{"meta":{"query_hash":"e7aa0bc94077","filters":{"venue":"IASTED PDCS"},"cohort_total":5,"direct_labels_cover":0,"predictions_cover":5,"exported":5,"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/e7aa0bc94077","api":"https://metacan.xera.ac/api/v1/cohort?venue=IASTED+PDCS"},"results":[{"id":"W113335647","doi":"","title":"A Lazy Replication Scheme for Loosely Synchronized UDDI Registries.","year":2005,"lang":"en","type":"article","venue":"IASTED PDCS","topic":"Distributed systems and fault tolerance","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":"Memorial University of Newfoundland","funders":"","keywords":"Computer science; Session (web analytics); Scalability; Replication (statistics); Scheme (mathematics); Failover; Web service; High availability; Distributed computing; Computer network; Database; World Wide Web","score_opus":0.020597982225951928,"score_gpt":0.2746282626516152,"score_spread":0.2540302804256633,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W113335647","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":[0.003790443,0.00026906744,0.9905806,0.00022426435,0.00019189264,0.00031000678,0.00009418468,0.002766554,0.0017730023],"genre_scores_gemma":[0.18107045,0.000396216,0.80654776,0.00027632542,0.00018629088,0.00059321005,0.0006816635,0.0004448075,0.009803265],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99540967,0.0014217894,0.00069489627,0.0007531889,0.0014002833,0.00032018358],"domain_scores_gemma":[0.99202067,0.0008617488,0.0007362385,0.004747103,0.0012041853,0.00042997667],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0057480494,0.00054102496,0.0008204217,0.0012392062,0.0027836636,0.0028293678,0.0037232898,0.001241708,0.0033092506],"category_scores_gemma":[0.011411855,0.00066173467,0.0007506029,0.0014404415,0.0012176504,0.0043763155,0.0055656633,0.0017959158,0.0021004686],"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":[0.000928047,0.000256828,0.0031240906,0.0005257987,0.00022319588,0.00048312946,0.0016279534,0.049224507,0.03606284,0.37311763,0.04049843,0.49392745],"study_design_scores_gemma":[0.00053041324,0.0005969056,0.0008703685,0.00013602439,0.0002304131,0.0013720695,0.00040890084,0.579999,0.037615746,0.13578197,0.24213652,0.00032159014],"about_ca_topic_score_codex":0.0025192366,"about_ca_topic_score_gemma":0.002746163,"teacher_disagreement_score":0.0057480494,"about_ca_system_score_codex":0.0017354856,"about_ca_system_score_gemma":0.0034827923,"threshold_uncertainty_score":0.030398965},"labels":[],"label_agreement":null},{"id":"W146732267","doi":"","title":"Clustering using an Autoassociator: A Case Study in Network Event Correlation.","year":2005,"lang":"en","type":"article","venue":"IASTED PDCS","topic":"Network Security and Intrusion Detection","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 Ottawa","funders":"","keywords":"Cluster analysis; Computer science; Novelty; Artificial intelligence; Data mining; Artificial neural network; Event (particle physics); Feedforward neural network; Feature (linguistics); Task (project management); Correlation clustering; Correlation; Machine learning; Pattern recognition (psychology); Mathematics; Engineering","score_opus":0.03270833436532282,"score_gpt":0.2903363437473334,"score_spread":0.2576280093820106,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W146732267","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":[0.6063398,0.001370229,0.38024592,0.0016801684,0.00013432441,0.00030491248,0.00045326748,0.0013946637,0.008076681],"genre_scores_gemma":[0.87386155,0.0004977529,0.12236563,0.00017410229,0.000064348584,0.00009527016,0.0003079501,0.00011047675,0.002522804],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99796283,0.0009105012,0.00009780538,0.00031742358,0.0005634181,0.00014809016],"domain_scores_gemma":[0.9919668,0.0051921434,0.0005312008,0.0010031974,0.001043607,0.0002630342],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003162557,0.00055636774,0.0007671688,0.001383858,0.0012784329,0.0012474974,0.001320877,0.0021922397,0.0011306399],"category_scores_gemma":[0.010590671,0.00029778894,0.0006751148,0.0029059807,0.0010076391,0.0017930296,0.0010691513,0.0011239771,0.0003609379],"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":[0.0017290555,0.0011349658,0.078969054,0.0012325773,0.0006642591,0.015878668,0.0048928536,0.3806051,0.028624052,0.042271327,0.014779897,0.4292182],"study_design_scores_gemma":[0.00010306925,0.000564763,0.021167703,0.000069758964,0.00015297196,0.007546625,0.0014746435,0.88644415,0.03644807,0.024836937,0.02106528,0.00012608332],"about_ca_topic_score_codex":0.0040628496,"about_ca_topic_score_gemma":0.0060954904,"teacher_disagreement_score":0.0040628496,"about_ca_system_score_codex":0.0008437447,"about_ca_system_score_gemma":0.0005815485,"threshold_uncertainty_score":0.016725421},"labels":[],"label_agreement":null},{"id":"W157886190","doi":"","title":"Communication Characteristics of Message-Passing Scientific and Engineering Applications.","year":2005,"lang":"en","type":"article","venue":"IASTED PDCS","topic":"Parallel Computing and Optimization Techniques","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":"Queen's University","funders":"","keywords":"Message passing; Computer science; Suite; Benchmark (surveying); Payload (computing); Distributed computing; Point-to-point; Message broker; Message Passing Interface; Communications system; Computer network","score_opus":0.011606274004377805,"score_gpt":0.2386618171016495,"score_spread":0.2270555430972717,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W157886190","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":[0.8858868,0.0014613429,0.09994699,0.0004963432,0.000081520295,0.00017800592,0.0007304126,0.0011214564,0.010097224],"genre_scores_gemma":[0.9816807,0.00035584354,0.015064613,0.000038366834,0.000049596747,0.00011410239,0.00079456426,0.00016221736,0.0017399002],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9980958,0.0004132752,0.00011610731,0.0001956791,0.0010165323,0.00016255476],"domain_scores_gemma":[0.9891165,0.006232403,0.001879751,0.0006762581,0.0018558572,0.00023921656],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011883384,0.0004950466,0.00034863365,0.0009582379,0.00057174114,0.0008491304,0.00047418394,0.0005384594,0.0012188014],"category_scores_gemma":[0.012316518,0.00021067704,0.0002118696,0.0015453913,0.00033957168,0.0013159511,0.0004953688,0.0004701647,0.00042407916],"study_design_candidate":"observational","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":[0.0012758359,0.00041021168,0.22533914,0.0015113946,0.0002277423,0.001255392,0.0020863314,0.29156065,0.2241726,0.018439183,0.007911817,0.2258097],"study_design_scores_gemma":[0.000067832494,0.0009458639,0.15931973,0.00009920091,0.00020405767,0.003708077,0.0013437176,0.6119921,0.16580445,0.016020412,0.040343255,0.00015134068],"about_ca_topic_score_codex":0.0011223892,"about_ca_topic_score_gemma":0.0010513053,"teacher_disagreement_score":0.0012188014,"about_ca_system_score_codex":0.00046697535,"about_ca_system_score_gemma":0.00059920165,"threshold_uncertainty_score":0.0062845945},"labels":[],"label_agreement":null},{"id":"W2400277655","doi":"","title":"Dynamic Multi-Resource Monitoring for Predictive Job Scheduling with ScoPro.","year":2005,"lang":"en","type":"article","venue":"IASTED PDCS","topic":"Distributed and Parallel Computing Systems","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 Windsor","funders":"","keywords":"Computer science; Workload; Distributed computing; Job scheduler; Scheduling (production processes); Grid; Intrusion detection system; Shared resource; Job queue; Real-time computing; Resource (disambiguation); Grid computing; Data mining; Cloud computing; Operating system; Computer network; Engineering; Operations management","score_opus":0.019365039111041826,"score_gpt":0.267704726324828,"score_spread":0.2483396872137862,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2400277655","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":[0.047218066,0.0004091854,0.89029664,0.00023900667,0.00016083501,0.0002748836,0.00067402946,0.055391937,0.0053354045],"genre_scores_gemma":[0.68186337,0.00018526835,0.31215373,0.00022281318,0.00007342744,0.00026328675,0.0009898266,0.0013267879,0.002921497],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989034,0.0002568146,0.00007299913,0.00024118158,0.00042729324,0.000098377124],"domain_scores_gemma":[0.99653697,0.0012546779,0.00044919422,0.0011621249,0.0004190574,0.00017798902],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012197695,0.0009200155,0.00060364406,0.0012341553,0.0004445369,0.0010559291,0.0014179521,0.0005121688,0.0025222902],"category_scores_gemma":[0.0053798887,0.0005451509,0.00033856797,0.0007867976,0.0006146163,0.0012878531,0.0010081582,0.0008367574,0.0008239222],"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":[0.0035304818,0.0006017565,0.032577936,0.0008321443,0.0002570353,0.001131367,0.0007779324,0.09708953,0.19343549,0.015050931,0.023325002,0.63139045],"study_design_scores_gemma":[0.00007654456,0.00023824316,0.0045423135,0.00005277418,0.000049299335,0.00053641153,0.000055385877,0.8919963,0.080200896,0.0041051377,0.018067356,0.00007943117],"about_ca_topic_score_codex":0.001582012,"about_ca_topic_score_gemma":0.0021306644,"teacher_disagreement_score":0.0025222902,"about_ca_system_score_codex":0.0004476343,"about_ca_system_score_gemma":0.0009184574,"threshold_uncertainty_score":0.008437872},"labels":[],"label_agreement":null},{"id":"W65480259","doi":"","title":"The BNAI Analyzer: A Tool for Verifying Admissible Information Flow in Protocols.","year":2002,"lang":"en","type":"article","venue":"IASTED PDCS","topic":"Physical Unclonable Functions (PUFs) and Hardware Security","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","funders":"","keywords":"Computer science; Property (philosophy); Protocol (science); Information flow; Bisimulation; State (computer science); Cryptographic protocol; Theoretical computer science; Finite-state machine; Confidentiality; Distributed computing; Programming language; Algorithm; Computer security; Cryptography","score_opus":0.025942878433576667,"score_gpt":0.25591780839669853,"score_spread":0.22997492996312185,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W65480259","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":[0.0028025485,0.000065371576,0.9828743,0.000038283943,0.000033323897,0.00010396139,0.00017518783,0.012428195,0.0014788681],"genre_scores_gemma":[0.14616355,0.0003179337,0.8452275,0.0001898038,0.000047911857,0.00088837894,0.0011359132,0.0023516633,0.0036773556],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9948631,0.0014848146,0.0004604347,0.00065934856,0.0022167,0.00031561728],"domain_scores_gemma":[0.9877509,0.0073572025,0.0011807102,0.002435597,0.0010517434,0.0002238753],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004563648,0.0018093048,0.00095266313,0.0023090632,0.00084640447,0.0022365204,0.0023626012,0.0015796331,0.0071143047],"category_scores_gemma":[0.019903466,0.0010733533,0.0010173013,0.0009387647,0.0024271472,0.0041030496,0.0028165705,0.0030377659,0.0030890445],"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":[0.0011642866,0.0004328241,0.0063529015,0.0020147874,0.00032113263,0.0020572126,0.0017271008,0.06205074,0.1323921,0.411149,0.020113166,0.36022475],"study_design_scores_gemma":[0.00016458746,0.00039768868,0.0013608853,0.00035301474,0.00013265168,0.002206943,0.00019491004,0.5245518,0.1958088,0.19871193,0.07593895,0.00017789325],"about_ca_topic_score_codex":0.001363876,"about_ca_topic_score_gemma":0.0007326514,"teacher_disagreement_score":0.0071143047,"about_ca_system_score_codex":0.0007736374,"about_ca_system_score_gemma":0.002414161,"threshold_uncertainty_score":0.024135172},"labels":[],"label_agreement":null}]}