{"meta":{"query_hash":"09c3fdbd6a59","filters":{"venue":"Conference on Network and Service Management"},"cohort_total":22,"direct_labels_cover":0,"predictions_cover":22,"exported":22,"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/09c3fdbd6a59","api":"https://metacan.xera.ac/api/v1/cohort?venue=Conference+on+Network+and+Service+Management"},"results":[{"id":"W1485420199","doi":"10.5555/2147671.2147673","title":"MODE: mix driven on-line resource demand estimation","year":2011,"lang":"en","type":"article","venue":"Conference on Network and Service Management","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":22,"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 Calgary","funders":"","keywords":"Computer science; Workload; Regression; Resource (disambiguation); Regression analysis; Linear regression; Support vector machine; Resource allocation; Abstraction; Data mining; Machine learning; Statistics; Mathematics","score_opus":0.04321958222279559,"score_gpt":0.2544180544082911,"score_spread":0.21119847218549553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1485420199","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":[0.08295534,0.00008915713,0.89982384,0.00013343414,0.000042489504,0.00018060216,0.00040851216,0.014005006,0.0023616583],"genre_scores_gemma":[0.64390856,0.00005503776,0.35173172,0.00016718016,0.000035820107,0.00027204788,0.000704736,0.0009326708,0.0021921687],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987118,0.000413823,0.00005615814,0.00023071302,0.00049970165,0.000087782835],"domain_scores_gemma":[0.99667656,0.001467176,0.0004574836,0.00074928947,0.000545271,0.00010431839],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015106321,0.0011974524,0.0008486462,0.0008796104,0.00025063226,0.00083854457,0.0019134333,0.0007064511,0.0022996704],"category_scores_gemma":[0.005796456,0.0004956349,0.00038011657,0.0006664177,0.00025569613,0.0012052676,0.00096175564,0.00086847163,0.00084471365],"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":[0.0008586152,0.0006122486,0.014321129,0.00015269461,0.00018838947,0.00012575262,0.00023810299,0.43572044,0.034900025,0.0023772023,0.008599107,0.5019063],"study_design_scores_gemma":[0.000016932348,0.00005435555,0.0009604189,0.0000026772707,0.00000509783,0.000029815928,0.00001243712,0.9920757,0.005489538,0.0006382655,0.00070192275,0.000012854551],"about_ca_topic_score_codex":0.0031287041,"about_ca_topic_score_gemma":0.0033742993,"teacher_disagreement_score":0.0031287041,"about_ca_system_score_codex":0.0005343357,"about_ca_system_score_gemma":0.0006781543,"threshold_uncertainty_score":0.007989109},"labels":[],"label_agreement":null},{"id":"W1509551190","doi":"","title":"DCSim: A data centre simulation tool for evaluating dynamic virtualized resource management","year":2012,"lang":"en","type":"article","venue":"Conference on Network and Service Management","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":49,"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":"Computer science; Virtualization; Server; Cloud computing; Provisioning; Scalability; Virtual machine; Data center; Host (biology); Live migration; Resource management (computing); Distributed computing; Workload; Operating system","score_opus":0.06810447680882105,"score_gpt":0.3225924567579244,"score_spread":0.2544879799491034,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1509551190","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":[0.39563748,0.0006148478,0.5194584,0.0009291635,0.0005701759,0.0014859175,0.010819743,0.022979945,0.047504295],"genre_scores_gemma":[0.85217214,0.00036146675,0.13934545,0.000121585144,0.000029567935,0.0007893514,0.0041372827,0.00065379805,0.0023893067],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994504,0.00018553491,0.000048075854,0.000051645788,0.00016305177,0.00010123121],"domain_scores_gemma":[0.9979443,0.001098952,0.00012724084,0.00021545295,0.00041108803,0.00020280993],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014180061,0.0011417549,0.0009821927,0.0010568651,0.00078735524,0.00093851157,0.0021209589,0.0010310237,0.0038279751],"category_scores_gemma":[0.0035404807,0.00045794257,0.0008445869,0.0013418607,0.0006358042,0.00095641415,0.0011385297,0.0013669931,0.00042889334],"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":[0.00016535942,0.0001293226,0.0024103476,0.00010030848,0.00004934506,0.000051091796,0.00007122467,0.9802832,0.0021473218,0.0032597948,0.0033515545,0.007981107],"study_design_scores_gemma":[0.00003991192,0.00004319329,0.00028211987,0.0000059579197,0.000010265011,0.000008125777,0.000021272173,0.9952727,0.0017152748,0.00052360544,0.0020660174,0.000011605166],"about_ca_topic_score_codex":0.028458634,"about_ca_topic_score_gemma":0.016645148,"teacher_disagreement_score":0.028458634,"about_ca_system_score_codex":0.0016246182,"about_ca_system_score_gemma":0.0022459903,"threshold_uncertainty_score":0.056585968},"labels":[],"label_agreement":null},{"id":"W1511574952","doi":"","title":"An analysis of first fit heuristics for the virtual machine relocation problem","year":2012,"lang":"en","type":"article","venue":"Conference on Network and Service Management","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":42,"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":"Relocation; Virtual machine; Computer science; Server; Heuristics; Virtualization; Live migration; Distributed computing; Host (biology); Operating system; Cloud computing","score_opus":0.027635113696245238,"score_gpt":0.25370470545764573,"score_spread":0.22606959176140048,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1511574952","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":[0.16833253,0.0061608586,0.7957234,0.0022236018,0.00040570874,0.0009638633,0.000590417,0.0014665232,0.024133163],"genre_scores_gemma":[0.7661288,0.0019212454,0.22526732,0.0007499051,0.00025535672,0.00051164924,0.0006753383,0.00041915473,0.004071285],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9962431,0.0020346711,0.00010844943,0.00035152648,0.00049086154,0.0007714813],"domain_scores_gemma":[0.97147423,0.02439886,0.0015055484,0.0006489932,0.0010373681,0.0009350022],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0063440986,0.0020054136,0.0030968778,0.0025548355,0.0015723004,0.002771009,0.0030061633,0.002496933,0.005589411],"category_scores_gemma":[0.022188935,0.0011118334,0.0016149367,0.0023308597,0.0014431573,0.002915054,0.0013656659,0.002645734,0.00056979246],"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":[0.0003457982,0.0003227223,0.0016380823,0.00023594934,0.00012432647,0.00008825859,0.00012966889,0.95371085,0.00062810944,0.015969593,0.0032875512,0.023519067],"study_design_scores_gemma":[0.000055004562,0.00018018903,0.0003243733,0.0000359489,0.00003072902,0.000044263383,0.0000599988,0.9904422,0.00014788186,0.008001484,0.0006636257,0.00001419378],"about_ca_topic_score_codex":0.010958078,"about_ca_topic_score_gemma":0.008369801,"teacher_disagreement_score":0.010958078,"about_ca_system_score_codex":0.003772647,"about_ca_system_score_gemma":0.00457447,"threshold_uncertainty_score":0.033551157},"labels":[],"label_agreement":null},{"id":"W1516820013","doi":"10.5555/2147671.2147701","title":"Mitigating the negative impact of preemption on heterogeneous MapReduce workloads","year":2011,"lang":"en","type":"article","venue":"Conference on Network and Service Management","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":29,"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":"Preemption; Computer science; Distributed computing; Production (economics); Execution time; Cluster (spacecraft); Parallel computing; Operating system","score_opus":0.04073886906813735,"score_gpt":0.24906061286178335,"score_spread":0.208321743793646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1516820013","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5027271,0.0008784093,0.4910705,0.0005140521,0.00017644289,0.00016498928,0.00005518354,0.0014812511,0.0029320633],"genre_scores_gemma":[0.9359124,0.00020206027,0.06284279,0.00008503538,0.000101380545,0.00003444539,0.000043453536,0.00006327935,0.0007151836],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99868006,0.00042238762,0.000101241385,0.00016644956,0.0004330978,0.00019676982],"domain_scores_gemma":[0.996351,0.0015049292,0.00048019117,0.00081147684,0.0005555604,0.00029686088],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017438568,0.00085303263,0.00088655343,0.0005910424,0.0010807368,0.0011311349,0.0015175656,0.0005830275,0.00031785588],"category_scores_gemma":[0.0057087457,0.000391042,0.00040208508,0.0005936923,0.00032377586,0.0011484332,0.0010612817,0.0007219091,0.00016175835],"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":[0.00122958,0.0009996824,0.020680968,0.00049516786,0.0002176537,0.0011914787,0.00074220233,0.28852427,0.32834494,0.008059283,0.00498801,0.34452674],"study_design_scores_gemma":[0.000048148187,0.00029683317,0.0048379824,0.000015782085,0.000070387425,0.0005733806,0.00021072624,0.9385247,0.048681844,0.0035000404,0.0032011988,0.000038980583],"about_ca_topic_score_codex":0.0016611154,"about_ca_topic_score_gemma":0.002515284,"teacher_disagreement_score":0.0017438568,"about_ca_system_score_codex":0.0005397273,"about_ca_system_score_gemma":0.0014144063,"threshold_uncertainty_score":0.0092225075},"labels":[],"label_agreement":null},{"id":"W1534738890","doi":"10.5555/2147671.2147728","title":"Collaborative policy-based autonomic management: in a hierarchical model","year":2011,"lang":"en","type":"article","venue":"Conference on Network and Service Management","topic":"Service-Oriented Architecture and Web Services","field":"Computer Science","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":"Western University","funders":"","keywords":"Computer science; Cloud computing; Hierarchy; Focus (optics); Autonomic computing; Knowledge management; Process management; Business","score_opus":0.021974737449395848,"score_gpt":0.23812901846925558,"score_spread":0.21615428101985973,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1534738890","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":[0.048526958,0.0009343424,0.90637565,0.004838222,0.00021042793,0.00029889788,0.000066303306,0.0007875538,0.037961617],"genre_scores_gemma":[0.74015975,0.0005502369,0.25043523,0.0007175587,0.00025999558,0.00041458217,0.00012277774,0.000115217845,0.0072246105],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99475694,0.002224211,0.00032115733,0.00074456463,0.0013957479,0.00055742473],"domain_scores_gemma":[0.9937177,0.0018668586,0.00082729553,0.001464522,0.0007985723,0.0013250483],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006449667,0.0004045804,0.0006389238,0.00072806707,0.0022795126,0.0058732373,0.0023238235,0.0018170782,0.0028412424],"category_scores_gemma":[0.007632167,0.0006501299,0.00067872484,0.001128653,0.0028179903,0.0077294027,0.003835037,0.0021871056,0.000927453],"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":[0.00022807061,0.00039617106,0.004857706,0.00023134185,0.00015010193,0.0005103483,0.005761232,0.15312971,0.005532223,0.7537473,0.0053029656,0.07015286],"study_design_scores_gemma":[0.00011922675,0.00015569032,0.001407654,0.00012930924,0.000087847504,0.00019860223,0.0011353511,0.5664835,0.0013469488,0.39271182,0.036135823,0.00008819234],"about_ca_topic_score_codex":0.005097003,"about_ca_topic_score_gemma":0.0046200617,"teacher_disagreement_score":0.006449667,"about_ca_system_score_codex":0.0025294856,"about_ca_system_score_gemma":0.004209847,"threshold_uncertainty_score":0.034109533},"labels":[],"label_agreement":null},{"id":"W1535492492","doi":"10.5555/2499406.2499465","title":"An architecture for overlaying private clouds on public providers","year":2012,"lang":"en","type":"article","venue":"Conference on Network and Service Management","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Cloud computing; Computer science; Service provider; Computer security; Architecture; Overlay; Set (abstract data type); Virtual machine; Access control; Best practice; Cloud computing security; Cloud service provider; Control (management); Service (business); Business; Operating system","score_opus":0.03314886167355966,"score_gpt":0.2518899322531304,"score_spread":0.21874107057957073,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1535492492","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":[0.06023643,0.00024368742,0.89875835,0.002164118,0.00018507108,0.00031655328,0.00015477651,0.007055016,0.030885974],"genre_scores_gemma":[0.5405723,0.00035235836,0.43701676,0.0002854352,0.00006314531,0.0002075617,0.00030979054,0.00037790224,0.020814747],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989994,0.00021816237,0.00008654708,0.00018229139,0.00030538574,0.00020821567],"domain_scores_gemma":[0.99869615,0.00014007893,0.000079343125,0.0005259644,0.00033845223,0.00022006636],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014270975,0.0003217459,0.0002739334,0.00069721404,0.0022657455,0.0039654705,0.0020146356,0.0017781791,0.00496862],"category_scores_gemma":[0.0023615868,0.00060331164,0.00052566174,0.0009523369,0.0014927456,0.004862717,0.0031689934,0.0013170306,0.0013568237],"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":[0.0003747151,0.00030994543,0.003755437,0.00023651858,0.00009092982,0.00078099675,0.0030179783,0.11366781,0.02720427,0.69023085,0.021058088,0.13927244],"study_design_scores_gemma":[0.00011291615,0.00029286632,0.001952077,0.00014800667,0.00014044042,0.00056913856,0.0010141175,0.62743956,0.015606459,0.13073544,0.22184041,0.00014852786],"about_ca_topic_score_codex":0.0153076695,"about_ca_topic_score_gemma":0.020385768,"teacher_disagreement_score":0.0153076695,"about_ca_system_score_codex":0.0024910741,"about_ca_system_score_gemma":0.0039104177,"threshold_uncertainty_score":0.030437112},"labels":[],"label_agreement":null},{"id":"W1663565304","doi":"10.5555/2147671.2147714","title":"Cross-layer cluster-based data dissemination for failure detection in MANETs","year":2011,"lang":"en","type":"article","venue":"Conference on Network and Service Management","topic":"Mobile Ad Hoc Networks","field":"Computer Science","cited_by":6,"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; Innovation, Science and Economic Development Canada","funders":"","keywords":"Computer science; Computer network; Gossip; Node (physics); Network layer; Overhead (engineering); Dissemination; Distributed computing; Wireless sensor network; Flooding (psychology); Layer (electronics); Engineering","score_opus":0.057374299895364564,"score_gpt":0.2902060172202093,"score_spread":0.2328317173248447,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1663565304","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":[0.04664985,0.0013601611,0.94763273,0.0002460033,0.000105899795,0.00018910592,0.000049956874,0.0021560057,0.0016103364],"genre_scores_gemma":[0.81039196,0.0006800882,0.1862771,0.000116282594,0.000056360732,0.00015610241,0.00014246833,0.00008634181,0.0020933042],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990414,0.0003457726,0.00009001533,0.00013199096,0.00032334562,0.000067438814],"domain_scores_gemma":[0.99766195,0.0010763552,0.00023653792,0.0004955547,0.0004348047,0.00009474767],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021712491,0.00037891144,0.0005464473,0.00096347387,0.0006077123,0.00082190265,0.0010618521,0.0006409312,0.0010849868],"category_scores_gemma":[0.005310286,0.00033355466,0.00032226287,0.0009312366,0.0005230298,0.0011956852,0.0010309471,0.0006392463,0.00029886916],"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":[0.0011522936,0.00029619536,0.00493655,0.0006375713,0.00032520134,0.0004700979,0.0007897289,0.4828776,0.08153936,0.033655003,0.0071452796,0.3861751],"study_design_scores_gemma":[0.000040134077,0.00020992325,0.00087779213,0.000016731488,0.00004558355,0.0001861032,0.000042303287,0.9780847,0.013021783,0.0034088402,0.004036669,0.000029484556],"about_ca_topic_score_codex":0.0018611202,"about_ca_topic_score_gemma":0.0014635551,"teacher_disagreement_score":0.0021712491,"about_ca_system_score_codex":0.00060674816,"about_ca_system_score_gemma":0.000531837,"threshold_uncertainty_score":0.011482775},"labels":[],"label_agreement":null},{"id":"W1707396638","doi":"10.5555/2147671.2147748","title":"A trace-based service level planning framework for enterprise application clouds","year":2011,"lang":"en","type":"article","venue":"Conference on Network and Service Management","topic":"Cloud Computing and Resource Management","field":"Computer Science","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 Calgary","funders":"","keywords":"Burstiness; Workload; Cloud computing; Computer science; Scalability; TRACE (psycholinguistics); Exploit; Distributed computing; Service (business); Service level; Data science; Database; Computer network; Computer security; Operating system","score_opus":0.07577305367032168,"score_gpt":0.2700646242146619,"score_spread":0.1942915705443402,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1707396638","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":[0.0025440664,0.00006969166,0.9934909,0.00018992925,0.000020664726,0.000101162375,0.00016879954,0.0023163504,0.0010983947],"genre_scores_gemma":[0.25868267,0.00033152764,0.73757213,0.000101804246,0.000045351044,0.00039068772,0.0008102734,0.0003410225,0.001724544],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989579,0.00030797717,0.00009987729,0.00014937524,0.00037790582,0.0001069689],"domain_scores_gemma":[0.9982345,0.00076274126,0.00017631153,0.00030876428,0.00033407766,0.00018353056],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002775151,0.00093339075,0.000848164,0.0014527093,0.0010789001,0.0027800642,0.0031442374,0.0011757895,0.0027727082],"category_scores_gemma":[0.0057053016,0.0006977308,0.0012241248,0.0012917737,0.00097083906,0.0021724747,0.0020989028,0.0019602766,0.00045208246],"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":[0.00008619066,0.000096947806,0.0008032309,0.0000722229,0.0000596579,0.00013663985,0.00021671553,0.8821915,0.0012053796,0.06761466,0.002252094,0.045264795],"study_design_scores_gemma":[0.0000072458733,0.000009603516,0.0000382076,0.000009265705,0.000006947466,0.00001246064,0.00001354663,0.9856339,0.00031670457,0.012321316,0.0016220339,0.000008676857],"about_ca_topic_score_codex":0.03753102,"about_ca_topic_score_gemma":0.03356457,"teacher_disagreement_score":0.03753102,"about_ca_system_score_codex":0.0026470681,"about_ca_system_score_gemma":0.0051739835,"threshold_uncertainty_score":0.074625134},"labels":[],"label_agreement":null},{"id":"W1877148809","doi":"10.5555/2147671.2147693","title":"Using strategy trees in change management in clouds","year":2011,"lang":"en","type":"article","venue":"Conference on Network and Service Management","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Cloud computing; Computer science; Software deployment; Schedule; Order (exchange); Service provider; Change management (ITSM); Change order; Service (business); Process management; Service level; Computer security; Business; Project management; Marketing; Operating system; Engineering; Project portfolio management; Systems engineering; Lean manufacturing","score_opus":0.14337111346126133,"score_gpt":0.2760781293276257,"score_spread":0.13270701586636438,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1877148809","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":[0.05986964,0.0007356584,0.9203869,0.001001384,0.00018466276,0.00046012292,0.00016316104,0.005132357,0.012066119],"genre_scores_gemma":[0.58411336,0.00040569593,0.41062254,0.00050215604,0.00005306799,0.00030290263,0.00026309636,0.0003890419,0.0033481377],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977348,0.00096972636,0.00013601164,0.00032824744,0.00056138873,0.0002698002],"domain_scores_gemma":[0.9958443,0.00229986,0.00044325698,0.00068283663,0.00040289937,0.00032685403],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027482207,0.00069059315,0.0006747115,0.0010427039,0.0011841389,0.0024098917,0.0013185204,0.0010401763,0.0024072737],"category_scores_gemma":[0.007076787,0.00056754064,0.000847114,0.0012097204,0.001305176,0.0033609057,0.0017532044,0.0017147175,0.0006621646],"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":[0.0004801385,0.00062209275,0.0066710617,0.00031700116,0.00015356703,0.00067789597,0.0019253375,0.46581584,0.010033695,0.0890918,0.007895788,0.4163158],"study_design_scores_gemma":[0.00006118353,0.0001841396,0.00088055135,0.000051248542,0.00004970335,0.00014962307,0.00030184654,0.908388,0.0042369175,0.07048853,0.0151554365,0.000052859516],"about_ca_topic_score_codex":0.0104063,"about_ca_topic_score_gemma":0.010358029,"teacher_disagreement_score":0.0104063,"about_ca_system_score_codex":0.0018657403,"about_ca_system_score_gemma":0.0021960782,"threshold_uncertainty_score":0.020691514},"labels":[],"label_agreement":null},{"id":"W2571825696","doi":"10.5555/3375069.3375107","title":"Let's Adapt to Network Change: Towards Energy Saving with Rate Adaptation in SDN","year":2016,"lang":"en","type":"article","venue":"Conference on Network and Service Management","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Greedy algorithm; Software-defined networking; Network topology; Energy consumption; Integer programming; Linear programming; Distributed computing; Adaptation (eye); Heuristic; Mathematical optimization; Routing (electronic design automation); Computer network; Algorithm; Mathematics","score_opus":0.04424163313290151,"score_gpt":0.22778638892435701,"score_spread":0.18354475579145552,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2571825696","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":[0.054804374,0.0011224105,0.9380879,0.0007601352,0.00011911971,0.000045124954,0.000025924155,0.00032784033,0.0047072116],"genre_scores_gemma":[0.8508485,0.0008196911,0.14653149,0.00021147572,0.00005308137,0.000047290498,0.000037937207,0.000071712595,0.0013788141],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99968374,0.00012943048,0.000010821652,0.000041445433,0.00009337503,0.00004109883],"domain_scores_gemma":[0.9996457,0.00015294991,0.000050984883,0.000043163604,0.00008031259,0.000026804775],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008488371,0.00040806198,0.00047913095,0.0002735362,0.00031221937,0.00086096587,0.0010012387,0.0006323107,0.0005502499],"category_scores_gemma":[0.0016685908,0.000169127,0.00033113148,0.00045684882,0.0005691409,0.001175812,0.0006856439,0.0007222532,0.00011560705],"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":[0.00009151165,0.00006572405,0.0013043412,0.000070560316,0.00004784099,0.00010559659,0.00010371448,0.8689024,0.0061778994,0.02234944,0.0011668664,0.09961418],"study_design_scores_gemma":[0.000007861095,0.000032043437,0.00011295996,0.000009414906,0.000009306764,0.000030305006,0.00002674961,0.98903906,0.0012693675,0.008173407,0.0012839666,0.000005515379],"about_ca_topic_score_codex":0.0016705443,"about_ca_topic_score_gemma":0.0015401447,"teacher_disagreement_score":0.0016705443,"about_ca_system_score_codex":0.0003894516,"about_ca_system_score_gemma":0.00045964666,"threshold_uncertainty_score":0.004489124},"labels":[],"label_agreement":null},{"id":"W2574335537","doi":"10.5555/3375069.3375115","title":"Enhanced Real Time Content Delivery using vCPE and NFV Service Chaining","year":2016,"lang":"en","type":"article","venue":"Conference on Network and Service Management","topic":"Software-Defined Networks and 5G","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":"University of Toronto","funders":"","keywords":"Chaining; Computer science; Distributed computing; Bandwidth (computing); Service (business); Computer network; Quality of service","score_opus":0.05277708798409988,"score_gpt":0.2323762777008321,"score_spread":0.17959918971673222,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2574335537","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":[0.15743043,0.00026776214,0.83616656,0.00018457949,0.00005703715,0.00014091314,0.00006376123,0.0011318468,0.004557062],"genre_scores_gemma":[0.8271382,0.00012387703,0.17056823,0.000056764173,0.000017878938,0.000062261555,0.0001216053,0.000058565896,0.0018527694],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994505,0.00012415843,0.000030411593,0.00009447799,0.00014106072,0.00015943138],"domain_scores_gemma":[0.99923205,0.00023471798,0.000096605436,0.00015833811,0.00016952517,0.00010874835],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00066058914,0.0005743785,0.00046976825,0.00067988114,0.0006069582,0.00094229315,0.0011126884,0.00067067833,0.0015501006],"category_scores_gemma":[0.0017432983,0.00020444315,0.000303156,0.0008351985,0.00043769626,0.0013002186,0.0013869314,0.00050628325,0.00029387587],"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":[0.0005475128,0.00034144276,0.0028658838,0.00013317102,0.0000425492,0.0003510321,0.00024284403,0.66383296,0.054857966,0.016112428,0.0023392534,0.25833297],"study_design_scores_gemma":[0.000015041605,0.000097448086,0.0002560864,0.0000062965205,0.0000073613155,0.00009682677,0.000044122884,0.98560417,0.008852533,0.0030736716,0.0019364506,0.000010053245],"about_ca_topic_score_codex":0.0034560205,"about_ca_topic_score_gemma":0.0027717312,"teacher_disagreement_score":0.0034560205,"about_ca_system_score_codex":0.00086579705,"about_ca_system_score_gemma":0.000691763,"threshold_uncertainty_score":0.0068718195},"labels":[],"label_agreement":null},{"id":"W2575022995","doi":"10.5555/3375069.3375125","title":"Dynamic Resource Allocation of Smart Home Workloads in the Cloud","year":2016,"lang":"en","type":"article","venue":"Conference on Network and Service Management","topic":"IoT and Edge/Fog Computing","field":"Computer Science","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":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Cloud computing; Quality of service; Distributed computing; Queueing theory; Computer network; Resource allocation; Cloudlet; Scalability; Server; Queue; Home automation; Service (business); Operating system","score_opus":0.01742955384075944,"score_gpt":0.2239495868264422,"score_spread":0.20652003298568275,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2575022995","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":[0.70720404,0.0005182323,0.28293863,0.00035498946,0.0000690566,0.00012334502,0.000095554366,0.0004004081,0.008295822],"genre_scores_gemma":[0.99276143,0.00006652744,0.0067675426,0.000017498209,0.0000065866,0.00001481362,0.000018397894,0.000010967773,0.00033607284],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996418,0.000076191005,0.000013248107,0.00005396716,0.00007077901,0.00014399081],"domain_scores_gemma":[0.99963236,0.00014789408,0.000048142883,0.00003354098,0.0000804584,0.000057561487],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00052483066,0.00030794088,0.00041136646,0.00030601164,0.000411748,0.0006842734,0.00053691084,0.00031882006,0.0006262596],"category_scores_gemma":[0.0011714781,0.00016134152,0.00021096191,0.00040828183,0.0002460634,0.0006377301,0.00039713207,0.00025496923,0.00010392723],"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":[0.00023334565,0.0001249636,0.0036950482,0.000037708378,0.000019959652,0.00024663986,0.000068422305,0.9491059,0.014319525,0.00817499,0.0011801088,0.022793543],"study_design_scores_gemma":[0.0000029162977,0.000013504669,0.00029270365,7.29354e-7,0.0000017889593,0.000009698038,0.000019118172,0.99832374,0.0005839389,0.0006449363,0.000104831044,0.000002114961],"about_ca_topic_score_codex":0.0057139965,"about_ca_topic_score_gemma":0.0044555017,"teacher_disagreement_score":0.0057139965,"about_ca_system_score_codex":0.00089602364,"about_ca_system_score_gemma":0.00096756977,"threshold_uncertainty_score":0.01136148},"labels":[],"label_agreement":null},{"id":"W2575192927","doi":"10.5555/3375069.3375118","title":"LLDP Based Link Latency Monitoring in Software Defined Networks","year":2016,"lang":"en","type":"article","venue":"Conference on Network and Service Management","topic":"Software-Defined Networks and 5G","field":"Computer Science","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":"University of British Columbia","funders":"","keywords":"Network packet; Forwarding plane; OpenFlow; Latency (audio); Computer science; Computer network; Software-defined networking; Real-time computing; Embedded system; Telecommunications","score_opus":0.025687643760410824,"score_gpt":0.227487017657974,"score_spread":0.20179937389756317,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2575192927","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":[0.1281712,0.0010118618,0.863227,0.00017658866,0.000099493904,0.00013044024,0.00015894731,0.004895175,0.0021291722],"genre_scores_gemma":[0.8986181,0.00030553722,0.10011337,0.000065059576,0.000031041487,0.000096801756,0.00015154642,0.000057347566,0.0005611399],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99842715,0.00039326985,0.00011838885,0.0002967869,0.0006178942,0.00014653563],"domain_scores_gemma":[0.9975345,0.00078978395,0.0005272474,0.00031111663,0.0007151613,0.00012213517],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014732393,0.0006440099,0.00040096277,0.0015544269,0.00044214807,0.001016384,0.0011394938,0.00039854043,0.000490371],"category_scores_gemma":[0.0048480085,0.00029639818,0.00016334007,0.0010116844,0.00041993742,0.0016692962,0.0007763814,0.00065097254,0.00016403054],"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":[0.0007865082,0.00041711147,0.022673894,0.00045703168,0.00015140741,0.00029837142,0.0004632475,0.2706334,0.11857353,0.01259192,0.0033028678,0.56965077],"study_design_scores_gemma":[0.000030248666,0.0002540729,0.0025776317,0.000025050158,0.000039313032,0.00013520746,0.00008539798,0.9266966,0.063558534,0.0034126795,0.0031359694,0.000049298495],"about_ca_topic_score_codex":0.0028628432,"about_ca_topic_score_gemma":0.0020082537,"teacher_disagreement_score":0.0028628432,"about_ca_system_score_codex":0.0013439609,"about_ca_system_score_gemma":0.0010616123,"threshold_uncertainty_score":0.009751201},"labels":[],"label_agreement":null},{"id":"W2576325362","doi":"10.5555/3375069.3375094","title":"Self-Optimizing Energy Management in Heterogeneous Cellular Networks","year":2016,"lang":"en","type":"article","venue":"Conference on Network and Service Management","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Base station; Energy consumption; Throughput; Distributed computing; Mathematical optimization; Optimization problem; Cellular network; Power control; Computer network; Power (physics); Algorithm; Wireless; Engineering; Mathematics","score_opus":0.009135516848284097,"score_gpt":0.1868406911089719,"score_spread":0.1777051742606878,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2576325362","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":[0.12873298,0.00024034956,0.8678502,0.00020110494,0.000030766998,0.000043999044,0.000022856178,0.00021626643,0.0026614778],"genre_scores_gemma":[0.9717362,0.000059454815,0.027243715,0.000040215677,0.000011388444,0.000037830112,0.000019293078,0.000021577715,0.00083030434],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99966395,0.0001187976,0.000011534157,0.00005977696,0.000090283764,0.000055613567],"domain_scores_gemma":[0.9994093,0.00033453305,0.00007944886,0.000050431514,0.00009056816,0.00003574538],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00085941755,0.0005343421,0.0006320218,0.00034468804,0.00040248464,0.00073939114,0.00090749864,0.0006250741,0.0005805071],"category_scores_gemma":[0.0016015468,0.00024600475,0.00022609676,0.00035889892,0.0009065333,0.0008252611,0.0008627233,0.00033429547,0.00008799057],"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":[0.000015478801,0.000011907619,0.000199706,0.000003843759,0.0000063036764,0.000010403398,0.0000069867765,0.99383473,0.00048116964,0.0016442728,0.000062180065,0.0037229757],"study_design_scores_gemma":[0.0000033757883,0.0000069731495,0.000028299708,3.814026e-7,0.0000010100377,0.0000018736735,0.0000023860543,0.99914885,0.00015732237,0.0006103172,0.00003848305,7.6359015e-7],"about_ca_topic_score_codex":0.0033590535,"about_ca_topic_score_gemma":0.0028086584,"teacher_disagreement_score":0.0033590535,"about_ca_system_score_codex":0.0009842404,"about_ca_system_score_gemma":0.00061678374,"threshold_uncertainty_score":0.007141173},"labels":[],"label_agreement":null},{"id":"W2576330472","doi":"10.5555/3375069.3375132","title":"Monitoring and Measurement System for Green Operation of Geographically Distributed ICT Services","year":2016,"lang":"en","type":"article","venue":"Conference on Network and Service Management","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; Université de Montréal; École de Technologie Supérieure","funders":"","keywords":"Testbed; Green computing; Computer science; Information and Communications Technology; Energy consumption; Reliability (semiconductor); Variety (cybernetics); Efficient energy use; Work (physics); Cloud computing; Environmental economics; Computer security; Computer network; Engineering; Power (physics)","score_opus":0.0280942851927396,"score_gpt":0.22072917730186828,"score_spread":0.19263489210912868,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2576330472","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":[0.041666403,0.00026306853,0.92316973,0.0004034789,0.0000817493,0.00058934535,0.00054414565,0.027541164,0.0057408405],"genre_scores_gemma":[0.6859223,0.00019163534,0.3075308,0.00028191978,0.00008315679,0.0005649061,0.001382956,0.0003622405,0.0036800709],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9979929,0.0005101124,0.00018417933,0.00043505308,0.00069086126,0.00018694508],"domain_scores_gemma":[0.99822885,0.0002747102,0.00025357865,0.00041449282,0.0006031157,0.00022535173],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024829074,0.00057708763,0.00084219244,0.0022442727,0.00084380823,0.0016474796,0.0016417587,0.00087685394,0.0018107005],"category_scores_gemma":[0.0023359347,0.0002379604,0.00036086809,0.00097565254,0.00036802856,0.0017561184,0.0015776535,0.00074206217,0.0008757806],"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":[0.0009568858,0.0012848106,0.032643244,0.0005117334,0.0002811461,0.0010322989,0.0021869591,0.08361728,0.14455149,0.049052384,0.030197803,0.653684],"study_design_scores_gemma":[0.00012282576,0.00044359948,0.013621069,0.00014556016,0.00014598444,0.0004869802,0.0004639849,0.8566938,0.056898065,0.010078207,0.06072509,0.000174833],"about_ca_topic_score_codex":0.006161407,"about_ca_topic_score_gemma":0.0045678588,"teacher_disagreement_score":0.006161407,"about_ca_system_score_codex":0.0012943773,"about_ca_system_score_gemma":0.001745025,"threshold_uncertainty_score":0.013131022},"labels":[],"label_agreement":null},{"id":"W2576427772","doi":"10.5555/3375069.3375109","title":"Online Characterization of Buggy Applications Running on the Cloud","year":2016,"lang":"en","type":"article","venue":"Conference on Network and Service Management","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Cloud computing; Computer science; Resource (disambiguation); Resource management (computing); Quality of service; Computer security; Distributed computing; Computer network; Operating system","score_opus":0.02291429358918484,"score_gpt":0.2309119831685328,"score_spread":0.20799768957934794,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2576427772","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":[0.9575563,0.00019523843,0.037977736,0.00010950265,0.000028739589,0.000077022036,0.00064241217,0.002550954,0.0008620595],"genre_scores_gemma":[0.99056256,0.00002965009,0.008721565,0.000020208503,0.000010392143,0.000019562258,0.00035578382,0.000046706326,0.00023360625],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991912,0.00015495741,0.00007310252,0.00018260568,0.00030025098,0.00009777916],"domain_scores_gemma":[0.98940176,0.004532775,0.002617776,0.0012959165,0.0016973325,0.00045441126],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008450075,0.00066236814,0.00046893177,0.002397643,0.00029785847,0.00066974387,0.0006934987,0.0005859849,0.00063693745],"category_scores_gemma":[0.007970738,0.00020603983,0.0002741066,0.0007120442,0.00029619364,0.0006933583,0.00037511412,0.00054407684,0.00028295032],"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":[0.0012802553,0.000829053,0.60259444,0.00032621872,0.0001625116,0.0015869616,0.0006382708,0.11014067,0.092560366,0.0014792919,0.003811322,0.18459065],"study_design_scores_gemma":[0.000011613498,0.00022817249,0.09786014,0.000018887511,0.000026371152,0.00059355726,0.00015068572,0.88086385,0.01849338,0.0009763039,0.0007415243,0.000035519377],"about_ca_topic_score_codex":0.0023436495,"about_ca_topic_score_gemma":0.0025208185,"teacher_disagreement_score":0.002397643,"about_ca_system_score_codex":0.0003902382,"about_ca_system_score_gemma":0.0004115508,"threshold_uncertainty_score":0.0046600103},"labels":[],"label_agreement":null},{"id":"W2579398908","doi":"10.5555/3375069.3375078","title":"Predicting Web Service Response Time Percentiles","year":2016,"lang":"en","type":"article","venue":"Conference on Network and Service Management","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":6,"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 Calgary","funders":"","keywords":"Response time; Computer science; Percentile; Workload; Service (business); Web service; Real-time computing; Data mining; World Wide Web; Statistics","score_opus":0.014805947602598218,"score_gpt":0.22063526992587487,"score_spread":0.20582932232327666,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2579398908","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":[0.8502349,0.00023404804,0.13655852,0.00014739322,0.00004416465,0.00008261169,0.0021582283,0.008827264,0.0017129143],"genre_scores_gemma":[0.9829791,0.00005628195,0.014841096,0.000014143041,0.000011882623,0.000029868437,0.0017941163,0.000082732666,0.00019076435],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99898595,0.00015031605,0.00007640171,0.0002190394,0.0004281656,0.0001401276],"domain_scores_gemma":[0.99489343,0.0023092825,0.0006092684,0.0008421133,0.0010456828,0.00030024725],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014935184,0.0010525224,0.00075726735,0.0017100924,0.00035391434,0.0009300046,0.00073759054,0.0006980557,0.0006031923],"category_scores_gemma":[0.008775334,0.000443568,0.00047774866,0.0011954723,0.00023225216,0.0011280784,0.000624091,0.0009457816,0.00070418883],"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":[0.0006767486,0.0002076171,0.10565209,0.000090684065,0.00008795027,0.00018613125,0.00014264496,0.7938527,0.018865982,0.0009260631,0.0022976506,0.077013835],"study_design_scores_gemma":[0.000003581331,0.000034911824,0.0060230796,0.0000025506117,0.0000044841026,0.000024545598,0.000021484257,0.9901288,0.0032059415,0.00035953446,0.00018162445,0.000009403499],"about_ca_topic_score_codex":0.009064177,"about_ca_topic_score_gemma":0.0065102284,"teacher_disagreement_score":0.009064177,"about_ca_system_score_codex":0.0007309462,"about_ca_system_score_gemma":0.00084955036,"threshold_uncertainty_score":0.018022835},"labels":[],"label_agreement":null},{"id":"W2579403893","doi":"10.5555/3375069.3375070","title":"A Connectionist Approach to Dynamic Resource Management for Virtualised Network Functions","year":2016,"lang":"en","type":"article","venue":"Conference on Network and Service Management","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":36,"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":"Computer science; Virtual network; Computer network; Network topology; Network virtualization; Voice over IP; Distributed computing; Latency (audio); Software deployment; Network Functions Virtualization; Call graph; Virtualization; The Internet; Cloud computing; Telecommunications; Operating system","score_opus":0.022291523471756235,"score_gpt":0.22877020914028529,"score_spread":0.20647868566852906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2579403893","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":[0.010541146,0.00019997264,0.98254573,0.0005021643,0.00006879766,0.000053706233,0.000054710265,0.00042632033,0.0056074304],"genre_scores_gemma":[0.73571634,0.0004820651,0.25419888,0.00026939242,0.00013087371,0.0001966801,0.00013386286,0.00009941555,0.008772647],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995041,0.00012018583,0.00002466553,0.0001507326,0.00013936231,0.000060933595],"domain_scores_gemma":[0.9995252,0.00019633755,0.0000515593,0.00006953323,0.00012130419,0.000036111538],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00070060464,0.00057601,0.00047716248,0.00078736275,0.0008539163,0.001637379,0.0020961992,0.0010895998,0.0027222913],"category_scores_gemma":[0.0018089861,0.00034169012,0.0004343389,0.00072849286,0.0010066364,0.0020166354,0.0010662427,0.001209717,0.00038837478],"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":[0.00006804664,0.00006287856,0.0008657688,0.00007102591,0.000060297363,0.00013216557,0.00011967994,0.8361839,0.0032710377,0.08139883,0.002018769,0.07574752],"study_design_scores_gemma":[0.0000041077024,0.000014656825,0.000105217216,0.000004487455,0.000006541549,0.000024570434,0.000012110468,0.98196226,0.00034263323,0.016088864,0.0014278154,0.000006691844],"about_ca_topic_score_codex":0.0118941,"about_ca_topic_score_gemma":0.016598882,"teacher_disagreement_score":0.0118941,"about_ca_system_score_codex":0.0017405596,"about_ca_system_score_gemma":0.0013598178,"threshold_uncertainty_score":0.023649752},"labels":[],"label_agreement":null},{"id":"W2906795940","doi":"","title":"Revive: A Reliable Software Defined Data Plane Failure Recovery Scheme","year":2018,"lang":"en","type":"article","venue":"Conference on Network and Service Management","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Backup; Forwarding plane; Computer science; Network topology; Scheme (mathematics); Computer network; Software-defined networking; Controller (irrigation); Reliability (semiconductor); Network switch; Software; Distributed computing; Operating system; Network packet","score_opus":0.040101235217427075,"score_gpt":0.2493413933005425,"score_spread":0.2092401580831154,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2906795940","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":[0.14695834,0.002169169,0.82577765,0.0007117167,0.00043275574,0.00062350463,0.00048363008,0.015328909,0.007514303],"genre_scores_gemma":[0.9227872,0.00040576383,0.071343884,0.0003228008,0.0001019651,0.00016908784,0.00047890458,0.00017890126,0.0042115073],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99895406,0.00019622498,0.00007887377,0.00017382018,0.00040511147,0.00019196281],"domain_scores_gemma":[0.99833727,0.0002388003,0.00027730345,0.00071091973,0.00031433807,0.000121367375],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014382798,0.0008351639,0.00081221457,0.0010360063,0.0007779181,0.0008991663,0.0032967422,0.000886132,0.0017567405],"category_scores_gemma":[0.0022235732,0.0002937025,0.0005058219,0.00048661194,0.00091690454,0.0021174427,0.0027269502,0.0013830358,0.0005273882],"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":[0.0038077787,0.0008730597,0.0030774842,0.00071319944,0.00028438185,0.0011008158,0.0006211376,0.128233,0.17492959,0.056164745,0.020741744,0.609453],"study_design_scores_gemma":[0.00044593535,0.0029838707,0.002106301,0.000081721606,0.00020602475,0.0019378827,0.0002294314,0.8479797,0.082432896,0.019381924,0.04194762,0.00026676845],"about_ca_topic_score_codex":0.0009974883,"about_ca_topic_score_gemma":0.00080959615,"teacher_disagreement_score":0.0032967422,"about_ca_system_score_codex":0.0006187838,"about_ca_system_score_gemma":0.0006248719,"threshold_uncertainty_score":0.007606387},"labels":[],"label_agreement":null},{"id":"W2907469545","doi":"","title":"Congestion-Constrained Virtual Link Embedding with Uncertain Demands","year":2018,"lang":"en","type":"article","venue":"Conference on Network and Service Management","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Network virtualization; Bandwidth (computing); Distributed computing; Mathematical optimization; Node (physics); Virtual network; Embedding; Computer network; Virtualization; Cloud computing; Mathematics; Artificial intelligence","score_opus":0.022464928240156026,"score_gpt":0.24800908115034845,"score_spread":0.22554415291019242,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2907469545","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":[0.10676837,0.0003706457,0.8861511,0.0004753247,0.000055674343,0.00005744257,0.0002609286,0.00020443053,0.0056561553],"genre_scores_gemma":[0.9688946,0.00024914954,0.027662436,0.00005130515,0.000024538476,0.00007647121,0.00013509594,0.000046971854,0.002859422],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99905413,0.00038730545,0.000033682154,0.00016801679,0.0001751165,0.00018175246],"domain_scores_gemma":[0.99742776,0.0017253514,0.00032739123,0.00013291725,0.0002601103,0.00012650773],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014217598,0.0009966329,0.0010838041,0.00047478708,0.00045568042,0.0014629944,0.0012667907,0.001022811,0.0015075533],"category_scores_gemma":[0.0046554725,0.0007252828,0.00053246826,0.0008262494,0.0009650909,0.0021643764,0.0011951734,0.0013824657,0.00013410393],"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":[0.000010611802,0.00000546723,0.00007425742,0.000007597595,0.0000026516882,0.000018231209,0.0000069125977,0.9953825,0.00010185392,0.0034326806,0.000091144146,0.0008660989],"study_design_scores_gemma":[0.0000011733531,0.0000035318403,0.000021088907,8.5947397e-7,9.126134e-7,0.0000032619232,0.0000032877638,0.9983748,0.000038927818,0.0014989801,0.000051755444,0.0000014241172],"about_ca_topic_score_codex":0.010635126,"about_ca_topic_score_gemma":0.006141252,"teacher_disagreement_score":0.010635126,"about_ca_system_score_codex":0.0016620916,"about_ca_system_score_gemma":0.0013918973,"threshold_uncertainty_score":0.021146476},"labels":[],"label_agreement":null},{"id":"W2907996729","doi":"","title":"eDoS Mitigation for Autonomic Management on Multi-Tier IoT","year":2018,"lang":"en","type":"article","venue":"Conference on Network and Service Management","topic":"Network Security and Intrusion Detection","field":"Computer Science","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 Toronto","funders":"","keywords":"Computer science; Anomaly detection; Cloud computing; Autonomic computing; Resource management (computing); Intrusion detection system; Internet of Things; Distributed computing; Data mining; Real-time computing; Computer security; Operating system","score_opus":0.02804915043296782,"score_gpt":0.25389466160409924,"score_spread":0.2258455111711314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2907996729","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":[0.4193536,0.0006140182,0.5685986,0.00040336442,0.0001642803,0.00009336756,0.00007636779,0.004614639,0.006081741],"genre_scores_gemma":[0.9774864,0.00004351681,0.021902762,0.00005354119,0.000012444812,0.000012531489,0.000024881258,0.000024968851,0.00043889435],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99956936,0.00008135,0.000023291299,0.00006787693,0.00016404371,0.00009413108],"domain_scores_gemma":[0.9993554,0.00016634371,0.000112738344,0.00016659612,0.00014481468,0.000054120206],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00060020166,0.0003641883,0.00036434128,0.00044412437,0.000526229,0.00058715366,0.00078845856,0.00030892037,0.0008113207],"category_scores_gemma":[0.0014644029,0.000115089104,0.00026032614,0.00025316,0.00035777144,0.0009856246,0.00096367265,0.0004696547,0.00010171728],"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":[0.0006844799,0.00050113554,0.020524902,0.00014364017,0.00016536872,0.00068334833,0.00023490345,0.50970423,0.11295551,0.015914628,0.004001244,0.33448663],"study_design_scores_gemma":[0.0000058863693,0.00007508314,0.0016728559,0.0000050142926,0.000014826838,0.00007333258,0.000040284158,0.9825178,0.011804759,0.0027676735,0.0010126486,0.000009873535],"about_ca_topic_score_codex":0.001779826,"about_ca_topic_score_gemma":0.0026032038,"teacher_disagreement_score":0.001779826,"about_ca_system_score_codex":0.00051482336,"about_ca_system_score_gemma":0.00047064625,"threshold_uncertainty_score":0.0037353039},"labels":[],"label_agreement":null},{"id":"W2908229855","doi":"","title":"Bitforest: a Portable and Efficient Blockchain-Based Naming System","year":2018,"lang":"en","type":"article","venue":"Conference on Network and Service Management","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Blockchain; Scalability; Computer security; Public-key cryptography; Flexibility (engineering); Public key infrastructure; Cryptography; Distributed computing; Operating system; Encryption","score_opus":0.01435347362804693,"score_gpt":0.2144734568269922,"score_spread":0.20011998319894528,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2908229855","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":[0.11838256,0.0006531438,0.84373915,0.00049748406,0.00023288492,0.0005794571,0.00067821844,0.017468235,0.017768944],"genre_scores_gemma":[0.77680504,0.00054739165,0.20627405,0.00013531021,0.000050495284,0.0003041149,0.0016615475,0.0005706022,0.0136515],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99918956,0.00017655849,0.000054789085,0.000109117296,0.00037649865,0.0000934238],"domain_scores_gemma":[0.99867815,0.0002831894,0.00013083343,0.00050742785,0.0002256498,0.0001748192],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010709368,0.00044518424,0.0006295189,0.00058696925,0.0011240023,0.0012687945,0.0016564613,0.00095381576,0.0049224054],"category_scores_gemma":[0.0023909882,0.00032457293,0.0003058754,0.0008902696,0.0008814667,0.0030536288,0.0019356175,0.0008332962,0.0014523503],"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":[0.0020473872,0.0005372141,0.004632862,0.00050237396,0.00011296847,0.0012599304,0.00059102057,0.37272656,0.08053399,0.0917264,0.024792101,0.42053717],"study_design_scores_gemma":[0.0003216183,0.000319568,0.00074945553,0.000036870504,0.000031391628,0.00048319827,0.000060162274,0.9124808,0.024734301,0.028078686,0.032610312,0.00009364617],"about_ca_topic_score_codex":0.004889188,"about_ca_topic_score_gemma":0.004576568,"teacher_disagreement_score":0.0049224054,"about_ca_system_score_codex":0.0007595475,"about_ca_system_score_gemma":0.0021276807,"threshold_uncertainty_score":0.016467154},"labels":[],"label_agreement":null}]}