{"meta":{"query_hash":"d16bd10738f3","filters":{"venue":"Journal of Computer Science and Technology"},"cohort_total":49,"direct_labels_cover":0,"predictions_cover":49,"exported":49,"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/d16bd10738f3","api":"https://metacan.xera.ac/api/v1/cohort?venue=Journal+of+Computer+Science+and+Technology"},"results":[{"id":"W1500816613","doi":"10.1007/s11390-010-9361-x","title":"A New Approach for Multi-Document Update Summarization","year":2010,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Automatic summarization; Computer science; NIST; Multi-document summarization; Information retrieval; Set (abstract data type); The Internet; Data mining; World Wide Web; Natural language processing","score_opus":0.013781065863221347,"score_gpt":0.268831526655241,"score_spread":0.25505046079201965,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1500816613","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":[0.0028628695,0.000933682,0.9910595,0.00021007074,0.0004308325,0.0001790607,0.00029584122,0.0028553996,0.0011726681],"genre_scores_gemma":[0.032798313,0.0007759003,0.9544558,0.0001985409,0.00072630926,0.00024708672,0.0013070102,0.0003358734,0.009155205],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975706,0.00032387002,0.00030931373,0.00053868076,0.0011333313,0.00012419926],"domain_scores_gemma":[0.99737716,0.00062985957,0.00013381976,0.0005452137,0.0012232203,0.00009068014],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012770559,0.0014615156,0.0017657804,0.004232118,0.0013017228,0.0025910127,0.0017374486,0.0013871018,0.0060694884],"category_scores_gemma":[0.0037997316,0.00055211596,0.0012478003,0.0037443016,0.00054971623,0.0028917897,0.0017035964,0.0015993165,0.004200967],"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":[0.00020600132,0.00012161569,0.00030335988,0.00023416786,0.00013558492,0.00013438631,0.0001535514,0.0056777955,0.03124106,0.006845803,0.011864901,0.9430818],"study_design_scores_gemma":[0.00015915347,0.0005530834,0.0015003763,0.00008538424,0.0005608184,0.0013395479,0.0002822015,0.78871197,0.081605054,0.026938036,0.09809916,0.00016532038],"about_ca_topic_score_codex":0.002544437,"about_ca_topic_score_gemma":0.005218999,"teacher_disagreement_score":0.0060694884,"about_ca_system_score_codex":0.00055612385,"about_ca_system_score_gemma":0.0013149192,"threshold_uncertainty_score":0.020304441},"labels":[],"label_agreement":null},{"id":"W1560117764","doi":"10.1007/s11390-011-9410-0","title":"A New Multiword Expression Metric and Its Applications","year":2011,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"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; Metric (unit); Artificial intelligence; Natural language processing; Theory of computation; Question answering; Semantics (computer science); Expression (computer science); Natural language; Programming language","score_opus":0.015518475762255969,"score_gpt":0.26688788907247896,"score_spread":0.251369413310223,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1560117764","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":[0.03449352,0.0036240031,0.95158803,0.00082296965,0.00059444754,0.00014082923,0.0011798191,0.0014382869,0.0061180606],"genre_scores_gemma":[0.23490167,0.00191569,0.750461,0.00032257318,0.0008217136,0.0004960664,0.0025688435,0.00078542053,0.007727074],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9951244,0.001424139,0.00070758513,0.00091662636,0.001685348,0.00014189188],"domain_scores_gemma":[0.9924469,0.00282379,0.000518426,0.0008641094,0.0028743662,0.00047242342],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003454671,0.0010480133,0.0014819553,0.0054815905,0.0011513787,0.0027752973,0.0017367831,0.0015383404,0.004754843],"category_scores_gemma":[0.01506962,0.0003586694,0.0010214535,0.0064531695,0.0010095976,0.0059488188,0.0023722108,0.0015013238,0.0024244955],"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":[0.00048859156,0.0002246875,0.0055597248,0.00058862317,0.00014565693,0.00030205568,0.00046466442,0.010020393,0.023359805,0.10112293,0.01123189,0.846491],"study_design_scores_gemma":[0.00009742097,0.0010077859,0.01000823,0.0001939997,0.0002700729,0.002448668,0.0006664782,0.63364094,0.024861429,0.2569485,0.06959409,0.00026245904],"about_ca_topic_score_codex":0.0012770589,"about_ca_topic_score_gemma":0.0010516209,"teacher_disagreement_score":0.0054815905,"about_ca_system_score_codex":0.000993265,"about_ca_system_score_gemma":0.0010575162,"threshold_uncertainty_score":0.018270254},"labels":[],"label_agreement":null},{"id":"W1573250459","doi":"10.1007/bf02949821","title":"A new classification method to overcome over-branching","year":2002,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Branching (polymer chemistry); Decision tree; Data mining; Theory of computation; Decision tree learning; Node (physics); Incremental decision tree; Binary decision diagram; Artificial intelligence; Machine learning; Algorithm","score_opus":0.024238915323537544,"score_gpt":0.2958042842500415,"score_spread":0.27156536892650396,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1573250459","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":[0.012179191,0.00068365474,0.97975326,0.00072723645,0.000719651,0.00020584418,0.0002778882,0.0024727038,0.0029805573],"genre_scores_gemma":[0.10464441,0.0004155682,0.8817555,0.0007193174,0.0006152994,0.0003544635,0.0009565459,0.00040862942,0.010130385],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997157,0.00037846484,0.00024667257,0.0006978841,0.001291231,0.00022874962],"domain_scores_gemma":[0.99374545,0.0019137659,0.00037933004,0.0009016777,0.002721037,0.00033878855],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028614076,0.00096138136,0.0016752094,0.0035732158,0.0018757454,0.0026867124,0.0038529288,0.0025908474,0.0054583587],"category_scores_gemma":[0.0074244216,0.00048738904,0.0012125139,0.0034602042,0.00083210843,0.0034719757,0.002136635,0.002966017,0.002673104],"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":[0.0002219118,0.00028043962,0.0028160452,0.00014920592,0.000078373785,0.00010049036,0.00013872431,0.006372154,0.008853942,0.015677202,0.018410053,0.9469015],"study_design_scores_gemma":[0.00017029225,0.00022414466,0.0021424543,0.000097492455,0.0002141238,0.0008772739,0.00012699343,0.88675845,0.015937723,0.049721435,0.04361594,0.00011367757],"about_ca_topic_score_codex":0.0022976035,"about_ca_topic_score_gemma":0.0034442672,"teacher_disagreement_score":0.0054583587,"about_ca_system_score_codex":0.0008319166,"about_ca_system_score_gemma":0.0020762368,"threshold_uncertainty_score":0.018260002},"labels":[],"label_agreement":null},{"id":"W1980666253","doi":"10.1007/s11390-008-9148-5","title":"Clustering by Pattern Similarity","year":2008,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"","keywords":"Similarity (geometry); Cluster analysis; Computer science; Closeness; Set (abstract data type); Data mining; Euclidean distance; Artificial intelligence; Task (project management); Range (aeronautics); Pattern recognition (psychology); Mathematics; Image (mathematics)","score_opus":0.009573061431451745,"score_gpt":0.24141486421708222,"score_spread":0.23184180278563046,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1980666253","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":[0.029496074,0.00050403795,0.9644519,0.00029654754,0.0001395587,0.00029622842,0.00045223447,0.001233849,0.0031295717],"genre_scores_gemma":[0.3159715,0.000498555,0.6710779,0.00016529944,0.00021879017,0.00046845095,0.0024035806,0.00043300545,0.008762899],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977156,0.00056137366,0.00015855955,0.0007680634,0.0006776614,0.00011878733],"domain_scores_gemma":[0.9962835,0.0011901415,0.00029496074,0.001176811,0.00091576844,0.00013880864],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013137914,0.0007030067,0.0017337102,0.0075032557,0.0017375131,0.0022231042,0.0021180746,0.0016509373,0.0044840635],"category_scores_gemma":[0.007841931,0.0008008349,0.0018508504,0.006033236,0.0012547409,0.0026814588,0.0018949124,0.0011589653,0.0023968974],"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":[0.0004936116,0.00030569264,0.007434618,0.00043462458,0.0007026057,0.00021927521,0.00040868486,0.114697434,0.016489113,0.060873855,0.016588349,0.7813521],"study_design_scores_gemma":[0.00005578199,0.00011184507,0.0032266784,0.000030841547,0.00012686633,0.00042867972,0.00015502109,0.88842183,0.0069753407,0.09215859,0.008257646,0.000050833212],"about_ca_topic_score_codex":0.0034081533,"about_ca_topic_score_gemma":0.0037302899,"teacher_disagreement_score":0.0075032557,"about_ca_system_score_codex":0.0010079526,"about_ca_system_score_gemma":0.00092469336,"threshold_uncertainty_score":0.015000641},"labels":[],"label_agreement":null},{"id":"W1982014661","doi":"10.1007/s11390-013-1389-2","title":"Non-Intrusive Elastic Query Processing in the Cloud","year":2013,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Cloud computing; Flexibility (engineering); Distributed computing; Elasticity (physics); Service level; Database; Theory of computation; Service-level agreement; Operating system; Algorithm","score_opus":0.006028355547624473,"score_gpt":0.2314365825682686,"score_spread":0.22540822702064411,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1982014661","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":[0.69333804,0.004573585,0.27475497,0.0024343603,0.0007698048,0.00046648164,0.0010036749,0.009676737,0.012982272],"genre_scores_gemma":[0.96772254,0.000314786,0.029111242,0.00014832459,0.000165134,0.000036320816,0.00031144283,0.00014176183,0.002048465],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9937103,0.0009094952,0.00044468194,0.0010084077,0.0025434392,0.0013836538],"domain_scores_gemma":[0.9879517,0.0034633162,0.0008193824,0.005609741,0.0014556618,0.0007001868],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034790556,0.0013648844,0.0017366516,0.0011136545,0.0029081076,0.0033316854,0.004468234,0.0011109932,0.0037143114],"category_scores_gemma":[0.0088735055,0.00091524917,0.00055955094,0.0033596458,0.0014048604,0.0060348175,0.0038034262,0.0015986444,0.0011083717],"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":[0.019220555,0.003164824,0.036894195,0.0007527066,0.000644195,0.0027343545,0.0013320615,0.21356052,0.13539438,0.035215396,0.044470225,0.5066166],"study_design_scores_gemma":[0.00022383615,0.0004165965,0.0040655276,0.000016657292,0.00010183393,0.00074130675,0.0006076171,0.95884633,0.019554209,0.011839448,0.0035368954,0.00004979877],"about_ca_topic_score_codex":0.00671999,"about_ca_topic_score_gemma":0.007298779,"teacher_disagreement_score":0.00671999,"about_ca_system_score_codex":0.0012891723,"about_ca_system_score_gemma":0.0028984135,"threshold_uncertainty_score":0.018399179},"labels":[],"label_agreement":null},{"id":"W1983413912","doi":"10.1007/bf02948810","title":"Extending the relational model to deal with probabilistic data","year":2000,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Soundness; Computer science; Relational database; Relational model; Probabilistic logic; Probabilistic database; Relational calculus; Relational algebra; Completeness (order theory); Theoretical computer science; Theory of computation; Semantics (computer science); Database model; Probabilistic relevance model; Data mining; Programming language; Artificial intelligence; Probabilistic analysis of algorithms; Mathematics","score_opus":0.046261918017077505,"score_gpt":0.27861652706140666,"score_spread":0.23235460904432914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1983413912","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":[0.0014076466,0.0001546798,0.99642867,0.0006359084,0.000046175624,0.000019015502,0.00010989266,0.00016508189,0.0010329612],"genre_scores_gemma":[0.16758905,0.0018511445,0.82170105,0.0009885946,0.00068645267,0.0002662631,0.0009078605,0.00036064064,0.005649038],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9915906,0.0039451397,0.00063945586,0.0016318258,0.0018433066,0.0003495575],"domain_scores_gemma":[0.97037405,0.019040927,0.0015302134,0.006489219,0.0019938266,0.0005718508],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011076667,0.0011333007,0.0018750911,0.0027093133,0.0015983033,0.006294356,0.004723881,0.0034793995,0.007349715],"category_scores_gemma":[0.048902825,0.0017882336,0.0041722865,0.0039883857,0.0025201472,0.018111601,0.005149488,0.0050297426,0.002672321],"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":[0.00008289728,0.00012958384,0.0023234899,0.00021897837,0.00025091323,0.00064826285,0.0008121959,0.08812059,0.0010602749,0.826652,0.0038587858,0.07584213],"study_design_scores_gemma":[0.000026903119,0.000033990735,0.00017964936,0.000050010436,0.00011312926,0.00039410338,0.00005794925,0.353629,0.00046684232,0.63641053,0.008594135,0.000043842832],"about_ca_topic_score_codex":0.0062716287,"about_ca_topic_score_gemma":0.005361356,"teacher_disagreement_score":0.011076667,"about_ca_system_score_codex":0.0012203912,"about_ca_system_score_gemma":0.0024486003,"threshold_uncertainty_score":0.058579743},"labels":[],"label_agreement":null},{"id":"W1985018844","doi":"10.1007/bf02944912","title":"An orientation update message filtering algorithm in collaborative virtual environments","year":2004,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Mobile Agent-Based Network Management","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"Killam Trusts","keywords":"Computer science; Orientation (vector space); Thresholding; Dead reckoning; Focus (optics); Rotation (mathematics); Theory of computation; Algorithm; Variable (mathematics); Collaborative filtering; Computer vision; Artificial intelligence; Telecommunications; Global Positioning System; Image (mathematics); Mathematics; Information retrieval","score_opus":0.004342605606649813,"score_gpt":0.22809720189492005,"score_spread":0.22375459628827024,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1985018844","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":[0.024954066,0.00025602317,0.97177684,0.00011718734,0.00014854994,0.000072154624,0.000039725997,0.0013739023,0.0012615977],"genre_scores_gemma":[0.34874725,0.0002298847,0.64487064,0.00011891156,0.00014421475,0.00012284146,0.0002567515,0.00014989614,0.005359685],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984812,0.0003364607,0.00011784588,0.0002534075,0.0006144495,0.00019668393],"domain_scores_gemma":[0.99694103,0.0011118212,0.00022121411,0.00057983916,0.00096382055,0.00018226466],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019213422,0.0007105234,0.0015012916,0.0018611114,0.0014356988,0.0017903841,0.0019126639,0.0014529653,0.0021356246],"category_scores_gemma":[0.005486529,0.000484226,0.0005105593,0.0014747354,0.0005607268,0.002189867,0.0013612392,0.0008971419,0.0009995741],"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":[0.0010800814,0.0004669693,0.003238213,0.00009150038,0.00010692521,0.00009544751,0.00031536695,0.09175755,0.018910082,0.014432839,0.0058430987,0.863662],"study_design_scores_gemma":[0.0000857537,0.00014995258,0.0009568546,0.000010543535,0.000055837194,0.000089289555,0.00008680195,0.9774534,0.012555686,0.0048268307,0.0036944486,0.000034518143],"about_ca_topic_score_codex":0.009592794,"about_ca_topic_score_gemma":0.00775924,"teacher_disagreement_score":0.009592794,"about_ca_system_score_codex":0.000863914,"about_ca_system_score_gemma":0.0013748882,"threshold_uncertainty_score":0.019073904},"labels":[],"label_agreement":null},{"id":"W1990984688","doi":"10.1007/bf02945466","title":"Analyzing and mining ordered information tables","year":2003,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Ranking (information retrieval); Table (database); Dependency (UML); Association rule learning; Data mining; Value (mathematics); Order (exchange); Information extraction; Theory of computation; Theoretical computer science; Information retrieval; Artificial intelligence; Machine learning; Algorithm","score_opus":0.00813276642335179,"score_gpt":0.21772165859485051,"score_spread":0.20958889217149873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1990984688","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":[0.55904716,0.0049828794,0.42140383,0.0011698059,0.00017179476,0.0004503782,0.0062894416,0.0013994983,0.005085092],"genre_scores_gemma":[0.66706085,0.002140509,0.32220373,0.000101821955,0.00008615917,0.00013778283,0.0065376386,0.00004962027,0.0016819179],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982632,0.0002728034,0.00027367266,0.00017022663,0.0008849009,0.0001351857],"domain_scores_gemma":[0.9918532,0.005686986,0.00081780914,0.00046664642,0.0009337816,0.000241666],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016260333,0.0004743738,0.0009629696,0.008555718,0.0008864112,0.0031442554,0.0009032299,0.00066484226,0.0013376756],"category_scores_gemma":[0.011504847,0.0006270207,0.0010390506,0.0070543503,0.00049296924,0.00523194,0.00080414995,0.0006992172,0.00036242887],"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":[0.00082517485,0.0007495525,0.09026209,0.0023168838,0.00068647746,0.0037483915,0.0018171195,0.084561795,0.017191906,0.07690015,0.013021277,0.70791924],"study_design_scores_gemma":[0.00010611141,0.0005173724,0.02127729,0.00049758825,0.00080507924,0.0019173541,0.0028870949,0.6807537,0.033361875,0.22865826,0.029090026,0.00012823452],"about_ca_topic_score_codex":0.0023591556,"about_ca_topic_score_gemma":0.0033747563,"teacher_disagreement_score":0.008555718,"about_ca_system_score_codex":0.0007689239,"about_ca_system_score_gemma":0.0015721074,"threshold_uncertainty_score":0.008599341},"labels":[],"label_agreement":null},{"id":"W1996087956","doi":"10.1007/s11390-006-1012-x","title":"Parallel Switch System with QoS Guarantee for Real-Time Traffic","year":2006,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Interconnection Networks and Systems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sierra Wireless (Canada)","funders":"","keywords":"Computer science; Quality of service; Computer network; Multicast; Network packet; Unicast; Scalability; Bandwidth (computing); Distributed computing; Differentiated services; Load balancing (electrical power)","score_opus":0.005619743502437127,"score_gpt":0.2053705500553666,"score_spread":0.19975080655292948,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1996087956","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":[0.5948768,0.0007511274,0.38577235,0.00079792214,0.00069550617,0.00022760067,0.0004280754,0.0077662137,0.008684394],"genre_scores_gemma":[0.97958434,0.00011572831,0.01682181,0.000107127584,0.00017196893,0.000057418754,0.00016061218,0.00005914506,0.0029217019],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995721,0.000073039635,0.0000284841,0.00012694267,0.00009197701,0.00010741261],"domain_scores_gemma":[0.999047,0.00025933995,0.000089717585,0.0002033586,0.00028471378,0.00011582726],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00076854223,0.00078950287,0.0013866052,0.0006538031,0.0012296359,0.0013167359,0.0017456756,0.00064001925,0.00529054],"category_scores_gemma":[0.00103713,0.00030140096,0.00036119728,0.0006639583,0.00046627678,0.0010037462,0.0007779781,0.00084751006,0.0006053939],"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":[0.011216608,0.0023341086,0.0076142224,0.0008018217,0.00074573566,0.002564847,0.0005704407,0.3998801,0.18199982,0.041205015,0.035567276,0.31550008],"study_design_scores_gemma":[0.000516028,0.0007204318,0.0010645068,0.0000079409765,0.00022342062,0.00041917825,0.000042166026,0.97161984,0.013573554,0.009277576,0.0024996535,0.000035684967],"about_ca_topic_score_codex":0.0021722058,"about_ca_topic_score_gemma":0.0028100368,"teacher_disagreement_score":0.00529054,"about_ca_system_score_codex":0.000829864,"about_ca_system_score_gemma":0.0012314104,"threshold_uncertainty_score":0.017698586},"labels":[],"label_agreement":null},{"id":"W1998214657","doi":"10.1007/bf02944790","title":"Provisioning QoS guarantee by multipath routing and reservation in Ad hoc networks","year":2004,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Mobile Ad Hoc Networks","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer network; Computer science; Quality of service; Multipath routing; Wireless ad hoc network; Bandwidth (computing); Mobile ad hoc network; Optimized Link State Routing Protocol; Network packet; Distributed computing; Routing protocol; Dynamic Source Routing; Wireless; Telecommunications","score_opus":0.0067813075484569755,"score_gpt":0.22922571477546658,"score_spread":0.2224444072270096,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1998214657","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":[0.19749597,0.0030628596,0.79243153,0.00087943947,0.0004219076,0.00006286476,0.00008390178,0.0016363915,0.003925204],"genre_scores_gemma":[0.9259952,0.0006987684,0.07108977,0.000072256036,0.00019418696,0.000025436877,0.00006332105,0.00006966883,0.0017915275],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99913967,0.00021318857,0.00006529934,0.000113518545,0.00031706895,0.00015124673],"domain_scores_gemma":[0.9964437,0.0019535492,0.00031200377,0.0005922531,0.0005228372,0.00017562369],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019247899,0.0005734086,0.0008401986,0.00089839543,0.0012568131,0.0016139362,0.0014277453,0.00089123973,0.0011035248],"category_scores_gemma":[0.0056164507,0.00058933406,0.00027441516,0.001129344,0.0008098473,0.0024000541,0.001106932,0.00094596465,0.00027047942],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017164556,0.00023591137,0.0061959424,0.0003036966,0.00020089514,0.00062398857,0.0005419678,0.46825668,0.064787224,0.07840371,0.0061550112,0.37257847],"study_design_scores_gemma":[0.000047313308,0.00013903674,0.0005011262,0.000015588754,0.00006633651,0.0002587698,0.00009878156,0.9592426,0.008565879,0.026780345,0.00424682,0.000037366313],"about_ca_topic_score_codex":0.0018934185,"about_ca_topic_score_gemma":0.0025578435,"teacher_disagreement_score":0.0019247899,"about_ca_system_score_codex":0.0008960066,"about_ca_system_score_gemma":0.0010655782,"threshold_uncertainty_score":0.010179341},"labels":[],"label_agreement":null},{"id":"W2002223291","doi":"10.1007/s11390-014-1415-z","title":"Minimizing the Discrepancy Between Source and Target Domains by Learning Adapting Components","year":2014,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Domain Adaptation and Few-Shot Learning","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; University of British Columbia","funders":"","keywords":"Computer science; Independence (probability theory); Embedding; Dimensionality reduction; Range (aeronautics); Feature (linguistics); Reproducing kernel Hilbert space; Domain (mathematical analysis); Theory of computation; Kernel (algebra); Domain adaptation; Feature vector; Curse of dimensionality; Artificial intelligence; Kernel method; Feature selection; Machine learning; Algorithm; Hilbert space; Support vector machine; Mathematics","score_opus":0.009523472966358878,"score_gpt":0.22457562986387813,"score_spread":0.21505215689751925,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2002223291","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":[0.05301847,0.00070459483,0.94372624,0.00022967748,0.000069880065,0.000070090246,0.000086235,0.0011738467,0.0009209003],"genre_scores_gemma":[0.6109488,0.00072091917,0.38182887,0.00051158475,0.00013770712,0.00018966608,0.0010161147,0.00042791467,0.0042183874],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991247,0.00025409053,0.000057250596,0.00033406672,0.00015822751,0.0000716355],"domain_scores_gemma":[0.99698406,0.0019612203,0.0001267307,0.00041876506,0.0004042967,0.00010486734],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015805396,0.0014625709,0.00160206,0.0010404632,0.0004562126,0.0010550024,0.0020425878,0.0021797824,0.0012269164],"category_scores_gemma":[0.007025308,0.000576623,0.00090921926,0.00091869844,0.0008106082,0.0023701952,0.0021379204,0.0022641895,0.00077621493],"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":[0.00079990027,0.00050348166,0.004864098,0.00040458742,0.00035310994,0.00019430541,0.00023912515,0.34876353,0.03526628,0.007231813,0.0066999486,0.5946799],"study_design_scores_gemma":[0.00002462968,0.0000852772,0.00055005064,0.000018045806,0.00006024196,0.00009340998,0.000049917006,0.98476195,0.005585084,0.008101689,0.00065314403,0.00001646782],"about_ca_topic_score_codex":0.003208378,"about_ca_topic_score_gemma":0.0035557395,"teacher_disagreement_score":0.003208378,"about_ca_system_score_codex":0.0005874075,"about_ca_system_score_gemma":0.0011816111,"threshold_uncertainty_score":0.008358777},"labels":[],"label_agreement":null},{"id":"W2004162621","doi":"10.1007/s11390-014-1478-x","title":"Allocating Bandwidth in Datacenter Networks: A Survey","year":2014,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":false,"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; Cloud computing; Bandwidth (computing); Predictability; Distributed computing; Virtual machine; Bandwidth allocation; Computer network; Operating system","score_opus":0.009527116322786296,"score_gpt":0.22880218658457224,"score_spread":0.21927507026178594,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2004162621","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.034259792,0.8343088,0.11246934,0.0021637315,0.00047590843,0.00010673361,0.00021754562,0.0004040369,0.015594112],"genre_scores_gemma":[0.184865,0.7451418,0.06366473,0.0008451678,0.0014982865,0.00010417193,0.00057280797,0.00014583864,0.0031622318],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99805766,0.00034132553,0.0002311116,0.000447859,0.0006918549,0.0002302569],"domain_scores_gemma":[0.9949268,0.0032211745,0.0003818786,0.00034261096,0.0009083855,0.00021911037],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025279124,0.0011995529,0.00166965,0.0032304279,0.00067478576,0.0034309325,0.0027846328,0.001367499,0.002003629],"category_scores_gemma":[0.006757652,0.0009561108,0.00059371634,0.0074375127,0.00065781415,0.00544095,0.001266901,0.001179311,0.0007296782],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001634129,0.0002626784,0.0070395344,0.003503386,0.00009850365,0.00006612617,0.00020176124,0.022031372,0.0026156914,0.01752706,0.0078679165,0.9386226],"study_design_scores_gemma":[0.00013401019,0.0013394146,0.014290191,0.0057452456,0.0006526496,0.0026956405,0.0023947097,0.24475707,0.018837849,0.07187981,0.63704556,0.00022783296],"about_ca_topic_score_codex":0.0021436438,"about_ca_topic_score_gemma":0.002304999,"teacher_disagreement_score":0.0034309325,"about_ca_system_score_codex":0.0010729209,"about_ca_system_score_gemma":0.0017957481,"threshold_uncertainty_score":0.013369024},"labels":[],"label_agreement":null},{"id":"W2010870819","doi":"10.1007/s11390-013-1327-3","title":"Exact Computation of the Topology and Geometric Invariants of the Voronoi Diagram of Spheres in 3D","year":2013,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Computational Geometry and Mesh Generation","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Voronoi diagram; Bowyer–Watson algorithm; Delaunay triangulation; Mathematics; Weighted Voronoi diagram; Computation; Power diagram; Polynomial; Discrete mathematics; Combinatorics; Algorithm; Geometry; Mathematical analysis","score_opus":0.007804314696087489,"score_gpt":0.2280808822904212,"score_spread":0.2202765675943337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2010870819","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":[0.27552116,0.00042829578,0.71380025,0.00019258953,0.00008244468,0.00005383962,0.00060256105,0.0016286061,0.0076902322],"genre_scores_gemma":[0.9108436,0.00010107013,0.08725754,0.000018592735,0.000022387352,0.000026981621,0.00042112995,0.00017367885,0.0011351305],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995958,0.00004963879,0.000022288345,0.000049679704,0.00023206521,0.00005059611],"domain_scores_gemma":[0.99866986,0.00054959056,0.00011679841,0.0002977564,0.00025791954,0.00010815002],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004427478,0.0004470341,0.001182281,0.0017488478,0.0006342542,0.0018260368,0.0015917791,0.00091997435,0.004560465],"category_scores_gemma":[0.003749793,0.00045821615,0.00051111344,0.0014346616,0.0010823512,0.002896982,0.0017377804,0.0007833585,0.0008394284],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044699086,0.00014490246,0.0064884233,0.000377767,0.00008668247,0.00040746748,0.000711604,0.6100003,0.010621658,0.20485441,0.0042946963,0.16156505],"study_design_scores_gemma":[0.000023277853,0.000018968576,0.0005223291,0.0000075028506,0.000005096319,0.000050622108,0.00006276958,0.95539653,0.0014258183,0.041627716,0.0008471607,0.000012169319],"about_ca_topic_score_codex":0.0049557206,"about_ca_topic_score_gemma":0.008559536,"teacher_disagreement_score":0.0049557206,"about_ca_system_score_codex":0.0010973639,"about_ca_system_score_gemma":0.0010794325,"threshold_uncertainty_score":0.015256286},"labels":[],"label_agreement":null},{"id":"W2011357342","doi":"10.1007/s11390-008-9140-0","title":"Performance of IEEE 802.15.4 Clusters with Power Management and Key Exchange","year":2008,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Security in Wireless Sensor Networks","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Computer network; Network packet; Key (lock); Reliability (semiconductor); Key management; Key exchange; Node (physics); Distributed coordination function; Personal area network; Power management; IEEE 802.15; IEEE 802.11; Wireless; Distributed computing; Wireless network; Wireless sensor network; Power (physics); Computer security; Public-key cryptography; Telecommunications; Encryption","score_opus":0.007823452779745608,"score_gpt":0.19796139236190113,"score_spread":0.19013793958215552,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2011357342","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":[0.9765196,0.0015927968,0.010943092,0.00095169985,0.00039878464,0.00008178569,0.00024427133,0.0014670041,0.007800928],"genre_scores_gemma":[0.9977755,0.00010898791,0.0010193699,0.000049402268,0.00002236047,0.000014564242,0.00011378879,0.000027760858,0.00086829544],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9972609,0.0006385567,0.00015096938,0.00039801377,0.0006551473,0.0008963354],"domain_scores_gemma":[0.9890956,0.006005533,0.00062099315,0.0007886084,0.0027574138,0.0007318218],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003573552,0.0010872445,0.0010437076,0.0009759612,0.001055373,0.0013265117,0.001620404,0.0011545302,0.0031904185],"category_scores_gemma":[0.010971735,0.0003751885,0.000266262,0.0009624569,0.0011043131,0.0016088876,0.0013390471,0.0008654518,0.0004103962],"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":[0.019123752,0.0009005184,0.01217867,0.0005319652,0.0003908271,0.00035776192,0.00064221775,0.8196391,0.027964517,0.0063009593,0.0152589055,0.096710786],"study_design_scores_gemma":[0.00042816665,0.002908748,0.009960905,0.00004282106,0.00019369788,0.0002858686,0.000500722,0.9638232,0.0177337,0.0022972324,0.001721309,0.000103710256],"about_ca_topic_score_codex":0.009546068,"about_ca_topic_score_gemma":0.005600633,"teacher_disagreement_score":0.009546068,"about_ca_system_score_codex":0.002081958,"about_ca_system_score_gemma":0.0017023523,"threshold_uncertainty_score":0.01898104},"labels":[],"label_agreement":null},{"id":"W2011531072","doi":"10.1007/s11390-008-9177-0","title":"Scalable Base-Station Model-Based Multicast in Wireless Sensor Networks","year":2008,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Hong Kong University of Science and Technology; University of Waterloo","keywords":"Multicast; Computer science; Source-specific multicast; Computer network; Protocol Independent Multicast; Xcast; Pragmatic General Multicast; Distributed computing; Wireless sensor network; Scalability; Base station; Distance Vector Multicast Routing Protocol; Reliable multicast; IP multicast; Network topology","score_opus":0.012371547765110808,"score_gpt":0.2225325987843088,"score_spread":0.210161051019198,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2011531072","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":[0.06807116,0.0009794452,0.92688125,0.0006142671,0.00019944004,0.00008599433,0.00011795749,0.00064630224,0.0024041845],"genre_scores_gemma":[0.9144324,0.0006458988,0.08316284,0.00010739908,0.00013312881,0.00012474132,0.0001353294,0.00010395825,0.0011544507],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99868995,0.0005579431,0.00005934198,0.0001433206,0.00043188452,0.00011763525],"domain_scores_gemma":[0.99806017,0.0011288247,0.00016947968,0.00032033396,0.00024713154,0.00007407967],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024430044,0.0006759781,0.0016058611,0.0006482963,0.0008129117,0.001035844,0.0021526446,0.001175803,0.0008208143],"category_scores_gemma":[0.005680997,0.0006081095,0.00057771994,0.001028379,0.0007217904,0.0025837487,0.0013374074,0.0011196699,0.00018028464],"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":[0.00017354215,0.00008415889,0.0004446943,0.0000899235,0.00006147234,0.00007999136,0.00007218717,0.9507432,0.00593374,0.018201442,0.0015856519,0.022529911],"study_design_scores_gemma":[0.0000059833465,0.000018098097,0.00003215897,0.000001895029,0.00000714674,0.000010432933,0.000005383916,0.9953843,0.00035715644,0.004053676,0.0001211131,0.0000025766717],"about_ca_topic_score_codex":0.001770009,"about_ca_topic_score_gemma":0.0022491417,"teacher_disagreement_score":0.0024430044,"about_ca_system_score_codex":0.0011351748,"about_ca_system_score_gemma":0.00095097325,"threshold_uncertainty_score":0.012919962},"labels":[],"label_agreement":null},{"id":"W2013794162","doi":"10.1007/s11390-008-9169-0","title":"Uplink Scheduling for Supporting Real Time Voice Traffic in IEEE 802.16 Backhaul Networks","year":2008,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Computer science; Computer network; Network packet; Scheduling (production processes); Real-time computing; Telecommunications link; Latency (audio); Real-time communication; Voice over IP; Telecommunications; Operating system; The Internet","score_opus":0.007132869994282196,"score_gpt":0.22649981576444358,"score_spread":0.2193669457701614,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013794162","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":[0.6518962,0.0024262257,0.3377502,0.00063227606,0.0004632214,0.00012204321,0.00011884104,0.0006316143,0.005959352],"genre_scores_gemma":[0.98811954,0.00013936775,0.011030713,0.000031985448,0.000075710166,0.000022248156,0.000019408111,0.000013937207,0.0005470054],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992617,0.00026369598,0.000055580796,0.00005535957,0.00017296508,0.00019068338],"domain_scores_gemma":[0.9976714,0.0012020367,0.00023624528,0.00021881146,0.00052914664,0.00014237138],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002092895,0.0003813917,0.0005853745,0.0004005034,0.0007203402,0.00083042873,0.00065458025,0.00030076684,0.0013122613],"category_scores_gemma":[0.0056756986,0.00023802121,0.000114260016,0.00037632242,0.0004472191,0.0006369481,0.0005169843,0.00042617638,0.00016335002],"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":[0.00217231,0.00033562985,0.0037240812,0.00023499195,0.00006466039,0.00032846525,0.000480111,0.70296055,0.03559464,0.020414293,0.0044537894,0.22923654],"study_design_scores_gemma":[0.00005457462,0.00020800806,0.0003751655,0.000009379042,0.000018066943,0.00006674071,0.00008098981,0.99133575,0.0035032323,0.0037065395,0.00063011685,0.000011441742],"about_ca_topic_score_codex":0.00308467,"about_ca_topic_score_gemma":0.004323557,"teacher_disagreement_score":0.00308467,"about_ca_system_score_codex":0.0009522376,"about_ca_system_score_gemma":0.0014924344,"threshold_uncertainty_score":0.011068463},"labels":[],"label_agreement":null},{"id":"W2016268596","doi":"10.1007/s11390-005-0017-1","title":"Book Review on ?Out of Their Minds: The Lives and Discoveries of 15 Great Computer Scientists?","year":2005,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Information Systems Theories and Implementation","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Reading (process); Theory of computation; Philosophy of science; Cognitive science; Engineering ethics; Mathematics education; Library science; Epistemology; Psychology; Philosophy; Programming language; Engineering; Linguistics","score_opus":0.014342962399030353,"score_gpt":0.3042089371027224,"score_spread":0.289865974703692,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2016268596","genre_codex":"review","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007137605,0.6883905,0.0008145267,0.1303588,0.07771601,0.00006496549,0.0005840051,0.00016955433,0.10118789],"genre_scores_gemma":[0.004576739,0.34762046,0.0008310844,0.046164352,0.055453174,0.000103825565,0.0006149013,0.00015101505,0.54448444],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9994142,0.00011654463,0.000024905868,0.00006786322,0.00033008683,0.000046405803],"domain_scores_gemma":[0.99741346,0.00092663267,0.00017327692,0.00006163419,0.0010638282,0.0003612028],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00070692686,0.000629659,0.00086263043,0.0016995699,0.00073971075,0.0032754506,0.00074600626,0.0021577647,0.04502898],"category_scores_gemma":[0.0036653958,0.0003125267,0.0003400654,0.0026842107,0.0006230916,0.0022826532,0.00079465087,0.0020890913,0.026861452],"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":[0.000006060937,0.000005303238,0.000047348138,0.0001443181,0.0000029614014,0.000012876457,0.000027662578,0.000017404094,0.00005266996,0.0008587253,0.9734769,0.025347762],"study_design_scores_gemma":[0.0000029869677,0.0000067049286,0.00017688223,0.00018590405,0.0000031119441,0.000054448163,0.00003078713,0.000011638032,0.000020604968,0.0005575098,0.9989465,0.0000029467876],"about_ca_topic_score_codex":0.0039938902,"about_ca_topic_score_gemma":0.014845632,"teacher_disagreement_score":0.04502898,"about_ca_system_score_codex":0.0017616996,"about_ca_system_score_gemma":0.0025703828,"threshold_uncertainty_score":0.15063697},"labels":[],"label_agreement":null},{"id":"W2016818970","doi":"10.1007/s11390-013-1324-6","title":"Formal Reasoning About Finite-State Discrete-Time Markov Chains in HOL","year":2013,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Formal Methods in Verification","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Markov chain; Theoretical computer science; Markov model; Markov property; Markov process; Variable-order Markov model; Formal verification; HOL; Probabilistic logic; Algorithm; Formal methods; Continuous-time Markov chain; Mathematics; Artificial intelligence; Machine learning; Programming language","score_opus":0.007466908350015211,"score_gpt":0.2520141899348308,"score_spread":0.24454728158481562,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2016818970","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":[0.023316218,0.00009769945,0.97110534,0.0005200646,0.000052147534,0.00010015138,0.0002453832,0.0010984823,0.003464559],"genre_scores_gemma":[0.7719461,0.00023143971,0.22290958,0.00029387814,0.00011795513,0.00020114236,0.0008020827,0.00029969052,0.0031981946],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9962948,0.0012025766,0.00038192567,0.00048566962,0.0010527761,0.00058227766],"domain_scores_gemma":[0.9727065,0.022859886,0.0011462708,0.0017173791,0.0011331898,0.00043683627],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0056556887,0.0008726777,0.0008751316,0.0017010221,0.0015428961,0.0048706657,0.0028592737,0.0014233828,0.0061438284],"category_scores_gemma":[0.018472603,0.0010803121,0.0036814932,0.0011157102,0.0042316737,0.008505559,0.003341989,0.003680084,0.000558449],"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":[0.00023779331,0.00017131302,0.0017454706,0.00028877112,0.00014144524,0.0006997177,0.0010418552,0.15130547,0.0024448521,0.8222842,0.0011098115,0.01852929],"study_design_scores_gemma":[0.0000882086,0.000024080853,0.00016734503,0.0000496358,0.00008392806,0.00006869562,0.0001596924,0.36104465,0.0036484129,0.63286895,0.0017699694,0.0000263132],"about_ca_topic_score_codex":0.0059073265,"about_ca_topic_score_gemma":0.007296607,"teacher_disagreement_score":0.0061438284,"about_ca_system_score_codex":0.0027247495,"about_ca_system_score_gemma":0.002380497,"threshold_uncertainty_score":0.029910505},"labels":[],"label_agreement":null},{"id":"W2018196039","doi":"10.1007/s11390-005-0008-2","title":"Online Palmprint Identification System for Civil Applications","year":2005,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"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; Preprocessor; Biometrics; Artificial intelligence; Identification (biology); Process (computing); Computer vision; Feature extraction; Feature (linguistics); Pattern recognition (psychology); Matching (statistics); False positive rate; Interface (matter); Identity (music)","score_opus":0.0144270102444696,"score_gpt":0.268303194913213,"score_spread":0.2538761846687434,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2018196039","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":[0.4627171,0.0012805682,0.47404128,0.0005252292,0.0006516398,0.0005701325,0.0013757049,0.024984494,0.033853933],"genre_scores_gemma":[0.83404666,0.00061726925,0.11381457,0.00047178738,0.00013425475,0.0003001435,0.00089777197,0.00036084917,0.049356654],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996934,0.000042425414,0.000015965341,0.000060195194,0.00014668034,0.00004138548],"domain_scores_gemma":[0.9995536,0.00008286881,0.000034649027,0.00010684199,0.00018934556,0.000032688607],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027834208,0.00039998695,0.00052650017,0.0008505568,0.0005343113,0.0004715473,0.00056186796,0.0007316254,0.023834879],"category_scores_gemma":[0.0005523473,0.00019956828,0.00021188293,0.00044991972,0.000119466466,0.00096428714,0.00043141743,0.0003624102,0.0071527343],"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":[0.0010839315,0.0004290693,0.0031175576,0.00015273398,0.000025517544,0.00038582226,0.00008543358,0.0008494418,0.42367378,0.00073080615,0.010466035,0.5589999],"study_design_scores_gemma":[0.00020958722,0.0012491385,0.043246564,0.000084241976,0.00028189571,0.003853129,0.0002147427,0.090412185,0.81141156,0.0012363388,0.047658667,0.00014189212],"about_ca_topic_score_codex":0.00049781695,"about_ca_topic_score_gemma":0.0009891362,"teacher_disagreement_score":0.023834879,"about_ca_system_score_codex":0.00021936443,"about_ca_system_score_gemma":0.0002967621,"threshold_uncertainty_score":0.07973564},"labels":[],"label_agreement":null},{"id":"W2044000055","doi":"10.1007/s11390-009-9205-8","title":"An Abstract Reachability Approach by Combining HOL Induction and Multiway Decision Graphs","year":2009,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Formal Methods in Verification","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"HOL; Reachability; Correctness; Computer science; Binary decision diagram; Automated theorem proving; Benchmark (surveying); Embedding; Theoretical computer science; Set (abstract data type); Binary number; Algorithm; Mathematics; Programming language; Artificial intelligence; Arithmetic","score_opus":0.01806091364229341,"score_gpt":0.29793431518903896,"score_spread":0.27987340154674556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2044000055","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":[0.0023389228,0.00002290502,0.9950676,0.00004581719,0.00001554746,0.00004985532,0.00004713275,0.000844204,0.0015680935],"genre_scores_gemma":[0.16478284,0.00013617665,0.82967955,0.00014414043,0.00003902613,0.00018223195,0.00047972138,0.0006335058,0.0039227516],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9977429,0.0005951247,0.00013655043,0.00048184893,0.0007273205,0.00031624694],"domain_scores_gemma":[0.9970605,0.0014393623,0.00014230565,0.0009790262,0.00029156954,0.00008725225],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016775739,0.00088203215,0.0009346714,0.0016595577,0.0009569862,0.0019034622,0.0024983326,0.00068365905,0.0068746987],"category_scores_gemma":[0.0027823986,0.000758666,0.0027138328,0.0009737646,0.0018153951,0.004257776,0.0030160663,0.0027901384,0.0014971523],"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":[0.0003311062,0.0006983643,0.0015522988,0.0006225183,0.00019846337,0.0004235969,0.00046704998,0.15183882,0.02941889,0.5196762,0.003404335,0.29136825],"study_design_scores_gemma":[0.00005818643,0.0001242085,0.0003251714,0.000077912046,0.00019166863,0.00010193306,0.00007283035,0.532752,0.029975742,0.42807803,0.008187757,0.000054641023],"about_ca_topic_score_codex":0.0018671936,"about_ca_topic_score_gemma":0.004238195,"teacher_disagreement_score":0.0068746987,"about_ca_system_score_codex":0.00086543406,"about_ca_system_score_gemma":0.0016678927,"threshold_uncertainty_score":0.022998214},"labels":[],"label_agreement":null},{"id":"W2044762750","doi":"10.1007/s11390-010-9335-z","title":"Towards Progressive and Load Balancing Distributed Computation: A Case Study on Skyline Analysis","year":2010,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"","keywords":"Skyline; Computer science; Load balancing (electrical power); Scalability; Distributed computing; Computation; Theory of computation; Distributed database; Load management; Data mining; Database; Algorithm","score_opus":0.009547070416137317,"score_gpt":0.2833963986359273,"score_spread":0.27384932821978997,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2044762750","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":[0.41765285,0.0008907462,0.5558274,0.0029383765,0.00008277965,0.00026998602,0.00029164428,0.0021435102,0.019902768],"genre_scores_gemma":[0.6816078,0.00047563127,0.31176528,0.00012815831,0.000069643385,0.000053712054,0.000301263,0.00043077595,0.005167638],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979996,0.00072119996,0.00009203905,0.0002625056,0.0007222868,0.00020225983],"domain_scores_gemma":[0.9925431,0.004073742,0.00031489116,0.0014308642,0.0012023723,0.00043503474],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031354972,0.0006043332,0.00059274724,0.0011611914,0.0024890727,0.00280502,0.0020117317,0.0017166653,0.002563614],"category_scores_gemma":[0.012092459,0.0003516804,0.000592956,0.004005019,0.0020436447,0.003430507,0.0016771746,0.0015042811,0.000491016],"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":[0.0009243846,0.00075130723,0.018669914,0.0008437034,0.0001622177,0.0025236527,0.008725371,0.35019284,0.02423296,0.23051652,0.019615842,0.34284124],"study_design_scores_gemma":[0.0001479988,0.00015477752,0.0037693884,0.00006942745,0.000074200056,0.0010437301,0.0028939878,0.8301032,0.013363873,0.10996288,0.038373485,0.00004308079],"about_ca_topic_score_codex":0.010825074,"about_ca_topic_score_gemma":0.014354182,"teacher_disagreement_score":0.010825074,"about_ca_system_score_codex":0.001538156,"about_ca_system_score_gemma":0.0018682247,"threshold_uncertainty_score":0.021524131},"labels":[],"label_agreement":null},{"id":"W2048682232","doi":"10.1007/s11390-009-9232-5","title":"A Scalable Testing Framework for Location-Based Services","year":2009,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; University of Alberta","funders":"","keywords":"Computer science; Scalability; Integration testing; Automation; Architecture; Model-based testing; Service (business); System testing; Unit testing; Test strategy; Software engineering; Distributed computing; Test case; Embedded system; Operating system; Software; Machine learning","score_opus":0.021245236870565853,"score_gpt":0.27247164064755136,"score_spread":0.2512264037769855,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2048682232","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":[0.017118743,0.00031009185,0.9456998,0.00022482169,0.00007017529,0.00019277613,0.00049135246,0.034599293,0.0012929251],"genre_scores_gemma":[0.48283133,0.00016630761,0.5117902,0.00020303723,0.000079097845,0.00031687014,0.0014568217,0.0011094965,0.0020468237],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99566287,0.0008148833,0.00034136997,0.0007204389,0.0019521822,0.0005083401],"domain_scores_gemma":[0.99366224,0.0028128582,0.00038204392,0.0016805012,0.0011123224,0.00035007304],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026506495,0.0016518807,0.0022004847,0.0020478726,0.00095533684,0.0025400296,0.006242247,0.0017597709,0.0067198505],"category_scores_gemma":[0.009786482,0.0008647314,0.001627398,0.001635504,0.0011675529,0.005657043,0.0039053208,0.001622292,0.0016030784],"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":[0.002059878,0.00094722357,0.009109309,0.00052458775,0.00041686426,0.00094372063,0.00033605797,0.2623506,0.0338747,0.041638467,0.027969647,0.61982894],"study_design_scores_gemma":[0.00006371899,0.00007241429,0.00029469654,0.000014801627,0.00004418001,0.00011003218,0.000038014285,0.9762706,0.0071215606,0.013894424,0.0020493397,0.000026201842],"about_ca_topic_score_codex":0.017641522,"about_ca_topic_score_gemma":0.015492342,"teacher_disagreement_score":0.017641522,"about_ca_system_score_codex":0.0015259701,"about_ca_system_score_gemma":0.0028794445,"threshold_uncertainty_score":0.03507763},"labels":[],"label_agreement":null},{"id":"W2049769908","doi":"10.1007/bf02960771","title":"Clustering DTDs: An interactive two-level approach","year":2002,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Cluster analysis; Document type definition; Document Structure Description; XML; Information retrieval; Data mining; Artificial intelligence","score_opus":0.04570929441094207,"score_gpt":0.31330563583075194,"score_spread":0.26759634141980987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2049769908","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":[0.0016715705,0.000041177096,0.99419034,0.0000952473,0.000021678059,0.00011145854,0.00010391654,0.0028195865,0.00094499416],"genre_scores_gemma":[0.029182145,0.00006700669,0.9673196,0.000077825985,0.000022345586,0.0001518771,0.0004287563,0.00074502657,0.0020054805],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99634296,0.00080269587,0.00027302175,0.0005442979,0.0017029622,0.0003340242],"domain_scores_gemma":[0.9954294,0.0020058742,0.00017908825,0.0010906238,0.0009670733,0.00032792432],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002858201,0.0017212763,0.0024917994,0.00416361,0.002556429,0.006072129,0.0058384077,0.003626963,0.019718684],"category_scores_gemma":[0.008563782,0.0018329691,0.0032432403,0.0030596864,0.0012083942,0.004565442,0.006371656,0.0028463844,0.0040657506],"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":[0.00078138633,0.00050595606,0.0019205969,0.0011903724,0.00035644675,0.0005514278,0.0015315933,0.14127722,0.04019524,0.07563295,0.023485076,0.71257174],"study_design_scores_gemma":[0.00009352887,0.00008321916,0.00039819564,0.000058872934,0.00008515065,0.00027349088,0.00026528357,0.92275864,0.015748441,0.041113276,0.019032383,0.00008949244],"about_ca_topic_score_codex":0.00611634,"about_ca_topic_score_gemma":0.012694247,"teacher_disagreement_score":0.019718684,"about_ca_system_score_codex":0.0019153676,"about_ca_system_score_gemma":0.0021878267,"threshold_uncertainty_score":0.06596553},"labels":[],"label_agreement":null},{"id":"W2058906553","doi":"10.1007/s11390-011-1149-0","title":"Energy Efficiency of a Multi-Core Processor by Tag Reduction","year":2011,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Hangzhou Dianzi University","keywords":"Computer science; Reduction (mathematics); Multi-core processor; Parallel computing; Core (optical fiber); Heuristics; Memory hierarchy; Single-core; Processor design; Efficient energy use; Energy (signal processing); Set (abstract data type); Many core; Embedded system; Operating system; Cache; Telecommunications","score_opus":0.020164666802462042,"score_gpt":0.2512085389561881,"score_spread":0.23104387215372607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2058906553","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":[0.7037824,0.0016060043,0.2710412,0.00052772847,0.0001625646,0.000056130906,0.000176835,0.0022261934,0.020420952],"genre_scores_gemma":[0.9573449,0.00013296132,0.035593156,0.00010361231,0.000019135501,0.000024603933,0.00012769095,0.000103291175,0.00655067],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99986744,0.000027741331,0.0000067928618,0.000020322837,0.000045280194,0.000032407363],"domain_scores_gemma":[0.99990165,0.000025788708,0.000009004229,0.000024008667,0.00003330582,0.0000062767695],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012145071,0.0003438983,0.0004898037,0.00032142337,0.00030718904,0.00036684336,0.0006626886,0.00033322035,0.0030917414],"category_scores_gemma":[0.00022776386,0.00013482348,0.00033909336,0.00053458405,0.0001350909,0.0005068982,0.00024651873,0.0002279231,0.0006603965],"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":[0.0029436976,0.0004097298,0.0030352355,0.0002911791,0.0001765294,0.0002720162,0.00008653262,0.22518145,0.49626446,0.008361171,0.0047535226,0.25822455],"study_design_scores_gemma":[0.000081291146,0.0006791013,0.003029187,0.000011493473,0.00014844956,0.00022171931,0.000043166157,0.83499396,0.15312524,0.0032025944,0.004439661,0.00002414742],"about_ca_topic_score_codex":0.000497455,"about_ca_topic_score_gemma":0.00101518,"teacher_disagreement_score":0.0030917414,"about_ca_system_score_codex":0.00021704657,"about_ca_system_score_gemma":0.0003689294,"threshold_uncertainty_score":0.010342956},"labels":[],"label_agreement":null},{"id":"W2061130392","doi":"10.1007/bf02950404","title":"Decision tree complexity of graph properties with dimension at most 5","year":2000,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Topological and Geometric Data Analysis","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Combinatorics; Monotone polygon; Conjecture; Vertex (graph theory); Graph; Discrete mathematics; Theory of computation; Mathematics; Computer science; Algorithm","score_opus":0.019459760509158333,"score_gpt":0.22352323356644951,"score_spread":0.20406347305729117,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2061130392","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":[0.7638748,0.0013030032,0.2117766,0.005497378,0.0000881292,0.00019087717,0.0039203814,0.0008053407,0.012543456],"genre_scores_gemma":[0.95984757,0.00053463434,0.03405684,0.0002951017,0.00016254596,0.00013164515,0.0023283246,0.00012522376,0.0025181363],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99721247,0.00065302337,0.00017174766,0.00050446263,0.0009272477,0.000531002],"domain_scores_gemma":[0.95616996,0.036322247,0.0022476313,0.0022138385,0.0013153304,0.0017309268],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022345802,0.00063685095,0.0019667242,0.0019997938,0.0012037834,0.00519612,0.0022114506,0.0019665968,0.008021026],"category_scores_gemma":[0.023378091,0.0007583198,0.0015196003,0.0026353274,0.001904438,0.010024414,0.0021152636,0.0033825326,0.00045875192],"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":[0.0017089256,0.0007107006,0.022028118,0.00073008955,0.0003239263,0.00059603323,0.000903891,0.20113118,0.0070939166,0.64946485,0.02162479,0.093683615],"study_design_scores_gemma":[0.00009995323,0.000090569214,0.0025241533,0.00003283827,0.00008545181,0.0003718717,0.00015231442,0.42589343,0.00153423,0.5675629,0.0016263473,0.000026000955],"about_ca_topic_score_codex":0.002274257,"about_ca_topic_score_gemma":0.0027137655,"teacher_disagreement_score":0.008021026,"about_ca_system_score_codex":0.0027831926,"about_ca_system_score_gemma":0.0018984798,"threshold_uncertainty_score":0.026832998},"labels":[],"label_agreement":null},{"id":"W2066687109","doi":"10.1007/s11390-007-9051-5","title":"Developing Project Duration Models in Software Engineering","year":2007,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Software Engineering Research","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal; Bell (Canada); École de Technologie Supérieure","funders":"","keywords":"Duration (music); Computer science; Benchmarking; Software; Software engineering; Theory of computation; Variable (mathematics); Software project management; Function point; Range (aeronautics); Industrial engineering; Operations research; Systems engineering; Software development; Software construction; Operating system; Engineering","score_opus":0.021558798790597647,"score_gpt":0.27681494181403127,"score_spread":0.25525614302343363,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2066687109","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":[0.017092602,0.00043818343,0.97832257,0.0003236033,0.000042210315,0.000065698434,0.00013098693,0.00021256087,0.0033716348],"genre_scores_gemma":[0.56683725,0.0017870793,0.4231686,0.00017413187,0.00013680846,0.0007002953,0.0008109233,0.00038352015,0.0060013966],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99728084,0.0014749545,0.00021288288,0.00029753998,0.00045833254,0.00027541368],"domain_scores_gemma":[0.9716912,0.023617577,0.0014834185,0.001021373,0.0016492467,0.0005372514],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008868127,0.0012075158,0.0010730538,0.0021290348,0.00083567936,0.0025662929,0.0027724877,0.0018686826,0.0033957716],"category_scores_gemma":[0.03203012,0.0017231331,0.0016857891,0.0022743272,0.0009096838,0.0046831425,0.0016892981,0.002673353,0.0008801772],"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":[0.000047073263,0.00009672209,0.0016069451,0.00010408104,0.00005366858,0.000067199195,0.00024696166,0.8449022,0.00036203966,0.11100046,0.0014418189,0.04007085],"study_design_scores_gemma":[0.000010033689,0.000020156038,0.00021917296,0.000030672767,0.000021972619,0.000012973617,0.000044457636,0.93657506,0.00015845336,0.0615319,0.0013649215,0.0000101580645],"about_ca_topic_score_codex":0.012476481,"about_ca_topic_score_gemma":0.010999805,"teacher_disagreement_score":0.012476481,"about_ca_system_score_codex":0.003188781,"about_ca_system_score_gemma":0.0033202036,"threshold_uncertainty_score":0.046899676},"labels":[],"label_agreement":null},{"id":"W2068220037","doi":"10.1007/bf02944804","title":"A note on the single genotype resolution problem","year":2004,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Genomic variations and chromosomal abnormalities","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Resolution (logic); Reduction (mathematics); Theory of computation; Computer science; NP-complete; Computational complexity theory; Algorithm; Mathematical optimization; Mathematics; Artificial intelligence; Geometry","score_opus":0.007527063486905003,"score_gpt":0.20816447713740835,"score_spread":0.20063741365050336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2068220037","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":[0.005851898,0.0136574535,0.7352771,0.19372284,0.01636245,0.00012981052,0.0005316813,0.0012010132,0.033265755],"genre_scores_gemma":[0.1420239,0.025015714,0.675869,0.056526348,0.064484425,0.0005682131,0.0010661767,0.0018144712,0.032631792],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98661774,0.0057187723,0.00068561686,0.0023875304,0.004007873,0.000582555],"domain_scores_gemma":[0.7598292,0.2161708,0.0017214187,0.014376275,0.0065435874,0.0013586611],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.014767976,0.0016483135,0.004373194,0.002940842,0.0051919413,0.0059520225,0.008432603,0.012403366,0.01648277],"category_scores_gemma":[0.10389017,0.0014145748,0.003304927,0.0046766815,0.00951825,0.020629007,0.0074808644,0.027914377,0.004177153],"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":[0.00033344727,0.00014069206,0.0010619807,0.0006976299,0.00021265313,0.002554785,0.00053040526,0.020996561,0.0013574542,0.5754345,0.19917025,0.1975097],"study_design_scores_gemma":[0.0000798608,0.000024658271,0.0001868834,0.00011865525,0.000045162986,0.0011136306,0.00012173871,0.018067587,0.0004190623,0.94471484,0.035029337,0.00007862763],"about_ca_topic_score_codex":0.0035298245,"about_ca_topic_score_gemma":0.0022344762,"teacher_disagreement_score":0.01648277,"about_ca_system_score_codex":0.0017372768,"about_ca_system_score_gemma":0.002286937,"threshold_uncertainty_score":0.078101456},"labels":[],"label_agreement":null},{"id":"W2071416419","doi":"10.1007/s11390-008-9115-1","title":"Clustering Text Data Streams","year":2008,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Data Stream Mining Techniques","field":"Computer Science","cited_by":57,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Simon Fraser University; Chinese University of Hong Kong; University of Hong Kong; Sun Yat-sen University","keywords":"Computer science; Cluster analysis; Data mining; Data stream mining; Data stream clustering; Smoothing; Document clustering; Fuzzy clustering; Semantics (computer science); Context (archaeology); Information retrieval; CURE data clustering algorithm; Artificial intelligence","score_opus":0.035988189501161005,"score_gpt":0.27897509842622664,"score_spread":0.24298690892506564,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2071416419","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":[0.1405475,0.0018805646,0.84304464,0.0011844352,0.000996647,0.0010825763,0.0032947417,0.004141348,0.003827539],"genre_scores_gemma":[0.43768042,0.002010755,0.5300859,0.00026450632,0.00096877135,0.0008120037,0.014089093,0.00039690617,0.013691599],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980692,0.00022181998,0.0002617652,0.0004511868,0.0008579333,0.00013810773],"domain_scores_gemma":[0.9967043,0.0009564135,0.00026185528,0.00045318124,0.0014681652,0.00015604931],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001522176,0.0010639958,0.001283575,0.009087631,0.0011320744,0.0028560655,0.001189881,0.0011422449,0.0025017278],"category_scores_gemma":[0.007556651,0.000525563,0.0014321642,0.0067720953,0.00046991959,0.0023916706,0.0010803939,0.0012429778,0.0020171632],"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":[0.0010974134,0.0006613533,0.017898746,0.00037349894,0.00032119785,0.0003657052,0.0003424887,0.032369647,0.029666565,0.008125515,0.017405564,0.8913723],"study_design_scores_gemma":[0.00009901564,0.00030926385,0.0088768825,0.00007474307,0.00024367197,0.0005521827,0.00040261916,0.9134007,0.036138795,0.022937773,0.016903099,0.00006127149],"about_ca_topic_score_codex":0.0021088768,"about_ca_topic_score_gemma":0.0024171532,"teacher_disagreement_score":0.009087631,"about_ca_system_score_codex":0.000855826,"about_ca_system_score_gemma":0.0012802918,"threshold_uncertainty_score":0.008369088},"labels":[],"label_agreement":null},{"id":"W2074047803","doi":"10.1007/s11390-010-9407-0","title":"Formally Analyzing Expected Time Complexity of Algorithms Using Theorem Proving","year":2010,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Logic, Reasoning, and Knowledge","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Probabilistic analysis of algorithms; Mathematical proof; Theory of computation; Computational complexity theory; Algorithm; Automated theorem proving; Probabilistic logic; Time complexity; Descriptive complexity theory; Theoretical computer science; Mathematics; Artificial intelligence","score_opus":0.01665396761359184,"score_gpt":0.2521595947787549,"score_spread":0.23550562716516305,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2074047803","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":[0.23670515,0.00072738936,0.75096583,0.0015716858,0.000094010196,0.00025745423,0.0005225123,0.0016096714,0.007546358],"genre_scores_gemma":[0.8299691,0.00032041073,0.166609,0.0001875136,0.00018715415,0.0001680015,0.0007475308,0.0004092745,0.0014019852],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98046446,0.0068556764,0.0012934459,0.0022699798,0.0056085484,0.0035079026],"domain_scores_gemma":[0.68754643,0.29132038,0.0067776926,0.008248334,0.0042655296,0.0018416818],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.016049549,0.002066412,0.002108012,0.0033353867,0.0015097498,0.008651337,0.0062932614,0.0025545123,0.0064739306],"category_scores_gemma":[0.111674525,0.0018809054,0.0035765604,0.003376046,0.0051656454,0.017016403,0.003706661,0.0051575233,0.0004244227],"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":[0.00092266285,0.0008302806,0.009942908,0.00045570917,0.0003998052,0.00022956166,0.0004262391,0.70861703,0.004433843,0.2257523,0.0017882042,0.046201393],"study_design_scores_gemma":[0.0001080789,0.000102951046,0.0008456679,0.00002358395,0.0001026165,0.00007032613,0.000059479764,0.8531631,0.002730955,0.1423853,0.00037706387,0.000030863113],"about_ca_topic_score_codex":0.0067499876,"about_ca_topic_score_gemma":0.0054236627,"teacher_disagreement_score":0.016049549,"about_ca_system_score_codex":0.0058754818,"about_ca_system_score_gemma":0.007278106,"threshold_uncertainty_score":0.08487916},"labels":[],"label_agreement":null},{"id":"W2086582257","doi":"10.1007/bf02962204","title":"Sequential combination methods for data clustering analysis","year":2002,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Cluster analysis; Computer science; CURE data clustering algorithm; Correlation clustering; Canopy clustering algorithm; Data stream clustering; Constrained clustering; Fuzzy clustering; Data mining; Clustering high-dimensional data; Algorithm; Artificial intelligence","score_opus":0.0811634130080792,"score_gpt":0.41144146351408606,"score_spread":0.3302780505060069,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2086582257","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":[0.00166235,0.00043067161,0.996863,0.00004597038,0.0000679143,0.000071866554,0.00008836374,0.00053101435,0.00023881749],"genre_scores_gemma":[0.034240816,0.00052960624,0.9620907,0.00006990105,0.00016398191,0.00045155297,0.0006437394,0.00028443264,0.0015253546],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99181527,0.0036976216,0.00061747007,0.0013181447,0.002312546,0.0002389619],"domain_scores_gemma":[0.9866599,0.007976015,0.0007139035,0.0022647663,0.002103712,0.00028159475],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0075704027,0.0020984455,0.0037904473,0.0040859464,0.0016991494,0.0018000749,0.0029701272,0.0013897364,0.004255399],"category_scores_gemma":[0.01536579,0.0019135763,0.003444755,0.008516218,0.0011204211,0.0027245407,0.0022007956,0.0031119108,0.0021735374],"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":[0.0007070606,0.00022725771,0.0020474733,0.0008253524,0.0009595724,0.00012422638,0.000256841,0.11414776,0.008629548,0.020177789,0.0076693995,0.84422773],"study_design_scores_gemma":[0.00009521714,0.00021877218,0.001315508,0.000046490575,0.00028478602,0.00025185593,0.00006157209,0.9206611,0.0045632496,0.0636488,0.008785234,0.00006754018],"about_ca_topic_score_codex":0.0039648567,"about_ca_topic_score_gemma":0.005541536,"teacher_disagreement_score":0.0075704027,"about_ca_system_score_codex":0.0010459227,"about_ca_system_score_gemma":0.0019869003,"threshold_uncertainty_score":0.04003656},"labels":[],"label_agreement":null},{"id":"W2088835748","doi":"10.1007/bf02949831","title":"The impact of non-Gaussian distribution traffic on network performance","year":2002,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Gaussian; Range (aeronautics); Gaussian process; Traffic generation model; Marginal distribution; Gaussian network model; Probability density function; Algorithm; Simulation; Real-time computing; Statistics; Mathematics; Random variable; Physics","score_opus":0.006624346709116896,"score_gpt":0.24712193004527663,"score_spread":0.24049758333615973,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2088835748","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":[0.96692765,0.0006152472,0.025957068,0.0011857803,0.00009795669,0.000019283041,0.00018006687,0.0002973334,0.004719647],"genre_scores_gemma":[0.9989422,0.00010697651,0.00050843623,0.000039940933,0.000026054933,0.0000030748897,0.00003644336,0.000024093979,0.00031269633],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99794596,0.000738513,0.000060887305,0.0001792406,0.0005038172,0.00057153235],"domain_scores_gemma":[0.9181983,0.072324574,0.0022549878,0.0020203644,0.004101708,0.0011001697],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003711974,0.000567861,0.00068785215,0.0008489103,0.0008372236,0.0014859693,0.00089301413,0.0015502697,0.0018670718],"category_scores_gemma":[0.04076438,0.00049407716,0.00030015013,0.0010671954,0.0012265221,0.0027614357,0.00076344504,0.0011354376,0.00033886553],"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":[0.0020366625,0.0006528747,0.027011923,0.00014791451,0.00011730487,0.0006347535,0.0001795539,0.889764,0.026636425,0.016284244,0.0022189645,0.034315314],"study_design_scores_gemma":[0.000027524991,0.0002270435,0.009354459,0.000010090221,0.00006253971,0.0002512112,0.00011101345,0.97797376,0.005656162,0.0060941316,0.00020415559,0.000027960497],"about_ca_topic_score_codex":0.0030191448,"about_ca_topic_score_gemma":0.003596453,"teacher_disagreement_score":0.003711974,"about_ca_system_score_codex":0.0019619453,"about_ca_system_score_gemma":0.0011670347,"threshold_uncertainty_score":0.019631028},"labels":[],"label_agreement":null},{"id":"W2102495876","doi":"10.1007/s11390-013-1411-8","title":"TuLP: A Family of Lightweight Message Authentication Codes for Body Sensor Networks","year":2014,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Security in Wireless Sensor Networks","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Natural Science Foundation of China; European Commission","keywords":"Computer science; Wireless sensor network; Message authentication code; Computer network; Authentication (law); Block (permutation group theory); Block cipher; Computer security; Cryptography; Encryption","score_opus":0.007124124298582951,"score_gpt":0.23301760556609105,"score_spread":0.2258934812675081,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2102495876","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":[0.00965875,0.0010339553,0.9790101,0.000370293,0.00030242026,0.00027636226,0.0002914422,0.0067327386,0.0023239923],"genre_scores_gemma":[0.39397308,0.0016561891,0.5831574,0.0013472781,0.00043425563,0.0020975054,0.0015648059,0.0011623316,0.014607252],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9978619,0.0005559573,0.00018774756,0.00019389526,0.0008835782,0.00031694898],"domain_scores_gemma":[0.994142,0.0020203188,0.0007725667,0.0013739092,0.001348199,0.00034301897],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002302705,0.0011757761,0.0010800816,0.0020836946,0.0017178489,0.0013936993,0.0015310593,0.0014841888,0.0043130904],"category_scores_gemma":[0.010201521,0.0005547384,0.00077401823,0.0013608692,0.0011518663,0.0027660974,0.0047084885,0.0030899006,0.0032078275],"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":[0.0022038096,0.00025874563,0.0016971242,0.0011136914,0.000164114,0.0006462706,0.0004686498,0.03201475,0.074173905,0.09909843,0.0315369,0.7566237],"study_design_scores_gemma":[0.00043949162,0.001398739,0.0016216522,0.0005318638,0.00024143566,0.00242228,0.00023887376,0.6597508,0.103179365,0.12827437,0.10149928,0.00040185644],"about_ca_topic_score_codex":0.0009264431,"about_ca_topic_score_gemma":0.0010009177,"teacher_disagreement_score":0.0043130904,"about_ca_system_score_codex":0.00094593264,"about_ca_system_score_gemma":0.0020450437,"threshold_uncertainty_score":0.014428675},"labels":[],"label_agreement":null},{"id":"W2117172400","doi":"10.1007/s11390-015-1511-8","title":"Survey of Large-Scale Data Management Systems for Big Data Applications","year":2015,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":48,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Scalability; Data science; Data management; Big data; Workload; Consistency (knowledge bases); Scale (ratio); Database; Data mining","score_opus":0.08446876235174079,"score_gpt":0.30633167810649614,"score_spread":0.22186291575475536,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2117172400","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.25260213,0.6077002,0.060786694,0.014408347,0.0012668039,0.000564411,0.0040051583,0.0024032244,0.056262955],"genre_scores_gemma":[0.57039624,0.35311142,0.049566474,0.0032849538,0.0016140539,0.00024109484,0.0097215865,0.00031267025,0.011751481],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9979358,0.0003640576,0.00023631059,0.0003425652,0.0009143439,0.00020699449],"domain_scores_gemma":[0.9919144,0.003420414,0.0010408221,0.0006169414,0.0023835655,0.0006238983],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027833923,0.00044357963,0.0005700782,0.004042186,0.00070791313,0.0022616617,0.0013119327,0.0005604391,0.0034474568],"category_scores_gemma":[0.006004865,0.00040041996,0.00048258284,0.00926667,0.0003999866,0.00377539,0.0010273997,0.0005733428,0.00094619085],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030388738,0.00032886822,0.034335032,0.004460974,0.00013224944,0.000094728355,0.00028303845,0.0033727079,0.0064864308,0.012894317,0.05136896,0.8859389],"study_design_scores_gemma":[0.00004354305,0.0007262966,0.10025528,0.0018317917,0.0002680138,0.0008581212,0.0012261495,0.02466235,0.010834145,0.0071726297,0.85202205,0.0000996315],"about_ca_topic_score_codex":0.0019459764,"about_ca_topic_score_gemma":0.0024496675,"teacher_disagreement_score":0.004042186,"about_ca_system_score_codex":0.0010318997,"about_ca_system_score_gemma":0.0023882168,"threshold_uncertainty_score":0.014720142},"labels":[],"label_agreement":null},{"id":"W2137042120","doi":"10.1007/s11390-008-9152-9","title":"New Information Distance Measure and Its Application in Question Answering System","year":2008,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Computability, Logic, AI Algorithms","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":false,"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; Question answering; Measure (data warehouse); Construct (python library); Ranking (information retrieval); Theory of computation; Information retrieval; Theoretical computer science; Algorithm; Data mining; Programming language","score_opus":0.0076057241386548345,"score_gpt":0.21490953061850027,"score_spread":0.20730380647984542,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2137042120","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":[0.03537794,0.0044308687,0.95481515,0.0007767126,0.0002710139,0.00010556649,0.00038419678,0.0006119639,0.0032265552],"genre_scores_gemma":[0.5598829,0.002312975,0.43253535,0.00023095595,0.0006029864,0.00026008664,0.00092361675,0.000087277935,0.0031638145],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9966888,0.0008499724,0.000352272,0.00065530173,0.0013313423,0.00012233948],"domain_scores_gemma":[0.9950422,0.002711821,0.0002129494,0.00043217442,0.001405816,0.00019504805],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024641682,0.00044226824,0.0011753724,0.0039559165,0.00090643746,0.0023031246,0.0014235772,0.0013168731,0.001770593],"category_scores_gemma":[0.010442002,0.00024405916,0.00081057154,0.0034075105,0.0008604312,0.0054152096,0.0014106325,0.0011330934,0.00035263086],"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":[0.0007743758,0.0004734341,0.01044122,0.0007368404,0.0003010186,0.00032611503,0.00060443237,0.05072978,0.015878508,0.25635985,0.012058671,0.6513158],"study_design_scores_gemma":[0.000045236124,0.00025960465,0.0042044283,0.00004162858,0.00012610585,0.0004853917,0.00015065857,0.8665485,0.009996169,0.106198385,0.011855279,0.0000885161],"about_ca_topic_score_codex":0.0018836644,"about_ca_topic_score_gemma":0.0009460891,"teacher_disagreement_score":0.0039559165,"about_ca_system_score_codex":0.0015075082,"about_ca_system_score_gemma":0.0011445954,"threshold_uncertainty_score":0.0130319595},"labels":[],"label_agreement":null},{"id":"W2460852158","doi":"10.1007/s11390-016-1654-2","title":"Mining Object Similarity for Predicting Next Locations","year":2016,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Computer science; Similarity (geometry); Markov chain; Trajectory; Object (grammar); Locality; Data mining; Markov model; Sequence (biology); Hidden Markov model; Artificial intelligence; Theory of computation; Machine learning; Algorithm; Image (mathematics)","score_opus":0.021658267926861267,"score_gpt":0.26099372336252996,"score_spread":0.2393354554356687,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2460852158","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":[0.81018645,0.0020294702,0.17756368,0.00035485555,0.00024190739,0.0002815863,0.003092404,0.0014811207,0.004768532],"genre_scores_gemma":[0.9154114,0.0004869445,0.07778232,0.00006439457,0.000116879615,0.00008817346,0.003987944,0.000056921253,0.002004966],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991732,0.000060573668,0.00010907254,0.00023255275,0.00032818096,0.00009635914],"domain_scores_gemma":[0.99824524,0.00047127885,0.00030935736,0.0002608506,0.00052462734,0.00018857598],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036329296,0.00060148584,0.00095266727,0.007897587,0.0009999702,0.0010547573,0.001473757,0.0010975286,0.0019616026],"category_scores_gemma":[0.0033302943,0.00030073733,0.0009122707,0.0055524283,0.00035661552,0.00232856,0.0011338951,0.00063571543,0.0010657645],"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":[0.0013408498,0.001495585,0.36529735,0.0004686066,0.0005067783,0.0015286371,0.00050719746,0.029034965,0.020626444,0.0073060086,0.01233201,0.5595556],"study_design_scores_gemma":[0.000076590026,0.0007930592,0.08507912,0.00010526079,0.00046086914,0.0022523657,0.0014417765,0.8629402,0.018632378,0.01806322,0.01006766,0.00008756254],"about_ca_topic_score_codex":0.0072022593,"about_ca_topic_score_gemma":0.012689289,"teacher_disagreement_score":0.007897587,"about_ca_system_score_codex":0.0004791762,"about_ca_system_score_gemma":0.0010213957,"threshold_uncertainty_score":0.014320672},"labels":[],"label_agreement":null},{"id":"W2550167848","doi":"10.1007/s11390-016-1690-y","title":"Enhanced Userspace and In-Kernel Trace Filtering for Production Systems","year":2016,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Computer science; Tracing; TRACE (psycholinguistics); Filter (signal processing); Real-time computing; Context (archaeology); Kernel (algebra); Rendering (computer graphics); Overhead (engineering); Software; Latency (audio); Distributed computing; Operating system; Computer graphics (images); Telecommunications","score_opus":0.009656570307727841,"score_gpt":0.2397008524398235,"score_spread":0.23004428213209566,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2550167848","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":[0.1640785,0.0004175574,0.8125838,0.00020466415,0.0001506111,0.00009173018,0.00039045527,0.019664347,0.0024182785],"genre_scores_gemma":[0.8760146,0.00010380541,0.11946395,0.00006027981,0.00005127535,0.000031574826,0.00038027627,0.0006372943,0.0032569808],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9979995,0.00037388338,0.00013334649,0.00032645307,0.0009008441,0.00026594257],"domain_scores_gemma":[0.99221593,0.002149998,0.00050785823,0.003243259,0.0015324461,0.00035045907],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015257514,0.00095069554,0.0009452723,0.001526436,0.00086369505,0.0019994294,0.0016095625,0.00085225597,0.0034816768],"category_scores_gemma":[0.009111368,0.00044183462,0.0005242364,0.001062531,0.00036845298,0.0026969418,0.0015356459,0.0011049218,0.0009849834],"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":[0.002497761,0.0011379735,0.017017499,0.00024232158,0.0001663133,0.0003190319,0.0007202551,0.06424899,0.066609934,0.007885008,0.0054732705,0.83368164],"study_design_scores_gemma":[0.00005372656,0.00028294727,0.005378344,0.000021431873,0.00006192464,0.00023601686,0.00017824714,0.9292765,0.053525336,0.0065296083,0.004402193,0.00005364664],"about_ca_topic_score_codex":0.0077372994,"about_ca_topic_score_gemma":0.011770447,"teacher_disagreement_score":0.0077372994,"about_ca_system_score_codex":0.00073543796,"about_ca_system_score_gemma":0.002034845,"threshold_uncertainty_score":0.015384555},"labels":[],"label_agreement":null},{"id":"W2593821117","doi":"10.1007/s11390-017-1727-x","title":"A New Feistel-Type White-Box Encryption Scheme","year":2017,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Cryptographic Implementations and Security","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Statistics Canada","funders":"","keywords":"White box; Computer science; Block cipher; S-box; Encryption; Cryptanalysis; Linear cryptanalysis; Cryptography; Key schedule; Context (archaeology); Theoretical computer science; Symmetric-key algorithm; Block size; Algorithm; Differential cryptanalysis; Key (lock); Computer network; Computer security; Public-key cryptography","score_opus":0.017715693433242637,"score_gpt":0.2950580230940829,"score_spread":0.27734232966084027,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2593821117","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":[0.06988047,0.001796309,0.864583,0.0025021126,0.0010561256,0.00030973923,0.00076696585,0.002146433,0.05695891],"genre_scores_gemma":[0.63046825,0.0013495348,0.29154798,0.0014314767,0.00039694982,0.0003603559,0.0009525965,0.00030784475,0.073185034],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99919194,0.00015494066,0.00005665308,0.00016072085,0.00029583398,0.00013986246],"domain_scores_gemma":[0.99955887,0.00008334916,0.000039182196,0.00018936444,0.000083247796,0.00004589031],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007878701,0.00050339365,0.00080232596,0.0005767959,0.0007860647,0.0014906029,0.00088458776,0.001245071,0.005840534],"category_scores_gemma":[0.00095196493,0.0002595987,0.0006052958,0.00069201423,0.0007173127,0.0034996832,0.001736063,0.0014760485,0.0031440074],"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":[0.0009431544,0.00028436078,0.0003997204,0.00038318918,0.00008634392,0.0005504501,0.00031878107,0.007607249,0.0655117,0.7632146,0.018077642,0.1426229],"study_design_scores_gemma":[0.00067635864,0.0006688953,0.00097532565,0.00020236922,0.00018162676,0.0035003684,0.00012924115,0.14803308,0.10778689,0.5297258,0.20782758,0.00029248305],"about_ca_topic_score_codex":0.00014105756,"about_ca_topic_score_gemma":0.0001963988,"teacher_disagreement_score":0.005840534,"about_ca_system_score_codex":0.0006180825,"about_ca_system_score_gemma":0.000928925,"threshold_uncertainty_score":0.019538581},"labels":[],"label_agreement":null},{"id":"W2912349718","doi":"10.1007/s11390-019-1896-x","title":"Controllability and Its Applications to Biological Networks","year":2019,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":33,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Controllability; Biological network; Computer science; Complex network; Biological data; Network controllability; Systems biology; Complex system; Distributed computing; Artificial intelligence; Bioinformatics; Centrality; Mathematics; Biology","score_opus":0.005921843677497686,"score_gpt":0.23383058211120905,"score_spread":0.22790873843371137,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2912349718","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":[0.024731487,0.0014584977,0.9630104,0.0006457417,0.00013109422,0.000031588734,0.00008046558,0.00020088952,0.00970978],"genre_scores_gemma":[0.88686043,0.0038468938,0.09813226,0.00029273104,0.0010531434,0.00025731407,0.00018617802,0.00014401616,0.009227122],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994123,0.0002054268,0.000035851725,0.00012642684,0.00017739694,0.000042635926],"domain_scores_gemma":[0.9928423,0.005961273,0.00041319078,0.0002329725,0.0003315438,0.00021880899],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012902785,0.0008511198,0.0007397922,0.0026674871,0.00060768635,0.0012713978,0.0008876045,0.0008684703,0.0027874266],"category_scores_gemma":[0.00827551,0.0003708065,0.001186566,0.0019718178,0.0024162463,0.0020562166,0.0015657621,0.0014479527,0.00019167479],"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":[0.000057037436,0.00006051533,0.0008979708,0.000113076705,0.000053285847,0.00018748213,0.00016912453,0.117800854,0.0041890154,0.836241,0.0006906413,0.039539922],"study_design_scores_gemma":[0.000013247401,0.000025869958,0.00021948629,0.000011105402,0.000015068184,0.000060610517,0.000023805285,0.48521033,0.0006712996,0.51230395,0.0014290509,0.000016156555],"about_ca_topic_score_codex":0.0029870335,"about_ca_topic_score_gemma":0.0016555137,"teacher_disagreement_score":0.0029870335,"about_ca_system_score_codex":0.00075676414,"about_ca_system_score_gemma":0.0005089675,"threshold_uncertainty_score":0.009324908},"labels":[],"label_agreement":null},{"id":"W2914522519","doi":"10.1007/s11390-019-1899-7","title":"ROCO: Using a Solid State Drive Cache to Improve the Performance of a Host-Aware Shingled Magnetic Recording Drive","year":2019,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; Cache; Operating system; Parallel computing; Host (biology)","score_opus":0.008948873919923585,"score_gpt":0.24744274182685375,"score_spread":0.23849386790693017,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2914522519","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":[0.89563453,0.0029640957,0.06048831,0.00051055365,0.00052676414,0.00012549685,0.00072142325,0.022077737,0.016951056],"genre_scores_gemma":[0.9675568,0.000260484,0.021549571,0.00023148624,0.00007787106,0.000034755023,0.00071913225,0.0003096854,0.009260249],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99975973,0.000030693387,0.000018331179,0.000050509134,0.00008153055,0.000059241025],"domain_scores_gemma":[0.99917114,0.00012034408,0.00007497425,0.00027325805,0.00026850178,0.00009190846],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022053863,0.00044297014,0.00047847096,0.0005129796,0.00042014103,0.000891655,0.0016895151,0.00028374646,0.0046052556],"category_scores_gemma":[0.0006487868,0.00019083009,0.00018085401,0.0005570615,0.0002775127,0.0011561739,0.0008241373,0.00039378557,0.00092620606],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0054321405,0.00089726236,0.016127244,0.00085243786,0.0002680114,0.0013927382,0.0005564039,0.019513907,0.47472247,0.008183782,0.055965252,0.4160884],"study_design_scores_gemma":[0.00057266327,0.004661106,0.0061194403,0.000102860984,0.00035106132,0.0013805554,0.000472935,0.43109035,0.4945224,0.0023449955,0.058201186,0.00018056745],"about_ca_topic_score_codex":0.0015342459,"about_ca_topic_score_gemma":0.005634498,"teacher_disagreement_score":0.0046052556,"about_ca_system_score_codex":0.00048274733,"about_ca_system_score_gemma":0.0008251935,"threshold_uncertainty_score":0.015406132},"labels":[],"label_agreement":null},{"id":"W2989546622","doi":"10.1007/s11390-020-0193-z","title":"Differential Privacy via a Truncated and Normalized Laplace Mechanism","year":2022,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Differential privacy; Laplace distribution; Normalization (sociology); Laplace transform; Computer science; Range (aeronautics); Scaling; Noise (video); Mathematical optimization; Theoretical computer science; Data mining; Mathematics; Artificial intelligence; Mathematical analysis","score_opus":0.011985350039328383,"score_gpt":0.2406716962186188,"score_spread":0.22868634617929043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2989546622","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":[0.023481261,0.0002580423,0.9680244,0.001274813,0.00014000633,0.000093337636,0.00011607231,0.0005183408,0.0060937232],"genre_scores_gemma":[0.8905484,0.00043272533,0.09392247,0.00071722147,0.00042707034,0.00022153856,0.00013337412,0.00011281228,0.013484402],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9924621,0.002576,0.00039670488,0.001132499,0.002553573,0.0008791091],"domain_scores_gemma":[0.98784804,0.006012195,0.00079987675,0.003593361,0.0012550134,0.00049155724],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006453423,0.000769216,0.0018157485,0.0013733741,0.0014044945,0.004011297,0.0033301169,0.0028413315,0.004437509],"category_scores_gemma":[0.024362763,0.0007126188,0.0017083831,0.0016667927,0.004669163,0.00834584,0.0072608865,0.0042863595,0.001168674],"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":[0.00044694485,0.00015279508,0.0004539023,0.00009437702,0.00006001166,0.00028661595,0.00024204288,0.044228077,0.0069623613,0.9083772,0.002662496,0.0360332],"study_design_scores_gemma":[0.00009510787,0.00014684518,0.00013823328,0.000024697223,0.00004137419,0.00055751915,0.000044882225,0.39443967,0.0043798215,0.5973906,0.0026844884,0.000056817076],"about_ca_topic_score_codex":0.00040573408,"about_ca_topic_score_gemma":0.00024833402,"teacher_disagreement_score":0.006453423,"about_ca_system_score_codex":0.002160145,"about_ca_system_score_gemma":0.00267814,"threshold_uncertainty_score":0.03412938},"labels":[],"label_agreement":null},{"id":"W3034810086","doi":"10.1007/s11390-020-0405-6","title":"Two-Stream Temporal Convolutional Networks for Skeleton-Based Human Action Recognition","year":2020,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Computer science; Artificial intelligence; Pattern recognition (psychology); Skeleton (computer programming); Feature (linguistics); Leverage (statistics); Convolutional neural network; Feature vector; Feature learning; Representation (politics); RGB color model; Computer vision","score_opus":0.0384129619373278,"score_gpt":0.28502092550176517,"score_spread":0.24660796356443737,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3034810086","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":[0.08570197,0.0019344204,0.8991839,0.00041930878,0.00031978887,0.00008718538,0.0016734708,0.0058231447,0.0048568104],"genre_scores_gemma":[0.74925333,0.0014875099,0.22556998,0.0002800947,0.00017739464,0.000129223,0.0036411637,0.00024542477,0.019215846],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997696,0.0000177151,0.00001108477,0.00008198523,0.00005817178,0.00006142805],"domain_scores_gemma":[0.99974126,0.0000652256,0.000030652158,0.000046462046,0.00008157508,0.000034926932],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045764452,0.00083439704,0.00068935595,0.000764997,0.00028119987,0.00053357764,0.0011796942,0.0007904638,0.0048731836],"category_scores_gemma":[0.00073126086,0.0003313219,0.0006409422,0.000919565,0.00028643978,0.0007516659,0.0007649164,0.0009194258,0.0016250389],"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":[0.0005912065,0.00028351415,0.0021045376,0.00010978374,0.000119224365,0.00015111384,0.000038256312,0.07318875,0.04813056,0.0041893926,0.011069155,0.8600246],"study_design_scores_gemma":[0.000007706917,0.00004981745,0.0012311197,0.000009181931,0.00002407595,0.00005387378,0.000008417429,0.9863999,0.00878062,0.002027004,0.0014000593,0.000008266847],"about_ca_topic_score_codex":0.019246608,"about_ca_topic_score_gemma":0.029094946,"teacher_disagreement_score":0.019246608,"about_ca_system_score_codex":0.0007224019,"about_ca_system_score_gemma":0.0011729761,"threshold_uncertainty_score":0.038269162},"labels":[],"label_agreement":null},{"id":"W3096943259","doi":"10.24215/16666038.20.e08","title":"Data Science &amp; Engineering into Food Science: A novel Big Data Platform for Low Molecular Weight Gelators’ Behavioral Analysis","year":2020,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Supramolecular Self-Assembly in Materials","field":"Materials 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 Guelph","funders":"","keywords":"Computer science; Big data; Data science; Scalability; Science and engineering; Limiting; Homogenization (climate); Data mining; Database","score_opus":0.06046403470218005,"score_gpt":0.30552458677521993,"score_spread":0.2450605520730399,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3096943259","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":[0.006100562,0.001542393,0.9159689,0.003625246,0.0005915318,0.0008060456,0.012126297,0.053892888,0.005346101],"genre_scores_gemma":[0.084186226,0.002108526,0.8703907,0.0022931944,0.00052795204,0.002056665,0.029737448,0.0034024268,0.005296839],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.993769,0.0011068217,0.0008154217,0.0015075594,0.0025055176,0.00029564067],"domain_scores_gemma":[0.98305744,0.0040018833,0.0013399388,0.0074166884,0.0028262332,0.0013578092],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0075013987,0.0026624051,0.002301913,0.005555873,0.0016466947,0.008586115,0.0052242177,0.0024247942,0.0054932665],"category_scores_gemma":[0.01781787,0.0013867551,0.0017347654,0.005793242,0.0018131592,0.010699985,0.010251461,0.0041152397,0.0049660304],"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":[0.002312263,0.0010714384,0.016518798,0.0027996749,0.00072944193,0.0017075251,0.0025038773,0.015565135,0.057264604,0.10337296,0.097915865,0.69823843],"study_design_scores_gemma":[0.00024385286,0.00046705492,0.0071350206,0.000566863,0.00021121322,0.00086425967,0.0011732127,0.343603,0.088550396,0.2618201,0.29489744,0.0004675362],"about_ca_topic_score_codex":0.0016019029,"about_ca_topic_score_gemma":0.0017293288,"teacher_disagreement_score":0.008586115,"about_ca_system_score_codex":0.0012759488,"about_ca_system_score_gemma":0.0030151284,"threshold_uncertainty_score":0.03967166},"labels":[],"label_agreement":null},{"id":"W3096975346","doi":"10.1007/s11390-020-9668-1","title":"Machine Learning Techniques for Software Maintainability Prediction: Accuracy Analysis","year":2020,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Software Engineering Research","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Maintainability; Machine learning; Computer science; Artificial intelligence; Support vector machine; Software; Artificial neural network; Data mining; Reliability engineering; Software engineering; Engineering","score_opus":0.01323511758263632,"score_gpt":0.27447270302207677,"score_spread":0.2612375854394404,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3096975346","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":[0.3528957,0.005774235,0.63393146,0.0011079311,0.00019992815,0.00008733555,0.0008615651,0.0020129099,0.003128879],"genre_scores_gemma":[0.91864663,0.0010913167,0.07744608,0.00010052419,0.00016053644,0.000050282302,0.00095879193,0.000082897546,0.0014630033],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9968141,0.0010006753,0.00036055341,0.00037755005,0.0012730489,0.00017419826],"domain_scores_gemma":[0.96905524,0.022898028,0.0015403349,0.0021933427,0.004128047,0.00018506216],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0058350903,0.0009006947,0.0011268379,0.0032833512,0.00046466925,0.001277253,0.0012903983,0.0012640746,0.0009520157],"category_scores_gemma":[0.030476063,0.00027999093,0.0008625113,0.002144604,0.00032892247,0.0017179936,0.00072198926,0.0017900007,0.00057200575],"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":[0.00039590264,0.00040443614,0.06254731,0.00022211281,0.00037386167,0.00007539256,0.00010248079,0.27452803,0.003667108,0.0017840663,0.0030064704,0.6528929],"study_design_scores_gemma":[0.000008985484,0.000096444084,0.0054976926,0.000025065325,0.000056961515,0.000047997524,0.00001573656,0.990274,0.0022151053,0.0014472436,0.00030491236,0.000009854648],"about_ca_topic_score_codex":0.005471905,"about_ca_topic_score_gemma":0.0047158552,"teacher_disagreement_score":0.0058350903,"about_ca_system_score_codex":0.0007098483,"about_ca_system_score_gemma":0.000717418,"threshold_uncertainty_score":0.030859232},"labels":[],"label_agreement":null},{"id":"W3150464090","doi":"10.1007/s11390-011-9421-x","title":"NuMDG: A New Tool for Multiway Decision Graphs Construction","year":2011,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Formal Methods in Verification","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Correctness; Binary decision diagram; Operator (biology); Representation (politics); Theoretical computer science; Pruning; Set (abstract data type); Tree traversal; Data structure; Programming language; Theory of computation; Tuple; Algorithm; Mathematics; Discrete mathematics","score_opus":0.02954144827780394,"score_gpt":0.28708517276760975,"score_spread":0.25754372448980584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3150464090","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":[0.0009223959,0.00004307614,0.983459,0.000057621684,0.000051685052,0.000075842676,0.00041203518,0.0135874925,0.001390863],"genre_scores_gemma":[0.037915386,0.00015087312,0.9505229,0.00014278236,0.000038506027,0.0003739598,0.0018081559,0.004475675,0.0045718257],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975999,0.00083563774,0.00027251864,0.00043518443,0.0007040051,0.00015274055],"domain_scores_gemma":[0.99442685,0.00347089,0.00024142097,0.0013054942,0.00039829564,0.00015695141],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027914988,0.0014478568,0.0010659173,0.0021856637,0.0010006302,0.0026200213,0.0025625767,0.0011004935,0.029077427],"category_scores_gemma":[0.01073885,0.0017213844,0.0024901999,0.0012975334,0.0011446635,0.0050510066,0.0040780143,0.0028464266,0.0062739085],"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":[0.0003747743,0.00031887778,0.0025115092,0.0016498762,0.00019607837,0.0006253558,0.0006944625,0.046426002,0.014493428,0.23044235,0.04133737,0.66093],"study_design_scores_gemma":[0.00015580464,0.000113369955,0.00043228187,0.00036875758,0.00014670675,0.0006276365,0.00014328334,0.41694558,0.031936426,0.32763454,0.22137253,0.0001230171],"about_ca_topic_score_codex":0.0016172966,"about_ca_topic_score_gemma":0.0034775927,"teacher_disagreement_score":0.029077427,"about_ca_system_score_codex":0.0009913652,"about_ca_system_score_gemma":0.0018520401,"threshold_uncertainty_score":0.09727371},"labels":[],"label_agreement":null},{"id":"W4249892919","doi":"10.1007/s11390-010-9377-2","title":"Volumetric Vector-Based Representation for Indirect Illumination Caching","year":2010,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer science; Rendering (computer graphics); Global illumination; Voxel; Ray tracing (physics); Robustness (evolution); Grid; Preprocessor; Computer vision; Representation (politics); Artificial intelligence; Data structure; 3D rendering; Computer graphics (images); Mathematics; Optics","score_opus":0.01567769270327406,"score_gpt":0.30549389716164754,"score_spread":0.28981620445837347,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4249892919","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":[0.01191668,0.00028127385,0.97967416,0.0001138935,0.00009596192,0.0000504673,0.00047941078,0.0047281366,0.0026600184],"genre_scores_gemma":[0.34525776,0.0008698419,0.6426846,0.00013815433,0.00009503243,0.00020453746,0.002290783,0.0015886058,0.0068707345],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99967515,0.00004606539,0.00002123885,0.00003080665,0.0001718634,0.000054936394],"domain_scores_gemma":[0.99936503,0.00010593627,0.00003958519,0.00024348535,0.00021150541,0.000034500976],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003010176,0.00095309794,0.0009394532,0.0012749934,0.00037368553,0.002443504,0.001810823,0.00062347983,0.008672619],"category_scores_gemma":[0.0016363434,0.00050358585,0.00066656695,0.0021963909,0.00031644083,0.0019763797,0.0016498262,0.0010670064,0.0016279714],"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":[0.0009902328,0.0002567649,0.0010859597,0.000318257,0.00011019009,0.00030025747,0.00024447977,0.15764266,0.08934231,0.05897995,0.03123088,0.65949804],"study_design_scores_gemma":[0.00004042802,0.000050261642,0.00023447591,0.00002343193,0.000027495393,0.00014404165,0.000045251727,0.9374983,0.038682282,0.011242545,0.011967832,0.000043681695],"about_ca_topic_score_codex":0.0042718756,"about_ca_topic_score_gemma":0.00648289,"teacher_disagreement_score":0.008672619,"about_ca_system_score_codex":0.0008285543,"about_ca_system_score_gemma":0.0010448581,"threshold_uncertainty_score":0.0290128},"labels":[],"label_agreement":null},{"id":"W4381515053","doi":"10.1007/s11390-023-2548-8","title":"Approximate Processing Element Design and Analysis for the Implementation of CNN Accelerators","year":2023,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Low-power high-performance VLSI design","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Adder; Multiplication (music); Overhead (engineering); Convolutional neural network; Rounding; Lookup table; Computation; Floating point; Algorithm; Dot product; Computer engineering; Computer hardware; Parallel computing; Artificial intelligence; Latency (audio); Mathematics","score_opus":0.017123856664640776,"score_gpt":0.27166503616506266,"score_spread":0.2545411795004219,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4381515053","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":[0.035262916,0.0005448016,0.9575232,0.00018599867,0.000058788875,0.000044200384,0.00007485198,0.0006009117,0.005704279],"genre_scores_gemma":[0.7142653,0.0004317212,0.27754253,0.00017502291,0.000047440037,0.0001187492,0.00019679952,0.00011264414,0.007109904],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99977404,0.000038503786,0.000009780807,0.00002115511,0.00012650782,0.000030082274],"domain_scores_gemma":[0.9996718,0.00012788129,0.00003117209,0.00004269371,0.000116810384,0.000009660394],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003104823,0.00037049025,0.0003602121,0.00028724925,0.00022367404,0.0006090225,0.0009182019,0.00046564805,0.004466571],"category_scores_gemma":[0.0011042273,0.00025781215,0.0003378203,0.00031580793,0.00021029775,0.0006331933,0.0002945182,0.0004956994,0.0005088167],"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":[0.0003298836,0.000087000655,0.0017072748,0.00032122748,0.00014750811,0.0001553271,0.00012315964,0.70247644,0.06155002,0.06445655,0.0045005414,0.16414507],"study_design_scores_gemma":[0.000006210698,0.00003911873,0.00012308791,0.0000069211765,0.000010822367,0.000027195649,0.000008748219,0.9907973,0.0053898636,0.0023788407,0.0012082413,0.0000037457426],"about_ca_topic_score_codex":0.003205549,"about_ca_topic_score_gemma":0.008840684,"teacher_disagreement_score":0.004466571,"about_ca_system_score_codex":0.0008144257,"about_ca_system_score_gemma":0.0010709852,"threshold_uncertainty_score":0.014942169},"labels":[],"label_agreement":null},{"id":"W4388541891","doi":"10.1007/s11390-022-1214-x","title":"Prepartition: Load Balancing Approach for Virtual Machine Reservations in a Cloud Data Center","year":2023,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Load balancing (electrical power); Virtual machine; Cloud computing; Distributed computing; Virtualization; Data center; Scheduling (production processes); Live migration; Load management; Job shop scheduling; Network Load Balancing Services; Round-robin DNS; Server; Computer network; Operating system; The Internet; Schedule; Mathematical optimization","score_opus":0.030562681806097197,"score_gpt":0.27816001928175527,"score_spread":0.24759733747565807,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388541891","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":[0.16376016,0.0006701017,0.8193712,0.0008294768,0.0004669675,0.00030873812,0.0001270326,0.0035305668,0.0109356735],"genre_scores_gemma":[0.89888716,0.00010385965,0.095559545,0.00013232998,0.000097199896,0.00006188332,0.000097348515,0.00008743608,0.00497315],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997162,0.00005626536,0.000016459242,0.000072391325,0.0000652781,0.000073365314],"domain_scores_gemma":[0.9997384,0.00005914368,0.000019677358,0.000048551865,0.00007463346,0.00005967273],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004439337,0.00043631278,0.0005529723,0.00047875592,0.0013881392,0.0010026633,0.0015660863,0.0004950171,0.0048012785],"category_scores_gemma":[0.00074185117,0.00020097427,0.00031372887,0.00041239182,0.00031468988,0.00081458513,0.00093814055,0.0006183152,0.00043167203],"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":[0.0021385336,0.00087224,0.0050629782,0.00036403048,0.00015517176,0.00075217395,0.0008355141,0.21435572,0.10548398,0.023979317,0.018278986,0.6277213],"study_design_scores_gemma":[0.00007695788,0.00027133827,0.0009071928,0.000011327842,0.0000385504,0.00017648943,0.0001626114,0.98290783,0.0070102094,0.0045137447,0.0038995703,0.00002424279],"about_ca_topic_score_codex":0.0042475266,"about_ca_topic_score_gemma":0.0079012895,"teacher_disagreement_score":0.0048012785,"about_ca_system_score_codex":0.00043753124,"about_ca_system_score_gemma":0.0011882219,"threshold_uncertainty_score":0.016061842},"labels":[],"label_agreement":null},{"id":"W4406480758","doi":"10.1007/s11390-023-2561-y","title":"P3DC: Reducing DRAM Cache Hit Latency by Hybrid Mappings","year":2024,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Interconnection Networks and Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Innovation Cluster (Canada)","funders":"","keywords":"Computer science; Cache; Parallel computing; Dram; Latency (audio); CAS latency; Theory of computation; Cache algorithms; CPU cache; Operating system; Embedded system; Computer hardware; Algorithm; Memory controller; Telecommunications","score_opus":0.006352724953010962,"score_gpt":0.22183695703123665,"score_spread":0.2154842320782257,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406480758","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":[0.6773586,0.0047656805,0.25571716,0.0005665469,0.0007065767,0.0002744307,0.00166244,0.029999455,0.02894904],"genre_scores_gemma":[0.9124799,0.00030814786,0.07969564,0.00018970107,0.00006151877,0.00009720968,0.000892719,0.00039111337,0.0058840336],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996574,0.00005552491,0.000015810523,0.000064008455,0.00011623885,0.000091043694],"domain_scores_gemma":[0.9992086,0.00016417669,0.000037721547,0.00031078607,0.00020448024,0.00007411895],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025890511,0.000812691,0.000434715,0.0007041281,0.00080402766,0.0009410582,0.0018920836,0.00047705238,0.005603943],"category_scores_gemma":[0.0011993576,0.00024700363,0.00025721407,0.0014970361,0.00032970417,0.0011978773,0.0010650544,0.0005706958,0.0009828802],"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":[0.0037210293,0.00082192844,0.007919001,0.0005551285,0.00023399525,0.0005837958,0.00029178726,0.08330725,0.13262336,0.009765246,0.06565964,0.6945179],"study_design_scores_gemma":[0.0005750426,0.0013801055,0.00457689,0.00004505921,0.00021424911,0.000779747,0.00036212895,0.81026417,0.14667584,0.008497258,0.026555046,0.00007447891],"about_ca_topic_score_codex":0.0056906994,"about_ca_topic_score_gemma":0.011515621,"teacher_disagreement_score":0.0056906994,"about_ca_system_score_codex":0.0005056859,"about_ca_system_score_gemma":0.0014917352,"threshold_uncertainty_score":0.018747032},"labels":[],"label_agreement":null},{"id":"W4408362526","doi":"10.1007/s11390-024-5036-x","title":"Caging AI","year":2025,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Computability, Logic, AI Algorithms","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"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; Artificial intelligence","score_opus":0.00567773826158046,"score_gpt":0.255621987237542,"score_spread":0.2499442489759615,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408362526","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":[0.04597881,0.0012581832,0.18833786,0.00477811,0.0009187607,0.00009766418,0.0004809974,0.001995978,0.75615364],"genre_scores_gemma":[0.7185217,0.001533643,0.06917458,0.0012682399,0.00043561196,0.00020275773,0.0011412865,0.0006295489,0.20709264],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99982834,0.000036090707,0.000008436191,0.00005729846,0.000046710105,0.000023075418],"domain_scores_gemma":[0.9995982,0.000103888924,0.000023949022,0.00013654794,0.00007711863,0.000060380396],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002288745,0.00036077228,0.0003247843,0.0007799043,0.0011022462,0.0012701367,0.00052750105,0.000580654,0.03837135],"category_scores_gemma":[0.0014265344,0.00019854281,0.00041985034,0.0005174966,0.0017214918,0.0022035514,0.001558447,0.0015603334,0.0038073598],"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":[0.000012733606,0.000010311605,0.00020207741,0.000028160199,0.0000061078567,0.000026603606,0.00015430259,0.0028474473,0.00081409246,0.9615064,0.0068995953,0.02749214],"study_design_scores_gemma":[0.0000070195038,0.000019083573,0.00017404293,0.000016621003,0.000005236759,0.000047964662,0.000092651666,0.010138163,0.00033010554,0.93841153,0.050751757,0.0000057386555],"about_ca_topic_score_codex":0.0021530166,"about_ca_topic_score_gemma":0.0018989678,"teacher_disagreement_score":0.03837135,"about_ca_system_score_codex":0.0007191882,"about_ca_system_score_gemma":0.00060198363,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null}]}