0015840598,0.0011206511],"category_scores_gemma":[0.10284262,0.0007451483,0.0012238905,0.00077442406,0.0037507887,0.0026958724,0.0029352491,0.0020714083,0.00028434547],"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":[0.00014818275,0.000031453794,0.004005338,0.00019066496,0.00013345272,0.00020326629,0.0001843241,0.77903193,0.003160209,0.2018569,0.00033471597,0.010719578],"study_design_scores_gemma":[0.000009071222,0.00003629205,0.00038960148,0.000030430332,0.000012267582,0.000040156207,0.000014314353,0.95298946,0.00115707,0.045066137,0.00023569465,0.000019434074],"about_ca_topic_score_codex":0.0022583522,"about_ca_topic_score_gemma":0.0007541228,"teacher_disagreement_score":0.015906012,"about_ca_system_score_codex":0.0016324671,"about_ca_system_score_gemma":0.0012272185,"threshold_uncertainty_score":0.084120035},"labels":[],"label_agreement":null},{"id":"W2131579983","doi":"10.1145/2043635.2043636","title":"The Effect of Robust Decisions on the Cost of Uncertainty in Military Airlift Operations","year":2011,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":54,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Defence Research and Development Canada","funders":"Air Force Office of Scientific Research","keywords":"Randomness; Airlift; Operations research; Computer science; Mathematical optimization; Dynamic programming; Robust optimization; Stochastic programming; Mathematics; Statistics","score_opus":0.058818627507876614,"score_gpt":0.24686031346182818,"score_spread":0.18804168595395157,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2131579983","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":[0.9711627,0.000678122,0.021674251,0.001126976,0.000039659833,0.00007679553,0.00020712106,0.0001053399,0.0049289493],"genre_scores_gemma":[0.99714607,0.00009284712,0.002500657,0.000052542688,0.000007403289,0.00001280548,0.000034667446,0.000009576513,0.00014345787],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9942006,0.0032971879,0.00029203316,0.0004177011,0.00094830047,0.00084431475],"domain_scores_gemma":[0.82913864,0.15540977,0.008350671,0.0038480237,0.0023393193,0.00091356144],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012192123,0.0007531967,0.0010492261,0.0006504178,0.00086622697,0.0025099146,0.0009607277,0.0015731787,0.0023239364],"category_scores_gemma":[0.08309905,0.0006725621,0.0006210763,0.0008761562,0.0015853075,0.0027852831,0.0011718817,0.0023697307,0.0001114935],"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":[0.0009260013,0.00012983248,0.0048840228,0.00006753115,0.00006429179,0.0001411842,0.00009417891,0.9731121,0.0012668609,0.0070497543,0.00030815735,0.011956087],"study_design_scores_gemma":[0.00014701333,0.00095840916,0.017203555,0.00004334307,0.00012547188,0.000104086226,0.00045708448,0.9609958,0.003371865,0.015965162,0.00052339514,0.00010481939],"about_ca_topic_score_codex":0.01577854,"about_ca_topic_score_gemma":0.008174241,"teacher_disagreement_score":0.01577854,"about_ca_system_score_codex":0.0038631267,"about_ca_system_score_gemma":0.0016821304,"threshold_uncertainty_score":0.064478815},"labels":[],"label_agreement":null},{"id":"W2143988898","doi":"10.1145/511442.511445","title":"Estimation of blocking probabilities in cellular networks with dynamic channel assignment","year":2002,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","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":"Université de Montréal","funders":"","keywords":"Blocking (statistics); Computer science; Estimator; Channel (broadcasting); Importance sampling; Mathematical optimization; Call blocking; Algorithm; Mathematics; Statistics; Monte Carlo method; Telecommunications","score_opus":0.018287219481313913,"score_gpt":0.21423291536648023,"score_spread":0.1959456958851663,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2143988898","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":[0.68222606,0.00017315571,0.3157658,0.00015432133,0.00001347563,0.00003974951,0.000051263287,0.00029410093,0.0012820272],"genre_scores_gemma":[0.98756593,0.00004609852,0.012192908,0.000008376043,0.0000047659214,0.000015389087,0.000039997234,0.000009190244,0.00011736516],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990609,0.00039299447,0.00003111569,0.00011435296,0.00022738635,0.00017331105],"domain_scores_gemma":[0.9888353,0.008573862,0.0010829285,0.0005962429,0.0006423011,0.00026935726],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002669976,0.00049717556,0.0005655246,0.0010898925,0.00049709855,0.00088821707,0.0009706496,0.00067405816,0.0003260327],"category_scores_gemma":[0.014081464,0.00052412576,0.0002824463,0.00094522006,0.0011101098,0.0012473892,0.0008405485,0.00076420204,0.00004832868],"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":[0.00005798348,0.000027156697,0.0034178887,0.0000076718,0.000010446462,0.000015627293,0.00002542152,0.9881693,0.00059540936,0.003467677,0.000060576556,0.0041448884],"study_design_scores_gemma":[0.0000024733731,0.000007032766,0.00026380896,7.2058384e-7,0.0000017081295,0.000003683481,0.0000046595196,0.9985227,0.00031173445,0.00085850235,0.000020856804,0.0000021038543],"about_ca_topic_score_codex":0.014542014,"about_ca_topic_score_gemma":0.0054917247,"teacher_disagreement_score":0.014542014,"about_ca_system_score_codex":0.0018226105,"about_ca_system_score_gemma":0.001067314,"threshold_uncertainty_score":0.02891475},"labels":[],"label_agreement":null},{"id":"W2152980722","doi":"10.1145/2414416.2414790","title":"Self-Avoiding Random Dynamics on Integer Complex Systems","year":2013,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Markov Chains and Monte Carlo Methods","field":"Mathematics","cited_by":15,"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 British Columbia; D-Wave Systems (Canada)","funders":"","keywords":"Ising model; Computer science; Gibbs sampling; Monte Carlo algorithm; Monte Carlo method; Statistical physics; Algorithm; State space; Sampling (signal processing); Theoretical computer science; Mathematics; Bayesian probability; Artificial intelligence; Physics","score_opus":0.0834318275074199,"score_gpt":0.3251388237474979,"score_spread":0.24170699624007802,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2152980722","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":[0.12749648,0.00020059822,0.867327,0.000257488,0.000028112794,0.00004947472,0.00004008102,0.0002749124,0.0043257917],"genre_scores_gemma":[0.7783745,0.00020259623,0.21827136,0.00012510849,0.000023920153,0.00014607886,0.0000952597,0.00013168562,0.0026294473],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995265,0.00022502236,0.00002269905,0.00006943273,0.00011534622,0.000040917486],"domain_scores_gemma":[0.99893945,0.0006504373,0.000114264825,0.00013734512,0.00007459794,0.00008388159],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009326058,0.0003060519,0.00048385226,0.00047759796,0.00040057788,0.0008833315,0.0007082901,0.0006404842,0.0016854247],"category_scores_gemma":[0.0036606446,0.0003122018,0.00038840197,0.00029595033,0.00117972,0.0013678826,0.000910639,0.000882643,0.00024541953],"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":[0.00007401634,0.000050267,0.00084037235,0.00005182042,0.000020859377,0.000113834314,0.00013627873,0.51966625,0.0049720574,0.457276,0.00061984616,0.01617837],"study_design_scores_gemma":[0.00000874105,0.0000073103533,0.000047548678,0.0000028593379,0.0000012569807,0.000014274756,0.000004716949,0.9597673,0.00046586755,0.03931815,0.00035778302,0.0000041882017],"about_ca_topic_score_codex":0.0011078392,"about_ca_topic_score_gemma":0.0009634147,"teacher_disagreement_score":0.0016854247,"about_ca_system_score_codex":0.00078862655,"about_ca_system_score_gemma":0.00048098923,"threshold_uncertainty_score":0.0057219267},"labels":[],"label_agreement":null},{"id":"W2164907674","doi":"10.1145/1899396.1899398","title":"The double CFTP method","year":2011,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Hungkuang University; Hong Kong University of Science and Technology; Research Grants Council, University Grants Committee","keywords":"Mathematics; Dirichlet distribution; Markov chain; Poisson distribution; Coalescence (physics); Combinatorics; Limit (mathematics); Poisson point process; Applied mathematics; Distribution (mathematics); Identity (music); Bessel function; Discrete mathematics; Mathematical analysis; Boundary value problem; Statistics; Physics","score_opus":0.07555412885911102,"score_gpt":0.31413135928981406,"score_spread":0.23857723043070306,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2164907674","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":[0.0029557871,0.00015121684,0.99258244,0.00016019962,0.0000916248,0.000066067914,0.00013473588,0.00046035543,0.0033975737],"genre_scores_gemma":[0.19390713,0.00036317552,0.79241556,0.00040914252,0.00018336618,0.0005996816,0.0006895601,0.000599701,0.010832569],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980636,0.00058692234,0.000079358535,0.00036868567,0.00072434195,0.00017708221],"domain_scores_gemma":[0.99383956,0.0031820168,0.0002799706,0.0012924781,0.0011432517,0.00026276035],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032821577,0.0007693201,0.0015957025,0.0016846667,0.0010893574,0.002157688,0.0036870888,0.0029480038,0.013134981],"category_scores_gemma":[0.016846461,0.0007726708,0.0012827244,0.001680448,0.0013894062,0.0027337787,0.0027385694,0.002378273,0.003083805],"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":[0.00021293863,0.00010411763,0.0021447607,0.00026973896,0.00012370714,0.00045276355,0.00021605464,0.44888023,0.0020300967,0.35579643,0.009142501,0.18062672],"study_design_scores_gemma":[0.0000324785,0.000018990217,0.00009444958,0.000027056052,0.0000116557,0.000103453865,0.000014897576,0.90554434,0.00053059816,0.08842216,0.0051851575,0.0000146899465],"about_ca_topic_score_codex":0.0054776296,"about_ca_topic_score_gemma":0.0037258198,"teacher_disagreement_score":0.013134981,"about_ca_system_score_codex":0.0012257332,"about_ca_system_score_gemma":0.0024274657,"threshold_uncertainty_score":0.0439409},"labels":[],"label_agreement":null},{"id":"W2237934651","doi":"10.1145/2775106","title":"Static Network Reliability Estimation under the Marshall-Olkin Copula","year":2016,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Australian Research Council; Canada Research Chairs","keywords":"Monte Carlo method; Estimator; Copula (linguistics); Computer science; Mathematical optimization; Bounded function; Mathematics; Algorithm; Econometrics; Statistics","score_opus":0.08701479158394684,"score_gpt":0.32700985599127497,"score_spread":0.23999506440732812,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2237934651","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":[0.015755994,0.000095971074,0.98328155,0.00007976209,0.000009000506,0.000018827111,0.000041883053,0.00016523102,0.0005518171],"genre_scores_gemma":[0.77957875,0.00051699916,0.21700573,0.00011821166,0.000070459486,0.00014145697,0.0003994679,0.00019147524,0.0019774095],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988927,0.00046551955,0.00003977987,0.00028486943,0.000214794,0.000102364604],"domain_scores_gemma":[0.99494135,0.002929939,0.0007247206,0.00076533674,0.0005181096,0.00012067376],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002980422,0.0010208256,0.0012394536,0.0010175292,0.00044903968,0.00080931577,0.0018125336,0.0008865758,0.0016411586],"category_scores_gemma":[0.0148508,0.000724956,0.000975049,0.0011318799,0.0012163804,0.002697546,0.0014145573,0.0019702213,0.00031546847],"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":[0.000024213658,0.000012209122,0.0012132737,0.00002694616,0.000039436873,0.000053022934,0.000040154602,0.9446225,0.0006017463,0.040478263,0.0005572275,0.01233096],"study_design_scores_gemma":[0.0000021336725,0.000007970204,0.00021437382,0.0000032568428,0.000004636563,0.000013900481,0.0000054054576,0.98387605,0.00018731946,0.015515252,0.00016381698,0.0000058576784],"about_ca_topic_score_codex":0.00767829,"about_ca_topic_score_gemma":0.0041865595,"teacher_disagreement_score":0.00767829,"about_ca_system_score_codex":0.0012375183,"about_ca_system_score_gemma":0.0012046357,"threshold_uncertainty_score":0.01576221},"labels":[],"label_agreement":null},{"id":"W2252287572","doi":"10.1145/2827696","title":"PAM","year":2016,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Computer science; Cellular automaton; Bridging (networking); Theoretical computer science; Scope (computer science); Automaton; Graph; Biological system; Particle system; Algorithm; Biology","score_opus":0.013099916203501287,"score_gpt":0.24817351557142087,"score_spread":0.23507359936791958,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2252287572","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":[0.006102832,0.001528093,0.69027054,0.0031799427,0.0019075063,0.00021084415,0.0030220966,0.015457786,0.27832043],"genre_scores_gemma":[0.18864189,0.0029553673,0.5492658,0.0024246091,0.00094282016,0.0008773002,0.009378046,0.004504773,0.24100937],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992268,0.00018951845,0.000054569606,0.00021250399,0.00024839686,0.000068241876],"domain_scores_gemma":[0.998793,0.00024091471,0.000053842406,0.0006105256,0.00022571362,0.00007597415],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000832085,0.00068780297,0.0006695202,0.0007787039,0.000961326,0.0024775171,0.0016581188,0.0013591608,0.09355071],"category_scores_gemma":[0.0028429057,0.00043513192,0.00087747874,0.0008449003,0.00060837215,0.0030912785,0.0026091174,0.0014757048,0.041957133],"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":[0.00012536928,0.00007999551,0.00078113686,0.0003129744,0.00005046644,0.00020431698,0.00015795094,0.023744063,0.0068536703,0.5894923,0.14052857,0.23766923],"study_design_scores_gemma":[0.000031499596,0.00004766809,0.00032629113,0.00006461972,0.00002150841,0.00042402642,0.000048340415,0.13401143,0.004072745,0.17334619,0.68756986,0.000035762136],"about_ca_topic_score_codex":0.0014782837,"about_ca_topic_score_gemma":0.0020172363,"teacher_disagreement_score":0.09355071,"about_ca_system_score_codex":0.00076121953,"about_ca_system_score_gemma":0.0010841896,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W2295070894","doi":"10.1145/945511.945512","title":"Guest introduction","year":2003,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Simulation Techniques and Applications","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer science","score_opus":0.11340201678110604,"score_gpt":0.37828863456396594,"score_spread":0.26488661778285993,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2295070894","genre_codex":"other","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008915487,0.0040097106,0.006550428,0.02249872,0.141391,0.00051594496,0.009973938,0.008992168,0.80517656],"genre_scores_gemma":[0.0025114713,0.0022014838,0.0012252103,0.004125322,0.020053048,0.0001344022,0.0042358795,0.0022354336,0.96327776],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987129,0.00010217864,0.000056253346,0.00022320844,0.00066544476,0.00024014624],"domain_scores_gemma":[0.99460053,0.0003823923,0.0001867458,0.00040769667,0.002551774,0.0018709127],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0010735968,0.001832205,0.0011718739,0.0022463342,0.0022604181,0.0077097192,0.002371235,0.0026126935,0.7990275],"category_scores_gemma":[0.0065765562,0.0006385561,0.001192167,0.0016048782,0.0006466188,0.004198805,0.00514919,0.0037262482,0.6817756],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020230234,0.000013126118,0.000040726056,0.000047101657,0.0000012187971,0.000033105913,0.000023820021,0.000022890456,0.00013279216,0.00086559623,0.98245853,0.016340852],"study_design_scores_gemma":[0.0000039987754,0.000009343351,0.000088602705,0.00003932677,0.0000014395468,0.00003777196,0.00002715371,0.000025938782,0.00005457972,0.00043035316,0.9992767,0.000004768195],"about_ca_topic_score_codex":0.0037702143,"about_ca_topic_score_gemma":0.0058237105,"teacher_disagreement_score":0.7990275,"about_ca_system_score_codex":0.0022261709,"about_ca_system_score_gemma":0.0026202856,"threshold_uncertainty_score":0.28666288},"labels":[],"label_agreement":null},{"id":"W2549616710","doi":"10.1145/2987373","title":"Multithreaded Stochastic PDES for Reactions and Diffusions in Neurons","year":2016,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"National Institutes of Health; National Institute of Mental Health; China Scholarship Council; U.S. National Library of Medicine; National Natural Science Foundation of China","keywords":"Computer science; Mathematical optimization; Parallel computing; Applied mathematics; Theoretical computer science; Mathematics","score_opus":0.023603215357950888,"score_gpt":0.26144662696955806,"score_spread":0.23784341161160716,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2549616710","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":[0.1274637,0.00046384404,0.86289734,0.0004988865,0.00018089385,0.00013202634,0.00036951437,0.0008615992,0.0071321805],"genre_scores_gemma":[0.831488,0.0005572619,0.1570508,0.00016598996,0.00006872881,0.00042097183,0.000312398,0.00025337155,0.009682593],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997398,0.00006129719,0.000020689627,0.00003866688,0.00010232477,0.000037149348],"domain_scores_gemma":[0.99940646,0.00029906412,0.00006530706,0.00005775917,0.00010921886,0.000062189734],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00064243627,0.0004388489,0.0008503931,0.00039759817,0.0007392182,0.0008573879,0.0015714548,0.0010726225,0.0025943655],"category_scores_gemma":[0.0019816784,0.00043062135,0.0013174653,0.0004385022,0.00076668063,0.0008982063,0.0009627572,0.0012718987,0.00026225057],"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":[0.00002859427,0.000029048442,0.0008087787,0.000031900247,0.000020415026,0.0000865871,0.000068942456,0.9704652,0.0034403396,0.022042135,0.0003059118,0.0026721216],"study_design_scores_gemma":[0.000007898495,0.000004080247,0.000048259815,0.0000011485029,0.0000019849685,0.0000071467016,0.0000032939804,0.9977102,0.00030751654,0.0015906873,0.00031487003,0.0000028401923],"about_ca_topic_score_codex":0.011362202,"about_ca_topic_score_gemma":0.0069894376,"teacher_disagreement_score":0.011362202,"about_ca_system_score_codex":0.0012405873,"about_ca_system_score_gemma":0.0018871588,"threshold_uncertainty_score":0.022592127},"labels":[],"label_agreement":null},{"id":"W2600394393","doi":"10.1145/3129130","title":"Green Simulation","year":2017,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":43,"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 Waterloo","funders":"","keywords":"Estimator; Stochastic simulation; Computer science; Weighting; Convergence (economics); Simulation modeling; Kriging; Mathematical optimization; Mean squared error; Applied mathematics; Mathematics; Statistics; Machine learning","score_opus":0.06756534662439492,"score_gpt":0.27382441710832073,"score_spread":0.2062590704839258,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2600394393","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":[0.0039018467,0.00020042123,0.9874922,0.000568325,0.00016820198,0.00024236937,0.00027460462,0.00060037675,0.006551723],"genre_scores_gemma":[0.2233685,0.0006117046,0.7644337,0.0012967929,0.0001930765,0.0026855276,0.0008691074,0.0005942305,0.0059473454],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.98540884,0.010413396,0.00044832967,0.0012136141,0.0021176557,0.00039818496],"domain_scores_gemma":[0.95184964,0.033048976,0.002089125,0.00929221,0.0028998998,0.0008201559],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01590125,0.0010783349,0.0014739282,0.0016978161,0.00067584676,0.0028822331,0.003061016,0.0021767002,0.011819072],"category_scores_gemma":[0.06019573,0.0006563231,0.0017404684,0.001554994,0.0022614207,0.0030488593,0.0036479947,0.0029998247,0.0017996553],"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":[0.00031437093,0.00021655217,0.0036098727,0.00035340607,0.00029194745,0.000121441924,0.0002716253,0.40359646,0.0015834173,0.50026345,0.0070453845,0.08233213],"study_design_scores_gemma":[0.00013748168,0.00018093562,0.00048505646,0.00010781309,0.000060507606,0.00006293272,0.000045243996,0.635896,0.0014889066,0.33896536,0.022525309,0.00004450154],"about_ca_topic_score_codex":0.0017882141,"about_ca_topic_score_gemma":0.0018357876,"teacher_disagreement_score":0.01590125,"about_ca_system_score_codex":0.0016965672,"about_ca_system_score_gemma":0.002961433,"threshold_uncertainty_score":0.08409488},"labels":[],"label_agreement":null},{"id":"W2803763401","doi":"10.1145/3230636","title":"Fast Random Integer Generation in an Interval","year":2019,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Chaos-based Image/Signal Encryption","field":"Computer Science","cited_by":49,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université TÉLUQ; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Integer (computer science); Interval (graph theory); Integer programming; Computer science; Mathematics; Combinatorics; Algorithm; Discrete mathematics","score_opus":0.03575391139524498,"score_gpt":0.2759761731571362,"score_spread":0.2402222617618912,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2803763401","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":[0.011363258,0.00013482766,0.98241454,0.00007638773,0.00004875015,0.00006230192,0.00010717011,0.0025265666,0.0032661704],"genre_scores_gemma":[0.28596628,0.00022312817,0.707061,0.00023075899,0.00005110565,0.00041626676,0.00047002296,0.0011221723,0.00445923],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985561,0.00039645197,0.000094225616,0.0002492763,0.000564992,0.00013901759],"domain_scores_gemma":[0.997523,0.0013756241,0.0001696824,0.000482674,0.00038692862,0.00006208568],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016111387,0.00048960175,0.00058894325,0.000831382,0.0005035371,0.0009938835,0.0009454524,0.00066104316,0.0051615597],"category_scores_gemma":[0.006972239,0.00030450238,0.00056065334,0.00078751094,0.000770953,0.0016857979,0.0012058876,0.00097246934,0.0019107169],"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":[0.0007093551,0.00014727876,0.0030146225,0.00039016746,0.000067393514,0.00053167675,0.00051949004,0.16317008,0.03913112,0.46282598,0.01118454,0.31830826],"study_design_scores_gemma":[0.00011628155,0.00018198682,0.00043072316,0.00007356383,0.000029674724,0.00053408515,0.00005109087,0.7636572,0.05253629,0.15291339,0.029396499,0.00007914889],"about_ca_topic_score_codex":0.0003815946,"about_ca_topic_score_gemma":0.00039027966,"teacher_disagreement_score":0.0051615597,"about_ca_system_score_codex":0.00045530745,"about_ca_system_score_gemma":0.00073609914,"threshold_uncertainty_score":0.017267108},"labels":[],"label_agreement":null},{"id":"W2899063537","doi":"10.1145/3317605","title":"Infinite Swapping using IID Samples","year":2019,"lang":"en","type":"preprint","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Probability and Risk Models","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Defense Advanced Research Projects Agency; U.S. Department of Energy; Wind Energy Technologies Office; National Science Foundation","keywords":"Rare events; Event (particle physics); Estimator; Scaling; Construct (python library); Variance (accounting); Variance reduction; Sampling (signal processing); Importance sampling; Mathematics; Statistical physics; Statistics; Variance components; Computer science; Algorithm; Applied mathematics; Monte Carlo method; Physics","score_opus":0.32085989360389405,"score_gpt":0.40377503774998336,"score_spread":0.0829151441460893,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2899063537","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":[0.003368982,0.000046622215,0.99603987,0.00003450773,0.00002174927,0.000020267544,0.000019589967,0.000113167436,0.00033522682],"genre_scores_gemma":[0.22128353,0.00026063801,0.77345425,0.0002584115,0.00017553901,0.00034330116,0.00034766473,0.00022820313,0.0036484166],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9963697,0.001747557,0.0001354291,0.0006811547,0.00090385275,0.00016226838],"domain_scores_gemma":[0.9865741,0.009231089,0.000910928,0.0023167392,0.0006390107,0.0003281922],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0069234846,0.00085310626,0.0015583051,0.0016456352,0.00060826604,0.0017890254,0.0029847485,0.0013067655,0.00398262],"category_scores_gemma":[0.025614908,0.0010112976,0.0012772931,0.0013944396,0.002575445,0.0033386757,0.002865549,0.0027561567,0.0010305498],"study_design_candidate":"theoretical_or_conceptual","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":[0.00045531528,0.00018681328,0.00436615,0.00022297286,0.00024896846,0.00042399377,0.00038908582,0.42528164,0.008166308,0.3374673,0.002238778,0.22055277],"study_design_scores_gemma":[0.000026873779,0.00004719514,0.0003471855,0.000016269578,0.000019270552,0.000087203174,0.000010086417,0.90627694,0.002245807,0.08932196,0.0015738714,0.00002740345],"about_ca_topic_score_codex":0.0006439829,"about_ca_topic_score_gemma":0.0006934623,"teacher_disagreement_score":0.0069234846,"about_ca_system_score_codex":0.00067426986,"about_ca_system_score_gemma":0.00086519873,"threshold_uncertainty_score":0.036615312},"labels":[],"label_agreement":null},{"id":"W3004559630","doi":"10.1145/3338530","title":"Extending Explicitly Modelled Simulation Debugging Environments with Dynamic Structure","year":2020,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Simulation Techniques and Applications","field":"Decision Sciences","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":"Autodesk (Canada)","funders":"Vlaamse regering; Flanders Make","keywords":"Rotation formalisms in three dimensions; Debugging; Computer science; Workflow; Modular design; DEVS; Programming language; Semantics (computer science); NetLogo; Distributed computing; Software engineering; Modeling and simulation; Simulation","score_opus":0.09033757020319406,"score_gpt":0.35236828015438587,"score_spread":0.2620307099511918,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3004559630","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":[0.0031785562,0.000029840756,0.9899301,0.00012745765,0.000026238486,0.0000463046,0.00004866204,0.0055739987,0.0010389802],"genre_scores_gemma":[0.09984219,0.00018614289,0.8950429,0.00015463404,0.000032863067,0.00022698124,0.00039714953,0.002211908,0.0019052416],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9952127,0.0021233517,0.0005448124,0.00063442736,0.0011907892,0.00029391827],"domain_scores_gemma":[0.98463976,0.0070696026,0.0009885174,0.0058338325,0.0011312561,0.00033694907],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008683711,0.0013941706,0.00087443483,0.0015274909,0.00086909824,0.0035429664,0.0038363065,0.0019695733,0.0037102848],"category_scores_gemma":[0.022676127,0.0016366739,0.0023682297,0.00087656034,0.002597132,0.0062574097,0.007760132,0.0033449524,0.0011328888],"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":[0.0003553728,0.00041852545,0.006431344,0.0006765422,0.0001860752,0.0013343733,0.0044389227,0.29002333,0.015829349,0.49630636,0.005673133,0.17832656],"study_design_scores_gemma":[0.00014766086,0.000114653776,0.0004585893,0.00026769337,0.00007500235,0.00048381236,0.00015579148,0.72432786,0.02012026,0.17858435,0.075152375,0.00011194453],"about_ca_topic_score_codex":0.001949972,"about_ca_topic_score_gemma":0.0027160794,"teacher_disagreement_score":0.008683711,"about_ca_system_score_codex":0.0010263054,"about_ca_system_score_gemma":0.0027759902,"threshold_uncertainty_score":0.045924425},"labels":[],"label_agreement":null},{"id":"W3113794249","doi":"10.1145/3434490","title":"Discrete-Event Modeling and Simulation of Diffusion Processes in Multiplex Networks","year":2020,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Opinion Dynamics and Social Influence","field":"Physics and Astronomy","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada; Banco Santander","keywords":"DEVS; Computer science; Process (computing); Diffusion; Distributed computing; Discrete event simulation; Usability; Set (abstract data type); Multiplex; Diffusion process; Modeling and simulation; Simulation; Programming language; Innovation diffusion","score_opus":0.026758952734707655,"score_gpt":0.28523316173679725,"score_spread":0.2584742090020896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3113794249","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":[0.25905043,0.00015117628,0.7301769,0.00045744525,0.000044370405,0.00014806562,0.00028973105,0.00047479605,0.009206971],"genre_scores_gemma":[0.9306005,0.00014582195,0.06615085,0.000033067536,0.000010215085,0.00015439883,0.000107542764,0.000024203848,0.0027733077],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995455,0.00022210719,0.00003295283,0.000058890055,0.00009403785,0.000046495188],"domain_scores_gemma":[0.99788034,0.0015827109,0.00017830137,0.00013422311,0.00013097962,0.00009351581],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012978956,0.00038080913,0.00040159663,0.00057996035,0.00048199508,0.0012384941,0.0006877096,0.00090506655,0.001913946],"category_scores_gemma":[0.0041241446,0.00027132037,0.0005837523,0.0005090437,0.0007299105,0.0012526673,0.00082371494,0.00072567654,0.00013859001],"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":[0.000028336759,0.00003241642,0.0012152306,0.000016666236,0.000012111181,0.00006517576,0.0001232536,0.96226406,0.0006953327,0.032667894,0.00009848466,0.0027810168],"study_design_scores_gemma":[0.0000044642425,0.000004874623,0.000059685237,0.0000017285623,0.0000022293398,0.000004433212,0.000010775249,0.9964647,0.0002466358,0.002932323,0.00026588255,0.0000022041195],"about_ca_topic_score_codex":0.008871917,"about_ca_topic_score_gemma":0.004460312,"teacher_disagreement_score":0.008871917,"about_ca_system_score_codex":0.0010448935,"about_ca_system_score_gemma":0.00070871843,"threshold_uncertainty_score":0.017640531},"labels":[],"label_agreement":null},{"id":"W3117918501","doi":"10.1145/3427753","title":"Application of Simulation in Healthcare Service Operations","year":2020,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Health care; Popularity; Computer science; Healthcare service; Service delivery framework; Management science; Domain (mathematical analysis); Service (business); Healthcare delivery; Process management; Knowledge management; Risk analysis (engineering); Operations research; Data science; Medicine; Engineering; Business; Psychology","score_opus":0.1061933032634809,"score_gpt":0.405444636926345,"score_spread":0.2992513336628641,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3117918501","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":[0.043860607,0.0072718677,0.85531944,0.008124084,0.0005508712,0.00044600802,0.0004110604,0.0006601492,0.083355784],"genre_scores_gemma":[0.7925812,0.012103516,0.18919301,0.0005782409,0.0003327813,0.000462347,0.00034027215,0.000114588634,0.0042940327],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9949502,0.003990898,0.00022575492,0.00022782995,0.00046130398,0.00014407242],"domain_scores_gemma":[0.9888297,0.009737494,0.00034157996,0.0004210727,0.00050282554,0.00016725411],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003668964,0.00074974116,0.000760733,0.001880968,0.0009074572,0.0030977672,0.0012585105,0.0017780514,0.0050860173],"category_scores_gemma":[0.0146840615,0.0004156572,0.0010200386,0.0023421473,0.001381341,0.001822954,0.0024561617,0.0014440749,0.00058006187],"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":[0.000091000955,0.00013002631,0.0051480583,0.00049199996,0.0001230813,0.00020635845,0.00090687163,0.7229123,0.00066589314,0.1909313,0.002586674,0.07580641],"study_design_scores_gemma":[0.000035774665,0.000100056764,0.00076541165,0.00038493276,0.00003997321,0.00009069736,0.00059321,0.8648728,0.00071900105,0.10453123,0.027824294,0.00004248683],"about_ca_topic_score_codex":0.010597853,"about_ca_topic_score_gemma":0.0062447526,"teacher_disagreement_score":0.010597853,"about_ca_system_score_codex":0.0022124988,"about_ca_system_score_gemma":0.0037194304,"threshold_uncertainty_score":0.021072328},"labels":[],"label_agreement":null},{"id":"W3123679449","doi":"10.1145/3429336","title":"Green Simulation with Database Monte Carlo","year":2021,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":5,"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 Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Control variates; Variance reduction; Computer science; Monte Carlo method; Variance (accounting); Convergence (economics); Reduction (mathematics); Idle; Database; Mathematical optimization; Simulation; Statistics; Mathematics; Monte Carlo molecular modeling","score_opus":0.11204015738904748,"score_gpt":0.32694047555853806,"score_spread":0.21490031816949057,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3123679449","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":[0.017709192,0.000098375895,0.97950065,0.0001275845,0.000029449511,0.000113084614,0.00006344609,0.0004204248,0.001937821],"genre_scores_gemma":[0.56305337,0.00015723566,0.43265128,0.00026616,0.000043017248,0.0010290615,0.0002579625,0.00022741806,0.0023145506],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99472517,0.0034348823,0.00015307889,0.00057499093,0.0008713655,0.0002405643],"domain_scores_gemma":[0.9721352,0.021696439,0.0011468722,0.0033943388,0.0012743224,0.0003528916],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008880114,0.0008038059,0.0011049012,0.0011279167,0.0006224553,0.0017462673,0.0022345867,0.0017791536,0.0031803665],"category_scores_gemma":[0.028393373,0.00063536566,0.0009781679,0.0012167686,0.001954024,0.0018384927,0.0017229215,0.0018883105,0.00045574494],"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":[0.00028871393,0.00011018076,0.0012634605,0.000058470923,0.000053101074,0.0000432339,0.00008006683,0.8968866,0.0010270211,0.08499527,0.00047497783,0.014718977],"study_design_scores_gemma":[0.000018243341,0.000021423972,0.000056770823,0.0000032801595,0.000004181105,0.0000048098987,0.0000051703764,0.98592687,0.000437256,0.013239856,0.00027725883,0.0000049954488],"about_ca_topic_score_codex":0.004436161,"about_ca_topic_score_gemma":0.0029649509,"teacher_disagreement_score":0.008880114,"about_ca_system_score_codex":0.0015356606,"about_ca_system_score_gemma":0.0018459449,"threshold_uncertainty_score":0.046963036},"labels":[],"label_agreement":null},{"id":"W3184040039","doi":"10.1145/3462202","title":"Explicit Modeling of Personal Space for Improved Local Dynamics in Simulated Crowds","year":2021,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Evacuation and Crowd Dynamics","field":"Engineering","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":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Crowds; Computer science; Crowd simulation; Entertainment; Space (punctuation); Focus (optics); Frame (networking); Human–computer interaction; Distributed computing; Simulation; Computer security; Computer network","score_opus":0.019784935368795865,"score_gpt":0.2495241054533798,"score_spread":0.22973917008458394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3184040039","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":[0.047428153,0.0001443607,0.94593847,0.00028948113,0.000065907654,0.00003949603,0.000056724344,0.00028719683,0.005750257],"genre_scores_gemma":[0.8904878,0.00022545317,0.1029533,0.00010988098,0.000051840678,0.00012804008,0.000082062485,0.00015765788,0.0058040377],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997316,0.00009059062,0.0000102512195,0.000035609075,0.00009357348,0.000038340528],"domain_scores_gemma":[0.9993481,0.0003347899,0.00006447932,0.00009357132,0.00008348925,0.000075611264],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005077851,0.0004975394,0.000719303,0.00041558803,0.00072173367,0.0008130977,0.0013015257,0.0010184263,0.001974416],"category_scores_gemma":[0.002729008,0.00040153923,0.0006181673,0.00039831235,0.0010735103,0.0013871184,0.0022988294,0.0010402373,0.0003782057],"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":[0.000017098475,0.000012163815,0.0002349634,0.000011379551,0.000005402985,0.000047546248,0.00006898596,0.9869747,0.000779101,0.008759648,0.00025937363,0.0028296977],"study_design_scores_gemma":[0.0000026313214,0.0000037778238,0.000022792776,0.0000017627084,9.214143e-7,0.0000071546388,0.0000060653956,0.99807173,0.00011212976,0.0014797635,0.00028892225,0.000002373239],"about_ca_topic_score_codex":0.009890776,"about_ca_topic_score_gemma":0.007663586,"teacher_disagreement_score":0.009890776,"about_ca_system_score_codex":0.0008221388,"about_ca_system_score_gemma":0.0010808381,"threshold_uncertainty_score":0.019666374},"labels":[],"label_agreement":null},{"id":"W3185643228","doi":"10.1145/3459605","title":"Falsification of Hybrid Systems Using Adaptive Probabilistic Search","year":2021,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":24,"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 Waterloo","funders":"Japan Science and Technology Agency; Japan Society for the Promotion of Science","keywords":"Probabilistic logic; Computer science; Robustness (evolution); Discriminative model; Exploit; Baseline (sea); Discretization; Algorithm; Key (lock); Tree traversal; Tree (set theory); Mathematical optimization; Machine learning; Artificial intelligence; Mathematics","score_opus":0.0666532214771873,"score_gpt":0.29892923341253497,"score_spread":0.23227601193534766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3185643228","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":[0.04980948,0.0001590395,0.9463061,0.0002326595,0.000025511485,0.00008284843,0.000052444953,0.0012872847,0.0020446086],"genre_scores_gemma":[0.79609734,0.000059679307,0.20219627,0.0001277492,0.000018882763,0.00014577387,0.00011409331,0.00019162508,0.0010486403],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99783045,0.00078362925,0.00012722025,0.00035306218,0.00065998733,0.0002456722],"domain_scores_gemma":[0.9810628,0.015335561,0.0012434748,0.001154938,0.0008715194,0.00033175535],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003963375,0.0014083325,0.0014309135,0.0013384414,0.00076179503,0.0017830009,0.002077904,0.0020847963,0.0039291],"category_scores_gemma":[0.02288067,0.0007291641,0.0011905511,0.0006200378,0.0030012866,0.002473329,0.0031144517,0.0018991116,0.0004544114],"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":[0.00022072585,0.00004104776,0.0018165576,0.00011421017,0.000063698186,0.0001718667,0.00012376487,0.9338158,0.0022610219,0.025041202,0.00051793,0.03581215],"study_design_scores_gemma":[0.000016033027,0.000030343597,0.000055791046,0.000010358988,0.000006133507,0.00002572373,0.000013033752,0.98578876,0.0008708348,0.013011976,0.00016467355,0.000006288991],"about_ca_topic_score_codex":0.0022151521,"about_ca_topic_score_gemma":0.0023808877,"teacher_disagreement_score":0.003963375,"about_ca_system_score_codex":0.0012373604,"about_ca_system_score_gemma":0.0017327542,"threshold_uncertainty_score":0.020960629},"labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"simulation_or_modeling","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low"},{"model":"gpt","categories":[],"domain":null,"study_design":"simulation_or_modeling","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"high"}],"label_agreement":"agree"},{"id":"W3186212639","doi":"10.1145/3449356","title":"Transfer Reinforcement Learning for Autonomous Driving","year":2021,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Autonomous Vehicle Technology and Safety","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 Waterloo","funders":"","keywords":"Reinforcement learning; Fidelity; Computer science; Domain (mathematical analysis); Perception; Transfer of learning; Reinforcement; Artificial intelligence; Mathematics; Engineering","score_opus":0.016745849241885002,"score_gpt":0.23099925646590616,"score_spread":0.21425340722402117,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3186212639","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":[0.053099636,0.00033729832,0.9407524,0.00036972656,0.00007911976,0.0000815426,0.00004033157,0.0012328268,0.00400711],"genre_scores_gemma":[0.95985484,0.00010305774,0.03763404,0.000090727146,0.00002084405,0.00011552028,0.00004595088,0.000047465885,0.0020875712],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99951184,0.00018920012,0.000023117931,0.00009956662,0.00011547672,0.000060806764],"domain_scores_gemma":[0.9982528,0.0011853746,0.0001410003,0.00013823263,0.00020102086,0.000081545586],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012862381,0.00057728234,0.0006737833,0.00032867858,0.00027608548,0.000510553,0.00085020025,0.00078157533,0.0025184015],"category_scores_gemma":[0.005902725,0.0002815467,0.00041831052,0.00021542462,0.0010438652,0.00066454295,0.0009115739,0.0014349424,0.00035214977],"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":[0.000033938268,0.000035151294,0.0002863688,0.000022158967,0.000011970316,0.00002181663,0.000022921946,0.98037934,0.0005377289,0.003256238,0.00024164209,0.015150721],"study_design_scores_gemma":[0.000005215038,0.00002018739,0.00004505969,0.0000017976153,0.0000014998282,0.000002529277,0.0000022587801,0.9965443,0.00017001847,0.003077913,0.00012724374,0.0000020196699],"about_ca_topic_score_codex":0.0053765727,"about_ca_topic_score_gemma":0.0025797703,"teacher_disagreement_score":0.0053765727,"about_ca_system_score_codex":0.0010645224,"about_ca_system_score_gemma":0.0009764936,"threshold_uncertainty_score":0.01069057},"labels":[],"label_agreement":null},{"id":"W3203605282","doi":"10.1145/3466169","title":"Uncertainty on Discrete-Event System Simulation","year":2021,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Simulation Techniques and Applications","field":"Decision Sciences","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":"Carleton University","funders":"","keywords":"DEVS; Rotation formalisms in three dimensions; Discrete event simulation; Computer science; Bounding overwatch; Formalism (music); Algorithm; Discrete event dynamic system; Theoretical computer science; Modeling and simulation; Discrete system; Mathematics; Simulation; Artificial intelligence","score_opus":0.10808459565139562,"score_gpt":0.39605454710687205,"score_spread":0.28796995145547644,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3203605282","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":[0.004180189,0.00031609822,0.99287134,0.00021154723,0.00003705396,0.00003341674,0.0000898768,0.00018356525,0.002077039],"genre_scores_gemma":[0.63092613,0.0018043678,0.36240733,0.00019590234,0.00015403409,0.0004225887,0.00058103236,0.00022707703,0.0032815372],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99528694,0.002100809,0.00030604642,0.00055714865,0.0015052372,0.00024377773],"domain_scores_gemma":[0.9846651,0.012631694,0.0005164267,0.0009948661,0.0009603909,0.00023151733],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004663666,0.001107792,0.0013359714,0.0012423635,0.0007848708,0.0025592016,0.0015863215,0.0013677152,0.00231116],"category_scores_gemma":[0.022812786,0.0007876224,0.0017969811,0.0014823738,0.0021810937,0.0033652226,0.0028917072,0.0028750817,0.0003972114],"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":[0.000043442073,0.000008687859,0.00038987727,0.00006394511,0.000027547072,0.000051581996,0.00007851068,0.85883516,0.00023010877,0.12964424,0.00024753998,0.010379291],"study_design_scores_gemma":[0.000007802321,0.000010092622,0.000044454613,0.000017438037,0.000008548506,0.00001227474,0.000011577661,0.9199536,0.00032283438,0.07804376,0.0015593619,0.000008227959],"about_ca_topic_score_codex":0.007304427,"about_ca_topic_score_gemma":0.0026715358,"teacher_disagreement_score":0.007304427,"about_ca_system_score_codex":0.0021228166,"about_ca_system_score_gemma":0.0018356966,"threshold_uncertainty_score":0.024664104},"labels":[],"label_agreement":null},{"id":"W4287831525","doi":"10.1145/3543849","title":"The DEVStone Metric: Performance Analysis of DEVS Simulation Engines","year":2022,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Simulation Techniques and Applications","field":"Decision Sciences","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":"Carleton University","funders":"Ministerio de Ciencia e Innovación","keywords":"DEVS; Benchmark (surveying); Discrete event simulation; Metric (unit); Computer science; Formalism (music); Performance metric; Modeling and simulation; Simulation; Engineering","score_opus":0.10120503686315428,"score_gpt":0.3780876981216702,"score_spread":0.2768826612585159,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4287831525","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":[0.6027522,0.0056719333,0.29874024,0.0013250686,0.0008534693,0.0015976796,0.028715583,0.020743586,0.039600212],"genre_scores_gemma":[0.8244684,0.0008205638,0.14392798,0.00019326148,0.00006239131,0.00073660724,0.026769996,0.0010407828,0.001980014],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9907266,0.0031279863,0.0015393251,0.000792388,0.0033030119,0.000510649],"domain_scores_gemma":[0.9762719,0.012699308,0.0015524293,0.0035585412,0.0052351737,0.00068267586],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008249374,0.0016572871,0.0009669993,0.004143319,0.00051668705,0.0018073242,0.002020594,0.00093929615,0.0024925133],"category_scores_gemma":[0.03991053,0.00042835932,0.0009215921,0.0034561043,0.0005606608,0.0026179673,0.0015757752,0.0010601948,0.00067148515],"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":[0.001533946,0.0009113195,0.029553562,0.0025832136,0.0007551618,0.00024300962,0.00038690766,0.7247166,0.015659766,0.02546049,0.03902391,0.15917209],"study_design_scores_gemma":[0.00013879985,0.000912847,0.006810468,0.00013323603,0.00009505981,0.00018835561,0.0002250161,0.9447437,0.02132982,0.0077973134,0.01753824,0.00008712769],"about_ca_topic_score_codex":0.0032575256,"about_ca_topic_score_gemma":0.0027873486,"teacher_disagreement_score":0.008249374,"about_ca_system_score_codex":0.0015964479,"about_ca_system_score_gemma":0.0016265692,"threshold_uncertainty_score":0.04362738},"labels":[],"label_agreement":null},{"id":"W4317036118","doi":"10.1145/3580491","title":"SEH: Size Estimate Hedging Scheduling of Queues","year":2023,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Advanced Bandit Algorithms Research","field":"Decision Sciences","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":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Scheduling (production processes); Computer science; Queue; Variance (accounting); Mathematical optimization; Mathematics; Computer network; Accounting; Economics","score_opus":0.16515148452082612,"score_gpt":0.44962101077759437,"score_spread":0.28446952625676825,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4317036118","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":[0.098209746,0.0004689533,0.8967165,0.00036178666,0.00016067467,0.00014795213,0.00012730961,0.0015387868,0.0022682846],"genre_scores_gemma":[0.8925477,0.000117492906,0.105446294,0.00016430416,0.00007646948,0.00006090954,0.00010669648,0.00007558154,0.0014044972],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982521,0.00064232067,0.000116690106,0.00027460686,0.0004563749,0.00025780327],"domain_scores_gemma":[0.9943561,0.0029942119,0.00065271463,0.0009903362,0.0006940714,0.00031258242],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00355805,0.0006579687,0.0009922076,0.00065959484,0.0005103134,0.0009481464,0.0018197214,0.0006618696,0.0018594151],"category_scores_gemma":[0.011570009,0.00045551278,0.00041261065,0.000623648,0.0008921276,0.0017399697,0.0013106957,0.0012605848,0.00031915976],"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":[0.00075553707,0.0001753007,0.003108561,0.0000908394,0.000074128795,0.00010486366,0.00016726032,0.8343306,0.0076705967,0.024034768,0.002913901,0.12657367],"study_design_scores_gemma":[0.000031648968,0.00013892491,0.00033909717,0.000005371401,0.0000090242565,0.000023809922,0.000015140168,0.9882824,0.0023436227,0.008349828,0.00044748426,0.000013731693],"about_ca_topic_score_codex":0.002368507,"about_ca_topic_score_gemma":0.0019397229,"teacher_disagreement_score":0.00355805,"about_ca_system_score_codex":0.0010681556,"about_ca_system_score_gemma":0.0016166999,"threshold_uncertainty_score":0.018817008},"labels":[],"label_agreement":null},{"id":"W4399320957","doi":"10.1145/3670401","title":"ENHANCE: Multilevel Heterogeneous Performance-Aware Re-Partitioning Algorithm For Microscopic Vehicle Traffic Simulation","year":2024,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Simulation Techniques and Applications","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Algorithm; Traffic simulation; Parallel computing; Distributed computing; Microsimulation; Engineering","score_opus":0.1039789151833709,"score_gpt":0.40096509404697434,"score_spread":0.29698617886360346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399320957","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":[0.05157854,0.0001422319,0.9406517,0.00014869316,0.000045349112,0.000103609316,0.00017075463,0.0027204277,0.0044385972],"genre_scores_gemma":[0.5792192,0.000117706535,0.41707033,0.000102871665,0.000023121625,0.00023389494,0.00041808008,0.00048947317,0.002325258],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998159,0.00004663501,0.000008603859,0.00002880051,0.000062685234,0.00003743999],"domain_scores_gemma":[0.9996362,0.00014034189,0.000041529787,0.000072931136,0.000067844965,0.000041170544],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004537747,0.000632667,0.00056807103,0.00042394034,0.00039126724,0.0005467982,0.0013760476,0.00048008142,0.0020699913],"category_scores_gemma":[0.0015123484,0.0003671175,0.00055201596,0.00028281493,0.00028825225,0.00068585534,0.0011241751,0.0008137402,0.00041239575],"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":[0.000047951416,0.00003396155,0.0008955437,0.000031766936,0.000034262957,0.000027967091,0.000050137663,0.9662318,0.0042691804,0.0053722584,0.0011224706,0.021882778],"study_design_scores_gemma":[0.0000062781296,0.000008551261,0.000065529755,0.0000016217718,0.0000027676758,0.000005372392,0.000004750787,0.9979936,0.0005709704,0.00076391717,0.0005743825,0.0000023077014],"about_ca_topic_score_codex":0.0060493937,"about_ca_topic_score_gemma":0.008461267,"teacher_disagreement_score":0.0060493937,"about_ca_system_score_codex":0.0007503873,"about_ca_system_score_gemma":0.0009716807,"threshold_uncertainty_score":0.012028396},"labels":[],"label_agreement":null},{"id":"W4399809040","doi":"10.1145/3673226","title":"Context, Composition, Automation, and Communication: The C <sup>2</sup> AC Roadmap for Modeling and Simulation","year":2024,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Deutsche Forschungsgemeinschaft","keywords":"Context (archaeology); Automation; Composition (language); Computer science; Engineering","score_opus":0.1132068962270859,"score_gpt":0.36895202251498604,"score_spread":0.25574512628790014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399809040","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":[0.007014541,0.018132186,0.83851695,0.048650984,0.0018296866,0.0004219326,0.000278111,0.0013629051,0.08379277],"genre_scores_gemma":[0.17422651,0.018846057,0.78349966,0.004973844,0.0018223679,0.0011709706,0.00040812188,0.00069080776,0.014361624],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.98656845,0.008945857,0.0007924385,0.0012139702,0.0018926229,0.00058658887],"domain_scores_gemma":[0.98122954,0.011243683,0.0011294683,0.0029554884,0.0021486294,0.0012931234],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012914361,0.0016710018,0.001312512,0.003235831,0.0034028275,0.016473275,0.0035570152,0.005030184,0.01573866],"category_scores_gemma":[0.018507294,0.0013757115,0.002785753,0.004631006,0.017374825,0.019639377,0.0074638748,0.005992889,0.0031119934],"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":[0.000049481172,0.000022288581,0.0006290175,0.0003638719,0.000028795936,0.00008380443,0.0007632369,0.007904939,0.00031937956,0.9391114,0.0055420883,0.045181677],"study_design_scores_gemma":[0.000025703652,0.000047333,0.00044828712,0.00071895163,0.00004468442,0.00015152195,0.0007197979,0.029578138,0.0005170033,0.79296005,0.1747372,0.000051311712],"about_ca_topic_score_codex":0.019475264,"about_ca_topic_score_gemma":0.01634075,"teacher_disagreement_score":0.019475264,"about_ca_system_score_codex":0.006250256,"about_ca_system_score_gemma":0.01089212,"threshold_uncertainty_score":0.06829846},"labels":[],"label_agreement":null}]}