{"meta":{"query_hash":"09445622c707","filters":{"topic":"Advanced Database Systems and Queries"},"cohort_total":1036,"direct_labels_cover":2,"predictions_cover":1036,"exported":1036,"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/09445622c707","api":"https://metacan.xera.ac/api/v1/cohort?topic=Advanced+Database+Systems+and+Queries"},"results":[{"id":"W100784785","doi":"","title":"Optimizing distributed XML queries through localization and pruning","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Query plan; Query optimization; XML database; Scalability; Sargable; XML; Query language; Relational database; Database; XPath; Distributed database; Pruning; Information retrieval; Distributed computing; Data mining; Web search query; Search engine; World Wide Web","score_opus":0.014088908812033205,"score_gpt":0.2512488820867139,"score_spread":0.23715997327468072,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W100784785","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":[0.07838784,0.0010229483,0.91483074,0.0006160375,0.000023432092,0.00016432125,0.00009648365,0.002742082,0.0021160827],"genre_scores_gemma":[0.40671778,0.0005494567,0.5890846,0.00020592958,0.00005668456,0.00026885417,0.00053981476,0.00037073847,0.00220603],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975267,0.0008216357,0.0001864526,0.0003816223,0.00086619216,0.00021746961],"domain_scores_gemma":[0.9960383,0.0024436505,0.00036608436,0.00070986326,0.00034841517,0.000093703515],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023418833,0.00091293117,0.0011751793,0.0009278184,0.0010666868,0.0013465604,0.0017776688,0.00097351405,0.00091647217],"category_scores_gemma":[0.0064172214,0.00054140826,0.00057699793,0.0016295384,0.001193758,0.0026133745,0.0019831453,0.0012319777,0.00037964],"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":[0.00057815993,0.00044713417,0.007947236,0.00035071402,0.00009416328,0.00054872496,0.0013663638,0.44515833,0.06203094,0.030386113,0.009322292,0.4417697],"study_design_scores_gemma":[0.00011338826,0.00014757509,0.0011194824,0.000029879653,0.00006204625,0.00029689667,0.00044545037,0.94785184,0.020074368,0.024767525,0.005060973,0.000030629475],"about_ca_topic_score_codex":0.0039006153,"about_ca_topic_score_gemma":0.005771495,"teacher_disagreement_score":0.0039006153,"about_ca_system_score_codex":0.00093408464,"about_ca_system_score_gemma":0.0012978332,"threshold_uncertainty_score":0.0123851895},"labels":[],"label_agreement":null},{"id":"W106747897","doi":"10.22260/isarc2011/0129","title":"The Use of Earned Value in Forcasting Project Durations","year":2011,"lang":"en","type":"article","venue":"Proceedings of the ... ISARC","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Earned value management; Baseline (sea); Computer science; Schedule; Download; Operations research; Software; Duration (music); Industrial engineering; Project management; Systems engineering; Project planning; Engineering; World Wide Web; Operating system","score_opus":0.12248274890562486,"score_gpt":0.25859423741837934,"score_spread":0.13611148851275448,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W106747897","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":[0.023212427,0.00079961796,0.9707863,0.00023602783,0.00016161532,0.000051858522,0.0003335216,0.00030645312,0.0041122157],"genre_scores_gemma":[0.65333194,0.0009995099,0.342043,0.00008072959,0.00018128299,0.00012317354,0.0005908063,0.00011659758,0.0025329357],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978695,0.0008081809,0.00017443243,0.00039411528,0.00066787883,0.00008582341],"domain_scores_gemma":[0.9924233,0.0047445185,0.0009876043,0.00075916457,0.0009291739,0.00015614182],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00437488,0.00066602055,0.0009228469,0.0019063215,0.0003136003,0.001960187,0.0014546418,0.0006589624,0.001323027],"category_scores_gemma":[0.023274776,0.0002998944,0.00045162346,0.0022042843,0.0004941047,0.0027969743,0.000972323,0.0012619314,0.00037467972],"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":[0.00020603092,0.00005849401,0.015201497,0.00032341486,0.00012727744,0.00010043788,0.000283949,0.38980204,0.002276824,0.052315097,0.002274935,0.5370299],"study_design_scores_gemma":[0.000021572225,0.00012730411,0.0041828626,0.00014766873,0.000031572938,0.00012772731,0.00009733239,0.9566965,0.002283882,0.02758122,0.008642199,0.00006008393],"about_ca_topic_score_codex":0.005092865,"about_ca_topic_score_gemma":0.004652402,"teacher_disagreement_score":0.005092865,"about_ca_system_score_codex":0.0010696572,"about_ca_system_score_gemma":0.000999298,"threshold_uncertainty_score":0.023136854},"labels":[],"label_agreement":null},{"id":"W108265174","doi":"10.4018/978-1-59140-560-3.ch017","title":"Converting a Legacy Database to Object-Oriented Database","year":2005,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Relational database; Database; Computer science; Database model; Database design; Object (grammar); Relational model; Database theory; View; Database schema; Realm; Artificial intelligence","score_opus":0.020011098008784617,"score_gpt":0.26515198502576587,"score_spread":0.24514088701698125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W108265174","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":[0.006057635,0.0030072967,0.90645045,0.0015632742,0.0015199481,0.000309749,0.00072653254,0.007469537,0.07289551],"genre_scores_gemma":[0.051498346,0.0077613154,0.8310438,0.0023802512,0.0010271429,0.000296747,0.0036293024,0.001869694,0.10049345],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9990669,0.00011150965,0.000091926755,0.0001568916,0.00051346706,0.000059367543],"domain_scores_gemma":[0.99816555,0.00029015663,0.0000652052,0.0008215811,0.00054653053,0.000110998415],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015959729,0.0004105657,0.00044737852,0.001928863,0.00074892025,0.0062836017,0.0029217033,0.0009554792,0.009263216],"category_scores_gemma":[0.0037940517,0.0005595245,0.00066184596,0.0034396776,0.0005596176,0.005713712,0.0025488276,0.0019081851,0.008694284],"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":[0.00006682488,0.00017547027,0.0010287105,0.00055995514,0.00008086899,0.0014598563,0.0012704922,0.0032630386,0.012005571,0.22976382,0.07526173,0.67506367],"study_design_scores_gemma":[0.000020964077,0.000047216025,0.0005353307,0.00016429483,0.00005978771,0.0011811202,0.00030737082,0.0074854195,0.004567494,0.043710385,0.94189095,0.000029707182],"about_ca_topic_score_codex":0.0017091663,"about_ca_topic_score_gemma":0.0016956984,"teacher_disagreement_score":0.009263216,"about_ca_system_score_codex":0.00097545644,"about_ca_system_score_gemma":0.0009227673,"threshold_uncertainty_score":0.030988574},"labels":[],"label_agreement":null},{"id":"W108855997","doi":"10.1007/978-3-7091-0738-6_16","title":"Tag Grid: Supporting Multidimensional Queries of Tagged Datasets","year":2011,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Database Systems and Queries","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":"Ontario Tech University","funders":"","keywords":"Computer science; Grid; Information retrieval; Data mining; Geography","score_opus":0.02739101278748787,"score_gpt":0.25488336128944555,"score_spread":0.22749234850195768,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W108855997","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":[0.0034242896,0.002421218,0.9162513,0.0007233652,0.0006453333,0.00016105294,0.006256262,0.05405154,0.016065665],"genre_scores_gemma":[0.060299933,0.0058683995,0.83211344,0.0013219365,0.00037169308,0.0005412331,0.034591697,0.01535462,0.049537003],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99852127,0.00018623615,0.00020422405,0.00022493265,0.0007556572,0.00010775315],"domain_scores_gemma":[0.998102,0.00060584745,0.00006755118,0.0008232252,0.00028216979,0.00011910677],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018303127,0.0012798583,0.0015737062,0.0022675584,0.000864343,0.00552716,0.003320379,0.0011780217,0.015379581],"category_scores_gemma":[0.0051173694,0.0012755316,0.0012379987,0.0077332947,0.00088873843,0.0077315276,0.0042771217,0.0022951257,0.013000106],"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":[0.00038009541,0.00009889147,0.00085012504,0.00097366096,0.00009368921,0.0004912673,0.00061529136,0.0062137195,0.009692606,0.11162336,0.38964382,0.47932345],"study_design_scores_gemma":[0.00014443569,0.000061612904,0.00065399,0.00028239115,0.000077563345,0.001287916,0.00028977654,0.07775866,0.020311229,0.20464951,0.6943339,0.00014900367],"about_ca_topic_score_codex":0.00488205,"about_ca_topic_score_gemma":0.0047168266,"teacher_disagreement_score":0.015379581,"about_ca_system_score_codex":0.0010818564,"about_ca_system_score_gemma":0.0013040961,"threshold_uncertainty_score":0.051449835},"labels":[],"label_agreement":null},{"id":"W110420163","doi":"10.4018/978-1-59140-560-3.ch121","title":"An XML Multi-Tier Pattern Dissemination System","year":2005,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"XML; World Wide Web; Computer science; The Internet; Human–computer interaction; Multimedia","score_opus":0.014899258062314359,"score_gpt":0.2682958029785067,"score_spread":0.25339654491619235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W110420163","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":[0.0053246324,0.0007795513,0.62763214,0.0011140215,0.00041668257,0.0009022933,0.018362723,0.30704454,0.038423352],"genre_scores_gemma":[0.07333816,0.0022865657,0.61195475,0.0022479,0.00026565447,0.0012888368,0.09643786,0.035618678,0.17656153],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988506,0.00021645012,0.0002572405,0.00019378905,0.0004115198,0.000070471724],"domain_scores_gemma":[0.9975146,0.00059178687,0.00012609403,0.0010672541,0.0005128258,0.0001874915],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003010598,0.0010350301,0.0008950589,0.0030148274,0.00096062414,0.0044755763,0.002506977,0.0020454912,0.05361268],"category_scores_gemma":[0.0056131952,0.0008793846,0.0011721106,0.0033428736,0.0005003113,0.005841653,0.003733167,0.0013240005,0.036845785],"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":[0.0008744689,0.00033741008,0.002160982,0.0011806388,0.00012264536,0.0008645914,0.00093238614,0.0036212404,0.022423279,0.058604535,0.33348668,0.57539123],"study_design_scores_gemma":[0.00021381801,0.0001556846,0.0011414938,0.00018922589,0.00006901271,0.0009663229,0.00021337111,0.029435739,0.01922604,0.03024731,0.91802526,0.00011663017],"about_ca_topic_score_codex":0.002608724,"about_ca_topic_score_gemma":0.0026065412,"teacher_disagreement_score":0.05361268,"about_ca_system_score_codex":0.0010052234,"about_ca_system_score_gemma":0.0011528768,"threshold_uncertainty_score":0.17935228},"labels":[],"label_agreement":null},{"id":"W11134361","doi":"10.1016/b978-155860642-5/50008-0","title":"Building component database systems using CORBA","year":2001,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Common Object Request Broker Architecture; Computer science; Component (thermodynamics); Object (grammar); Distributed object; Component Object Model; Orb (optics); Database; Distributed database; Distributed computing; Object model; Object request broker; Interoperable Object Reference; Architecture; Software engineering; Operating system; Software","score_opus":0.036812868933708734,"score_gpt":0.2709624556384907,"score_spread":0.23414958670478198,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W11134361","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":[0.004911545,0.0010324162,0.9647829,0.0002402607,0.00015166383,0.00017294576,0.00014987675,0.013422713,0.015135701],"genre_scores_gemma":[0.045338474,0.002730559,0.9125384,0.00023959734,0.00007515833,0.00020704734,0.0012314168,0.0034553995,0.0341839],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992557,0.000104086044,0.00007782774,0.00011785498,0.00036524452,0.0000792741],"domain_scores_gemma":[0.9990676,0.00025931193,0.000036519228,0.00039028176,0.00018750029,0.000058857797],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015574382,0.001329313,0.00093456043,0.0011538826,0.0009437289,0.0035135243,0.0020900895,0.0009936047,0.012973928],"category_scores_gemma":[0.0024263426,0.0018278222,0.0011139802,0.0022937974,0.00089282054,0.003961585,0.00176964,0.002231597,0.006689159],"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":[0.00012950053,0.00020834127,0.0009610153,0.0014734963,0.00014439363,0.00040067633,0.0011879246,0.017496806,0.050552722,0.14185503,0.039624587,0.74596554],"study_design_scores_gemma":[0.00019336895,0.00023246379,0.0014383191,0.0005190982,0.0003697382,0.0014535002,0.00037701734,0.12444444,0.07228441,0.15741716,0.641139,0.00013143351],"about_ca_topic_score_codex":0.0038141224,"about_ca_topic_score_gemma":0.0034385922,"teacher_disagreement_score":0.012973928,"about_ca_system_score_codex":0.0007123774,"about_ca_system_score_gemma":0.0012832603,"threshold_uncertainty_score":0.043402135},"labels":[],"label_agreement":null},{"id":"W114958004","doi":"10.1023/a:1016028629702","title":"Extending IDEF1X to model fuzzy data","year":2002,"lang":"en","type":"article","venue":"Journal of Intelligent Manufacturing","topic":"Advanced Database Systems and Queries","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":"University of Saskatchewan","funders":"","keywords":"Computer-integrated manufacturing; Computer science; Information integration; Fuzzy logic; Data integration; Integrated Computer-Aided Manufacturing; Manufacturing engineering; Systems engineering; Engineering; Artificial intelligence; Data mining","score_opus":0.10268163624618487,"score_gpt":0.30215490293538544,"score_spread":0.19947326668920057,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W114958004","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":[0.0137632955,0.00022472344,0.9761054,0.00017462065,0.00008159912,0.0000782037,0.0007254998,0.0059894198,0.0028572313],"genre_scores_gemma":[0.23528935,0.0005181536,0.74903274,0.00024730584,0.00013017979,0.00023359044,0.0028555514,0.0018005761,0.009892541],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99897027,0.00020315322,0.00013454116,0.00016856936,0.0003919333,0.00013154752],"domain_scores_gemma":[0.99800676,0.00079505786,0.00010653452,0.000654987,0.00038445677,0.000052334184],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026731712,0.0007083235,0.00072201545,0.001340083,0.00058276695,0.0023730982,0.0020340483,0.001170336,0.004706786],"category_scores_gemma":[0.006313521,0.0005313349,0.0012298152,0.00083773275,0.0006516193,0.0044519794,0.0018137081,0.0013585661,0.0016255605],"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":[0.00074131234,0.00025322675,0.008033654,0.0007412127,0.00019313922,0.001461184,0.0012552872,0.22634758,0.012088235,0.285348,0.018443702,0.44509342],"study_design_scores_gemma":[0.00009274135,0.000119539895,0.0004847686,0.000156391,0.00007950963,0.00054591027,0.00008146907,0.76242167,0.018223794,0.12568824,0.09204862,0.00005732382],"about_ca_topic_score_codex":0.004151713,"about_ca_topic_score_gemma":0.0028420528,"teacher_disagreement_score":0.004706786,"about_ca_system_score_codex":0.0007186075,"about_ca_system_score_gemma":0.00080423726,"threshold_uncertainty_score":0.015745819},"labels":[],"label_agreement":null},{"id":"W115407445","doi":"10.1007/978-3-642-14010-5_7","title":"Attractive Interface for XML: Convincing Naive Users to Go Online","year":2010,"lang":"en","type":"book-chapter","venue":"Studies in fuzziness and soft computing","topic":"Advanced Database Systems and Queries","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 Calgary","funders":"","keywords":"Computer science; XML; XML database; User interface; Interface (matter); World Wide Web; Database; Information retrieval; Programming language","score_opus":0.06437618669628398,"score_gpt":0.353384099706739,"score_spread":0.28900791301045503,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W115407445","genre_codex":"methods","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":[0.1468445,0.0021972717,0.53233325,0.044571225,0.0010103706,0.00024555752,0.00052739354,0.015258461,0.25701195],"genre_scores_gemma":[0.73340386,0.0010048633,0.12926729,0.0104459105,0.0005627842,0.00025617596,0.00048315496,0.0027176924,0.12185827],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99836737,0.00085297646,0.00005795733,0.00013238886,0.00049121986,0.00009811123],"domain_scores_gemma":[0.9919376,0.0056129433,0.00022317335,0.0010038622,0.0008596165,0.000362773],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002753716,0.0006790461,0.00035462645,0.00054174615,0.0015018444,0.004595907,0.0015089931,0.0039964686,0.028001392],"category_scores_gemma":[0.019404655,0.00038907866,0.00032798084,0.0004269724,0.002277138,0.014693752,0.0035580755,0.0026205073,0.008814787],"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":[0.00093361636,0.00031863412,0.0042030853,0.0005158725,0.00003220697,0.0011964686,0.031974573,0.00094488595,0.023155307,0.4380474,0.20915122,0.28952667],"study_design_scores_gemma":[0.00020711446,0.0004313903,0.00284485,0.00038384422,0.00008944503,0.0033617914,0.015521629,0.0513658,0.021870416,0.45699835,0.44672874,0.0001965915],"about_ca_topic_score_codex":0.0006125038,"about_ca_topic_score_gemma":0.0004572754,"teacher_disagreement_score":0.028001392,"about_ca_system_score_codex":0.00043563053,"about_ca_system_score_gemma":0.00050727866,"threshold_uncertainty_score":0.093674004},"labels":[],"label_agreement":null},{"id":"W124949239","doi":"","title":"On the decidability of consistent query answering","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Decidability; Computer science; Question answering; Query language; Boolean conjunctive query; Query optimization; Information retrieval; Theoretical computer science; Mathematics; Sargable; Web search query; Search engine","score_opus":0.011046914871102414,"score_gpt":0.22743231506413042,"score_spread":0.21638540019302802,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W124949239","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":[0.23532417,0.0023214575,0.711854,0.01947451,0.00040750208,0.00054854964,0.002028528,0.0023569136,0.025684336],"genre_scores_gemma":[0.8892714,0.0009667268,0.09958625,0.0024731078,0.0009461824,0.00058672816,0.0021553063,0.00039077108,0.0036236567],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.97840995,0.008671099,0.0014964588,0.0039863614,0.004847292,0.0025889452],"domain_scores_gemma":[0.7985213,0.1858153,0.0026845508,0.0068183662,0.0046478286,0.0015126838],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.016512055,0.0011067152,0.0021145048,0.0021605326,0.0028719504,0.00947315,0.00448694,0.0032378817,0.005902224],"category_scores_gemma":[0.072375715,0.0014434253,0.0039653596,0.0029227412,0.009968255,0.015427797,0.005232325,0.010492735,0.0004959312],"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":[0.00066254666,0.00045397456,0.0035538613,0.000606689,0.00019404192,0.00070998434,0.0017239931,0.040354103,0.004035926,0.9071357,0.0068666283,0.03370254],"study_design_scores_gemma":[0.00012603805,0.000041318108,0.00031423883,0.00004552766,0.000087276785,0.00013485065,0.0001780881,0.098456375,0.0023683284,0.896437,0.0017802147,0.00003077851],"about_ca_topic_score_codex":0.0051756604,"about_ca_topic_score_gemma":0.0029450536,"teacher_disagreement_score":0.016512055,"about_ca_system_score_codex":0.004825353,"about_ca_system_score_gemma":0.0050029326,"threshold_uncertainty_score":0.087325096},"labels":[],"label_agreement":null},{"id":"W145709543","doi":"10.4018/978-1-59140-560-3.ch079","title":"Path-Oriented Queries and Tree Inclusion Problem","year":2005,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Computer science; SGML; XML; Markup language; Document type definition; World Wide Web; Data exchange; RuleML; Efficient XML Interchange; Document Structure Description; The Internet; Information retrieval; Database","score_opus":0.009854811332505606,"score_gpt":0.22883174849135046,"score_spread":0.21897693715884486,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W145709543","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":[0.06168175,0.0057335477,0.8298012,0.019532336,0.00044303288,0.0005087711,0.002929228,0.0029601695,0.07641003],"genre_scores_gemma":[0.2947903,0.0075366767,0.6318178,0.0032771553,0.0010950912,0.0009145765,0.009071849,0.0014754331,0.05002105],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99282247,0.0020918495,0.0005966568,0.0010424488,0.0028801193,0.0005665491],"domain_scores_gemma":[0.97728443,0.01805442,0.00079575455,0.001699124,0.0015695023,0.0005967457],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005634364,0.0008103753,0.0019865052,0.0031063596,0.0033514444,0.00771263,0.0043272143,0.004073775,0.013203238],"category_scores_gemma":[0.026095958,0.0011031753,0.0015057657,0.011041387,0.003343096,0.025846163,0.0070547275,0.005667841,0.0027058355],"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":[0.00012883029,0.00015710936,0.0007412582,0.00045930242,0.000034482604,0.00056411425,0.0015039977,0.009193118,0.0008077612,0.8572918,0.033768732,0.0953495],"study_design_scores_gemma":[0.000044826626,0.000020238767,0.00016039994,0.000103946884,0.00002072682,0.0006822925,0.0004693278,0.03710735,0.00072027557,0.9219678,0.038677532,0.00002526285],"about_ca_topic_score_codex":0.0048011853,"about_ca_topic_score_gemma":0.0030861998,"teacher_disagreement_score":0.013203238,"about_ca_system_score_codex":0.0028370775,"about_ca_system_score_gemma":0.0023468705,"threshold_uncertainty_score":0.044169188},"labels":[],"label_agreement":null},{"id":"W1480424271","doi":"","title":"Relational methods in computer science : 8th International Seminar on Relational Methods in Computer Science 3rd International Workshop on Applications of Kleene Algebra and Workshop of COST Action 274: TARSKI, St. Catharines, ON, Canada, February 22-26, 2005 : selected revised papers","year":2006,"lang":"en","type":"book","venue":"Springer eBooks","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Kleene algebra; Relational algebra; Algebra over a field; Kripke semantics; Relational calculus; Duality (order theory); Mathematics; Universal algebra; Codd's theorem; Two-element Boolean algebra; Subalgebra; Relational database; Computer science; Relational model; Theoretical computer science; Discrete mathematics; Pure mathematics; Algebra representation; Intermediate logic; Description logic","score_opus":0.027898912936227024,"score_gpt":0.32088347192722466,"score_spread":0.2929845589909976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1480424271","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":[0.0017709398,0.5219229,0.11304083,0.016143516,0.0270955,0.0001955316,0.0012586764,0.0017600991,0.31681195],"genre_scores_gemma":[0.02202155,0.24935324,0.055337597,0.0033621022,0.017929323,0.00022992487,0.002215021,0.0019032706,0.647648],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987029,0.00014264396,0.000072241986,0.00022321577,0.0007985169,0.000060518196],"domain_scores_gemma":[0.99861825,0.0005226532,0.00005545122,0.00016275622,0.0004924703,0.00014839062],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017560173,0.0012501826,0.0013483719,0.0022898407,0.00074846967,0.0035214117,0.0013797422,0.0011301995,0.049441762],"category_scores_gemma":[0.00235991,0.0008349864,0.0009187537,0.0044296966,0.001298857,0.00436771,0.0013076358,0.0032134939,0.017177915],"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":[0.000034178775,0.00004996218,0.000073782096,0.0006871357,0.000022701624,0.000032107375,0.0002712096,0.0005082516,0.0014752317,0.07291064,0.7426646,0.1812703],"study_design_scores_gemma":[0.000012680776,0.000026500938,0.00034495513,0.0002478119,0.000011692623,0.00014928012,0.00005652288,0.0005010093,0.0006235069,0.024186159,0.97382855,0.000011349882],"about_ca_topic_score_codex":0.0020798498,"about_ca_topic_score_gemma":0.003623904,"teacher_disagreement_score":0.049441762,"about_ca_system_score_codex":0.002262173,"about_ca_system_score_gemma":0.0018322982,"threshold_uncertainty_score":0.16539913},"labels":[],"label_agreement":null},{"id":"W1480732106","doi":"10.1007/3-540-44469-6_9","title":"Dynamic Reconfiguration Algorithm: Dynamically Tuning Multiple Buffer Pools","year":2000,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada); Queen's University","funders":"","keywords":"Computer science; Buffer (optical fiber); Control reconfiguration; Database transaction; Database; Write buffer; Distributed computing; Workload; Set (abstract data type); Parallel computing; Operating system; Embedded system; Cache algorithms","score_opus":0.010511875499685025,"score_gpt":0.23549483995184675,"score_spread":0.22498296445216173,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1480732106","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":[0.10349041,0.0012997948,0.86981905,0.0003114335,0.00028048092,0.0002032054,0.00018947729,0.017525246,0.0068809227],"genre_scores_gemma":[0.6220597,0.00021284177,0.37203303,0.00024316301,0.000071861716,0.00018107964,0.0002879558,0.00066825177,0.0042421287],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9992512,0.00016024918,0.000051510666,0.00022990478,0.00018415146,0.00012305434],"domain_scores_gemma":[0.9988201,0.00046015525,0.00010622166,0.0002737538,0.00022526513,0.00011446854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010843225,0.0011229856,0.001079194,0.001263602,0.0007856113,0.0015714063,0.0036232653,0.0009179753,0.0048806416],"category_scores_gemma":[0.003355379,0.00059071014,0.0003227976,0.0010760316,0.00043967212,0.001998969,0.0012326697,0.0007881168,0.0008255989],"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":[0.0014386867,0.00047133936,0.002013902,0.00016011515,0.00011468106,0.000109185385,0.00015907302,0.16560662,0.051271237,0.0052697975,0.012496339,0.76088905],"study_design_scores_gemma":[0.0001874376,0.00017663282,0.00053564116,0.000015070366,0.000070196795,0.00011863079,0.000048493304,0.96402776,0.02672732,0.0035986598,0.004457591,0.00003660558],"about_ca_topic_score_codex":0.0031037854,"about_ca_topic_score_gemma":0.0037292643,"teacher_disagreement_score":0.0048806416,"about_ca_system_score_codex":0.00096115284,"about_ca_system_score_gemma":0.001420468,"threshold_uncertainty_score":0.016327381},"labels":[],"label_agreement":null},{"id":"W1481890926","doi":"10.1609/socs.v5i1.18319","title":"A* with Lookahead Re-Evaluated","year":2021,"lang":"en","type":"article","venue":"Proceedings of the International Symposium on Combinatorial Search","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Pruning; Node (physics); Bounded function; Value (mathematics); Unit (ring theory); Algorithm; Mathematical optimization; Parallel computing; Mathematics; Machine learning","score_opus":0.018758077535113257,"score_gpt":0.26843175903666694,"score_spread":0.24967368150155367,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1481890926","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":[0.15547279,0.0013053627,0.70969766,0.0019042066,0.0013140598,0.0007724053,0.0046119154,0.07670542,0.04821614],"genre_scores_gemma":[0.507026,0.0002229134,0.46150526,0.0010979326,0.00009996199,0.00029761114,0.0038936248,0.0038289994,0.022027649],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99893576,0.00020364471,0.000097874596,0.0002540335,0.00031880205,0.00018994161],"domain_scores_gemma":[0.9946607,0.0015212863,0.00020796186,0.0024569521,0.000951738,0.00020128021],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009281474,0.0007938002,0.0005756713,0.00088720536,0.0008160177,0.0015044879,0.0027900112,0.0009880201,0.015490429],"category_scores_gemma":[0.005474285,0.0004492799,0.0009042718,0.0008891523,0.0007897681,0.0023082418,0.0017331954,0.0014815199,0.0042338083],"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":[0.0027164428,0.00068553677,0.0080624055,0.00079725386,0.00020569858,0.0004784314,0.00030603056,0.10197495,0.042487286,0.050278153,0.095681295,0.69632655],"study_design_scores_gemma":[0.00056394696,0.00081547705,0.0017306838,0.000116030664,0.00018097766,0.00050356094,0.00032630918,0.74879545,0.07366305,0.08461755,0.08855933,0.00012760148],"about_ca_topic_score_codex":0.0043261214,"about_ca_topic_score_gemma":0.0067366217,"teacher_disagreement_score":0.015490429,"about_ca_system_score_codex":0.0007654364,"about_ca_system_score_gemma":0.0022913846,"threshold_uncertainty_score":0.051820695},"labels":[],"label_agreement":null},{"id":"W1482054002","doi":"","title":"Specifying and locating hierarchical patterns in event data","year":2004,"lang":"en","type":"article","venue":"Conference of the Centre for Advanced Studies on Collaborative Research","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Event (particle physics); Pattern matching; Eclipse; Context (archaeology); Data mining; Matching (statistics); Complex event processing; Closure (psychology); Component (thermodynamics); Theoretical computer science; Artificial intelligence; Programming language; Mathematics","score_opus":0.20886100867938634,"score_gpt":0.44006182925401544,"score_spread":0.2312008205746291,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1482054002","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":[0.018406926,0.000109283756,0.9755636,0.00026367532,0.000030676332,0.00029245738,0.00088987965,0.0038811762,0.0005623134],"genre_scores_gemma":[0.09420071,0.00019832529,0.8999235,0.00013109649,0.000031477564,0.0002826868,0.0028124924,0.001121737,0.0012979923],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9892519,0.0020718805,0.0023763492,0.002177715,0.0033920782,0.00073002104],"domain_scores_gemma":[0.9702277,0.015857346,0.0029594924,0.0074355067,0.0024128405,0.0011071173],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013688107,0.001146664,0.0022671442,0.00366888,0.0025418194,0.006210291,0.0029896847,0.0022786397,0.0023231348],"category_scores_gemma":[0.041914027,0.0021465814,0.002991981,0.0045498656,0.0036301787,0.013174814,0.008627755,0.0040920163,0.0008917209],"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":[0.001155102,0.0005353272,0.034165833,0.0021156336,0.00022382045,0.0029853145,0.013877165,0.05978909,0.04360865,0.43209746,0.013142808,0.39630368],"study_design_scores_gemma":[0.00020932895,0.00027181976,0.0039669443,0.00056333863,0.00015846733,0.0015994868,0.0055729775,0.38555208,0.066896856,0.4213902,0.113546245,0.00027233068],"about_ca_topic_score_codex":0.00987924,"about_ca_topic_score_gemma":0.015428109,"teacher_disagreement_score":0.013688107,"about_ca_system_score_codex":0.0019106779,"about_ca_system_score_gemma":0.005043296,"threshold_uncertainty_score":0.0723905},"labels":[],"label_agreement":null},{"id":"W1486350349","doi":"10.1007/978-3-540-39429-7_12","title":"Finding ID Attributes in XML Documents","year":2003,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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 Toronto","funders":"","keywords":"Computer science; XML; Information retrieval; Streaming XML; Programming language; World Wide Web; Database","score_opus":0.021930871252392757,"score_gpt":0.26553715294751906,"score_spread":0.2436062816951263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1486350349","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":[0.11213338,0.0044168932,0.8342791,0.0012422052,0.0005296063,0.000360242,0.0067311055,0.01850791,0.02179944],"genre_scores_gemma":[0.14082143,0.0029526257,0.80902773,0.0002902394,0.00014869386,0.00009074541,0.016255245,0.0014119969,0.02900124],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99927264,0.000068838526,0.00010083342,0.00018217455,0.00031028624,0.00006531152],"domain_scores_gemma":[0.99856085,0.0008120622,0.000097782264,0.00025037938,0.00020894481,0.00007007169],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008112778,0.0007943242,0.0011784716,0.005668142,0.0009593428,0.0034605267,0.0015982105,0.001310889,0.0055499193],"category_scores_gemma":[0.003435597,0.00088667334,0.0011195457,0.0042185537,0.00062882324,0.005585066,0.0016650653,0.001060655,0.0044563673],"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":[0.00027821522,0.00022416451,0.012215814,0.000932151,0.00009322208,0.0013455733,0.0012584776,0.003890947,0.03264541,0.04445305,0.02510906,0.8775539],"study_design_scores_gemma":[0.000126197,0.00040737787,0.011435179,0.0011552663,0.0006319087,0.009097165,0.0033038934,0.13960901,0.26196933,0.20081043,0.37120402,0.00025022848],"about_ca_topic_score_codex":0.0021801216,"about_ca_topic_score_gemma":0.0028153786,"teacher_disagreement_score":0.005668142,"about_ca_system_score_codex":0.00084527355,"about_ca_system_score_gemma":0.0010280821,"threshold_uncertainty_score":0.01856631},"labels":[],"label_agreement":null},{"id":"W1486651402","doi":"10.1007/978-3-540-45227-0_78","title":"Integrating Quality of Service into Database Systems","year":2003,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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 Ottawa; Université du Québec à Montréal; Université de Montréal","funders":"","keywords":"Computer science; Quality of service; Software deployment; Database; Service (business); Mobile QoS; Web service; Distributed computing; Computer network; World Wide Web; Software engineering; Service provider","score_opus":0.03191293253067976,"score_gpt":0.29230321173534446,"score_spread":0.2603902792046647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1486651402","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":[0.011261999,0.0057786885,0.9492174,0.004123977,0.00046664264,0.00014742847,0.00015359782,0.0027665978,0.026083728],"genre_scores_gemma":[0.408679,0.008079933,0.5625511,0.0009897536,0.0009436984,0.0001529274,0.00067331304,0.0012298386,0.016700448],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9942715,0.0013343354,0.00042148103,0.00033012757,0.0032422605,0.00040028882],"domain_scores_gemma":[0.9934481,0.002546611,0.00049864576,0.0014315073,0.0016987189,0.00037635697],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006930022,0.0005781298,0.00094052794,0.0022231457,0.0007447458,0.0060689533,0.0024268737,0.001494071,0.005267724],"category_scores_gemma":[0.017159693,0.0009596893,0.00085775356,0.004037502,0.0017562029,0.0115869595,0.0030445447,0.0027283838,0.0017214869],"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":[0.00019041587,0.00015614634,0.0030609756,0.00054669933,0.00009300985,0.00011282025,0.00073997764,0.023298725,0.004846981,0.55513155,0.013968814,0.39785382],"study_design_scores_gemma":[0.00006208341,0.0002069451,0.0018782981,0.0004125399,0.00018580006,0.00040995533,0.0004671209,0.2616178,0.008472874,0.5196538,0.20652895,0.00010384033],"about_ca_topic_score_codex":0.0050390484,"about_ca_topic_score_gemma":0.003063602,"teacher_disagreement_score":0.006930022,"about_ca_system_score_codex":0.002685411,"about_ca_system_score_gemma":0.0021716128,"threshold_uncertainty_score":0.036649883},"labels":[],"label_agreement":null},{"id":"W1486998273","doi":"10.1109/icdew.2015.7129584","title":"Improving the quality of large-scale database-centric software systems by analyzing database access code","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Database; Database schema; SQL; View; Relational database management system; Database administrator; Database design; Database tuning; Database model; Relational database","score_opus":0.058856819044013194,"score_gpt":0.3361835446933748,"score_spread":0.2773267256493616,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1486998273","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":[0.6164802,0.001499426,0.36317402,0.0013451199,0.000110065805,0.00049350655,0.00085916906,0.011946487,0.0040919124],"genre_scores_gemma":[0.75224406,0.0007275214,0.24184363,0.00018022434,0.00004295687,0.0001327757,0.0017583165,0.0018338045,0.0012368199],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9845408,0.0031289456,0.0014628533,0.0014344531,0.0088317515,0.0006011851],"domain_scores_gemma":[0.84305,0.04899274,0.02775944,0.025989436,0.05244975,0.0017586249],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.014574461,0.0010373727,0.000716173,0.0058377935,0.0007242523,0.0056270678,0.0017979522,0.0007688162,0.00081723626],"category_scores_gemma":[0.097961076,0.0010127578,0.0007219363,0.004098329,0.0013218687,0.0044476492,0.002043184,0.0015915912,0.0005286711],"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":[0.0005895695,0.0007710993,0.32244515,0.0014395751,0.0004885662,0.0005810566,0.0065659615,0.069246,0.062254537,0.009384027,0.004452586,0.5217818],"study_design_scores_gemma":[0.00012552853,0.0010394099,0.21608312,0.00072317815,0.00055725296,0.0008246734,0.0029628677,0.6306527,0.105451554,0.020301364,0.020990573,0.00028782286],"about_ca_topic_score_codex":0.0061750547,"about_ca_topic_score_gemma":0.0056668413,"teacher_disagreement_score":0.014574461,"about_ca_system_score_codex":0.0017185009,"about_ca_system_score_gemma":0.0035331505,"threshold_uncertainty_score":0.077077985},"labels":[],"label_agreement":null},{"id":"W1487530975","doi":"10.1007/3-540-48196-6_9","title":"Change Propagation in an Axiomatic Model of Schema Evolution for Objectbase Management Systems","year":2001,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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 Calgary; University of Manitoba","funders":"","keywords":"Computer science; Schema (genetic algorithms); Axiom; Schema evolution; Database schema; Semi-structured model; Conceptual schema; Theoretical computer science; Axiomatic system; Information retrieval; Mathematics; Database design","score_opus":0.041651206676096626,"score_gpt":0.2685586333325518,"score_spread":0.2269074266564552,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1487530975","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":[0.016441332,0.00030053704,0.9668893,0.0018688972,0.00010305544,0.00009593409,0.00022594245,0.00074355403,0.013331482],"genre_scores_gemma":[0.35509452,0.0005312112,0.6303076,0.0010435429,0.00024393408,0.00032133833,0.00083562045,0.0004312446,0.011190938],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9950094,0.0019532503,0.0004866482,0.00067648076,0.0015064083,0.00036771694],"domain_scores_gemma":[0.992393,0.00374077,0.00034938456,0.0021648377,0.0011409852,0.00021095325],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0056533217,0.00058955146,0.00066536583,0.0015937482,0.0021188224,0.0048377295,0.003976628,0.0031819693,0.0044883657],"category_scores_gemma":[0.013186437,0.0015150424,0.002001059,0.0022665672,0.005002965,0.013294965,0.0043028044,0.005526245,0.0009746082],"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":[0.000037329617,0.000036586094,0.00038022286,0.000053669508,0.000018915562,0.00016729238,0.00052386324,0.013563742,0.0006371938,0.9722837,0.0014177848,0.010879775],"study_design_scores_gemma":[0.000035361685,0.000024624313,0.00013260222,0.000026658361,0.00004589043,0.00021591593,0.0000943195,0.10642518,0.0010656432,0.883398,0.008507388,0.000028453174],"about_ca_topic_score_codex":0.0067482237,"about_ca_topic_score_gemma":0.0061189584,"teacher_disagreement_score":0.0067482237,"about_ca_system_score_codex":0.002251138,"about_ca_system_score_gemma":0.0018710071,"threshold_uncertainty_score":0.029897988},"labels":[],"label_agreement":null},{"id":"W1488255798","doi":"10.1109/cloud.2015.21","title":"From Relations to Multi-dimensional Maps: Towards an SQL-to-HBase Transformation Methodology","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Transformation (genetics); Schema (genetic algorithms); Data transformation; SQL; Relational database management system; Database; Relational database; Process (computing); Distributed database; Set (abstract data type); Data mining; Data warehouse; Information retrieval; Programming language; Chemistry","score_opus":0.16989446576942346,"score_gpt":0.3718602840117867,"score_spread":0.20196581824236326,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1488255798","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":[0.00063863886,0.000075159245,0.9966419,0.0002060612,0.00003070029,0.00010006521,0.00007915591,0.0014924079,0.00073596666],"genre_scores_gemma":[0.01632159,0.0002492579,0.98019767,0.00018230567,0.000040484618,0.00018666808,0.0004945969,0.0007843977,0.0015430535],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99076277,0.00305477,0.0010985725,0.0012054216,0.0035571726,0.00032130294],"domain_scores_gemma":[0.9913795,0.0027056343,0.00051943073,0.003157577,0.0019567772,0.00028119434],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011166437,0.00087833026,0.0007564754,0.0028982908,0.0010600494,0.006549902,0.0035758978,0.0013751339,0.0032246935],"category_scores_gemma":[0.013939408,0.0013687571,0.0024246685,0.0028888106,0.002333216,0.008120179,0.0051266346,0.0040997756,0.0025331527],"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":[0.00008841254,0.00033654232,0.0025432669,0.0008988577,0.00019884534,0.00072227936,0.004293268,0.014190135,0.01127913,0.59114754,0.014849643,0.35945207],"study_design_scores_gemma":[0.00006872929,0.00014317251,0.0013365232,0.00052580744,0.00016122061,0.0014933188,0.0023894343,0.16244318,0.049903646,0.37279192,0.4085929,0.00015008115],"about_ca_topic_score_codex":0.002563581,"about_ca_topic_score_gemma":0.00316729,"teacher_disagreement_score":0.011166437,"about_ca_system_score_codex":0.00097365415,"about_ca_system_score_gemma":0.0038005293,"threshold_uncertainty_score":0.059054494},"labels":[],"label_agreement":null},{"id":"W1489366126","doi":"10.1007/978-3-662-07003-1","title":"Elements of Finite Model Theory","year":2004,"lang":"en","type":"book","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":990,"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":"Model theory; Computer science; Abstract model theory; Mathematical theory; Theoretical computer science; Calculus (dental); Mathematics; Physics; Discrete mathematics; Relationship between string theory and quantum field theory","score_opus":0.016500652095639386,"score_gpt":0.24126319559599288,"score_spread":0.2247625435003535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1489366126","genre_codex":"other","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":[0.0047614286,0.015156696,0.3531643,0.0042412034,0.0011900109,0.00006706722,0.00063667365,0.00073843036,0.62004405],"genre_scores_gemma":[0.278712,0.02010232,0.14977273,0.0024799802,0.002934277,0.0006015127,0.001997791,0.0010059311,0.5423935],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99956113,0.00010613454,0.000020799278,0.00007378036,0.00020487625,0.000033303782],"domain_scores_gemma":[0.99960893,0.00019625366,0.000014926226,0.00009523781,0.000066616056,0.000018038287],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004862983,0.0011040595,0.0011577052,0.001732383,0.0014177825,0.002692714,0.0010201941,0.0009779643,0.021356352],"category_scores_gemma":[0.0013019453,0.00061872404,0.0008670915,0.0022861387,0.0031945338,0.0054460843,0.0010544771,0.002794616,0.006524421],"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":[0.0000025072802,0.000005354182,0.000016751641,0.000032717493,0.0000029846615,0.000009570082,0.00007434436,0.00052763516,0.00008023584,0.9784264,0.009514177,0.011307408],"study_design_scores_gemma":[0.0000019578063,0.0000028195313,0.0000178002,0.000021509135,0.0000032349276,0.000025814481,0.00002244787,0.0011111039,0.0000713553,0.94261724,0.05610154,0.0000032064095],"about_ca_topic_score_codex":0.0018565878,"about_ca_topic_score_gemma":0.0017911369,"teacher_disagreement_score":0.021356352,"about_ca_system_score_codex":0.002216857,"about_ca_system_score_gemma":0.0010158892,"threshold_uncertainty_score":0.071444094},"labels":[],"label_agreement":null},{"id":"W1489499991","doi":"","title":"Personalizing XML text search in PIMENT","year":2005,"lang":"en","type":"article","venue":"Very Large Data Bases","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Information retrieval; Web search query; Ranking (information retrieval); Personalization; Query expansion; Web query classification; XML; World Wide Web; Search engine","score_opus":0.056066286513882985,"score_gpt":0.31407353981900304,"score_spread":0.2580072533051201,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1489499991","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":[0.12130383,0.0008991062,0.79181707,0.0006876909,0.00009227661,0.0007707912,0.0017662148,0.06979152,0.012871568],"genre_scores_gemma":[0.4514003,0.0005329584,0.521467,0.0007933828,0.00013963191,0.00041754107,0.0070129894,0.0015708441,0.016665295],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9972198,0.0008176783,0.00026537597,0.00053525297,0.0009824252,0.00017948393],"domain_scores_gemma":[0.9971547,0.0009407081,0.00017884553,0.0011512142,0.00046037458,0.00011408275],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029846674,0.0005597528,0.00094831095,0.002111426,0.00076843385,0.0018688046,0.0014406822,0.00082679914,0.0023989426],"category_scores_gemma":[0.008237071,0.00050192483,0.0006928549,0.001721826,0.0005085737,0.0029845678,0.0020000022,0.0007569488,0.0018312093],"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":[0.0017181006,0.00068668334,0.008517252,0.0004789566,0.00026235895,0.0012357589,0.00251842,0.023845015,0.079916365,0.028452527,0.048951413,0.8034171],"study_design_scores_gemma":[0.00019926035,0.00044388504,0.0075951484,0.000072063536,0.00024343838,0.0019115862,0.0008297662,0.6380879,0.16082951,0.03739826,0.15213831,0.00025078873],"about_ca_topic_score_codex":0.0025018468,"about_ca_topic_score_gemma":0.0041519315,"teacher_disagreement_score":0.0029846674,"about_ca_system_score_codex":0.00066206994,"about_ca_system_score_gemma":0.0007425213,"threshold_uncertainty_score":0.015784621},"labels":[],"label_agreement":null},{"id":"W1489856527","doi":"10.1109/ftdcs.1990.138289","title":"Some 1990's challenges for multimedia distributed data base systems","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Distributed database; Integrated Services Digital Network; Multimedia; OSI model; Architecture; Broadband; World Wide Web; Broadband networks; Computer network; Database; Interconnection; Telecommunications","score_opus":0.1119554815228185,"score_gpt":0.28027647660620875,"score_spread":0.16832099508339024,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1489856527","genre_codex":"commentary","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":[0.011099089,0.18069595,0.18604456,0.4287022,0.009519261,0.00026388472,0.00047139387,0.00083316246,0.18237047],"genre_scores_gemma":[0.22887716,0.26664785,0.21971746,0.070244685,0.028314907,0.001183168,0.0012410432,0.0011109164,0.18266286],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.996443,0.00076598686,0.000281337,0.0003675955,0.0018501296,0.00029212938],"domain_scores_gemma":[0.9939085,0.0023978516,0.00019644525,0.0006423504,0.0022794297,0.0005753757],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0074916487,0.00080285635,0.00080872106,0.002097571,0.002990721,0.0105922595,0.0021992633,0.006918018,0.011288383],"category_scores_gemma":[0.0126004,0.00110979,0.0009838706,0.0024975687,0.0040474217,0.019532947,0.0033191359,0.007223888,0.0050028116],"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":[0.00007997975,0.00006977355,0.000562902,0.000474101,0.000018770827,0.00047032107,0.0011029203,0.0025325858,0.0014448587,0.7177248,0.1058061,0.16971295],"study_design_scores_gemma":[0.000028407449,0.00005499061,0.000408457,0.0003628015,0.0000089223795,0.00078965176,0.0004907255,0.00512207,0.0005062468,0.18351312,0.80867445,0.000040158084],"about_ca_topic_score_codex":0.0073862458,"about_ca_topic_score_gemma":0.004682216,"teacher_disagreement_score":0.011288383,"about_ca_system_score_codex":0.0052880067,"about_ca_system_score_gemma":0.0026211732,"threshold_uncertainty_score":0.0396201},"labels":[],"label_agreement":null},{"id":"W1490098952","doi":"10.1007/978-3-319-23519-6_259-2","title":"Database Schema Integration","year":2016,"lang":"de","type":"book-chapter","venue":"Encyclopedia of GIS","topic":"Advanced Database Systems and Queries","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 British Columbia","funders":"","keywords":"Database; Computer science; Information retrieval","score_opus":0.018777540507991547,"score_gpt":0.2505599565701912,"score_spread":0.23178241606219965,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1490098952","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":[0.0048782197,0.009346163,0.74296635,0.0027032958,0.0015643468,0.0010602379,0.015206717,0.039668802,0.18260589],"genre_scores_gemma":[0.050218813,0.0126281055,0.699991,0.0025143186,0.00046027382,0.00061332365,0.08377217,0.007884596,0.14191738],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99734503,0.00029843845,0.0003677478,0.0005363911,0.0013295617,0.00012283589],"domain_scores_gemma":[0.997517,0.00037162303,0.00007716817,0.0011179049,0.00082256336,0.00009380281],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026866307,0.0012225028,0.0011960224,0.0047328547,0.0009866642,0.00825533,0.0028259205,0.0011691862,0.04309124],"category_scores_gemma":[0.00664117,0.0010095547,0.001703269,0.0077630146,0.0006046552,0.0073350416,0.004809337,0.0022893047,0.03352998],"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":[0.0001036977,0.00016528106,0.0010549926,0.0008755709,0.00012616633,0.00026822416,0.0005639398,0.0012769683,0.007398798,0.10072541,0.20060916,0.6868318],"study_design_scores_gemma":[0.000023025941,0.000025748242,0.00051056617,0.0003309337,0.000083929845,0.00071515696,0.00021346359,0.00612484,0.009856389,0.04245034,0.93963283,0.00003280164],"about_ca_topic_score_codex":0.0024193653,"about_ca_topic_score_gemma":0.001971629,"teacher_disagreement_score":0.04309124,"about_ca_system_score_codex":0.0010348945,"about_ca_system_score_gemma":0.002209116,"threshold_uncertainty_score":0.14415455},"labels":[],"label_agreement":null},{"id":"W1492100919","doi":"","title":"Database publication practices","year":2005,"lang":"en","type":"article","venue":"VBN Forskningsportal (Aalborg Universitet)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Very large database; Computer science; Database; Database theory; Data administration; Intelligent database; Information retrieval; Database design; Data science; World Wide Web; View; Database tuning; Database model","score_opus":0.016866643852235953,"score_gpt":0.25401924361680045,"score_spread":0.2371525997645645,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1492100919","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"reporting","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":"reporting","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016221218,0.09627692,0.06877087,0.10194383,0.009737832,0.0013204531,0.016423326,0.008337415,0.6809682],"genre_scores_gemma":[0.1612906,0.15571728,0.18721311,0.02723191,0.009288049,0.0013022218,0.039732866,0.005929818,0.4122942],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.8779786,0.026328932,0.02255857,0.010353662,0.059211038,0.0035691585],"domain_scores_gemma":[0.647481,0.07984708,0.025952581,0.08395411,0.1437566,0.019008629],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.07717561,0.00059425645,0.00090079807,0.018023051,0.0053842585,0.023002293,0.005470748,0.0034566561,0.06496602],"category_scores_gemma":[0.21602038,0.0010387463,0.0010740483,0.036290873,0.0016825565,0.014610589,0.0056096083,0.0037425447,0.08477186],"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":[0.0001562959,0.00020967444,0.015443044,0.001656596,0.00007436898,0.00026264653,0.0045417817,0.00046322722,0.0018757125,0.058698647,0.42473128,0.49188668],"study_design_scores_gemma":[0.0000126342475,0.000023617888,0.002484032,0.0004250969,0.000014782517,0.0003127724,0.0008495693,0.00010614482,0.00043899953,0.00333072,0.991975,0.000026727148],"about_ca_topic_score_codex":0.0073596817,"about_ca_topic_score_gemma":0.0069101937,"teacher_disagreement_score":0.9228244,"about_ca_system_score_codex":0.0077482746,"about_ca_system_score_gemma":0.014510267,"threshold_uncertainty_score":0.40814853},"labels":[],"label_agreement":null},{"id":"W1493148642","doi":"10.1007/3-540-44555-2_11","title":"Objects and Classification","year":2000,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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":"Université du Québec à Montréal","funders":"","keywords":"Viewpoints; Computer science; Object-oriented programming; Object (grammar); Representation (politics); Knowledge representation and reasoning; Information retrieval; Artificial intelligence; Programming language","score_opus":0.019233320596600267,"score_gpt":0.2455053830318103,"score_spread":0.22627206243521003,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1493148642","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":[0.015506423,0.18622383,0.28441718,0.018004702,0.007925302,0.0001633405,0.0030244812,0.0017782245,0.48295647],"genre_scores_gemma":[0.21160792,0.062861785,0.118945725,0.003317561,0.007803964,0.0003180407,0.0073588914,0.0008884592,0.5868977],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9991703,0.00013597423,0.000056972054,0.0002843679,0.00029602737,0.00005647513],"domain_scores_gemma":[0.99930835,0.00021215036,0.000051147254,0.00023587137,0.00014144638,0.000051114486],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007841363,0.0007688818,0.0012283939,0.0025921182,0.001325526,0.0057040597,0.001270156,0.0012043288,0.021765642],"category_scores_gemma":[0.0023122455,0.000518284,0.00067412114,0.0048011052,0.0031146826,0.0077502183,0.0019091988,0.001952861,0.0100120725],"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":[0.000018488017,0.000012664794,0.00038634907,0.0001826173,0.000018741679,0.00003412295,0.00024520748,0.0005216252,0.0002847274,0.76751107,0.060307965,0.17047648],"study_design_scores_gemma":[0.0000043567425,0.000009240304,0.0004436334,0.00006808726,0.000017285056,0.000167273,0.000105872394,0.001516667,0.00032056545,0.71741873,0.27991942,0.0000088843735],"about_ca_topic_score_codex":0.0028092726,"about_ca_topic_score_gemma":0.0021264742,"teacher_disagreement_score":0.021765642,"about_ca_system_score_codex":0.0015353361,"about_ca_system_score_gemma":0.00086451555,"threshold_uncertainty_score":0.07281333},"labels":[],"label_agreement":null},{"id":"W1493197938","doi":"10.1007/3-540-45876-x_11","title":"On Efficient Matching of Streaming XML Documents and Queries","year":2002,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":40,"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 British Columbia","funders":"","keywords":"Computer science; Scalability; XML; Matching (statistics); Database; Index (typography); Set (abstract data type); Requirements analysis; Service (business); Information retrieval; Data mining; World Wide Web; Software; Programming language","score_opus":0.010800471698987754,"score_gpt":0.23817247239127143,"score_spread":0.22737200069228367,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1493197938","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":[0.0310399,0.0015210785,0.95338166,0.0006307347,0.00023008342,0.0003598822,0.00085995614,0.0070362603,0.0049404213],"genre_scores_gemma":[0.15229714,0.001397126,0.8270897,0.00045898792,0.00030923783,0.0003058545,0.005527303,0.0013165476,0.01129806],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9938234,0.0014631755,0.0007316021,0.00096110115,0.0024327862,0.00058795133],"domain_scores_gemma":[0.98642075,0.007863961,0.0005278859,0.0038611975,0.0010533972,0.00027287734],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004677263,0.0014223163,0.003149022,0.0032316719,0.0016450947,0.0035964155,0.0044788243,0.0023993305,0.009427236],"category_scores_gemma":[0.01976173,0.001339778,0.0015945884,0.008964405,0.0017505252,0.011842643,0.005519485,0.0017875205,0.0030884747],"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":[0.0024655496,0.00046252212,0.0022068422,0.0005539409,0.00019337884,0.00027582093,0.0005679662,0.08257471,0.019754024,0.092579,0.03313116,0.76523507],"study_design_scores_gemma":[0.00035493835,0.00036690672,0.0011886831,0.000090951944,0.00016501955,0.0004926259,0.0003560009,0.69515836,0.02185688,0.26081663,0.019066283,0.00008671158],"about_ca_topic_score_codex":0.009369181,"about_ca_topic_score_gemma":0.008314972,"teacher_disagreement_score":0.009427236,"about_ca_system_score_codex":0.0023051482,"about_ca_system_score_gemma":0.0029100303,"threshold_uncertainty_score":0.031537294},"labels":[],"label_agreement":null},{"id":"W1493773376","doi":"10.1109/icde.2015.7113302","title":"Meaningful keyword search in relational databases with large and complex schema","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University; York University","funders":"","keywords":"Computer science; Information schema; Information retrieval; SQL; Schema (genetic algorithms); Probabilistic database; Relational database; Database schema; Tuple; Relevance (law); View; Query by Example; Database; Web search query; Database model; Database design; Semi-structured model; Search engine","score_opus":0.13253908859220975,"score_gpt":0.31212819421450555,"score_spread":0.1795891056222958,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1493773376","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":[0.2629348,0.008338699,0.70369565,0.0023683228,0.00013286874,0.0009397911,0.0026087565,0.0135981385,0.005382996],"genre_scores_gemma":[0.49553308,0.0016408311,0.49702206,0.00044577473,0.00009349955,0.0002338085,0.0034377314,0.0005105499,0.0010826677],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.97277516,0.009967302,0.0036397364,0.0026280712,0.0103347935,0.0006548852],"domain_scores_gemma":[0.9480004,0.032919306,0.0040216185,0.0088115595,0.005130971,0.0011161552],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0115220705,0.0011044992,0.0020234105,0.0051841154,0.0015591229,0.0062183007,0.003071907,0.002451331,0.0016420871],"category_scores_gemma":[0.07394146,0.00086402765,0.0008825345,0.009731664,0.0014338994,0.014613925,0.003403489,0.001218978,0.0010070628],"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":[0.002233458,0.0010496412,0.033059154,0.0048772506,0.0005369511,0.002128478,0.0069718724,0.14258668,0.06909328,0.08802223,0.031140117,0.61830086],"study_design_scores_gemma":[0.00018957144,0.00075022946,0.0092675835,0.00023692792,0.00014868284,0.002409333,0.004134018,0.79872686,0.039436165,0.1198503,0.024659384,0.00019101563],"about_ca_topic_score_codex":0.005867858,"about_ca_topic_score_gemma":0.0067263627,"teacher_disagreement_score":0.0115220705,"about_ca_system_score_codex":0.0017869031,"about_ca_system_score_gemma":0.0023067873,"threshold_uncertainty_score":0.06093526},"labels":[],"label_agreement":null},{"id":"W1494439078","doi":"10.1007/11511854_8","title":"Exploitation of Referential Integrity Constraints for Efficient Update of Data Warehouse Views","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","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 Manitoba","funders":"Korea Science and Engineering Foundation","keywords":"Computer science; Joins; Star schema; Tuple; Schema (genetic algorithms); Data warehouse; Exploit; Data integrity; Materialized view; Data source; Information retrieval; Database; Theoretical computer science; Data mining; Programming language; Database schema; Database design; View","score_opus":0.08156817350424389,"score_gpt":0.3206919336221838,"score_spread":0.2391237601179399,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1494439078","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":[0.0275536,0.0010297762,0.9598017,0.0005055467,0.000087688284,0.00013936397,0.00042425413,0.0070293243,0.0034287197],"genre_scores_gemma":[0.32868138,0.00092481147,0.6641425,0.0002656724,0.00013072146,0.00012019356,0.0014884201,0.001640244,0.002606059],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9950388,0.0013325854,0.0006409163,0.0004777798,0.0021526641,0.0003573106],"domain_scores_gemma":[0.97912073,0.0076136817,0.0014504376,0.009437103,0.0021100685,0.00026796566],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005743146,0.00091068365,0.0013494381,0.0017731172,0.00077252934,0.0048813415,0.003349723,0.0010405713,0.003137853],"category_scores_gemma":[0.025050953,0.0013391114,0.0009663528,0.0034654865,0.0009982084,0.009170536,0.003996044,0.0022991758,0.0010235343],"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":[0.0009402604,0.00041438293,0.0046519707,0.0007055512,0.00028973786,0.0005854206,0.0016288682,0.032930598,0.056301776,0.06628543,0.019744135,0.81552196],"study_design_scores_gemma":[0.00026501447,0.00032348384,0.0016703156,0.00020637538,0.0003815943,0.00091924454,0.000503631,0.7188651,0.14437735,0.0954881,0.036825523,0.00017429721],"about_ca_topic_score_codex":0.0021730524,"about_ca_topic_score_gemma":0.004782262,"teacher_disagreement_score":0.005743146,"about_ca_system_score_codex":0.0007045976,"about_ca_system_score_gemma":0.002197737,"threshold_uncertainty_score":0.030373037},"labels":[],"label_agreement":null},{"id":"W1496974946","doi":"10.1007/bfb0024355","title":"Reflection in a uniform behavioral object model","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":24,"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":"Reflection (computer programming); Computer science; Encapsulation (networking); Object (grammar); Architecture; Semantics (computer science); Object model; Programming language; Common Object Request Broker Architecture; Artificial intelligence","score_opus":0.032665096886315435,"score_gpt":0.2958074335323978,"score_spread":0.2631423366460824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1496974946","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":[0.01936753,0.000068547444,0.9625933,0.0003544529,0.000046701054,0.00005830988,0.000065745015,0.0011945594,0.01625074],"genre_scores_gemma":[0.44265187,0.00024531328,0.5208346,0.00047977155,0.00011284658,0.00042169596,0.00042797677,0.0012268302,0.033598997],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9968876,0.0010709147,0.00029498458,0.0006668327,0.0007016558,0.00037805474],"domain_scores_gemma":[0.99323684,0.0016409808,0.00032165405,0.0038879355,0.00071222073,0.00020042741],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035976546,0.00064599176,0.0008577961,0.00073301524,0.0011959985,0.0037597422,0.002383177,0.0015901051,0.0061825216],"category_scores_gemma":[0.009167803,0.0010144685,0.0016080507,0.0011446942,0.0034113328,0.010525401,0.0038411587,0.0030940778,0.0016710096],"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":[0.000025920684,0.000021210331,0.00014090796,0.00001935131,0.0000054614743,0.000028516859,0.00021655364,0.002576768,0.0006656935,0.98841417,0.0003876603,0.007497782],"study_design_scores_gemma":[0.000038458627,0.000036946138,0.00009578064,0.000024688467,0.000039477087,0.00007263378,0.00010576259,0.041157555,0.0022533657,0.9474498,0.008708323,0.000017197515],"about_ca_topic_score_codex":0.0018076685,"about_ca_topic_score_gemma":0.0013482164,"teacher_disagreement_score":0.0061825216,"about_ca_system_score_codex":0.0011236201,"about_ca_system_score_gemma":0.0014948437,"threshold_uncertainty_score":0.020682573},"labels":[],"label_agreement":null},{"id":"W1500615737","doi":"","title":"Designing information-preserving mapping schemes for XML","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":54,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University of Calgary","funders":"","keywords":"Computer science; Relational database; XML; Undecidable problem; Scheme (mathematics); Equivalence (formal languages); Set (abstract data type); Information retrieval; Data mining; Enhanced Data Rates for GSM Evolution; Theoretical computer science; XML database; Database; Programming language; Mathematics; Artificial intelligence","score_opus":0.02247398678485313,"score_gpt":0.2528989283675945,"score_spread":0.23042494158274135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1500615737","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":[0.03170599,0.0001198526,0.9650232,0.00021220295,0.000017084003,0.00015312168,0.00006269968,0.0011579244,0.0015478686],"genre_scores_gemma":[0.29104,0.0001989168,0.705694,0.00016010737,0.000021943799,0.00021942891,0.00028195133,0.00023997297,0.0021436352],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99623305,0.0015223882,0.00050904707,0.00051868625,0.00091356406,0.00030320213],"domain_scores_gemma":[0.9907045,0.0037630785,0.0007364498,0.0039401073,0.0006633376,0.00019245126],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00744531,0.00045012953,0.00053467246,0.0011529196,0.001085511,0.0024956735,0.0021193933,0.0012534771,0.0016898682],"category_scores_gemma":[0.015532372,0.00069009216,0.00087322626,0.0015048339,0.0023593642,0.008109786,0.0039998945,0.0016109692,0.0006048881],"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":[0.00047585252,0.0002506707,0.0026651495,0.00039864515,0.00006350851,0.00020477995,0.0020726349,0.071250506,0.024712516,0.6279048,0.003333287,0.26666772],"study_design_scores_gemma":[0.00016211573,0.00032973482,0.00045334687,0.000109930515,0.00007279371,0.00031194155,0.0005199447,0.42339042,0.095411114,0.44406423,0.035099074,0.00007535129],"about_ca_topic_score_codex":0.0006770607,"about_ca_topic_score_gemma":0.0006859714,"teacher_disagreement_score":0.00744531,"about_ca_system_score_codex":0.0012464866,"about_ca_system_score_gemma":0.0013234491,"threshold_uncertainty_score":0.039375007},"labels":[],"label_agreement":null},{"id":"W1500756752","doi":"10.1007/978-3-540-45160-0_9","title":"Logical Foundation for Updating XML","year":2003,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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":"Carleton University","funders":"","keywords":"Computer science; Efficient XML Interchange; XML Schema Editor; XML validation; Streaming XML; XML database; Programming language; Document Structure Description; XML; XML framework; XML Encryption; XML Signature; XML Schema (W3C); Information retrieval; World Wide Web","score_opus":0.027729798359938773,"score_gpt":0.2743152278401508,"score_spread":0.246585429480212,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1500756752","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":[0.0032484492,0.00067303487,0.96253985,0.0021476834,0.00057283667,0.00012059213,0.000590083,0.0042265584,0.025880791],"genre_scores_gemma":[0.12922482,0.0018306854,0.81378436,0.0020511446,0.0014434158,0.00068035536,0.0034630431,0.0027846736,0.04473749],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9953342,0.001167824,0.00071835966,0.00093821593,0.0014903884,0.0003510787],"domain_scores_gemma":[0.9932075,0.0025339047,0.00033430976,0.0024006823,0.0013103212,0.00021324465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0060145864,0.00091007905,0.001080412,0.0034459825,0.0030632813,0.008247319,0.0036520283,0.0023115901,0.016362315],"category_scores_gemma":[0.012645412,0.0021048237,0.0023361503,0.0037488402,0.004701696,0.02089829,0.0054722372,0.0060552885,0.0060507874],"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":[0.0000309201,0.000025230282,0.00014161285,0.00009618819,0.00001568692,0.0000678712,0.00030188475,0.00073421927,0.0005927243,0.9555615,0.007866956,0.034565218],"study_design_scores_gemma":[0.00003623038,0.00002811091,0.00010873224,0.0001077781,0.00010761326,0.00017922506,0.00011677767,0.014543623,0.003372275,0.8752904,0.10606592,0.000043403707],"about_ca_topic_score_codex":0.0033027644,"about_ca_topic_score_gemma":0.0029302489,"teacher_disagreement_score":0.016362315,"about_ca_system_score_codex":0.002522751,"about_ca_system_score_gemma":0.0028468093,"threshold_uncertainty_score":0.05473739},"labels":[],"label_agreement":null},{"id":"W1500858206","doi":"","title":"Proceedings of the 2007 inaugural international conference on Distributed event-based systems","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Event (particle physics); Computer science; Library science","score_opus":0.01939802971185279,"score_gpt":0.26902320715360406,"score_spread":0.24962517744175128,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1500858206","genre_codex":"methods","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":[0.029447962,0.057007357,0.47516808,0.04434856,0.087090634,0.0015379587,0.0035022895,0.009407502,0.2924897],"genre_scores_gemma":[0.16445363,0.056925144,0.18301521,0.009610525,0.023105012,0.0012591974,0.022711458,0.0036245417,0.53529525],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99699414,0.00072979246,0.00024024885,0.00041960983,0.0014125259,0.00020377329],"domain_scores_gemma":[0.9953087,0.0011491246,0.00013558804,0.0007868453,0.0017664487,0.0008532324],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0045457385,0.0011568557,0.0013526852,0.00087495276,0.0009506607,0.0067505348,0.0019569611,0.0016501546,0.051056568],"category_scores_gemma":[0.0068282024,0.0004464813,0.00074780383,0.0009233332,0.0012830592,0.003971985,0.0030629814,0.0035953822,0.018201143],"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":[0.0005017981,0.00040201144,0.0010329013,0.00051961275,0.00010462241,0.0004876838,0.0007183188,0.0028205533,0.005107063,0.03189208,0.69597125,0.2604422],"study_design_scores_gemma":[0.000054804867,0.00009033641,0.0008415555,0.00018330259,0.000033230812,0.00027709213,0.00022707257,0.006317312,0.0015744818,0.010141141,0.980228,0.00003165791],"about_ca_topic_score_codex":0.0029746394,"about_ca_topic_score_gemma":0.0031339342,"teacher_disagreement_score":0.051056568,"about_ca_system_score_codex":0.0016439493,"about_ca_system_score_gemma":0.0030462155,"threshold_uncertainty_score":0.17080122},"labels":[],"label_agreement":null},{"id":"W150096117","doi":"","title":"On the twig joins","year":2006,"lang":"en","type":"article","venue":"Annual Conference on Computers","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Computer science; Twig; Joins; XML; Redundancy (engineering); XML Schema (W3C); Document Structure Description; Tree (set theory); Encoding (memory); Theoretical computer science; Information retrieval; Data mining; Programming language; Mathematics; Document type definition; Artificial intelligence; Combinatorics","score_opus":0.0221631567468676,"score_gpt":0.24076822436601772,"score_spread":0.2186050676191501,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W150096117","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":[0.020791164,0.002888846,0.9520134,0.001098395,0.00027970818,0.00023325827,0.000539256,0.0018596272,0.020296285],"genre_scores_gemma":[0.20468266,0.004571126,0.76349354,0.0012045392,0.001145421,0.00048909616,0.0019921777,0.0013385976,0.021082861],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9960265,0.00081201096,0.00021672423,0.00087044766,0.001712763,0.00036156364],"domain_scores_gemma":[0.99525106,0.0023357212,0.0002620247,0.0014233101,0.00054272945,0.0001851409],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031826107,0.0010475382,0.0015798097,0.0020285696,0.0020664788,0.0041812393,0.0026823988,0.0014549792,0.010939448],"category_scores_gemma":[0.009683715,0.00086434593,0.0012739683,0.004832688,0.002309115,0.010784786,0.0047519174,0.003508808,0.003099103],"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":[0.0010684035,0.0001827043,0.0007200353,0.00034800675,0.00007928501,0.00032566334,0.0006346556,0.04837651,0.00700277,0.6610357,0.02124797,0.2589782],"study_design_scores_gemma":[0.000106923595,0.00020542677,0.00030461035,0.00008109702,0.00005380801,0.00038198096,0.00019413482,0.14984809,0.0048105507,0.7880558,0.05591695,0.000040625942],"about_ca_topic_score_codex":0.0025759058,"about_ca_topic_score_gemma":0.0023240545,"teacher_disagreement_score":0.010939448,"about_ca_system_score_codex":0.0013555844,"about_ca_system_score_gemma":0.0014557394,"threshold_uncertainty_score":0.03659612},"labels":[],"label_agreement":null},{"id":"W1501261365","doi":"10.1007/3-540-44469-6_71","title":"Design and Implementation of the OLOG Deductive Object-Oriented Database Management System","year":2000,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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 Regina","funders":"","keywords":"Computer science; SQL; Data definition language; Deductive database; Relational database; Programming language; Database design; Relational database management system; Query language; Object (grammar); Database; Query by Example; Information retrieval; Artificial intelligence; Web search query","score_opus":0.013128312577857957,"score_gpt":0.25447665151037846,"score_spread":0.2413483389325205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1501261365","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":[0.03894901,0.0003623352,0.92695624,0.00046809198,0.00012540327,0.0007116093,0.00036873014,0.022141907,0.009916721],"genre_scores_gemma":[0.15561585,0.0003270644,0.8310635,0.00059804553,0.00005964374,0.00037148403,0.00091525103,0.0009739238,0.01007533],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99936515,0.00010734594,0.000058510268,0.000106419284,0.00027603563,0.0000866052],"domain_scores_gemma":[0.99933606,0.00020392051,0.000060234885,0.00014059067,0.00018840453,0.00007062502],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00138918,0.00027094712,0.00040504927,0.00060017704,0.00047119232,0.0024694824,0.002550404,0.00084375555,0.005664338],"category_scores_gemma":[0.0019309986,0.0005411642,0.00033662163,0.00044677276,0.0006093744,0.0012720398,0.00087270513,0.00094821013,0.0017194623],"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":[0.00094587397,0.0011058176,0.0058895242,0.0007858445,0.00014996546,0.0008546718,0.0014338014,0.02707254,0.14541912,0.11215371,0.024431529,0.6797576],"study_design_scores_gemma":[0.0007492533,0.001071674,0.004672934,0.00022030748,0.0003543337,0.0011374061,0.0004985872,0.4568743,0.26034623,0.030536564,0.24338269,0.00015572531],"about_ca_topic_score_codex":0.0020247984,"about_ca_topic_score_gemma":0.0019736728,"teacher_disagreement_score":0.005664338,"about_ca_system_score_codex":0.00071219826,"about_ca_system_score_gemma":0.0016131351,"threshold_uncertainty_score":0.018949151},"labels":[],"label_agreement":null},{"id":"W1502557952","doi":"10.1007/bfb0018391","title":"Novel terms and cooperation in a natural language interface","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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":"Simon Fraser University","funders":"","keywords":"Lexicon; Term (time); Interface (matter); Computer science; Heuristics; Set (abstract data type); Natural language user interface; Conjunction (astronomy); Natural language processing; Personalization; Value (mathematics); Natural language; Natural (archaeology); Artificial intelligence; Information retrieval; Programming language; Machine learning; World Wide Web","score_opus":0.009698452942246477,"score_gpt":0.25272567296172127,"score_spread":0.2430272200194748,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1502557952","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":[0.012829947,0.00020076706,0.969427,0.00085880846,0.00012619326,0.00007099279,0.00010082078,0.0023014895,0.014084068],"genre_scores_gemma":[0.27405015,0.00037738026,0.693835,0.00043871018,0.00020596248,0.00029965976,0.0004631271,0.0017381294,0.028591953],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9970391,0.0014300247,0.00022657563,0.00044445987,0.0006718159,0.00018813739],"domain_scores_gemma":[0.9968004,0.0020806994,0.000104373845,0.0006025497,0.00026864832,0.00014329018],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027656844,0.0006200558,0.000857024,0.0007798364,0.0016135804,0.003703885,0.0022028186,0.0024390868,0.015846016],"category_scores_gemma":[0.007723616,0.0009290569,0.0010211987,0.0010192571,0.0029831948,0.014182788,0.0057749986,0.0030721466,0.0045636804],"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":[0.00025114545,0.000051876385,0.000334145,0.00016558937,0.000015926753,0.0005189274,0.0034575257,0.0019974476,0.012439153,0.9112366,0.009211991,0.06031963],"study_design_scores_gemma":[0.000095934265,0.00009177389,0.00018129758,0.000069873975,0.00007551303,0.0011683614,0.0008405066,0.07760203,0.010693244,0.8258175,0.08329211,0.00007188222],"about_ca_topic_score_codex":0.000831247,"about_ca_topic_score_gemma":0.0011134503,"teacher_disagreement_score":0.015846016,"about_ca_system_score_codex":0.0006706307,"about_ca_system_score_gemma":0.0005833727,"threshold_uncertainty_score":0.053010225},"labels":[],"label_agreement":null},{"id":"W1502629466","doi":"10.1007/978-3-030-26253-2","title":"Principles of Distributed Database Systems","year":2019,"lang":"en","type":"book","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2349,"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":"NoSQL; Computer science; Data integration; Database; Distributed database; Schema (genetic algorithms); Schema evolution; Database schema; World Wide Web; Database design; Information retrieval","score_opus":0.028501266473769684,"score_gpt":0.24060350791899107,"score_spread":0.21210224144522138,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1502629466","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008030882,0.06282955,0.3590395,0.0050433907,0.0052189264,0.0002892917,0.0007909432,0.004583244,0.561402],"genre_scores_gemma":[0.02479191,0.056825023,0.23434171,0.002989356,0.0044700573,0.000618969,0.0017501456,0.0013584289,0.6728544],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985261,0.00015095102,0.000091723174,0.00022118348,0.00092526583,0.00008477548],"domain_scores_gemma":[0.9991891,0.00023088293,0.000034974222,0.00024236485,0.00023007517,0.00007254689],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008987312,0.0016513978,0.0012112563,0.0017782224,0.001372187,0.005701713,0.0020753478,0.0014721944,0.03360518],"category_scores_gemma":[0.0022524386,0.0010845296,0.0006810065,0.0031085534,0.0026859397,0.004769013,0.002277441,0.0045154816,0.03698754],"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":[0.000026581472,0.000045743673,0.0001212921,0.00042753207,0.0000281946,0.00008065022,0.00030093995,0.0018511381,0.0012593039,0.5495077,0.2522614,0.19408962],"study_design_scores_gemma":[0.000011628933,0.000012886869,0.00010177067,0.00011602331,0.000009198314,0.00016763025,0.000029573484,0.0019046195,0.0002493523,0.1488165,0.84856963,0.000011260469],"about_ca_topic_score_codex":0.0017233505,"about_ca_topic_score_gemma":0.0017800167,"teacher_disagreement_score":0.03360518,"about_ca_system_score_codex":0.001467418,"about_ca_system_score_gemma":0.00208801,"threshold_uncertainty_score":0.11242056},"labels":[],"label_agreement":null},{"id":"W1502696193","doi":"10.1007/978-3-7908-1846-8_30","title":"A Strategy for Partial Evaluation of Views","year":2000,"lang":"en","type":"book-chapter","venue":"Intelligent Information Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Computer science; Tuple; Rewriting; Materialized view; Information retrieval; Spatial query; Query optimization; Query language; Cache; Data integrity; Database; Web search query; View; Web query classification; Programming language; Search engine; Database design; Mathematics","score_opus":0.13245894625041543,"score_gpt":0.33332790040425064,"score_spread":0.2008689541538352,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1502696193","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":[0.0044018994,0.0005512887,0.96319747,0.00075613864,0.00016931162,0.0002112296,0.000142927,0.0018588951,0.028710807],"genre_scores_gemma":[0.15031019,0.0007196594,0.8092572,0.0009632806,0.0001774075,0.00056789024,0.0004997024,0.0015608547,0.035943802],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9957612,0.0014964319,0.00032872634,0.00086169975,0.0012825582,0.00026938983],"domain_scores_gemma":[0.99602985,0.0013990782,0.00009608541,0.0015729688,0.0007506466,0.00015137317],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0042178323,0.0012970052,0.00096055196,0.0014056868,0.0015664159,0.004839548,0.0024694472,0.0016130405,0.008638386],"category_scores_gemma":[0.007852463,0.0010435063,0.0017319971,0.0012251934,0.0035878017,0.008841109,0.004138032,0.0030798055,0.0031301037],"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":[0.000112818714,0.000051029132,0.00027988912,0.00015545392,0.00004665005,0.00023317889,0.0011033673,0.001821956,0.0065247435,0.85073924,0.008699248,0.13023245],"study_design_scores_gemma":[0.00008112033,0.00019730457,0.00018994782,0.00013978839,0.00013033602,0.00089684577,0.00050186296,0.033197742,0.026064983,0.747742,0.19076243,0.0000957245],"about_ca_topic_score_codex":0.0018311841,"about_ca_topic_score_gemma":0.0016710827,"teacher_disagreement_score":0.008638386,"about_ca_system_score_codex":0.001576591,"about_ca_system_score_gemma":0.0017208208,"threshold_uncertainty_score":0.02889824},"labels":[],"label_agreement":null},{"id":"W1502949834","doi":"","title":"Techniques for automatically sizing multiple buffer pools in DB2","year":2003,"lang":"en","type":"article","venue":"Conference of the Centre for Advanced Studies on Collaborative Research","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Buffer (optical fiber); Computer science; Sizing; Benchmark (surveying); Buffer zone; Table (database); Database","score_opus":0.12126272213382853,"score_gpt":0.41538944083845436,"score_spread":0.2941267187046258,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1502949834","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":[0.033776455,0.00082859024,0.9565413,0.00023798647,0.000044787477,0.00022299205,0.00020581149,0.0064558894,0.001686113],"genre_scores_gemma":[0.17756137,0.00025381637,0.81995046,0.00009764434,0.000025351215,0.00020118454,0.00037344135,0.0004022154,0.0011344546],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986235,0.00033745592,0.00016975284,0.00025594173,0.00045028204,0.0001631417],"domain_scores_gemma":[0.9964324,0.0016800297,0.00044060897,0.0008228614,0.0004803312,0.00014368533],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020368272,0.0013516942,0.0010506896,0.0016980415,0.00085365516,0.0020816668,0.0031694483,0.0007633418,0.0027673563],"category_scores_gemma":[0.0054224283,0.0010332577,0.0006503313,0.0020798142,0.00056768267,0.003214557,0.0017565716,0.0008029557,0.0008964229],"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":[0.0008301845,0.00025092863,0.0045939097,0.0004543343,0.00010569957,0.00018587775,0.0004724223,0.102134116,0.078904554,0.013695935,0.01203842,0.7863336],"study_design_scores_gemma":[0.0002657955,0.000202441,0.0012138996,0.00004098754,0.000108991684,0.00034181683,0.00028653225,0.8958713,0.072511345,0.01361304,0.015470536,0.000073288444],"about_ca_topic_score_codex":0.00539952,"about_ca_topic_score_gemma":0.007250803,"teacher_disagreement_score":0.00539952,"about_ca_system_score_codex":0.0011095454,"about_ca_system_score_gemma":0.0021068398,"threshold_uncertainty_score":0.010771871},"labels":[],"label_agreement":null},{"id":"W1508182360","doi":"10.1007/978-3-642-15576-5_25","title":"Exploiting Conflict Structures in Inconsistent Databases","year":2010,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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 British Columbia","funders":"","keywords":"Computer science; Database; Information retrieval","score_opus":0.03678842332174959,"score_gpt":0.27661527829436355,"score_spread":0.23982685497261397,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1508182360","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":[0.04134719,0.0015196203,0.9493898,0.0008569789,0.00015732675,0.00013420063,0.00027336853,0.001856346,0.004465242],"genre_scores_gemma":[0.40126455,0.0010806104,0.5916068,0.00033590302,0.00016079145,0.00013352191,0.0010263831,0.00061662117,0.0037748371],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9938455,0.0020195043,0.00057409727,0.0004550444,0.002715047,0.00039070696],"domain_scores_gemma":[0.97145534,0.020364793,0.0012527144,0.004698836,0.0019032027,0.0003251958],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00634384,0.0009152601,0.0014427217,0.0021846262,0.0012870915,0.0037906815,0.003918842,0.0013847076,0.004022679],"category_scores_gemma":[0.030140286,0.0017217835,0.0013686559,0.003544172,0.001820722,0.011179602,0.0060804696,0.0030768232,0.0005407703],"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":[0.0011763124,0.00043156563,0.0062392727,0.0010574205,0.000442155,0.0013787984,0.0015051094,0.0812142,0.012878025,0.31955197,0.014659418,0.5594657],"study_design_scores_gemma":[0.000112806876,0.00012045242,0.00046849772,0.00013191317,0.0002715661,0.0008911372,0.00045807203,0.4298597,0.017072052,0.5383002,0.012241467,0.000072200324],"about_ca_topic_score_codex":0.0009954614,"about_ca_topic_score_gemma":0.0013761183,"teacher_disagreement_score":0.00634384,"about_ca_system_score_codex":0.0007452722,"about_ca_system_score_gemma":0.0011730108,"threshold_uncertainty_score":0.033549845},"labels":[],"label_agreement":null},{"id":"W1508620658","doi":"","title":"Supporting capacity planning for DB2 UDB","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Capacity planning; Computer science; IBM; Workload; Capacity management; Online transaction processing; Process (computing); Database; Distributed computing; Transaction processing; Operating system; Database transaction","score_opus":0.0730831974408855,"score_gpt":0.3065056263743842,"score_spread":0.23342242893349874,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1508620658","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":[0.15071318,0.0006081676,0.7859722,0.0028253712,0.00016537638,0.00034699106,0.0017127771,0.011978364,0.04567763],"genre_scores_gemma":[0.88543767,0.00020666352,0.109093405,0.00021015095,0.00004484997,0.00015870093,0.00088236155,0.00039467163,0.003571425],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974139,0.0010762559,0.00010872858,0.0002615459,0.00064727,0.00049235875],"domain_scores_gemma":[0.9940673,0.0030255495,0.00039626006,0.0009320197,0.0011105216,0.00046832906],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030934482,0.0006491461,0.0006581882,0.0007413508,0.0014185862,0.0033164534,0.0023219383,0.0011672837,0.007698907],"category_scores_gemma":[0.014320187,0.0006332033,0.0003879864,0.0016287534,0.0006337116,0.0027577823,0.0016285821,0.0010272671,0.0012890343],"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":[0.0002498291,0.0001976377,0.0042531383,0.00015750997,0.000033326785,0.0003717136,0.00045505358,0.80026305,0.005862011,0.079594284,0.027765788,0.080796674],"study_design_scores_gemma":[0.000010882433,0.0000126530595,0.00016537859,0.000008908798,0.0000029573016,0.00003136262,0.00007523946,0.98531765,0.0011311964,0.00771437,0.0055196453,0.000009731153],"about_ca_topic_score_codex":0.028918104,"about_ca_topic_score_gemma":0.01956986,"teacher_disagreement_score":0.028918104,"about_ca_system_score_codex":0.0020913002,"about_ca_system_score_gemma":0.0035018777,"threshold_uncertainty_score":0.057499588},"labels":[],"label_agreement":null},{"id":"W1510826524","doi":"10.1007/978-3-642-00887-0_55","title":"Materialized View Selection in XML Databases","year":2009,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":27,"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":"Materialized view; Computer science; XML; Selection (genetic algorithm); XML database; Information retrieval; Data warehouse; Database; Relational database management system; Context (archaeology); Graph; Streaming XML; XML validation; Efficient XML Interchange; Relational database; Theoretical computer science; View; World Wide Web; Database design; Artificial intelligence","score_opus":0.02280143752678639,"score_gpt":0.2710076934982822,"score_spread":0.2482062559714958,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1510826524","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":[0.023543997,0.0027784074,0.9480128,0.00040262475,0.00014558286,0.00016013793,0.00072129286,0.00810106,0.016134132],"genre_scores_gemma":[0.23005722,0.0023591917,0.73253155,0.00032128207,0.00019205883,0.0001954686,0.003925699,0.0020076607,0.028409781],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99784994,0.000582424,0.00021806643,0.00025039283,0.000957107,0.00014209692],"domain_scores_gemma":[0.9981914,0.00089420815,0.00006307339,0.0005559441,0.00022381196,0.00007152095],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022744916,0.0005858819,0.0010104862,0.001410517,0.00072589377,0.0035894269,0.002323041,0.00089485175,0.011065448],"category_scores_gemma":[0.0040575527,0.0008405878,0.0008806759,0.0025478192,0.0009797311,0.0052007437,0.0021573512,0.0013751514,0.0028267025],"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":[0.00071282947,0.00025312486,0.0016188115,0.0007233523,0.000090296024,0.00065528735,0.00073008565,0.01707896,0.015676823,0.217502,0.030925665,0.7140329],"study_design_scores_gemma":[0.0002053203,0.00032667466,0.0015400947,0.00045001722,0.00019534523,0.0015036748,0.00071638403,0.322703,0.07337967,0.4173998,0.18142046,0.00015959068],"about_ca_topic_score_codex":0.0010131404,"about_ca_topic_score_gemma":0.0014128851,"teacher_disagreement_score":0.011065448,"about_ca_system_score_codex":0.0008376469,"about_ca_system_score_gemma":0.0006281404,"threshold_uncertainty_score":0.037017643},"labels":[],"label_agreement":null},{"id":"W1512034865","doi":"10.1007/3-540-44801-2_18","title":"Towards a Novel OLAP Interface for Distributed Data Warehouses","year":2001,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":17,"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":"Online analytical processing; Computer science; Data warehouse; Interface (matter); Database; Operating system","score_opus":0.05422229387345219,"score_gpt":0.30263209788310247,"score_spread":0.2484098040096503,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1512034865","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":[0.002714709,0.00012234542,0.98235345,0.00018146311,0.000084078834,0.00007018888,0.00013025377,0.013383162,0.00096046826],"genre_scores_gemma":[0.024491558,0.00024372079,0.9651097,0.0004843672,0.000104198574,0.00018121743,0.0008946769,0.002345903,0.0061446894],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99726355,0.00038707838,0.00039619606,0.00040520844,0.001361674,0.0001862071],"domain_scores_gemma":[0.99667907,0.0008169785,0.0001315586,0.0011068297,0.0009559465,0.00030963824],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038117226,0.0009867572,0.0013326019,0.0011218169,0.00095733727,0.007507983,0.005346597,0.0025655741,0.007969938],"category_scores_gemma":[0.007050767,0.0016941702,0.0012244816,0.0018757802,0.00090308185,0.008764398,0.0065921163,0.0034255337,0.0043720314],"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":[0.0017669352,0.0006159322,0.0031882366,0.001067617,0.00035078663,0.0009009325,0.0027489888,0.010891655,0.09685545,0.11797881,0.078706875,0.6849278],"study_design_scores_gemma":[0.00040393157,0.00042649923,0.000994493,0.0002933003,0.00035688127,0.0015378232,0.00068670063,0.5237226,0.10683218,0.099098116,0.26542303,0.0002244338],"about_ca_topic_score_codex":0.0015511534,"about_ca_topic_score_gemma":0.00215151,"teacher_disagreement_score":0.007969938,"about_ca_system_score_codex":0.000700415,"about_ca_system_score_gemma":0.0010236289,"threshold_uncertainty_score":0.026662111},"labels":[],"label_agreement":null},{"id":"W1514429059","doi":"10.1007/3-540-44543-9_17","title":"On the Difference between Navigating Semi-structured Data and Querying It","year":2000,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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":"Concordia University","funders":"","keywords":"Computer science; Query language; Schema (genetic algorithms); Data structure; Theoretical computer science; Semi-structured data; Programming language; Information retrieval; Relational database","score_opus":0.03567632543008109,"score_gpt":0.2779481489879913,"score_spread":0.24227182355791022,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1514429059","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":[0.031033495,0.019019313,0.85808814,0.030733913,0.0015255617,0.00012924112,0.0004335712,0.001108503,0.057928193],"genre_scores_gemma":[0.35676256,0.025000377,0.574685,0.0061442996,0.0019677684,0.00034434904,0.0012492678,0.0022783203,0.031568047],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99319285,0.0024089145,0.00058263855,0.001040325,0.0023254424,0.0004498297],"domain_scores_gemma":[0.9417001,0.048696563,0.00071476767,0.0059970883,0.002093963,0.00079752726],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009244159,0.00091117836,0.0018589356,0.0019734257,0.0024830278,0.012360548,0.0041492926,0.0056865592,0.0086909225],"category_scores_gemma":[0.049277596,0.0018381918,0.0011784638,0.0053118854,0.015555618,0.07202333,0.009608086,0.008604444,0.0016649876],"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":[0.00015036041,0.00004290976,0.00038942616,0.00025289,0.000013933948,0.000099958655,0.002138703,0.0027968273,0.00083406235,0.9333911,0.0077415407,0.052148357],"study_design_scores_gemma":[0.000029499693,0.000044160635,0.00030582395,0.00018054011,0.00002931717,0.00023977744,0.0010439502,0.020814234,0.0013441517,0.9378151,0.03810428,0.000049061313],"about_ca_topic_score_codex":0.007720375,"about_ca_topic_score_gemma":0.006390025,"teacher_disagreement_score":0.012360548,"about_ca_system_score_codex":0.0022699654,"about_ca_system_score_gemma":0.0019093087,"threshold_uncertainty_score":0.048888385},"labels":[],"label_agreement":null},{"id":"W1518166664","doi":"","title":"Use of XML for Web-Based Query Processing of Geospatial Data","year":2000,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Geospatial PDF; Information retrieval; Geospatial analysis; XML; Database; World Wide Web; Geography; Remote sensing","score_opus":0.07859621580861738,"score_gpt":0.2973395027713441,"score_spread":0.2187432869627267,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1518166664","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":[0.009907709,0.0010365095,0.94082147,0.0010360933,0.00024275451,0.0007783521,0.0020584057,0.029423036,0.014695687],"genre_scores_gemma":[0.13174388,0.0023573071,0.8396754,0.0014365766,0.00017240095,0.00095126574,0.010122204,0.00423892,0.0093019],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9930101,0.002674473,0.0010996887,0.00063332915,0.0023403263,0.00024205845],"domain_scores_gemma":[0.98942775,0.0056714374,0.0005104138,0.0028180121,0.0013861114,0.00018629883],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006965197,0.0008837567,0.00071007333,0.0022390469,0.0010891686,0.003934953,0.0025098466,0.0012997981,0.005504613],"category_scores_gemma":[0.014840521,0.000673366,0.0012276337,0.0035946118,0.0010963383,0.0063539296,0.0021061862,0.0017430534,0.0030471901],"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":[0.000734224,0.00047074025,0.0062044724,0.0023910087,0.0004279808,0.0023418125,0.003572326,0.022225713,0.051502667,0.21733142,0.06917363,0.623624],"study_design_scores_gemma":[0.00020356299,0.0004970848,0.0036296642,0.0009245737,0.0002807394,0.0022713155,0.0009752814,0.19037531,0.09492983,0.1389244,0.56673104,0.00025715187],"about_ca_topic_score_codex":0.0050426694,"about_ca_topic_score_gemma":0.0029359832,"teacher_disagreement_score":0.006965197,"about_ca_system_score_codex":0.001094424,"about_ca_system_score_gemma":0.0012911267,"threshold_uncertainty_score":0.03683591},"labels":[],"label_agreement":null},{"id":"W1519007291","doi":"10.1007/978-3-540-27772-9_36","title":"Tree Multivalued Dependencies for XML Datasets","year":2004,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":15,"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":"XML; Computer science; Tree (set theory); Functional dependency; Relational database; Data mining; Theoretical computer science; Dependency theory (database theory); XML database; Mathematics; Combinatorics; World Wide Web","score_opus":0.024186690029958102,"score_gpt":0.2707238614658031,"score_spread":0.24653717143584497,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1519007291","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":[0.029612873,0.0014677211,0.95618457,0.0005751204,0.00012271096,0.00009681257,0.004536244,0.004533294,0.002870737],"genre_scores_gemma":[0.2808283,0.0011471024,0.69346195,0.00024822386,0.00023892909,0.00024307563,0.015163293,0.0015826677,0.00708647],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99865204,0.00029430547,0.00021056627,0.00030417668,0.00045721635,0.00008160621],"domain_scores_gemma":[0.9936558,0.0035881225,0.00045758008,0.0016102734,0.0005221345,0.0001661472],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025332372,0.0003020044,0.0007158792,0.0020212498,0.00067458866,0.0015398719,0.0014617988,0.00081031356,0.004016656],"category_scores_gemma":[0.008850776,0.0007399508,0.00083532144,0.0035896283,0.00060320925,0.0056891968,0.0012916568,0.0014721446,0.00075599184],"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":[0.0005440272,0.00016640588,0.005692829,0.0009049286,0.00015078274,0.00048583857,0.00064489315,0.058474455,0.013844348,0.33612987,0.043510374,0.5394512],"study_design_scores_gemma":[0.000057386125,0.00010481568,0.0022933807,0.00016339432,0.00009371455,0.0005234548,0.00011620896,0.34721386,0.012987592,0.58998656,0.046396792,0.00006290875],"about_ca_topic_score_codex":0.0018263184,"about_ca_topic_score_gemma":0.00401012,"teacher_disagreement_score":0.004016656,"about_ca_system_score_codex":0.000903721,"about_ca_system_score_gemma":0.0008574496,"threshold_uncertainty_score":0.013437092},"labels":[],"label_agreement":null},{"id":"W1520918022","doi":"10.1007/3-540-36469-2_4","title":"Managing Digital Mathematical Discourse","year":2003,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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; Metadata; Field (mathematics); Ontology; Rubric; Data science; Information retrieval; World Wide Web","score_opus":0.014219560881667221,"score_gpt":0.25558130602287565,"score_spread":0.24136174514120842,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1520918022","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":[0.0226155,0.0045795296,0.28179607,0.01312046,0.00088860095,0.000141033,0.0006182586,0.0032899254,0.6729506],"genre_scores_gemma":[0.50622475,0.0063404427,0.15735102,0.0017250706,0.0015776703,0.00041709363,0.0022442879,0.0019920117,0.32212773],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99708956,0.0011517253,0.00021603986,0.00035407313,0.0009866678,0.00020185986],"domain_scores_gemma":[0.99487644,0.0019596005,0.00034036432,0.0018550593,0.00070257543,0.00026595997],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033285206,0.00061326346,0.0005748593,0.004473731,0.0029500748,0.01643395,0.0020224892,0.0014676047,0.04211923],"category_scores_gemma":[0.013718584,0.00063020503,0.0005515384,0.0052691335,0.0050898143,0.028311918,0.009426476,0.0021577976,0.01066568],"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":[0.000013413527,0.000014249244,0.00010998227,0.000052113563,0.0000042621655,0.000045695087,0.001787219,0.00030284768,0.00047130836,0.93930656,0.00981549,0.048076883],"study_design_scores_gemma":[0.000013804316,0.000011473455,0.00010679653,0.000091179936,0.000019223824,0.00012321712,0.0019754884,0.003122736,0.0019036725,0.63385147,0.35876703,0.000013901827],"about_ca_topic_score_codex":0.001172618,"about_ca_topic_score_gemma":0.0011814535,"teacher_disagreement_score":0.04211923,"about_ca_system_score_codex":0.002882787,"about_ca_system_score_gemma":0.0022444404,"threshold_uncertainty_score":0.14090288},"labels":[],"label_agreement":null},{"id":"W1522493222","doi":"10.3233/jcm-2009-0236","title":"Towards automatic integration of the business-data layers in enterprise-systems1","year":2009,"lang":"en","type":"article","venue":"Journal of Computational Methods in Sciences and Engineering","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Business","score_opus":0.053090097389433225,"score_gpt":0.37423288988083997,"score_spread":0.32114279249140676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1522493222","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":[0.009123061,0.0003590547,0.97277033,0.0004743255,0.000057889938,0.00018156,0.00033392687,0.015016883,0.0016829541],"genre_scores_gemma":[0.0826383,0.0002434493,0.91225797,0.0002169156,0.0000309511,0.000090326655,0.0013132554,0.0014911407,0.0017175892],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9917719,0.0023140816,0.001001654,0.0012060197,0.003207208,0.0004991454],"domain_scores_gemma":[0.98352283,0.0054643066,0.0012668663,0.006345193,0.002940688,0.0004601256],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007832369,0.0013581326,0.0016190505,0.0023978746,0.0015699861,0.009522463,0.0029263033,0.002630823,0.0030886668],"category_scores_gemma":[0.021885471,0.002770104,0.0021277466,0.0029745332,0.0016504421,0.013497482,0.008051162,0.004150956,0.0028860949],"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":[0.00086109235,0.0006406306,0.017397879,0.0018793893,0.00059257576,0.0011650346,0.0036265685,0.054556068,0.053501777,0.1500165,0.032713667,0.68304884],"study_design_scores_gemma":[0.000084105486,0.00010810085,0.0029414776,0.00048136848,0.00023919904,0.00036151885,0.0006263349,0.6980695,0.06855671,0.16425173,0.06412563,0.00015434014],"about_ca_topic_score_codex":0.00503814,"about_ca_topic_score_gemma":0.007344967,"teacher_disagreement_score":0.009522463,"about_ca_system_score_codex":0.0014956845,"about_ca_system_score_gemma":0.0028704815,"threshold_uncertainty_score":0.04142201},"labels":[],"label_agreement":null},{"id":"W1522669822","doi":"","title":"Proceedings of the Thirtieth International Conference on Very Large Data Bases, Toront, Canada, August 31-September 3, 2004","year":2004,"lang":"en","type":"book","venue":"Morgan Kaufmann eBooks","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Very large database; Endowment; Library science; Political science; Computer science; Database","score_opus":0.027357448462044933,"score_gpt":0.23920984797720063,"score_spread":0.2118523995151557,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1522669822","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0087197,0.06895276,0.11376911,0.024172008,0.05641868,0.0011482026,0.019944327,0.014931248,0.69194394],"genre_scores_gemma":[0.0047499626,0.015547689,0.011832948,0.0010147279,0.0020183276,0.00009344719,0.010979288,0.0007871122,0.9529766],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991008,0.00009612023,0.000033655666,0.0001196805,0.00053559383,0.00011411142],"domain_scores_gemma":[0.99634993,0.00027771908,0.000055282966,0.0002551193,0.0021865463,0.0008754948],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016239253,0.0011489645,0.0013510359,0.001384426,0.0020713462,0.005283293,0.0015248357,0.00095230644,0.20324676],"category_scores_gemma":[0.0028883035,0.00046539336,0.00051363494,0.0026413852,0.00093393377,0.0026560691,0.0015955172,0.002110494,0.12951253],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005577453,0.0000350327,0.00024037024,0.00008909099,0.000010044324,0.00004877102,0.000054467244,0.00014712104,0.0007098389,0.0012347162,0.9281712,0.06920371],"study_design_scores_gemma":[0.000010721229,0.000016270698,0.00072751386,0.000060585207,0.000013103357,0.00008246852,0.000083227394,0.0006077285,0.00039992377,0.00069801847,0.99728703,0.000013465902],"about_ca_topic_score_codex":0.1358829,"about_ca_topic_score_gemma":0.30111223,"teacher_disagreement_score":0.8641171,"about_ca_system_score_codex":0.0040274155,"about_ca_system_score_gemma":0.008795219,"threshold_uncertainty_score":0.6799282},"labels":[],"label_agreement":null},{"id":"W1522872673","doi":"10.5555/1357910.1358113","title":"An open issue on applying sharing modeling patterns in DEVS","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"DEVS; Formalism (music); Computer science; Component (thermodynamics); Modeling and simulation; Distributed computing; Theoretical computer science; Simulation; Physics","score_opus":0.05247596651933349,"score_gpt":0.34230464766985585,"score_spread":0.28982868115052235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1522872673","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":[0.014071564,0.00074232015,0.9444702,0.020276312,0.00049507554,0.00016864092,0.00016107643,0.0011964769,0.01841829],"genre_scores_gemma":[0.23144172,0.0015601977,0.75144905,0.004177612,0.0006328459,0.00041790403,0.0003830882,0.0015352095,0.008402308],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.96339524,0.018776525,0.0043450273,0.0032050908,0.008396657,0.0018813234],"domain_scores_gemma":[0.87493044,0.063911736,0.0037669616,0.04560942,0.009757891,0.0020235784],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.052225757,0.0009559819,0.0017168059,0.0014547553,0.0035424766,0.0117007485,0.009470563,0.0071552033,0.008180695],"category_scores_gemma":[0.07930309,0.00221519,0.0032423555,0.0029371139,0.009380973,0.043315426,0.013061568,0.009625012,0.0014850455],"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":[0.000042531316,0.000045582816,0.0012096377,0.00019416209,0.00003843758,0.00013532315,0.0013051529,0.003294183,0.0006363036,0.95720494,0.002832763,0.033061046],"study_design_scores_gemma":[0.00005161612,0.000074801654,0.00032773818,0.00043118186,0.000051755713,0.00065860973,0.0020539113,0.030977057,0.0033746278,0.79856086,0.16335782,0.000079970305],"about_ca_topic_score_codex":0.003246954,"about_ca_topic_score_gemma":0.0026417295,"teacher_disagreement_score":0.052225757,"about_ca_system_score_codex":0.002976951,"about_ca_system_score_gemma":0.0055395183,"threshold_uncertainty_score":0.27619946},"labels":[],"label_agreement":null},{"id":"W1525512896","doi":"10.1007/978-3-540-39648-2_39","title":"A Declarative XML-RL Update Language","year":2003,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":20,"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":"Programming language; XML; Computer science; Declarative programming; Linguistics; Natural language processing; World Wide Web; Philosophy","score_opus":0.012814543865592403,"score_gpt":0.25242050198801835,"score_spread":0.23960595812242594,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1525512896","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":[0.001430406,0.00016800789,0.91644484,0.0001951803,0.0001429471,0.00015288002,0.0012338682,0.07102678,0.009205108],"genre_scores_gemma":[0.05979355,0.0006776352,0.8456015,0.0010321122,0.00019913379,0.00054911256,0.009521248,0.027709527,0.054916233],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99813926,0.00031077932,0.00032057756,0.0002953665,0.00079144945,0.00014249019],"domain_scores_gemma":[0.9982316,0.00064782595,0.00010876086,0.00058653485,0.00034524366,0.00008012054],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002520049,0.0011300752,0.0010494755,0.0011157824,0.0007202152,0.0045450525,0.0044946996,0.0014390703,0.023991618],"category_scores_gemma":[0.0045277374,0.0016445387,0.0011080486,0.0012535212,0.0013795135,0.005094165,0.003074706,0.0031875416,0.014941463],"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":[0.00054844003,0.00036167313,0.0008560917,0.0011955189,0.00009400893,0.00069982704,0.001505805,0.016283194,0.03069399,0.3058151,0.14736605,0.49458042],"study_design_scores_gemma":[0.0002880995,0.00019405327,0.0003287323,0.0002938888,0.00018779577,0.0010891295,0.00026450114,0.14774151,0.07751751,0.09637331,0.6754803,0.00024120467],"about_ca_topic_score_codex":0.0029859943,"about_ca_topic_score_gemma":0.0029146885,"teacher_disagreement_score":0.023991618,"about_ca_system_score_codex":0.0007244411,"about_ca_system_score_gemma":0.0014294506,"threshold_uncertainty_score":0.08025992},"labels":[],"label_agreement":null},{"id":"W1526440997","doi":"10.1007/978-0-387-27696-0_5","title":"Optimizing Tree Pattern Queries over Secure XML Databases","year":2007,"lang":"en","type":"book-chapter","venue":"Advances in information security","topic":"Advanced Database Systems and Queries","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 British Columbia","funders":"","keywords":"Computer science; XML database; Efficient XML Interchange; Streaming XML; XML; XML Schema Editor; XML validation; XML Encryption; XML Signature; Database; Information retrieval; Document Structure Description; Representation (politics); Data exchange; World Wide Web","score_opus":0.019328933051228365,"score_gpt":0.2821673882415743,"score_spread":0.26283845519034593,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1526440997","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":[0.131628,0.0012256037,0.840974,0.00080780813,0.00013356363,0.0001924307,0.00091732887,0.014460168,0.009661086],"genre_scores_gemma":[0.48513365,0.0009694089,0.497595,0.00022657675,0.00014449861,0.00017245812,0.0028313196,0.0018432798,0.011083764],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99730206,0.00045037825,0.00024592763,0.00027380057,0.001457207,0.0002705374],"domain_scores_gemma":[0.9976609,0.0012430879,0.00013127016,0.0006227681,0.00028141882,0.000060569142],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013839931,0.0008801713,0.0012607421,0.00076155073,0.0004998096,0.0020968495,0.0016230976,0.0008912583,0.0040483833],"category_scores_gemma":[0.0046501174,0.00062329863,0.0007532358,0.0027709207,0.00067731267,0.0037640403,0.0016429487,0.0011783745,0.0013614758],"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":[0.0012447538,0.00033790336,0.003321934,0.00048208062,0.00013159205,0.00040855753,0.00048015674,0.16759668,0.035119917,0.08142095,0.036014944,0.6734405],"study_design_scores_gemma":[0.00014778857,0.0001500744,0.0006999415,0.000027012116,0.000068856796,0.00034878074,0.00018825001,0.8650064,0.029290713,0.0951066,0.008937693,0.000027837803],"about_ca_topic_score_codex":0.002758197,"about_ca_topic_score_gemma":0.0036654654,"teacher_disagreement_score":0.0040483833,"about_ca_system_score_codex":0.0010272514,"about_ca_system_score_gemma":0.00096527155,"threshold_uncertainty_score":0.013543189},"labels":[],"label_agreement":null},{"id":"W1526741618","doi":"","title":"An analytical model for buffer hit rate prediction","year":2001,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Buffer (optical fiber); IBM; Sizing; Task (project management); Markov chain; Process (computing); Data modeling; Markov process; Buffer overflow; Database; Real-time computing; Operating system; Statistics; Engineering; Machine learning; Mathematics","score_opus":0.04234769980963039,"score_gpt":0.30397515641236206,"score_spread":0.2616274566027317,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1526741618","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":[0.09395947,0.0011011616,0.89185387,0.0012891975,0.00009735401,0.00016652251,0.00077718386,0.0017657871,0.008989498],"genre_scores_gemma":[0.9120154,0.0015366536,0.07362578,0.00034377858,0.00012904256,0.0004418357,0.0007368786,0.0002813186,0.010889337],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982955,0.0004163318,0.00007780881,0.00038882854,0.0005114543,0.00031006974],"domain_scores_gemma":[0.99273175,0.004780752,0.00069948344,0.00047865816,0.0011752058,0.00013402074],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024281286,0.0009602861,0.0014045602,0.001465133,0.00055552385,0.0020330795,0.0027194123,0.0019293819,0.0027896913],"category_scores_gemma":[0.017122673,0.00090828363,0.0006500029,0.0015820791,0.000924997,0.0033754958,0.000684363,0.0014410121,0.0012997808],"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":[0.000058650407,0.000036226837,0.0012863122,0.00006244613,0.000020071982,0.00011533062,0.00010801018,0.9683108,0.0018629127,0.017659921,0.0015881337,0.0088912025],"study_design_scores_gemma":[0.0000028859786,0.0000071848,0.000092088754,0.000005170361,0.0000041119624,0.000020369624,0.000005861508,0.9972204,0.0002266752,0.0021660214,0.00024398565,0.0000053004583],"about_ca_topic_score_codex":0.0142114125,"about_ca_topic_score_gemma":0.0046840673,"teacher_disagreement_score":0.0142114125,"about_ca_system_score_codex":0.0023742963,"about_ca_system_score_gemma":0.0017528405,"threshold_uncertainty_score":0.02825737},"labels":[],"label_agreement":null},{"id":"W1528213927","doi":"10.1007/978-3-540-24655-8_101","title":"Capturing Semantic Hierarchies to Perform Meaningful Integration in HTML Tables","year":2004,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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":"Carleton University","funders":"","keywords":"Computer science; Schema (genetic algorithms); Information retrieval; Nondeterministic algorithm; Natural language processing; Normalization (sociology); Artificial intelligence; Theoretical computer science","score_opus":0.014215124770221152,"score_gpt":0.23811574985855766,"score_spread":0.2239006250883365,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1528213927","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":[0.016938452,0.0002765395,0.96050215,0.0001680786,0.00007649031,0.0001500524,0.0011636448,0.017663632,0.0030609053],"genre_scores_gemma":[0.17249122,0.00047123316,0.8126855,0.00022606284,0.000060399176,0.00018878405,0.005811219,0.0038446647,0.0042209574],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.998351,0.00022847115,0.0002221123,0.00020574419,0.00085183216,0.0001410295],"domain_scores_gemma":[0.99686337,0.0013435974,0.00017636176,0.0008786391,0.0006357333,0.00010229839],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014284538,0.0011097456,0.0008988193,0.0026839068,0.00087378186,0.004406294,0.0015630345,0.0013572773,0.00547663],"category_scores_gemma":[0.006823454,0.0012138693,0.001252718,0.0036575608,0.00088974717,0.0064891055,0.00300365,0.0015442976,0.0024583966],"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":[0.0005986398,0.0004709313,0.007679349,0.0013428353,0.00020059553,0.00097251526,0.0037977488,0.036666743,0.07796363,0.17817183,0.047293212,0.644842],"study_design_scores_gemma":[0.00011305415,0.00016213158,0.0025285447,0.00034361196,0.0003304536,0.00052286574,0.0012108724,0.52802944,0.17256238,0.19775528,0.096286885,0.00015451048],"about_ca_topic_score_codex":0.003449466,"about_ca_topic_score_gemma":0.007186215,"teacher_disagreement_score":0.00547663,"about_ca_system_score_codex":0.0006618094,"about_ca_system_score_gemma":0.0009605592,"threshold_uncertainty_score":0.018321157},"labels":[],"label_agreement":null},{"id":"W1529320414","doi":"","title":"MDL summarization with holes","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Automatic summarization; Heuristics; Computer science; Greedy algorithm; Minimum description length; Dynamic programming; Theoretical computer science; Mathematical optimization; Algorithm; Mathematics; Artificial intelligence","score_opus":0.006758488811433875,"score_gpt":0.20848154628205648,"score_spread":0.2017230574706226,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1529320414","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":[0.021861812,0.0010342648,0.96824104,0.00081715547,0.00008172026,0.00018349326,0.00095871167,0.003020792,0.0038010976],"genre_scores_gemma":[0.31357366,0.00064962415,0.67712414,0.00036258617,0.00013462726,0.00026099742,0.0025068934,0.0004598205,0.004927587],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983119,0.00043603836,0.00022299714,0.0003289862,0.000549664,0.00015043409],"domain_scores_gemma":[0.99588627,0.0019202963,0.0004848072,0.0008902872,0.00068498973,0.0001333211],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019483374,0.0006853424,0.0011676418,0.0015255793,0.0007599754,0.0020448412,0.0011883706,0.0008400829,0.0036582819],"category_scores_gemma":[0.00864524,0.00040378247,0.00074693706,0.002186219,0.0007290658,0.0037490379,0.0019424149,0.001000984,0.0008833745],"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":[0.000690443,0.00019063843,0.0018263288,0.0010165463,0.00011200623,0.00055148196,0.0007767569,0.21164228,0.015914634,0.1152349,0.026799008,0.62524486],"study_design_scores_gemma":[0.00010466899,0.00025105072,0.00051445345,0.000081371974,0.000075027536,0.00038854248,0.0002998674,0.8325545,0.020802649,0.11017148,0.03470895,0.000047469784],"about_ca_topic_score_codex":0.001468312,"about_ca_topic_score_gemma":0.0017403201,"teacher_disagreement_score":0.0036582819,"about_ca_system_score_codex":0.0011152262,"about_ca_system_score_gemma":0.0011965892,"threshold_uncertainty_score":0.0122382045},"labels":[],"label_agreement":null},{"id":"W1531908099","doi":"10.17705/1jais.00233","title":"A New Design for Open and Scalable Collaboration of Independent Databases in Digitally Connected Enterprises","year":2010,"lang":"en","type":"article","venue":"Journal of the Association for Information Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Computer science; Interoperation; Supply chain; Flexibility (engineering); Scalability; Database; Information sharing; Knowledge management; Business; Interoperability; World Wide Web","score_opus":0.01995403178683136,"score_gpt":0.2770854317570992,"score_spread":0.25713139997026785,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1531908099","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":[0.02164276,0.00013632732,0.96940696,0.0006081149,0.00008470304,0.0002522279,0.00003399114,0.0011641211,0.0066707707],"genre_scores_gemma":[0.34619278,0.00023854659,0.64250845,0.00048548658,0.000097727076,0.0006083094,0.00014012623,0.00015998706,0.009568614],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9962064,0.0010164161,0.00044220279,0.0009204764,0.0011461054,0.00026832466],"domain_scores_gemma":[0.99657553,0.00070513814,0.00034414965,0.0012575967,0.000739499,0.0003779467],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029792236,0.00040220236,0.00047420454,0.0007436285,0.0013464054,0.0040449086,0.0024756878,0.0016804928,0.0030292792],"category_scores_gemma":[0.005699302,0.0007295913,0.0006817754,0.00085573795,0.0017824841,0.007528609,0.005206969,0.0015447977,0.0008137407],"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":[0.00064709864,0.00058648287,0.0039888974,0.0006272912,0.00016792779,0.0009519012,0.0046674334,0.04236517,0.07155994,0.5584512,0.008892556,0.30709416],"study_design_scores_gemma":[0.00057349086,0.0016152414,0.0017969484,0.00022966745,0.0004267447,0.0030463638,0.0013582433,0.45841947,0.07068687,0.23195803,0.22967689,0.00021202373],"about_ca_topic_score_codex":0.0007045812,"about_ca_topic_score_gemma":0.0008000595,"teacher_disagreement_score":0.0040449086,"about_ca_system_score_codex":0.0010878232,"about_ca_system_score_gemma":0.0015854903,"threshold_uncertainty_score":0.015755832},"labels":[],"label_agreement":null},{"id":"W1533605675","doi":"10.1023/a:1008736910058","title":"Partial Evaluation of Views","year":2001,"lang":"en","type":"article","venue":"Journal of Intelligent Information Systems","topic":"Advanced Database Systems and Queries","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":"York University","funders":"","keywords":"Computer science; Tuple; Query optimization; Materialized view; Information retrieval; Spatial query; Query language; Web query classification; Web search query; Sargable; Data warehouse; View; Database; Data mining; Theoretical computer science; Search engine; Database design","score_opus":0.08159113884016463,"score_gpt":0.3311095683310115,"score_spread":0.2495184294908469,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1533605675","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":[0.15751475,0.007690447,0.7396354,0.0026938466,0.00092417916,0.00043625978,0.005571377,0.00815681,0.077376924],"genre_scores_gemma":[0.75747347,0.0020872476,0.20247105,0.0005314723,0.00053154276,0.00016633762,0.00688402,0.0014253895,0.028429434],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9936678,0.001728533,0.00041417588,0.0007766302,0.0028940882,0.0005188377],"domain_scores_gemma":[0.9844775,0.004816166,0.0004394524,0.0065090586,0.00336352,0.0003941828],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037539655,0.00087376096,0.0013161962,0.0017673908,0.00081575103,0.004667271,0.00159848,0.0010705201,0.017664392],"category_scores_gemma":[0.016803458,0.00070611684,0.0013674052,0.0020192128,0.0013419765,0.00966284,0.0033260917,0.0014923583,0.002492078],"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":[0.0018658366,0.0002325636,0.0067458902,0.0009531261,0.00046229493,0.0005590335,0.0009074874,0.019752838,0.020924706,0.3690465,0.033203907,0.54534584],"study_design_scores_gemma":[0.00019464368,0.0005776476,0.0036805281,0.0003538446,0.00068435946,0.0009659561,0.00076850597,0.17980383,0.056478903,0.64081424,0.1155333,0.00014431607],"about_ca_topic_score_codex":0.0020569654,"about_ca_topic_score_gemma":0.0031194568,"teacher_disagreement_score":0.017664392,"about_ca_system_score_codex":0.0011497145,"about_ca_system_score_gemma":0.0013551151,"threshold_uncertainty_score":0.059093297},"labels":[],"label_agreement":null},{"id":"W1533768523","doi":"10.1109/wcre.1996.558889","title":"Reverse engineering a medical database","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; Reverse engineering; Variety (cybernetics); Relational database; Database; Database design; Data science; Software engineering; Artificial intelligence","score_opus":0.01612089944636406,"score_gpt":0.214473635856314,"score_spread":0.19835273640994994,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1533768523","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":[0.013398863,0.0016049781,0.972326,0.0034009658,0.00039351603,0.00040164308,0.00066129345,0.0022983903,0.005514453],"genre_scores_gemma":[0.072363056,0.0021113725,0.9170039,0.001559902,0.00012948386,0.0001618002,0.0015909277,0.00029880105,0.0047806436],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9932683,0.002160603,0.0005005493,0.0006814887,0.003190758,0.00019837126],"domain_scores_gemma":[0.9730521,0.010663088,0.0011276877,0.010223066,0.004636351,0.00029768544],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009078231,0.0006245313,0.0007668191,0.0031208938,0.0011395639,0.004113794,0.0023751503,0.001433827,0.0035055017],"category_scores_gemma":[0.029200954,0.00087328366,0.0015914235,0.0025881382,0.0013554972,0.0051864493,0.0034213285,0.0032739795,0.0019445765],"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":[0.00025753424,0.0002764999,0.004596494,0.0010723647,0.00017907414,0.0026663083,0.0015241811,0.02442994,0.024439912,0.1539853,0.020844107,0.76572824],"study_design_scores_gemma":[0.00012072049,0.000543322,0.0015939932,0.00088525075,0.00038215867,0.013066655,0.0013523657,0.19048348,0.07475552,0.14536507,0.5712732,0.00017819193],"about_ca_topic_score_codex":0.0030922105,"about_ca_topic_score_gemma":0.003757646,"teacher_disagreement_score":0.009078231,"about_ca_system_score_codex":0.0014545773,"about_ca_system_score_gemma":0.0039873533,"threshold_uncertainty_score":0.048010886},"labels":[],"label_agreement":null},{"id":"W1533886078","doi":"10.1007/978-3-540-74553-2_1","title":"A Hilbert Space Compression Architecture for Data Warehouse Environments","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":17,"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; Tuple; Data warehouse; Relational database; Compression (physics); Data compression; Exploit; Data mining; Database; Memory footprint; Volume (thermodynamics); Hilbert curve; Theoretical computer science; Algorithm; Mathematics; Programming language","score_opus":0.04023864711103215,"score_gpt":0.2834590318157358,"score_spread":0.24322038470470364,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1533886078","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":[0.01712398,0.0007324604,0.9638306,0.00040971072,0.00010670563,0.000084161526,0.00029996195,0.014398579,0.0030138409],"genre_scores_gemma":[0.29105347,0.0008082762,0.6914457,0.00057449465,0.00022207604,0.00024370739,0.002035669,0.00088764494,0.012728979],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99937326,0.0001066877,0.000058469188,0.000081761,0.0003025727,0.00007723506],"domain_scores_gemma":[0.9991704,0.00015350014,0.00003371352,0.00031499696,0.0002741992,0.00005323188],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00078767195,0.000584981,0.0006882813,0.0010048127,0.0006378915,0.0016657462,0.0026303476,0.00078692543,0.006739651],"category_scores_gemma":[0.0016658384,0.00046158602,0.00047832006,0.0021460587,0.00065374986,0.0040384745,0.0021195374,0.0011826656,0.0023351682],"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":[0.0011441926,0.0003275295,0.0012489675,0.0002589023,0.00011614405,0.00022434413,0.00036931224,0.049590558,0.04190455,0.086134836,0.0448703,0.77381027],"study_design_scores_gemma":[0.00012465726,0.00030461434,0.00065615907,0.00004442202,0.000093509036,0.00036930604,0.00013841489,0.8125742,0.05941807,0.097207434,0.02897843,0.00009085005],"about_ca_topic_score_codex":0.0025746978,"about_ca_topic_score_gemma":0.0027798142,"teacher_disagreement_score":0.006739651,"about_ca_system_score_codex":0.0007738475,"about_ca_system_score_gemma":0.00095263415,"threshold_uncertainty_score":0.022546351},"labels":[],"label_agreement":null},{"id":"W1536826708","doi":"10.1007/978-0-387-39940-9","title":"Encyclopedia of Database Systems","year":2009,"lang":"en","type":"book","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1737,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Lawrence Livermore National Laboratory; National Institutes of Health; Jacobs University; Masarykova Univerzita; Universität Konstanz; Libera Università di Bolzano; Universidad de Castilla-La Mancha; Università di Bologna; Universidad de Chile; Technische Universität Darmstadt; China Scholarship Council; École Polytechnique Fédérale de Lausanne; Indian Institute of Technology Kanpur; Yale University; University of Toronto; Foundation for Research and Technology-Hellas; Eidgenössische Technische Hochschule Zürich; National University of Singapore; University of Alberta; Tampereen Yliopisto; Università degli Studi di Milano; Institut national de recherche en informatique et en automatique (INRIA); University of Patras; Drexel University; University of Notre Dame; Vrije Universiteit Amsterdam; University of Southern California; Purdue University; Google; University of Washington; Technische Universiteit Eindhoven; Università degli Studi di Firenze; Brown University; Arizona State University; Microsoft Research; Microsoft","keywords":"Encyclopedia; Computer science; Database; Information retrieval; World Wide Web; Library science","score_opus":0.01269069514839712,"score_gpt":0.23548840151582215,"score_spread":0.22279770636742502,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1536826708","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007817193,0.1323513,0.07262238,0.0071134316,0.022375604,0.0005407421,0.010975858,0.010310471,0.7429284],"genre_scores_gemma":[0.002798102,0.06313288,0.023945298,0.0037898363,0.0051108515,0.00040760942,0.009153566,0.0023541686,0.8893077],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99806446,0.00021751631,0.00020967794,0.0003265827,0.0010677854,0.00011392382],"domain_scores_gemma":[0.99715674,0.0006124324,0.00014517122,0.00065395964,0.0011250345,0.00030674832],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010559915,0.0023716784,0.0032898306,0.0072176666,0.0012999795,0.008762513,0.0027233956,0.0013418116,0.214366],"category_scores_gemma":[0.0049723815,0.0010836058,0.0009169622,0.014285364,0.0012861694,0.006541034,0.0034027935,0.003877011,0.21856116],"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":[0.000014370568,0.000029862991,0.00007500999,0.0005017699,0.000012199122,0.00003884641,0.000058066915,0.00018476663,0.00039035716,0.0155368345,0.8144605,0.16869736],"study_design_scores_gemma":[0.000003941571,0.0000051140537,0.000082159924,0.00013435123,0.0000056257977,0.00010877541,0.00001826705,0.00012634318,0.000059137576,0.0037841622,0.99566674,0.0000053775093],"about_ca_topic_score_codex":0.0029061812,"about_ca_topic_score_gemma":0.003497763,"teacher_disagreement_score":0.214366,"about_ca_system_score_codex":0.0023542172,"about_ca_system_score_gemma":0.00419847,"threshold_uncertainty_score":0.7171257},"labels":[],"label_agreement":null},{"id":"W1538527648","doi":"10.20381/ruor-4427","title":"Collaborative Web-Based Mapping of Real-Time Sensor Data","year":2011,"lang":"en","type":"dissertation","venue":"Library and Archives Canada (Government of Canada)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Sensor web; Web application; Real-time computing; World Wide Web; Data science; Database; Operating system; Key distribution in wireless sensor networks","score_opus":0.007000315042363244,"score_gpt":0.17584609777799284,"score_spread":0.1688457827356296,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1538527648","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":[0.051014077,0.00039563494,0.8895343,0.0005344073,0.00016469837,0.0003382117,0.00048215626,0.025887026,0.031649522],"genre_scores_gemma":[0.50017124,0.000799625,0.45561028,0.0002662373,0.000096098134,0.00037354865,0.0020211034,0.0011797316,0.03948211],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9983615,0.00035292195,0.000095439624,0.00026932682,0.00079914887,0.00012161875],"domain_scores_gemma":[0.9972339,0.00064731645,0.00011108344,0.001149684,0.00067825924,0.00017981509],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018254643,0.0005667844,0.0007240846,0.0016856503,0.0010505164,0.0038977892,0.0018089474,0.0011037923,0.004441697],"category_scores_gemma":[0.0035120922,0.00041285716,0.00065886066,0.0021636002,0.0007704716,0.0033823943,0.002487914,0.0008872984,0.0025679753],"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":[0.0009675724,0.0012520446,0.007947183,0.0005800445,0.0002565453,0.002070789,0.0042111557,0.08343912,0.057273407,0.052248012,0.03447215,0.755282],"study_design_scores_gemma":[0.00014084647,0.00020946092,0.006748482,0.00011707592,0.00012359385,0.00089336466,0.001441822,0.7102972,0.093660295,0.036385987,0.14980642,0.00017538207],"about_ca_topic_score_codex":0.008051207,"about_ca_topic_score_gemma":0.009131369,"teacher_disagreement_score":0.008051207,"about_ca_system_score_codex":0.00062637596,"about_ca_system_score_gemma":0.0015678297,"threshold_uncertainty_score":0.016008735},"labels":[],"label_agreement":null},{"id":"W1538704367","doi":"10.1007/978-0-387-39940-9_1531","title":"Temporal Relational Calculus","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","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 Waterloo","funders":"","keywords":"Calculus (dental); Computer science; Medicine","score_opus":0.01929975933781691,"score_gpt":0.237105269253554,"score_spread":0.21780550991573708,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1538704367","genre_codex":"other","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":[0.0023480551,0.026668662,0.37118855,0.0028180142,0.0014293257,0.00011939473,0.0012365076,0.0019139984,0.5922775],"genre_scores_gemma":[0.1522495,0.038186934,0.26498517,0.0026063821,0.00288176,0.00034323984,0.0041801413,0.0013255551,0.5332414],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9994135,0.000097558426,0.000041902495,0.00013601616,0.00027066917,0.000040319876],"domain_scores_gemma":[0.9996183,0.00014772525,0.000019206893,0.00008134366,0.00010847544,0.000024992405],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007201394,0.0008298054,0.0006914654,0.0013543094,0.0011296495,0.0041204705,0.0011935971,0.00070184126,0.023273328],"category_scores_gemma":[0.001496508,0.00050276425,0.0007180845,0.0023207865,0.0021757,0.004323947,0.0011566355,0.0021894106,0.009272143],"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":[0.000011800046,0.0000142047165,0.000048577927,0.000099768826,0.0000068882055,0.00004660564,0.00017397254,0.00040160678,0.0005575933,0.9240495,0.027338251,0.04725132],"study_design_scores_gemma":[0.00000842015,0.000008340645,0.000092264214,0.00006839077,0.00001464932,0.00017287732,0.0000429561,0.0014841997,0.0005817758,0.65353113,0.34398544,0.000009629263],"about_ca_topic_score_codex":0.0022020661,"about_ca_topic_score_gemma":0.0016887047,"teacher_disagreement_score":0.023273328,"about_ca_system_score_codex":0.0016286295,"about_ca_system_score_gemma":0.0012783965,"threshold_uncertainty_score":0.07785702},"labels":[],"label_agreement":null},{"id":"W1538798823","doi":"10.1007/11901181_49","title":"Auto-completion of Underspecified SQL Queries","year":2006,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Computer science; Stored procedure; SQL; SQL/PSM; PL/SQL; Query by Example; Joins; SQL injection; Language Integrated Query; Programming language; Data definition language; Database; Data Transformation Services; Information retrieval; Web search query; Search engine","score_opus":0.02050467328655909,"score_gpt":0.24317446881437982,"score_spread":0.22266979552782074,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1538798823","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":[0.07705099,0.0005479701,0.894507,0.00018950006,0.0001531653,0.000127839,0.0005648461,0.018990243,0.007868358],"genre_scores_gemma":[0.46143472,0.0005578534,0.5088756,0.00033205198,0.000299029,0.00014556694,0.004488655,0.0051974277,0.018669046],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99417734,0.0010421078,0.00049368845,0.0009413403,0.0028515835,0.0004938987],"domain_scores_gemma":[0.9873438,0.004216203,0.000580578,0.0049019996,0.0026843862,0.000273065],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035505279,0.0009437293,0.0014425555,0.0010739549,0.0006547771,0.001999827,0.0016764698,0.00063255633,0.0043956344],"category_scores_gemma":[0.008760332,0.0010957103,0.0016731094,0.0010984349,0.0013314913,0.00390746,0.0026602244,0.002202717,0.0022284396],"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":[0.0014310315,0.0006141457,0.0048675933,0.0011057395,0.00019588397,0.0013213642,0.0022501268,0.06295007,0.06699618,0.2035524,0.034757104,0.61995834],"study_design_scores_gemma":[0.00012330442,0.0003506617,0.0022531687,0.00015255074,0.00018265615,0.0014394997,0.0004554904,0.48476908,0.15211059,0.29554006,0.062452856,0.0001700652],"about_ca_topic_score_codex":0.0020139108,"about_ca_topic_score_gemma":0.0023464686,"teacher_disagreement_score":0.0043956344,"about_ca_system_score_codex":0.0006244117,"about_ca_system_score_gemma":0.0012528374,"threshold_uncertainty_score":0.018777192},"labels":[],"label_agreement":null},{"id":"W1539153042","doi":"10.14778/2831360.2831367","title":"S-Store","year":2015,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":82,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"National Science Foundation","keywords":"Online transaction processing; Computer science; Stream processing; Transaction processing; Distributed transaction; Database; Database transaction; Correctness; Operating system; Programming language","score_opus":0.02531497744140868,"score_gpt":0.22789163883845423,"score_spread":0.20257666139704555,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1539153042","genre_codex":"software","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":"software","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.027662832,0.0030029637,0.3359903,0.0020863006,0.0014913538,0.0014781007,0.0349041,0.43129197,0.16209215],"genre_scores_gemma":[0.27307147,0.004173631,0.30961448,0.004615123,0.0011017997,0.0012215995,0.14417894,0.045960087,0.21606281],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99775463,0.000178919,0.00027338148,0.0004907149,0.00097177684,0.00033070578],"domain_scores_gemma":[0.9937782,0.00093644595,0.00029595202,0.0025323234,0.001979575,0.00047748405],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016781858,0.0016451676,0.0012639939,0.0018851837,0.0012404746,0.0057783173,0.006863098,0.001519828,0.07205056],"category_scores_gemma":[0.00720215,0.0012476494,0.0012970676,0.0024547414,0.0010240742,0.009809266,0.0062142,0.0025710845,0.045749217],"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":[0.0031810165,0.0005456772,0.0068908758,0.0019173797,0.00035602125,0.00070042355,0.0007807652,0.0063967165,0.01978284,0.08858516,0.58031815,0.290545],"study_design_scores_gemma":[0.00044908028,0.0004507771,0.0018833578,0.00024178863,0.0002097395,0.0010877039,0.00040575798,0.055743035,0.039884303,0.04018129,0.85923725,0.00022591728],"about_ca_topic_score_codex":0.0048176586,"about_ca_topic_score_gemma":0.0049220314,"teacher_disagreement_score":0.07205056,"about_ca_system_score_codex":0.0011348482,"about_ca_system_score_gemma":0.0029119982,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W1539415337","doi":"10.1109/ccece.1999.807227","title":"Design issues for a trusted electronic document management system","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Computer science; Metadata; Database; Component (thermodynamics); Document management system; Database design; Homogeneous; World Wide Web","score_opus":0.0149448898279505,"score_gpt":0.25902625630008935,"score_spread":0.24408136647213885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1539415337","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":[0.022597369,0.0017541946,0.9336298,0.0050866473,0.00037636832,0.00045554835,0.00006288198,0.0026447517,0.033392407],"genre_scores_gemma":[0.39802516,0.0018481384,0.5709849,0.0014157553,0.0005559041,0.0008107397,0.00020172249,0.00049324334,0.02566441],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9936659,0.0016457458,0.0005931902,0.00045418012,0.0032262097,0.00041473514],"domain_scores_gemma":[0.99505085,0.0012352844,0.0004536587,0.0010340394,0.001873227,0.0003530386],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0044405395,0.00035287632,0.00051330315,0.0007756323,0.0020110435,0.005282729,0.0015956189,0.0022233792,0.0048859455],"category_scores_gemma":[0.010759741,0.0007677284,0.00045657938,0.00064779574,0.0014589806,0.0053173755,0.002397739,0.0019666408,0.00367145],"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":[0.0005455434,0.00016135153,0.002162802,0.00095109345,0.0000772155,0.0012000358,0.0020244243,0.022586478,0.041955464,0.6526465,0.01820279,0.2574864],"study_design_scores_gemma":[0.0003838703,0.0007529181,0.0010459635,0.0008072118,0.0002460566,0.003668123,0.001111344,0.1885881,0.06486937,0.16741952,0.57093924,0.00016832267],"about_ca_topic_score_codex":0.00081751787,"about_ca_topic_score_gemma":0.0007448672,"teacher_disagreement_score":0.005282729,"about_ca_system_score_codex":0.001309216,"about_ca_system_score_gemma":0.002230594,"threshold_uncertainty_score":0.02348411},"labels":[],"label_agreement":null},{"id":"W1540277706","doi":"10.1109/icde.1994.283001","title":"Performing group-by before join [query processing]","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Joins; Computer science; SQL; Null (SQL); Group (periodic table); Semantics (computer science); Join (topology); Query optimization; Transformation (genetics); Theoretical computer science; Database; Information retrieval; Programming language; Mathematics; Combinatorics","score_opus":0.01338241844144647,"score_gpt":0.21472433094693552,"score_spread":0.20134191250548905,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1540277706","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":[0.007537669,0.00017120701,0.9462899,0.00092759356,0.0001382865,0.0007873266,0.0014247678,0.031360317,0.011362957],"genre_scores_gemma":[0.11380153,0.00030200498,0.8691029,0.0009466696,0.000108475615,0.00031718623,0.00460167,0.0035230988,0.007296463],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99420655,0.0010786796,0.00044298358,0.0014084791,0.0020972465,0.0007661052],"domain_scores_gemma":[0.9930682,0.0021990477,0.00048550018,0.0030955607,0.0009693917,0.00018224548],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004323212,0.0014907782,0.0012658981,0.0008444513,0.0015807714,0.0034773133,0.0044247448,0.002227865,0.022208476],"category_scores_gemma":[0.012402075,0.0008925399,0.0013611134,0.0016085681,0.002109785,0.006460949,0.0028895605,0.0015180468,0.014263277],"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":[0.0014394397,0.00062275905,0.0058873063,0.001151202,0.00021132671,0.0013165678,0.0015178617,0.020853132,0.038861703,0.2333695,0.2219472,0.47282204],"study_design_scores_gemma":[0.0003476599,0.0005223786,0.0024059443,0.00019452338,0.00014293435,0.0025572814,0.0005900244,0.36190757,0.090247266,0.24454556,0.296276,0.00026288346],"about_ca_topic_score_codex":0.0042554233,"about_ca_topic_score_gemma":0.003451691,"teacher_disagreement_score":0.022208476,"about_ca_system_score_codex":0.0009414514,"about_ca_system_score_gemma":0.002056062,"threshold_uncertainty_score":0.074294746},"labels":[],"label_agreement":null},{"id":"W1541476024","doi":"","title":"Consistent query answering under inclusion dependencies","year":2004,"lang":"en","type":"article","venue":"Conference of the Centre for Advanced Studies on Collaborative Research","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Decidability; Set (abstract data type); Query language; Semantics (computer science); Data integrity; Null (SQL); Database; Information retrieval; Query optimization; Theoretical computer science; Programming language","score_opus":0.13238244842112423,"score_gpt":0.40081471930346296,"score_spread":0.26843227088233873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1541476024","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":[0.08831685,0.00026593567,0.9014529,0.0019998876,0.00003429771,0.00019075075,0.00032465655,0.0024379867,0.0049767117],"genre_scores_gemma":[0.6298337,0.00040869828,0.36202434,0.001016384,0.00018289992,0.0003369564,0.0013994979,0.00046328988,0.004334211],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9844662,0.005842837,0.0011181475,0.002146558,0.004898644,0.0015276134],"domain_scores_gemma":[0.9639603,0.026800564,0.001643334,0.0033744923,0.0037624077,0.00045895737],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009616793,0.0006292762,0.0013030805,0.0011392088,0.0013128939,0.004566736,0.0027245602,0.0019585572,0.002721829],"category_scores_gemma":[0.03058653,0.0012064363,0.0015804379,0.0020461816,0.002939932,0.008351189,0.0043767164,0.0027924783,0.00047307718],"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":[0.0013765442,0.0007476273,0.0069554667,0.0010390999,0.0003586115,0.0019371477,0.004945713,0.14263476,0.029498013,0.6128139,0.010714641,0.18697855],"study_design_scores_gemma":[0.00026708707,0.0001682885,0.0005902654,0.00005301461,0.00022952526,0.00051140576,0.0008550737,0.5297808,0.021813411,0.43872413,0.0069421297,0.00006481772],"about_ca_topic_score_codex":0.0063321674,"about_ca_topic_score_gemma":0.0044762585,"teacher_disagreement_score":0.009616793,"about_ca_system_score_codex":0.0021433756,"about_ca_system_score_gemma":0.0029291417,"threshold_uncertainty_score":0.050859094},"labels":[],"label_agreement":null},{"id":"W1542320810","doi":"","title":"Utilizing histogram information","year":2001,"lang":"en","type":"article","venue":"Conference of the Centre for Advanced Studies on Collaborative Research","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Histogram; Computer science; Quantile; Data mining; Oracle; Value (mathematics); Pattern recognition (psychology); Artificial intelligence; Mathematics; Statistics; Image (mathematics); Machine learning","score_opus":0.13561771433857447,"score_gpt":0.40625728388316035,"score_spread":0.2706395695445859,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1542320810","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":[0.067348085,0.0014425723,0.91487294,0.00037114677,0.000115100374,0.00016226586,0.0023669093,0.005658371,0.0076625585],"genre_scores_gemma":[0.7590819,0.0012536466,0.23283176,0.00027986872,0.00026629778,0.000121523466,0.0041139196,0.00064524036,0.0014058336],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975061,0.00055209285,0.00013550498,0.00044696074,0.0011031012,0.00025613687],"domain_scores_gemma":[0.97907937,0.013115554,0.0013235266,0.0031624858,0.0029721502,0.00034693565],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003051877,0.0007641867,0.0009398311,0.005667613,0.0006546929,0.0032658128,0.0013373226,0.0010444596,0.0041929535],"category_scores_gemma":[0.027656218,0.0006076692,0.00069437793,0.0068552536,0.00080108107,0.005839562,0.0018039535,0.00093339203,0.0012298656],"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":[0.0010732941,0.0002669343,0.037449732,0.00069013715,0.0003695308,0.00020513871,0.0006180302,0.122242466,0.023067607,0.029156014,0.012805151,0.77205586],"study_design_scores_gemma":[0.00013996559,0.00044505709,0.04969019,0.00019334252,0.00040755022,0.0011508069,0.00062887673,0.78396654,0.048507478,0.08546301,0.028918402,0.00048891525],"about_ca_topic_score_codex":0.0054047056,"about_ca_topic_score_gemma":0.0051124874,"teacher_disagreement_score":0.005667613,"about_ca_system_score_codex":0.0010877273,"about_ca_system_score_gemma":0.0008645444,"threshold_uncertainty_score":0.016140044},"labels":[],"label_agreement":null},{"id":"W1542362256","doi":"10.1007/978-3-540-88594-8_10","title":"A Top-Down Approach to Rewriting Conjunctive Queries Using Views","year":2008,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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":"Concordia University","funders":"","keywords":"Rewriting; Computer science; Conjunctive query; Context (archaeology); Graph; Theoretical computer science; Top-down and bottom-up design; Query language; Information retrieval; Programming language; Relational database","score_opus":0.043135234032639594,"score_gpt":0.27193436959338396,"score_spread":0.22879913556074438,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1542362256","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":[0.0019994788,0.0002776355,0.991795,0.00018562381,0.00011877204,0.00012743025,0.0002377586,0.002826336,0.0024319992],"genre_scores_gemma":[0.047529295,0.00046895104,0.94263685,0.0003995353,0.00014354794,0.00014749417,0.0010553421,0.0013927196,0.0062262933],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9941203,0.0012618286,0.0006737149,0.00096669584,0.0025988407,0.00037859892],"domain_scores_gemma":[0.9938545,0.0025444706,0.00016183314,0.0020831334,0.0012059828,0.00015012336],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002474733,0.0013012649,0.0017925543,0.0016983415,0.0013822266,0.0039804564,0.0037323853,0.0016566499,0.0070879767],"category_scores_gemma":[0.007477392,0.0016382891,0.0044398564,0.0024080903,0.0025700699,0.005480166,0.0040494218,0.004635811,0.0029071523],"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":[0.0003645803,0.0003460375,0.00082932686,0.0010382714,0.00040122602,0.0009792536,0.001868573,0.028321313,0.057967123,0.30839506,0.031298872,0.56819034],"study_design_scores_gemma":[0.00012950548,0.00027222658,0.00047098656,0.00017713866,0.00067563256,0.0011328195,0.00052717514,0.26553115,0.08562792,0.5573736,0.087799564,0.00028237436],"about_ca_topic_score_codex":0.0063560456,"about_ca_topic_score_gemma":0.009100994,"teacher_disagreement_score":0.0070879767,"about_ca_system_score_codex":0.0012009317,"about_ca_system_score_gemma":0.0014571609,"threshold_uncertainty_score":0.023711622},"labels":[],"label_agreement":null},{"id":"W1542792433","doi":"","title":"ConQuer: a system for efficient querying over inconsistent databases","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; SQL; Scalability; Consistency (knowledge bases); Database; Set (abstract data type); Rewriting; Data integrity; Divide and conquer algorithms; Key (lock); Deductive database; Query by Example; Query language; Information retrieval; Programming language; Web search query; Search engine; Operating system; Artificial intelligence","score_opus":0.026291324520922053,"score_gpt":0.2773316556387543,"score_spread":0.25104033111783225,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1542792433","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":[0.008912302,0.0009811729,0.7804989,0.0009850714,0.00022583468,0.0004958959,0.0034462272,0.19646066,0.007993889],"genre_scores_gemma":[0.13503225,0.0015926776,0.79909587,0.0020611032,0.0003950945,0.0010967744,0.02464504,0.01693398,0.01914724],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9939395,0.0012575486,0.0005815433,0.001023326,0.0027915318,0.00040652178],"domain_scores_gemma":[0.9937236,0.0020254073,0.00045166054,0.002397716,0.0011479798,0.00025356625],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004941904,0.0015692769,0.0017956422,0.0019944173,0.0015960132,0.0038926809,0.0054793945,0.0020458612,0.0129457405],"category_scores_gemma":[0.0147243105,0.0012862515,0.0010847832,0.0026721405,0.0018014052,0.008465095,0.006261625,0.003107352,0.004712083],"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":[0.003194874,0.00039835868,0.00644096,0.0013304988,0.0004357679,0.001765269,0.0013569385,0.016226495,0.03785557,0.08940677,0.3548657,0.48672274],"study_design_scores_gemma":[0.0012654528,0.00034922516,0.002114286,0.00024100523,0.00030438643,0.0024641082,0.00055556075,0.45312494,0.07784479,0.10731917,0.35406026,0.00035683403],"about_ca_topic_score_codex":0.0058165393,"about_ca_topic_score_gemma":0.0060841595,"teacher_disagreement_score":0.0129457405,"about_ca_system_score_codex":0.0010324523,"about_ca_system_score_gemma":0.0028370519,"threshold_uncertainty_score":0.04330784},"labels":[],"label_agreement":null},{"id":"W1543636397","doi":"10.3233/fi-2018-1627","title":"Anatomy of the Chase","year":2018,"lang":"en","type":"preprint","venue":"Fundamenta Informaticae","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Chase; Undecidable problem; Computer science; Completeness (order theory); Set (abstract data type); Theoretical computer science; Algorithm; Mathematics; Programming language","score_opus":0.018567064667733963,"score_gpt":0.2900648519673199,"score_spread":0.27149778729958596,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1543636397","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":[0.0151896505,0.0030361675,0.8004274,0.0071738786,0.00054217264,0.00035215038,0.00042209952,0.001199123,0.17165728],"genre_scores_gemma":[0.4939071,0.005845027,0.40405858,0.00419244,0.0012282382,0.0015803676,0.0016288755,0.002204211,0.085355125],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9919606,0.002602515,0.0006632608,0.0019340712,0.001965877,0.0008736193],"domain_scores_gemma":[0.98114955,0.011223564,0.00086726167,0.0033570286,0.002692556,0.00070998824],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0065830825,0.0009476385,0.0012476316,0.0038051067,0.0055432315,0.007756538,0.0031423222,0.0046540145,0.022038696],"category_scores_gemma":[0.026786495,0.0014418892,0.002824573,0.00329205,0.01505859,0.01937492,0.0087899,0.009484011,0.006774251],"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":[0.00002003108,0.000010828611,0.00015768067,0.000048908812,0.000007719687,0.000077658784,0.0003269351,0.0006710801,0.0002553276,0.99016905,0.0015764361,0.0066783517],"study_design_scores_gemma":[0.000020015063,0.000034956294,0.00013238682,0.0000769176,0.000015286543,0.0002436725,0.00012375129,0.0062530497,0.0007016356,0.94988453,0.042487286,0.00002652521],"about_ca_topic_score_codex":0.0040448895,"about_ca_topic_score_gemma":0.0023802558,"teacher_disagreement_score":0.022038696,"about_ca_system_score_codex":0.0040179417,"about_ca_system_score_gemma":0.0039234348,"threshold_uncertainty_score":0.07372677},"labels":[],"label_agreement":null},{"id":"W1546338010","doi":"10.1007/11527695_24","title":"UBCSAT: An Implementation and Experimentation Environment for SLS Algorithms for SAT and MAX-SAT","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":166,"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 British Columbia","funders":"","keywords":"Implementation; Computer science; Algorithm; Parallel computing; Theoretical computer science; Programming language","score_opus":0.027692267524924458,"score_gpt":0.3104371693902008,"score_spread":0.28274490186527634,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1546338010","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":[0.021752778,0.00044835417,0.46281317,0.0006076921,0.0005038567,0.00092598994,0.01390001,0.45617834,0.042869795],"genre_scores_gemma":[0.13923663,0.0003664998,0.7588736,0.0007114378,0.00009633582,0.0024614867,0.03174194,0.051851522,0.014660652],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9944734,0.0022976622,0.00052104006,0.0007613308,0.0014523722,0.000494259],"domain_scores_gemma":[0.9890205,0.0064388765,0.00028129705,0.0022594437,0.0016981055,0.00030173184],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0044743656,0.002144305,0.0010397285,0.0024327647,0.0014024497,0.0021502983,0.005378287,0.0013942071,0.057359446],"category_scores_gemma":[0.0136817675,0.0017677516,0.0018258952,0.0030376704,0.0010001808,0.004285318,0.0021886306,0.0032099201,0.018320477],"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":[0.004696257,0.0027232207,0.005144092,0.0025817284,0.00035199177,0.00026916852,0.0009283734,0.0556675,0.019156031,0.043190032,0.46241808,0.40287346],"study_design_scores_gemma":[0.002806264,0.0007878432,0.0025220383,0.00033883512,0.00024355973,0.000323697,0.00039358492,0.6358534,0.07723314,0.034567308,0.2447357,0.0001945503],"about_ca_topic_score_codex":0.007933493,"about_ca_topic_score_gemma":0.010745341,"teacher_disagreement_score":0.057359446,"about_ca_system_score_codex":0.0018111134,"about_ca_system_score_gemma":0.002465397,"threshold_uncertainty_score":0.19188643},"labels":[],"label_agreement":null},{"id":"W1548870362","doi":"10.3217/jucs-008-07-0722","title":"Heyting Algebras and Formal Languages","year":2002,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Exponentiation; Computer science; Formal language; Heyting algebra; Context (archaeology); Programming language; Abstract family of languages; Ontology language; Algebra over a field; Second-generation programming language; Mathematics; Artificial intelligence; Pure mathematics; Fifth-generation programming language","score_opus":0.028998209049501445,"score_gpt":0.23566989282712142,"score_spread":0.20667168377761996,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1548870362","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":[0.26216283,0.012388634,0.57300234,0.006699896,0.0011074175,0.00022367697,0.0010754536,0.0010233112,0.14231645],"genre_scores_gemma":[0.9278801,0.0024947664,0.045991696,0.00082490564,0.0008434789,0.00012199718,0.00050165114,0.00012533554,0.021216052],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9981603,0.0005085699,0.00019652492,0.0003494263,0.00051123364,0.00027396405],"domain_scores_gemma":[0.9978638,0.0008534379,0.00027277457,0.00026359822,0.0005121264,0.00023430941],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002347832,0.0005964067,0.0005091143,0.001439511,0.0013137576,0.0035177644,0.0006993785,0.0009009131,0.0068747634],"category_scores_gemma":[0.0038733538,0.00029023114,0.0007017162,0.001717244,0.0045101885,0.008971767,0.002019282,0.0026200525,0.0010401951],"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":[0.000019652422,0.000011328602,0.000105674226,0.000028653041,0.000005811306,0.00005545893,0.0002086183,0.0005289781,0.00052132347,0.9944659,0.00051868986,0.0035298304],"study_design_scores_gemma":[0.000013009741,0.000014138785,0.00011036576,0.000017499677,0.0000053514727,0.00011102535,0.000074423966,0.0022528437,0.00074815255,0.98872024,0.007921937,0.000011061839],"about_ca_topic_score_codex":0.0011530009,"about_ca_topic_score_gemma":0.0005413616,"teacher_disagreement_score":0.0068747634,"about_ca_system_score_codex":0.0017162616,"about_ca_system_score_gemma":0.0009957388,"threshold_uncertainty_score":0.022998393},"labels":[],"label_agreement":null},{"id":"W1549926299","doi":"","title":"XML Conversions of Bibliographical Data","year":2005,"lang":"en","type":"article","venue":"EdMedia: World Conference on Educational Media and Technology","topic":"Advanced Database Systems and Queries","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":"Acadia University","funders":"","keywords":"Computer science; Database; Information retrieval; Programming language","score_opus":0.053923779244402566,"score_gpt":0.29759886579762207,"score_spread":0.2436750865532195,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1549926299","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":[0.06725342,0.0016953965,0.5659488,0.0016422443,0.0017416071,0.0012563649,0.09415938,0.13161492,0.1346879],"genre_scores_gemma":[0.24582204,0.0030141382,0.48262864,0.0008461477,0.00042189957,0.0008607247,0.14831479,0.024962265,0.093129255],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9979292,0.00035125593,0.0004289443,0.00026706498,0.00089385005,0.00012955003],"domain_scores_gemma":[0.99434835,0.0021943045,0.00030539936,0.0019166883,0.0011096887,0.00012557267],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016688546,0.00083468534,0.00059746916,0.009181548,0.0011369832,0.004636339,0.0013721818,0.00094252074,0.03389861],"category_scores_gemma":[0.0104248095,0.0008840519,0.0014651638,0.0094892215,0.0007650564,0.0029816,0.0023619304,0.0011768736,0.010339534],"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":[0.0011489001,0.0004057576,0.0067288564,0.0025845624,0.0003312166,0.0032455162,0.0036826637,0.010261175,0.030658646,0.14349641,0.17435786,0.6230985],"study_design_scores_gemma":[0.00016431716,0.000081948194,0.00460287,0.00058059534,0.00019177984,0.0016947787,0.0010079008,0.027846681,0.087235674,0.041881848,0.8345356,0.00017609686],"about_ca_topic_score_codex":0.005022765,"about_ca_topic_score_gemma":0.00535146,"teacher_disagreement_score":0.03389861,"about_ca_system_score_codex":0.0012247441,"about_ca_system_score_gemma":0.0009954353,"threshold_uncertainty_score":0.11340219},"labels":[],"label_agreement":null},{"id":"W1550285949","doi":"10.1007/978-0-387-39940-9_797","title":"XML Tree Pattern, XML Twig Query","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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 British Columbia","funders":"","keywords":"Twig; Computer science; XML; Streaming XML; Efficient XML Interchange; XML database; Document Structure Description; XML Schema Editor; Information retrieval; World Wide Web; Botany; Biology","score_opus":0.014614299415547328,"score_gpt":0.23031858525212137,"score_spread":0.21570428583657406,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1550285949","genre_codex":"methods","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":[0.009107095,0.011916047,0.8122948,0.002978725,0.001161427,0.0006171022,0.013552357,0.041992787,0.10637967],"genre_scores_gemma":[0.09117692,0.016690135,0.6370512,0.0027349289,0.00079465937,0.0007968119,0.040650982,0.007115517,0.20298883],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99918586,0.00007331646,0.00007936901,0.0001727591,0.0004429688,0.000045787823],"domain_scores_gemma":[0.9996655,0.00008022637,0.000026829373,0.00011096164,0.00008170274,0.000034766737],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00054502697,0.00083370996,0.0009156269,0.0017963321,0.0006796518,0.002717782,0.0017801633,0.0014379518,0.019450549],"category_scores_gemma":[0.0023249735,0.0003820405,0.00050451263,0.006328295,0.00065477524,0.004946927,0.0016497211,0.00094526814,0.017554032],"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":[0.0003073355,0.0001263782,0.0006264653,0.0010251802,0.000029993304,0.00048543068,0.00022891427,0.0029803591,0.0131530315,0.08893584,0.2767799,0.6153212],"study_design_scores_gemma":[0.00010555272,0.00010413333,0.00118329,0.00018114455,0.00006743273,0.0035536045,0.0002863114,0.035373982,0.009995767,0.1466306,0.8024533,0.0000649173],"about_ca_topic_score_codex":0.004764773,"about_ca_topic_score_gemma":0.005352496,"teacher_disagreement_score":0.019450549,"about_ca_system_score_codex":0.0008216771,"about_ca_system_score_gemma":0.0008770667,"threshold_uncertainty_score":0.06506854},"labels":[],"label_agreement":null},{"id":"W1550673449","doi":"10.1007/3-540-44503-x_19","title":"Algebraic Rewritings for Optimizing Regular Path Queries","year":2001,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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":"Concordia University","funders":"","keywords":"Rewriting; Computer science; Query optimization; Materialized view; Context (archaeology); Relational algebra; Algebraic number; Path (computing); Query language; Conjunctive query; Theoretical computer science; Focus (optics); Product (mathematics); Relational database; View; Information retrieval; Programming language; Mathematics; Database design","score_opus":0.015655398096001822,"score_gpt":0.24259114404018642,"score_spread":0.22693574594418459,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1550673449","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":[0.022357818,0.000682977,0.9538108,0.00035179083,0.0001877075,0.00014498398,0.0002752908,0.004626089,0.017562626],"genre_scores_gemma":[0.35611138,0.0010028748,0.62363255,0.00029314458,0.00035018593,0.00022307188,0.0010077144,0.001681706,0.015697306],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9970552,0.0005664901,0.0002321501,0.000361819,0.0015270704,0.00025733165],"domain_scores_gemma":[0.9973405,0.001393995,0.00014840032,0.00059573055,0.00045390968,0.00006745048],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013840221,0.00073103857,0.0010886847,0.0011773434,0.000878671,0.0020295572,0.0017850252,0.00073059596,0.00650309],"category_scores_gemma":[0.0067372127,0.00075366657,0.0013541004,0.0023118518,0.0016366701,0.0041788495,0.0017824416,0.0026095978,0.001602346],"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":[0.00023763365,0.00013397727,0.00038468852,0.00033848878,0.00005919582,0.00018344894,0.0004980077,0.03333759,0.009453104,0.6791388,0.011883457,0.26435167],"study_design_scores_gemma":[0.00008718733,0.00010603205,0.0002089354,0.00004585139,0.00010024544,0.00023203746,0.00014932167,0.17567895,0.011260256,0.78798455,0.024094708,0.00005186143],"about_ca_topic_score_codex":0.0019864116,"about_ca_topic_score_gemma":0.0028536303,"teacher_disagreement_score":0.00650309,"about_ca_system_score_codex":0.0012087984,"about_ca_system_score_gemma":0.00086088624,"threshold_uncertainty_score":0.02175498},"labels":[],"label_agreement":null},{"id":"W1552234820","doi":"","title":"Autonomic Database Management: State of the Art and Future Trends","year":2012,"lang":"en","type":"article","venue":"Scholarship@Western (Western University)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Database; Data administration; Computer science; Database administrator; Database testing; Obstacle; Task (project management); Intelligent database; State (computer science); Database design; Database schema; Engineering","score_opus":0.04490498324003425,"score_gpt":0.2796103031552831,"score_spread":0.23470531991524887,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1552234820","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":[0.008420961,0.93472385,0.015722731,0.024751652,0.00078053254,0.00004920962,0.000066668996,0.0002998776,0.015184483],"genre_scores_gemma":[0.0822869,0.86646724,0.03905329,0.004633689,0.003946004,0.000081588616,0.00021307051,0.00007336868,0.0032449008],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9973857,0.000656839,0.00026309077,0.00041159068,0.0010904965,0.00019223752],"domain_scores_gemma":[0.9890159,0.0064783962,0.00074951694,0.00045546817,0.0024792168,0.0008216476],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009640803,0.0005310238,0.0008452011,0.0020175606,0.00091387844,0.0072386037,0.00237971,0.0034712364,0.0031234229],"category_scores_gemma":[0.005923573,0.0005077331,0.000509239,0.004336154,0.0021772285,0.011478656,0.001696626,0.0028331007,0.0011827406],"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":[0.00016141076,0.00035130497,0.0039176107,0.0030839604,0.000044021413,0.00010078543,0.00047787186,0.0015781318,0.0013696228,0.039184146,0.012179882,0.9375513],"study_design_scores_gemma":[0.00010914554,0.001133734,0.00956495,0.007126091,0.00019718523,0.0017345756,0.0038791024,0.028988138,0.0033371903,0.1173093,0.82640946,0.00021111716],"about_ca_topic_score_codex":0.0011838446,"about_ca_topic_score_gemma":0.0013043687,"teacher_disagreement_score":0.009640803,"about_ca_system_score_codex":0.0015446962,"about_ca_system_score_gemma":0.0022249816,"threshold_uncertainty_score":0.05098605},"labels":[],"label_agreement":null},{"id":"W1554673294","doi":"","title":"Benefits of path summaries in an XML query optimizer supporting multiple access methods","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":44,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Heuristics; Exploit; Query optimization; Path (computing); XML; Data mining; Range (aeronautics); Path expression; Range query (database); Index (typography); Information retrieval; Web search query; Web query classification; Query language; Search engine; World Wide Web","score_opus":0.05331633857844409,"score_gpt":0.38046620290148536,"score_spread":0.3271498643230413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1554673294","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":[0.77447027,0.003986528,0.19637404,0.0007434417,0.00006014451,0.0003179536,0.00062899996,0.018973734,0.0044450187],"genre_scores_gemma":[0.7369319,0.0007019889,0.25892875,0.00008760876,0.000048898808,0.00012580927,0.0008446608,0.0010866029,0.0012437907],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99423826,0.0028489868,0.0005495657,0.00032534834,0.0017244698,0.00031326961],"domain_scores_gemma":[0.9870308,0.010124732,0.0006985675,0.0009780348,0.00095218467,0.00021567696],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0045366073,0.0014963306,0.0008838144,0.0012113497,0.00071709085,0.0018856226,0.0012039114,0.0010702116,0.0017567755],"category_scores_gemma":[0.015501166,0.00073464675,0.0005051695,0.002188844,0.00045228784,0.0034088437,0.0011382602,0.0007321897,0.00041801494],"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":[0.012080318,0.0011298483,0.019559402,0.0012636926,0.0005410093,0.0004230376,0.0009500539,0.282625,0.11797215,0.011735517,0.009593439,0.5421266],"study_design_scores_gemma":[0.0005466628,0.0018158477,0.007159377,0.000043117907,0.0004165612,0.00033515203,0.00025053177,0.9002346,0.080539696,0.0030737906,0.0054628984,0.000121834935],"about_ca_topic_score_codex":0.0053139236,"about_ca_topic_score_gemma":0.005945737,"teacher_disagreement_score":0.0053139236,"about_ca_system_score_codex":0.0008341077,"about_ca_system_score_gemma":0.00098301,"threshold_uncertainty_score":0.02399218},"labels":[],"label_agreement":null},{"id":"W1557668034","doi":"10.1609/socs.v5i1.18330","title":"Non-Linear Merging Strategies for Merge-and-Shrink Based on Variable Interactions","year":2021,"lang":"en","type":"article","venue":"Proceedings of the International Symposium on Combinatorial Search","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Merge (version control); Heuristics; Computer science; Variable (mathematics); Theoretical computer science; Nonlinear system; Algorithm; Mathematics; Mathematical optimization; Parallel computing","score_opus":0.018115225935575824,"score_gpt":0.28731736492347815,"score_spread":0.26920213898790235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1557668034","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":[0.0100782085,0.00017248598,0.98682666,0.00010064223,0.000016357038,0.00014013972,0.00005808738,0.0011521584,0.0014552665],"genre_scores_gemma":[0.16630045,0.00014019277,0.8308351,0.00014998378,0.00002302894,0.00027834915,0.00026210747,0.00040685962,0.0016039425],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9977889,0.0007869264,0.00017872459,0.0003477333,0.000613822,0.0002837609],"domain_scores_gemma":[0.99395955,0.0033210353,0.00059216755,0.0013311871,0.0005753174,0.00022080759],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036710857,0.0012895782,0.0012197607,0.0015587972,0.0013157581,0.0014053996,0.0032344456,0.0010618075,0.0044323467],"category_scores_gemma":[0.0122501915,0.0008287782,0.0015389023,0.0015300493,0.0017790571,0.0035371701,0.003957066,0.002069679,0.00070867693],"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":[0.0006037106,0.00027530445,0.004018114,0.00060782465,0.00023037694,0.00019894881,0.0015045118,0.32003447,0.015395225,0.18143067,0.007852977,0.46784782],"study_design_scores_gemma":[0.00006209769,0.00011719551,0.00047106808,0.00003850317,0.00007549815,0.0000707127,0.00017347353,0.9127807,0.009328683,0.070666574,0.00616971,0.000045704946],"about_ca_topic_score_codex":0.004741096,"about_ca_topic_score_gemma":0.007817294,"teacher_disagreement_score":0.004741096,"about_ca_system_score_codex":0.0018762568,"about_ca_system_score_gemma":0.002820355,"threshold_uncertainty_score":0.019414783},"labels":[],"label_agreement":null},{"id":"W1558494856","doi":"10.1007/978-3-642-00672-2_64","title":"Complete and Equivalent Query Rewriting Using Views","year":2009,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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 Toronto; IBM (Canada); University of Windsor","funders":"","keywords":"Rewriting; Computer science; Materialized view; Conjunctive query; Query optimization; Query language; Set (abstract data type); Theoretical computer science; Information retrieval; Programming language; View; Relational database; Database design","score_opus":0.05899105264639242,"score_gpt":0.29226862465899583,"score_spread":0.2332775720126034,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1558494856","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":[0.028733242,0.000981013,0.9351467,0.00066045864,0.00029300255,0.00014720229,0.0005620251,0.0026983381,0.030778006],"genre_scores_gemma":[0.51105964,0.0011067009,0.45589933,0.00078776263,0.0004949716,0.00023479498,0.0022443805,0.0026107808,0.02556163],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9904344,0.0023829753,0.0007282675,0.0013403483,0.00429337,0.0008206315],"domain_scores_gemma":[0.9916459,0.0034986716,0.00023303597,0.003144594,0.001305994,0.00017179898],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030938468,0.00078820955,0.0014591946,0.0012384098,0.0010110582,0.0040247003,0.002192924,0.0013487802,0.005358839],"category_scores_gemma":[0.011120231,0.00102247,0.002679971,0.001639521,0.0026856484,0.007292922,0.0030326217,0.0037222109,0.0016167499],"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":[0.00021442657,0.00011306103,0.00034861956,0.0003389096,0.00013032024,0.0003394182,0.0011755008,0.009686102,0.0121850595,0.8559304,0.009618757,0.10991951],"study_design_scores_gemma":[0.000062440966,0.000048307687,0.00023969171,0.000041033134,0.00013094288,0.0003566787,0.00017865367,0.031627104,0.011589436,0.9348915,0.02078288,0.000051342853],"about_ca_topic_score_codex":0.0019916971,"about_ca_topic_score_gemma":0.0017156026,"teacher_disagreement_score":0.005358839,"about_ca_system_score_codex":0.0011602383,"about_ca_system_score_gemma":0.0011335689,"threshold_uncertainty_score":0.01792711},"labels":[],"label_agreement":null},{"id":"W1559066648","doi":"10.1007/978-3-540-39597-3_39","title":"Extending XML Schema with Nonmonotonic Inheritance","year":2003,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","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":"Carleton University","funders":"","keywords":"Computer science; Inheritance (genetic algorithm); Schema (genetic algorithms); XML; XML Schema (W3C); Document Structure Description; Theoretical computer science; Information retrieval; XML Encryption; World Wide Web","score_opus":0.014453287019744231,"score_gpt":0.23829901951868543,"score_spread":0.22384573249894119,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1559066648","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":[0.027674556,0.00046757062,0.95587814,0.00041383595,0.00018697805,0.00010477071,0.0002532456,0.004943179,0.010077686],"genre_scores_gemma":[0.15776353,0.00081021327,0.82494324,0.0003964121,0.00011361806,0.00008271796,0.001260545,0.0015411826,0.013088513],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9984628,0.0003783686,0.00028088246,0.00022726561,0.0005555122,0.00009516427],"domain_scores_gemma":[0.9973047,0.0009937941,0.00012566477,0.0012634847,0.00025059585,0.000061718754],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034555083,0.0004018716,0.0006046789,0.0008748178,0.0005086622,0.001879292,0.0016961672,0.0009331519,0.0034930015],"category_scores_gemma":[0.004408707,0.00081907545,0.0011135256,0.0011336743,0.0006388857,0.0063829897,0.0028099592,0.0014418447,0.0009816136],"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":[0.00024094644,0.00034934646,0.002583843,0.0005616817,0.000104433486,0.0019562615,0.0018407975,0.0085492935,0.029207787,0.351616,0.010355252,0.59263444],"study_design_scores_gemma":[0.00016536281,0.00017304027,0.0015571383,0.00031939268,0.0003896088,0.0036043387,0.0005015349,0.19562352,0.06775463,0.45235243,0.2774146,0.00014440555],"about_ca_topic_score_codex":0.00085359823,"about_ca_topic_score_gemma":0.0012284582,"teacher_disagreement_score":0.0034930015,"about_ca_system_score_codex":0.00040782924,"about_ca_system_score_gemma":0.00043909534,"threshold_uncertainty_score":0.018274665},"labels":[],"label_agreement":null},{"id":"W1560728783","doi":"10.1007/978-3-642-15364-8_19","title":"A Disk-Based, Adaptive Approach to Memory-Limited Computation of Windowed Stream Joins","year":2010,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Joins; Computer science; Sliding window protocol; Window (computing); Data stream mining; Parallel computing; Data stream; Hash function; Partition (number theory); Auxiliary memory; Hard disk drive performance characteristics; Algorithm; Real-time computing; Distributed computing; Computer hardware; Data mining; Operating system","score_opus":0.020618991022628864,"score_gpt":0.2453739940352483,"score_spread":0.22475500301261941,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1560728783","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":[0.018343067,0.00039044552,0.9785648,0.00008683014,0.0000811226,0.000052128427,0.00006169111,0.0011668332,0.0012529676],"genre_scores_gemma":[0.27089366,0.0004411538,0.7229147,0.00014176851,0.00025697707,0.00019404605,0.00025075805,0.00042955443,0.004477439],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989666,0.00018674703,0.00008751639,0.00020443363,0.00044198407,0.00011279748],"domain_scores_gemma":[0.9973168,0.0012305654,0.00012723992,0.00076108857,0.0004084607,0.00015581705],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010903858,0.0007311525,0.0012773782,0.00090547634,0.00085827155,0.0019167373,0.0037857974,0.00076533493,0.003982291],"category_scores_gemma":[0.0055424217,0.0006963156,0.000613965,0.0017217989,0.0007547914,0.003042956,0.002208455,0.0016290636,0.0008843914],"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":[0.0022886414,0.00036509446,0.0022688126,0.00034427125,0.00017407745,0.00025977244,0.00065142324,0.26625317,0.07668928,0.07039358,0.011770711,0.56854117],"study_design_scores_gemma":[0.000037420592,0.00005894355,0.00013465357,0.000006953203,0.000017991773,0.00003361822,0.000027764501,0.9797538,0.00508265,0.013346371,0.0014879094,0.000011817559],"about_ca_topic_score_codex":0.002757474,"about_ca_topic_score_gemma":0.0043877535,"teacher_disagreement_score":0.003982291,"about_ca_system_score_codex":0.00074294704,"about_ca_system_score_gemma":0.001078829,"threshold_uncertainty_score":0.013322115},"labels":[],"label_agreement":null},{"id":"W1561685912","doi":"","title":"Proceedings of the Fourth ACM International Conference on Distributed Event-Based Systems","year":2010,"lang":"en","type":"article","venue":"Distributed Event-Based Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Complex event processing; Event (particle physics); World Wide Web; Publication; Middleware (distributed applications); Data science; Cloud computing; Stream processing; The Internet; Variety (cybernetics); Process (computing); Database; Political science; Distributed computing","score_opus":0.02064392669238604,"score_gpt":0.26696945777282194,"score_spread":0.2463255310804359,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1561685912","genre_codex":"methods","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":[0.011631462,0.05224893,0.5622432,0.019542016,0.093043655,0.0020107788,0.0034425575,0.011189754,0.24464758],"genre_scores_gemma":[0.1357673,0.051594965,0.23693979,0.010130423,0.021748155,0.0020260944,0.020471063,0.0028302122,0.518492],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99709225,0.0007268053,0.00037161855,0.00046279008,0.0011258172,0.0002207692],"domain_scores_gemma":[0.99527115,0.0014451839,0.0001505603,0.0010169903,0.0015431598,0.0005730317],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004086515,0.0017193739,0.0020626602,0.0009796022,0.0008585479,0.0060331794,0.0027794496,0.0022047374,0.084819645],"category_scores_gemma":[0.008528136,0.00056604773,0.0012080634,0.0010924533,0.0011685821,0.0041228444,0.0029279261,0.0038955219,0.03308805],"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":[0.00046899938,0.0003744108,0.0012575698,0.000829882,0.00023770906,0.000676184,0.00039122946,0.004016861,0.005590934,0.02918339,0.55964345,0.39732936],"study_design_scores_gemma":[0.00008053903,0.00013135711,0.0005816855,0.0002511633,0.00005881441,0.00043215905,0.00014084189,0.011991089,0.0011502489,0.01399327,0.9711519,0.000037024125],"about_ca_topic_score_codex":0.0021278355,"about_ca_topic_score_gemma":0.0015698449,"teacher_disagreement_score":0.084819645,"about_ca_system_score_codex":0.0007135842,"about_ca_system_score_gemma":0.0020082186,"threshold_uncertainty_score":0.28375},"labels":[],"label_agreement":null},{"id":"W1562696372","doi":"10.1007/978-3-540-85836-2_3","title":"An MDA Approach for the Development of Spatial Data Warehouses","year":2008,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":39,"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":"Ontario Council on Graduate Studies, Council of Ontario Universities; Universidad de Alicante","keywords":"Computer science; Data warehouse; Logical data model; Representation (politics); Extension (predicate logic); Transformation (genetics); Spatial analysis; Eclipse; Set (abstract data type); Online analytical processing; Development (topology); Logical framework; Data transformation; Architecture; Data mining; Theoretical computer science; Data modeling; Database; Programming language","score_opus":0.06150636132431073,"score_gpt":0.28362894861120874,"score_spread":0.22212258728689802,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1562696372","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":[0.0040070843,0.0002438179,0.9898317,0.00031553314,0.000033051525,0.00011855886,0.0001569934,0.0027189623,0.002574366],"genre_scores_gemma":[0.036534153,0.00034082326,0.96012145,0.00010592452,0.00001300444,0.00011948878,0.0006004565,0.00037691675,0.0017878148],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974733,0.00085340656,0.00036906562,0.00027506152,0.00086857355,0.00016055125],"domain_scores_gemma":[0.9968304,0.0008563941,0.00018193966,0.001041711,0.00093691185,0.00015273895],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0039855624,0.0005613945,0.00052395,0.0013196083,0.0010084108,0.004569982,0.0023661375,0.0010405796,0.0019868303],"category_scores_gemma":[0.007261774,0.001195614,0.0014499313,0.0013439185,0.00090114656,0.0034766973,0.0027177485,0.0022904703,0.0008888532],"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":[0.00015018805,0.00032073868,0.0044866204,0.00096970965,0.00036463395,0.0011692034,0.0048491354,0.050903674,0.03070465,0.34511432,0.02261009,0.5383571],"study_design_scores_gemma":[0.00007552457,0.00018622479,0.0017190856,0.0007358347,0.0004546916,0.0016675174,0.0012317896,0.40518188,0.044743825,0.17665787,0.36717817,0.00016754294],"about_ca_topic_score_codex":0.0059469016,"about_ca_topic_score_gemma":0.008543895,"teacher_disagreement_score":0.0059469016,"about_ca_system_score_codex":0.0010541069,"about_ca_system_score_gemma":0.003344685,"threshold_uncertainty_score":0.02107793},"labels":[],"label_agreement":null},{"id":"W1563085466","doi":"10.1007/978-3-540-73888-6_10","title":"Efficient, Effective and Flexible XML Retrieval Using Summaries","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":13,"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; Information retrieval; XML; Flexibility (engineering); World Wide Web","score_opus":0.024579848016829275,"score_gpt":0.2814022573163169,"score_spread":0.25682240929948763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1563085466","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":[0.04190648,0.004327977,0.9225274,0.0004781047,0.00020815142,0.00026962292,0.0017204885,0.02308343,0.0054783355],"genre_scores_gemma":[0.24252738,0.0034117233,0.72815514,0.00024355213,0.00034262915,0.00017689822,0.00574357,0.0019973265,0.017401764],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99841285,0.00036302276,0.00027061306,0.0002301105,0.0005961155,0.00012718396],"domain_scores_gemma":[0.996376,0.0015824854,0.00024774036,0.0012370031,0.00044711563,0.00010971219],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015326433,0.000997475,0.0016098766,0.0023757515,0.00075268943,0.0034032837,0.0017258542,0.0010661386,0.0049404344],"category_scores_gemma":[0.0071081743,0.0007394232,0.0007941051,0.0026499638,0.00040055855,0.0060224654,0.0021642859,0.00078578014,0.0046063988],"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":[0.00075380417,0.00013291065,0.0009941356,0.0009524998,0.00009241797,0.00042356545,0.0005817053,0.007861411,0.0658986,0.012626481,0.039002467,0.87068],"study_design_scores_gemma":[0.0005320887,0.0013356102,0.0029822832,0.00029955746,0.00079472235,0.0042248038,0.0015618582,0.4233466,0.32876834,0.060300738,0.17550862,0.00034477146],"about_ca_topic_score_codex":0.0009896439,"about_ca_topic_score_gemma":0.0015835048,"teacher_disagreement_score":0.0049404344,"about_ca_system_score_codex":0.00033965198,"about_ca_system_score_gemma":0.000739351,"threshold_uncertainty_score":0.016527355},"labels":[],"label_agreement":null},{"id":"W1563601331","doi":"10.1007/3-540-48196-6_8","title":"QFD Matrix for Incremental Construction of a Warehouse via Data Marts","year":2001,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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 Winnipeg","funders":"","keywords":"Data warehouse; Computer science; Quality function deployment; Construct (python library); Warehouse; Process (computing); Database; Software deployment; Data mining; Software engineering; Programming language; Operations management; Engineering","score_opus":0.028118667682933966,"score_gpt":0.2798995513708967,"score_spread":0.25178088368796275,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1563601331","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":[0.008148134,0.00010987038,0.9827571,0.00021737849,0.00005631385,0.00020448881,0.0017653188,0.005125352,0.0016161401],"genre_scores_gemma":[0.072230175,0.00011868223,0.92104614,0.000060592043,0.000022854236,0.00019254073,0.0038446959,0.0002817734,0.0022026203],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989936,0.00012758201,0.00009156514,0.00017872684,0.00052111084,0.00008740574],"domain_scores_gemma":[0.9983191,0.000522946,0.00009633444,0.0003960148,0.00058144104,0.000084215084],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00091107114,0.0006640469,0.0006763844,0.0022776905,0.00072647125,0.0017881792,0.0015455892,0.0004394517,0.009173415],"category_scores_gemma":[0.005001945,0.0006360988,0.0011577625,0.0024024656,0.00036530208,0.002250667,0.0018147529,0.0010591132,0.002311742],"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":[0.0003519546,0.0002510682,0.0025746287,0.00042218404,0.00009734763,0.0004148918,0.00035467243,0.057367414,0.01736886,0.034352522,0.034704577,0.85173976],"study_design_scores_gemma":[0.00009395259,0.00013751062,0.0012706664,0.00006206423,0.000067058434,0.0004380744,0.00032905987,0.87859637,0.017738238,0.06517665,0.03602247,0.000067886045],"about_ca_topic_score_codex":0.009300662,"about_ca_topic_score_gemma":0.013362998,"teacher_disagreement_score":0.009300662,"about_ca_system_score_codex":0.00072173297,"about_ca_system_score_gemma":0.0016850837,"threshold_uncertainty_score":0.030688167},"labels":[],"label_agreement":null},{"id":"W1565760524","doi":"10.1007/978-1-4419-8834-8","title":"Principles of Distributed Database Systems, Third Edition","year":2011,"lang":"en","type":"book","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":344,"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; Database; Information retrieval","score_opus":0.04033012863573607,"score_gpt":0.2414625773059741,"score_spread":0.20113244867023802,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1565760524","genre_codex":"other","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":[0.0011022218,0.21129431,0.3715407,0.004917967,0.013869628,0.00033039562,0.00423631,0.0097743375,0.38293412],"genre_scores_gemma":[0.010405417,0.09674026,0.17207229,0.0024986814,0.0048601916,0.00041282637,0.005159491,0.0023104905,0.7055405],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99878246,0.00008573873,0.00009652146,0.00017560547,0.0008040782,0.00005561632],"domain_scores_gemma":[0.99845314,0.00044872382,0.000063872714,0.0002633636,0.0006807075,0.0000901726],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009889525,0.0022941313,0.0023438772,0.0022973719,0.0009615678,0.005375007,0.0026073796,0.0013508963,0.048971944],"category_scores_gemma":[0.0028564716,0.001615949,0.00090580294,0.004257024,0.0014654875,0.005971297,0.0013623013,0.0042486642,0.05129622],"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":[0.000049835504,0.00006769108,0.00020719219,0.0009483096,0.00005738198,0.00010097914,0.0002809876,0.0021646896,0.0019407012,0.09299988,0.66689324,0.23428914],"study_design_scores_gemma":[0.000018244487,0.000018124429,0.00024782246,0.00021823189,0.000024565468,0.0004194768,0.000035236597,0.0020015086,0.0003711775,0.035478305,0.96114814,0.000019100886],"about_ca_topic_score_codex":0.0030929071,"about_ca_topic_score_gemma":0.0043756864,"teacher_disagreement_score":0.048971944,"about_ca_system_score_codex":0.0013698589,"about_ca_system_score_gemma":0.0023719831,"threshold_uncertainty_score":0.16382748},"labels":[],"label_agreement":null},{"id":"W1568146547","doi":"10.1007/3-540-44957-4_68","title":"Reasoning about Duplicate Elimination with Description Logic","year":2000,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":36,"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; Conjunctive query; Relational database; Object (grammar); Description logic; Semantics (computer science); P; Programming language; Logic program; Theoretical computer science; Relational calculus; Relational model; Data mining; Information retrieval; Logic programming; Artificial intelligence; Algorithm; Time complexity","score_opus":0.017021833721029687,"score_gpt":0.23640277011123365,"score_spread":0.21938093639020395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1568146547","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":[0.018289533,0.0010388306,0.9657768,0.0023925104,0.00016386666,0.00014943696,0.00079730124,0.0014285665,0.009963234],"genre_scores_gemma":[0.4035636,0.0020852198,0.57810783,0.001260251,0.00031921925,0.00024884564,0.0037049986,0.00048985827,0.010220253],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99075586,0.0032882951,0.0007581388,0.0012059087,0.0033235978,0.0006683231],"domain_scores_gemma":[0.97900885,0.016404405,0.00063907786,0.00240722,0.0012910872,0.00024928892],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008110695,0.0016125775,0.0015712775,0.0030358112,0.0019980227,0.0052843536,0.0056639565,0.0023207865,0.0067717875],"category_scores_gemma":[0.027097171,0.002429849,0.0042858813,0.003652355,0.0039967457,0.023013987,0.007745185,0.004641507,0.0008290396],"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":[0.00039845146,0.00018733338,0.0022494043,0.0012282162,0.00047271818,0.0019263519,0.0009696662,0.058963265,0.0021824231,0.7927681,0.016396785,0.1222572],"study_design_scores_gemma":[0.00010046473,0.00002206128,0.00013891912,0.00009173704,0.00021162425,0.0005756486,0.0002561357,0.12123276,0.0053638625,0.8617571,0.010202415,0.000047267014],"about_ca_topic_score_codex":0.004356525,"about_ca_topic_score_gemma":0.004193356,"teacher_disagreement_score":0.008110695,"about_ca_system_score_codex":0.0024534445,"about_ca_system_score_gemma":0.0018545251,"threshold_uncertainty_score":0.042893946},"labels":[],"label_agreement":null},{"id":"W1568465595","doi":"","title":"Review of 'John Bell, Set Theory: Boolean-Valued Models and Independence Proofs, 3rd Edition","year":2005,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Mathematical proof; Independence (probability theory); Mathematical economics; Set (abstract data type); Mathematics; Calculus (dental); Computer science; Discrete mathematics; Programming language; Statistics; Medicine","score_opus":0.013889325339669608,"score_gpt":0.2656397531211184,"score_spread":0.2517504277814488,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1568465595","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":[0.0001441359,0.94072586,0.0047330093,0.039426085,0.008001831,0.000007079464,0.00016839529,0.000035349047,0.0067582107],"genre_scores_gemma":[0.005236873,0.92601085,0.0041541387,0.02212765,0.029538076,0.0000295599,0.00030001628,0.00008125512,0.012521501],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982316,0.0004994383,0.00015216334,0.00029970097,0.0007327827,0.00008428347],"domain_scores_gemma":[0.9932882,0.0041578733,0.00022502668,0.00024881947,0.0018961827,0.0001839366],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034097992,0.0009438171,0.0019268759,0.0041670455,0.0011220927,0.004307653,0.0023103743,0.0033059022,0.011143225],"category_scores_gemma":[0.012689951,0.0009513488,0.00070128165,0.007267348,0.0043402077,0.009507098,0.0013728837,0.0067462423,0.0057891207],"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":[0.00002246091,0.000027285194,0.00012396992,0.0014053843,0.00002939443,0.000028193259,0.00015965654,0.0004564351,0.00011305364,0.09790644,0.81760377,0.082124],"study_design_scores_gemma":[0.000007918916,0.000010411782,0.0002475948,0.00078762084,0.000012405279,0.00011835942,0.00006790493,0.0001766127,0.00008294423,0.04272849,0.9557383,0.000021459211],"about_ca_topic_score_codex":0.009343109,"about_ca_topic_score_gemma":0.011498395,"teacher_disagreement_score":0.011143225,"about_ca_system_score_codex":0.0039904206,"about_ca_system_score_gemma":0.003985863,"threshold_uncertainty_score":0.037277818},"labels":[],"label_agreement":null},{"id":"W1570688426","doi":"","title":"XBench - A Family of Benchmarks for XML DBMSs","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; XML; XML database; Programming language; Set (abstract data type); Database; Benchmark (surveying); World Wide Web","score_opus":0.01657071109428587,"score_gpt":0.2521326325280782,"score_spread":0.23556192143379234,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1570688426","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":[0.2883609,0.0115214465,0.44683754,0.0018243899,0.0012793321,0.005264593,0.048134234,0.14261924,0.054158323],"genre_scores_gemma":[0.42412454,0.004873342,0.45112166,0.0006947828,0.00028579423,0.004123113,0.089136094,0.009587198,0.016053513],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99251467,0.0014785596,0.0011676787,0.0005634731,0.0037917744,0.00048374754],"domain_scores_gemma":[0.9893506,0.0038818414,0.0009049093,0.0019514118,0.0034877267,0.00042349417],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004652371,0.0019885784,0.0009629857,0.0032615827,0.0011832949,0.0023385321,0.003929018,0.0009973348,0.003136022],"category_scores_gemma":[0.017887097,0.00069545803,0.0007560397,0.0057794657,0.0006345372,0.0033835901,0.0016037097,0.0017370683,0.0016497714],"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":[0.0032334258,0.0017436246,0.026350297,0.005737999,0.00043685353,0.000857626,0.0014169749,0.12898354,0.06644545,0.03740006,0.23093244,0.49646175],"study_design_scores_gemma":[0.0007052725,0.0022863992,0.023076927,0.00056383386,0.00024466836,0.0014460278,0.0007457621,0.54590976,0.17592697,0.027797114,0.220955,0.00034230982],"about_ca_topic_score_codex":0.0053862175,"about_ca_topic_score_gemma":0.0045254105,"teacher_disagreement_score":0.0053862175,"about_ca_system_score_codex":0.0014105035,"about_ca_system_score_gemma":0.0016920777,"threshold_uncertainty_score":0.02460438},"labels":[],"label_agreement":null},{"id":"W157236388","doi":"10.5591/978-1-57735-516-8/ijcai11-180","title":"An assertion retrieval algebra for object queries over knowledge bases","year":2011,"lang":"en","type":"article","venue":"International Joint Conference on Artificial Intelligence","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Assertion; Information retrieval; Knowledge base; Identifier; Rewriting; Context (archaeology); Object (grammar); Focus (optics); Generalization; Relational algebra; Theoretical computer science; Programming language; Artificial intelligence; Relational database; Mathematics","score_opus":0.1745760442987635,"score_gpt":0.3595382497468571,"score_spread":0.1849622054480936,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W157236388","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":[0.008357261,0.00028605774,0.9817926,0.0008044158,0.00007378771,0.00023394558,0.0004897132,0.0014255091,0.006536653],"genre_scores_gemma":[0.19255102,0.0008522472,0.7928554,0.0007384915,0.00042540574,0.0005279686,0.0017869414,0.00040522643,0.009857358],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99582314,0.0009643166,0.00055313716,0.00074393564,0.0015801487,0.00033521603],"domain_scores_gemma":[0.997083,0.00095691514,0.0003443354,0.00072013366,0.0006473126,0.00024828978],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004844584,0.0006526202,0.0010329516,0.0017303093,0.0018027785,0.0055995523,0.0025077034,0.001295322,0.0068570557],"category_scores_gemma":[0.007082767,0.00061898853,0.0031090968,0.0028526618,0.0028373757,0.011264336,0.0030938848,0.0029710187,0.0020915652],"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":[0.000085619955,0.000119218035,0.00031048036,0.00020644636,0.000050735885,0.00020394585,0.0004353694,0.011241037,0.0043034526,0.9526763,0.0030990057,0.027268423],"study_design_scores_gemma":[0.000074211,0.0001276799,0.00025896006,0.00008321372,0.000173472,0.00045573994,0.00025891856,0.12724943,0.00822098,0.8285866,0.034391675,0.000119053075],"about_ca_topic_score_codex":0.00608053,"about_ca_topic_score_gemma":0.005436776,"teacher_disagreement_score":0.0068570557,"about_ca_system_score_codex":0.0017302056,"about_ca_system_score_gemma":0.0033706983,"threshold_uncertainty_score":0.025620937},"labels":[],"label_agreement":null},{"id":"W1574590432","doi":"10.4018/978-1-59140-053-0.ch006","title":"Time in Multidimensional Databases","year":2003,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Online analytical processing; Computer science; Data warehouse; Database; Schema (genetic algorithms); Temporal database; Software versioning; Schema evolution; Abstraction; Query language; Data mining; Information retrieval; Database schema; Programming language; Database design; Software","score_opus":0.021931846851173883,"score_gpt":0.2543738975964139,"score_spread":0.23244205074524,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1574590432","genre_codex":"methods","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":[0.005335233,0.1285918,0.72766167,0.007293755,0.0038454419,0.00016533212,0.0012307093,0.0017769285,0.124099076],"genre_scores_gemma":[0.11928324,0.12354612,0.6459219,0.004052099,0.0050736424,0.0006623688,0.0031876466,0.0012402538,0.097032756],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99777067,0.000556361,0.00024579364,0.00036768272,0.0009482386,0.000111367735],"domain_scores_gemma":[0.99825007,0.00085558865,0.000087821696,0.000497336,0.00022717711,0.00008196186],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020237388,0.0009779955,0.0009413119,0.0024290208,0.0012393048,0.006858803,0.0016634364,0.0013970223,0.008544213],"category_scores_gemma":[0.00477081,0.00070795225,0.001105672,0.008233851,0.002322549,0.011956219,0.0032228057,0.0028379774,0.004001101],"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":[0.000024289862,0.000018158726,0.00022967097,0.0004246483,0.000019775127,0.00018537787,0.0006455001,0.0021328144,0.0006211913,0.8692499,0.032189123,0.0942596],"study_design_scores_gemma":[0.000010675605,0.000017423234,0.00016030285,0.00021839673,0.00001895919,0.00046517223,0.00019082849,0.007961149,0.0006378569,0.46314028,0.5271563,0.000022582677],"about_ca_topic_score_codex":0.0018620082,"about_ca_topic_score_gemma":0.0012036728,"teacher_disagreement_score":0.008544213,"about_ca_system_score_codex":0.0019328605,"about_ca_system_score_gemma":0.0010536717,"threshold_uncertainty_score":0.028583229},"labels":[],"label_agreement":null},{"id":"W1574865981","doi":"10.1007/978-3-642-11829-6_6","title":"Conjunctive Queries with Constraints: Homomorphism, Containment and Rewriting","year":2010,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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":"Concordia University","funders":"","keywords":"Homomorphism; Rewriting; Containment (computer programming); Computer science; Conjunctive query; Algebra homomorphism; Programming language; Mathematics; Discrete mathematics; Database; Relational database","score_opus":0.008694925432390636,"score_gpt":0.21714104901340864,"score_spread":0.208446123581018,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1574865981","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":[0.008906833,0.0058898283,0.96072614,0.0011994916,0.0002794418,0.00012434626,0.0002675413,0.0010114559,0.021594897],"genre_scores_gemma":[0.21464801,0.0076408884,0.75595915,0.00077582354,0.0012942979,0.00040886988,0.0017861912,0.0009901879,0.01649653],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99387205,0.0021919382,0.000634471,0.0010539033,0.0019605581,0.00028707174],"domain_scores_gemma":[0.99302715,0.0049234172,0.00023451132,0.0011756739,0.0005038435,0.00013538008],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004440921,0.0010019052,0.0016684016,0.0016130459,0.0012893074,0.0054046465,0.002862545,0.001817905,0.003929998],"category_scores_gemma":[0.013370078,0.0015272704,0.0021890106,0.00458756,0.00488272,0.012687933,0.0035417713,0.004044273,0.0015732455],"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":[0.00007367336,0.000098518365,0.0002739645,0.0004020132,0.0000584561,0.00031447114,0.0011789817,0.0060893144,0.0030559031,0.8549685,0.0108661745,0.122620046],"study_design_scores_gemma":[0.000030110477,0.000035973106,0.00019288973,0.00007087176,0.00005575344,0.00071157166,0.00022365336,0.030898271,0.0041160816,0.9387195,0.024900094,0.000045219243],"about_ca_topic_score_codex":0.0019068533,"about_ca_topic_score_gemma":0.0013907724,"teacher_disagreement_score":0.0054046465,"about_ca_system_score_codex":0.0020407808,"about_ca_system_score_gemma":0.0012463862,"threshold_uncertainty_score":0.023486078},"labels":[],"label_agreement":null},{"id":"W1577423246","doi":"10.1007/11596370_4","title":"Database and Information Retrieval Techniques for XML","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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":"University of Toronto","funders":"","keywords":"Computer science; Viewpoints; Information retrieval; XML; XML database; Focus (optics); XML Schema Editor; Variety (cybernetics); Relational database; Efficient XML Interchange; Document Structure Description; Human–computer information retrieval; Database; Data retrieval; World Wide Web; Search engine; Artificial intelligence","score_opus":0.01337730080614261,"score_gpt":0.25478786221655575,"score_spread":0.24141056141041314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1577423246","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":[0.0029165754,0.03733307,0.93029666,0.0018495502,0.00085875107,0.0001332179,0.00053979806,0.003002577,0.023069832],"genre_scores_gemma":[0.040626608,0.032577127,0.8763978,0.0010809302,0.0015334529,0.00024025058,0.0023534917,0.000789209,0.04440115],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9979347,0.00046545823,0.0002689961,0.00025355106,0.000970611,0.00010666325],"domain_scores_gemma":[0.99867177,0.0005681147,0.00006577716,0.00041478706,0.00024750878,0.000032054108],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020860904,0.00092525664,0.0013406441,0.004743475,0.001093233,0.0045495224,0.0027825043,0.0014140031,0.014846698],"category_scores_gemma":[0.004859905,0.0008927601,0.001599845,0.007928961,0.0014740258,0.008741999,0.001865916,0.0026233154,0.009060777],"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":[0.000090428366,0.00007552072,0.00036890252,0.0012275332,0.00009477633,0.00031566122,0.0006089594,0.0030400718,0.0073245647,0.32432657,0.06266078,0.5998662],"study_design_scores_gemma":[0.00007961972,0.00009926966,0.0008184239,0.0005413841,0.00017653982,0.0025919622,0.0004076823,0.04137905,0.013752152,0.48078865,0.45926693,0.0000983056],"about_ca_topic_score_codex":0.0014874033,"about_ca_topic_score_gemma":0.0016186469,"teacher_disagreement_score":0.014846698,"about_ca_system_score_codex":0.0010343253,"about_ca_system_score_gemma":0.0007273379,"threshold_uncertainty_score":0.04966718},"labels":[],"label_agreement":null},{"id":"W1578656974","doi":"10.1007/978-0-387-39940-9_261","title":"Parallel and Distributed Data Warehouses","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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":"Concordia University","funders":"","keywords":"Data warehouse; Computer science; Database; Warehouse; Business","score_opus":0.03078580710918331,"score_gpt":0.2549172725970601,"score_spread":0.2241314654878768,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1578656974","genre_codex":"methods","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":[0.014141619,0.012154062,0.8786571,0.0029316104,0.0014519321,0.00021948718,0.0010694396,0.008048052,0.08132664],"genre_scores_gemma":[0.14965633,0.016436646,0.6823519,0.0010106172,0.0015139711,0.00033192543,0.0056679435,0.0021313399,0.14089938],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988416,0.00014506704,0.00008875715,0.00025182165,0.00058882404,0.00008400169],"domain_scores_gemma":[0.99876225,0.00028555596,0.00003669282,0.0005973936,0.0002517649,0.00006627453],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014953349,0.00075472525,0.0011604411,0.0010788352,0.00094695843,0.004645216,0.0027125075,0.00078404817,0.015161698],"category_scores_gemma":[0.002803556,0.001164829,0.00093874324,0.004185536,0.0008897871,0.006073324,0.0025988347,0.001688342,0.0060964497],"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":[0.00032803437,0.00022209159,0.0008785715,0.00053015474,0.00012147365,0.0002799859,0.00036308414,0.018407384,0.006712949,0.19735222,0.12286503,0.651939],"study_design_scores_gemma":[0.00014074244,0.00009889566,0.0011925641,0.00014459222,0.0001245667,0.001003184,0.00021889075,0.11931915,0.008860409,0.4229248,0.44591168,0.00006060841],"about_ca_topic_score_codex":0.0012051912,"about_ca_topic_score_gemma":0.0015512715,"teacher_disagreement_score":0.015161698,"about_ca_system_score_codex":0.00080435106,"about_ca_system_score_gemma":0.001294214,"threshold_uncertainty_score":0.05072093},"labels":[],"label_agreement":null},{"id":"W15807817","doi":"10.1007/978-1-4419-8834-8_15","title":"Distributed Object Database Management","year":2011,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Computer science; Relational database; Database design; Database model; XML; Database; Data model (GIS); Semi-structured model; Object (grammar); Relational database management system; Relational model; World Wide Web; Artificial intelligence","score_opus":0.026913706167775088,"score_gpt":0.22986134577480966,"score_spread":0.20294763960703457,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W15807817","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":[0.00197048,0.033295967,0.6060073,0.002036101,0.0030919453,0.00031998337,0.0013222365,0.010246369,0.3417096],"genre_scores_gemma":[0.015717357,0.023326755,0.17381054,0.0011593291,0.0013689826,0.0002839582,0.0048470283,0.0018122095,0.7776739],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99914885,0.00007198657,0.00005772204,0.00017028782,0.0005064914,0.000044699183],"domain_scores_gemma":[0.9994029,0.00010500674,0.00001991799,0.00025432254,0.00018044455,0.000037351077],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008263324,0.0012468202,0.0012748514,0.001751627,0.0010127858,0.0034334476,0.0019505343,0.00089179527,0.035626367],"category_scores_gemma":[0.001308708,0.0010032959,0.0006027805,0.004054752,0.000929869,0.004474746,0.0019902873,0.0023057042,0.039280284],"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":[0.000030189827,0.00006425398,0.00014085446,0.00032710942,0.00002578478,0.000062775594,0.00018141247,0.0012783142,0.0028478552,0.07887231,0.2698631,0.64630604],"study_design_scores_gemma":[0.000009567395,0.000017186267,0.00025624354,0.00012070637,0.000018808038,0.00028341974,0.00003127845,0.0041485047,0.0015684303,0.052637782,0.940891,0.0000170608],"about_ca_topic_score_codex":0.0011724327,"about_ca_topic_score_gemma":0.0017501027,"teacher_disagreement_score":0.035626367,"about_ca_system_score_codex":0.0009982631,"about_ca_system_score_gemma":0.0010777094,"threshold_uncertainty_score":0.11918211},"labels":[],"label_agreement":null},{"id":"W1581000938","doi":"10.1007/978-3-540-30081-6_6","title":"Information Preservation in XML-to-Relational Mappings","year":2004,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":21,"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":"XML; Computer science; Information retrieval; World Wide Web","score_opus":0.01635513214985388,"score_gpt":0.23342142095960067,"score_spread":0.2170662888097468,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1581000938","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":[0.033107795,0.0022900563,0.94729894,0.0009834602,0.00021646198,0.000084946245,0.00028586065,0.0020596832,0.013672817],"genre_scores_gemma":[0.5284092,0.003871849,0.44394815,0.0007509652,0.00051211624,0.00017391506,0.0014290488,0.0010728743,0.01983194],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99485517,0.0017710032,0.0007332771,0.00063718855,0.0016055013,0.00039782774],"domain_scores_gemma":[0.9840502,0.0065289205,0.00060768105,0.0073382165,0.0013021926,0.00017269858],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0059432182,0.0004623234,0.00089232513,0.0018891438,0.0011913469,0.004616204,0.002249329,0.0012376957,0.0039566546],"category_scores_gemma":[0.017106928,0.0009264713,0.0011242877,0.0043274094,0.0022880351,0.014299156,0.0039328136,0.001833318,0.0011933806],"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":[0.0003699455,0.000116610754,0.0018147709,0.000556643,0.00008127089,0.00054749777,0.0013022716,0.017254703,0.0069622067,0.6606428,0.007958312,0.3023929],"study_design_scores_gemma":[0.00005435411,0.00014862897,0.000902112,0.00019236917,0.00023964509,0.0015232341,0.00066564244,0.07556876,0.060251165,0.81802535,0.04236626,0.0000625108],"about_ca_topic_score_codex":0.000878391,"about_ca_topic_score_gemma":0.00068045186,"teacher_disagreement_score":0.0059432182,"about_ca_system_score_codex":0.0007725993,"about_ca_system_score_gemma":0.0010032243,"threshold_uncertainty_score":0.03143114},"labels":[],"label_agreement":null},{"id":"W1581459791","doi":"10.1007/978-3-642-28872-2_12","title":"Intermodeling, Queries, and Kleisli Categories","year":2012,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":30,"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; University of Waterloo","funders":"","keywords":"Computer science; Merge (version control); Metamodeling; Programming language; Algebraic number; Class (philosophy); Algebraic specification; Theoretical computer science; Formal specification; Information retrieval; Artificial intelligence; Mathematics","score_opus":0.017547488329851868,"score_gpt":0.24208348275103417,"score_spread":0.2245359944211823,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1581459791","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":[0.03509612,0.03925299,0.4995351,0.013169363,0.0015535249,0.00017050884,0.0019684727,0.002038886,0.407215],"genre_scores_gemma":[0.6701704,0.0270966,0.18388987,0.0027294669,0.0026300824,0.00054533663,0.005565638,0.0012695604,0.106102966],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99750406,0.00052539125,0.00030817074,0.0005399057,0.0008110759,0.00031139268],"domain_scores_gemma":[0.9985501,0.0006296865,0.00011438958,0.00036381825,0.00024687633,0.00009508423],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020703508,0.0012324513,0.0013186906,0.0034883043,0.0027459462,0.008505494,0.002225998,0.0017229476,0.010071776],"category_scores_gemma":[0.003908744,0.0009341127,0.0014529271,0.0057210033,0.006097681,0.02562764,0.003697029,0.005604868,0.0032964726],"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":[0.000009400722,0.0000065902695,0.00005467906,0.000039296432,0.0000021389453,0.000014811344,0.00018871267,0.00014518823,0.00010947233,0.9881443,0.0025000677,0.008785308],"study_design_scores_gemma":[0.0000035032272,0.0000067701153,0.00004543327,0.000026646636,0.000004914169,0.0000741942,0.0001067824,0.00067927834,0.00014087831,0.9724171,0.026486145,0.000008408824],"about_ca_topic_score_codex":0.0022232535,"about_ca_topic_score_gemma":0.0015596324,"teacher_disagreement_score":0.010071776,"about_ca_system_score_codex":0.0036749244,"about_ca_system_score_gemma":0.0014419265,"threshold_uncertainty_score":0.033693492},"labels":[],"label_agreement":null},{"id":"W1581905079","doi":"10.1007/11546924_73","title":"Control-Based Quality Adaptation in Data Stream Management Systems","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":17,"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; Adaptation (eye); Leverage (statistics); Data quality; Quality (philosophy); Distributed computing; Snapshot (computer storage); Database; Real-time computing; Data mining; Artificial intelligence; Operations management","score_opus":0.044759512239752566,"score_gpt":0.2916343012536584,"score_spread":0.24687478901390586,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1581905079","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":[0.032275174,0.0019053924,0.95989746,0.00035183952,0.00020404997,0.00008747535,0.000045453166,0.0022084026,0.0030247993],"genre_scores_gemma":[0.8771872,0.0009685137,0.116238445,0.000219364,0.00031229752,0.00007374626,0.00014589554,0.0002624117,0.004592112],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99894017,0.00019437209,0.000092270784,0.00017664528,0.00050193776,0.00009457034],"domain_scores_gemma":[0.99814034,0.0007363018,0.00014929341,0.00025968146,0.0006435839,0.00007076624],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021270378,0.0004770933,0.00072674826,0.00063233933,0.00037907166,0.001761843,0.0015932407,0.00054290635,0.001697479],"category_scores_gemma":[0.0054545,0.0003218944,0.00026068676,0.0006971057,0.00058817526,0.001206923,0.00069194136,0.00095183705,0.0003436954],"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":[0.000811552,0.0003758697,0.0021100824,0.0001891959,0.000084332,0.00016894356,0.00034920228,0.16625418,0.062433224,0.019153744,0.007591557,0.74047816],"study_design_scores_gemma":[0.000039824128,0.00010936507,0.00067585096,0.00001348973,0.00003075422,0.00008002044,0.00002479542,0.97501194,0.014497523,0.00640428,0.0030902135,0.000022010472],"about_ca_topic_score_codex":0.0032233528,"about_ca_topic_score_gemma":0.0019732811,"teacher_disagreement_score":0.0032233528,"about_ca_system_score_codex":0.0006921016,"about_ca_system_score_gemma":0.00041387457,"threshold_uncertainty_score":0.011249006},"labels":[],"label_agreement":null},{"id":"W1583292227","doi":"10.1007/3-540-47961-9_21","title":"Babel: An XML-Based Application Integration Framework","year":2002,"lang":"en","type":"book-chapter","venue":"Notes on numerical fluid mechanics and multidisciplinary design","topic":"Advanced Database Systems and Queries","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 Alberta","funders":"","keywords":"Computer science; Business logic; XML; Architectural style; Database; Database schema; Software engineering; Architecture; World Wide Web; Database design","score_opus":0.04159326601869294,"score_gpt":0.2778976785735423,"score_spread":0.23630441255484935,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1583292227","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":[0.0016205362,0.0005988138,0.8518779,0.00033947232,0.00016356604,0.0001591602,0.0016865163,0.13650875,0.0070452886],"genre_scores_gemma":[0.06309601,0.0023986853,0.8120382,0.0022387332,0.00022822696,0.0012830418,0.027995955,0.048959915,0.041761298],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99784875,0.00038303682,0.00026095644,0.00030719253,0.0010073935,0.00019259144],"domain_scores_gemma":[0.99843866,0.0005981189,0.00008397037,0.0003753896,0.00034740486,0.00015648209],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0039228667,0.0017911684,0.001825532,0.0026911343,0.0012200896,0.005065941,0.0043886304,0.0022238714,0.015262225],"category_scores_gemma":[0.0051272935,0.0022135063,0.001681426,0.0025860907,0.001007116,0.007461731,0.0045808298,0.0045212125,0.012932982],"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":[0.0012580844,0.0004509343,0.0012552943,0.0016234372,0.00038392906,0.0007367056,0.0011212799,0.016146488,0.02505107,0.13024978,0.2973656,0.52435744],"study_design_scores_gemma":[0.0004416585,0.00019489034,0.0010879465,0.0006012148,0.0003600973,0.001024331,0.0002079182,0.17999808,0.05063168,0.12542287,0.6397188,0.00031055833],"about_ca_topic_score_codex":0.0039933175,"about_ca_topic_score_gemma":0.0029071553,"teacher_disagreement_score":0.015262225,"about_ca_system_score_codex":0.0008775619,"about_ca_system_score_gemma":0.0018454269,"threshold_uncertainty_score":0.05105722},"labels":[],"label_agreement":null},{"id":"W1583453694","doi":"10.1007/978-3-540-45160-0_50","title":"SQL-Relay: An Event-Driven Rule-Based Database Gateway","year":2003,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","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":"York University","funders":"","keywords":"Computer science; SQL; Gateway (web page); Database; Relay; Data Transformation Services; Event (particle physics); World Wide Web; Query by Example; Physics","score_opus":0.018743500526425153,"score_gpt":0.26022921578115416,"score_spread":0.241485715254729,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1583453694","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":[0.008121047,0.0002663167,0.585946,0.00025134912,0.00019746313,0.00063742796,0.003248414,0.39434138,0.0069905855],"genre_scores_gemma":[0.25099483,0.001221316,0.64275706,0.0025867766,0.00029684138,0.0010974075,0.025385283,0.036672022,0.038988493],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9975139,0.00032896848,0.00038496125,0.0005219504,0.0011226328,0.00012758358],"domain_scores_gemma":[0.9964819,0.0013636459,0.00021614306,0.0011436595,0.00049217936,0.0003024671],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030735796,0.0011466837,0.001841679,0.0017501808,0.00035866155,0.0037227534,0.005452307,0.0016882786,0.014414064],"category_scores_gemma":[0.0073472275,0.0011616666,0.0010103085,0.0010325487,0.0008192722,0.0032833575,0.0024945152,0.002206492,0.01098759],"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":[0.006643657,0.001934236,0.004175112,0.0015154255,0.00057673873,0.002721866,0.0010932509,0.025705649,0.12226556,0.041150227,0.24438116,0.54783714],"study_design_scores_gemma":[0.0014286833,0.0008593393,0.0025102524,0.00022401572,0.00043918937,0.0016131079,0.00020554879,0.5458131,0.2133716,0.040787514,0.19239318,0.0003544893],"about_ca_topic_score_codex":0.0016073626,"about_ca_topic_score_gemma":0.00088963954,"teacher_disagreement_score":0.014414064,"about_ca_system_score_codex":0.00048779344,"about_ca_system_score_gemma":0.0010727057,"threshold_uncertainty_score":0.04821986},"labels":[],"label_agreement":null},{"id":"W1583684453","doi":"","title":"Report: 4th Int'l Workshop on Self-Managing Database Systems (SMDB 2009)","year":2009,"lang":"en","type":"article","venue":"IEEE Data(base) Engineering Bulletin","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Workgroup; Computer science; Database; Cloud computing; Data administration; Database design; Database schema; Operating system","score_opus":0.01998809429709718,"score_gpt":0.24448003281036307,"score_spread":0.22449193851326588,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1583684453","genre_codex":"methods","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":[0.017051712,0.05716744,0.34672874,0.15835248,0.13280262,0.0036437544,0.017257635,0.012162346,0.25483337],"genre_scores_gemma":[0.043182045,0.02982567,0.14561827,0.014616433,0.02474072,0.0018054583,0.044858415,0.004629998,0.69072294],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9926358,0.0016492431,0.0004553148,0.0009529247,0.003595448,0.00071122317],"domain_scores_gemma":[0.9847706,0.0021678114,0.00043289587,0.001816897,0.007479121,0.0033325779],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015929898,0.0017075432,0.0016331364,0.0024793125,0.00212486,0.009031829,0.0035368055,0.0039653876,0.09761753],"category_scores_gemma":[0.01282084,0.00084100955,0.0014049982,0.0019401994,0.0008730806,0.00819083,0.005421338,0.005501338,0.058747727],"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":[0.00020919819,0.00023609734,0.0005712559,0.0002040205,0.000028039862,0.00009955946,0.00017159682,0.0004968246,0.0019160844,0.0056152428,0.88588977,0.10456233],"study_design_scores_gemma":[0.000087700166,0.00016671112,0.0009388557,0.00028265503,0.000036068734,0.00021012752,0.00017266726,0.003329504,0.0028257715,0.0045402627,0.9873646,0.00004515395],"about_ca_topic_score_codex":0.0059063355,"about_ca_topic_score_gemma":0.006602607,"teacher_disagreement_score":0.09761753,"about_ca_system_score_codex":0.002057116,"about_ca_system_score_gemma":0.0053286385,"threshold_uncertainty_score":0.32656318},"labels":[],"label_agreement":null},{"id":"W1584345587","doi":"10.1007/978-1-4419-8834-8_17","title":"Web Data Management","year":2011,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Web page; World Wide Web; Web development; Static web page; Computer science; Dynamic web page; Data Web; Web standards; Page view; Web analytics; Web application security","score_opus":0.07100462287568303,"score_gpt":0.2541407689070059,"score_spread":0.18313614603132283,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1584345587","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":[0.0017571917,0.023134042,0.23058121,0.00328608,0.0023456574,0.00028998972,0.0022022924,0.010311213,0.7260923],"genre_scores_gemma":[0.00689624,0.013174698,0.048375756,0.0013477387,0.0007363794,0.00013571973,0.003592001,0.0016102084,0.92413133],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99941695,0.00004633849,0.00003558565,0.00011456403,0.00035305927,0.000033510605],"domain_scores_gemma":[0.99953246,0.00009850791,0.000015456826,0.00016430726,0.00014805597,0.00004118237],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00060528656,0.0009525008,0.00074700825,0.002612132,0.0008893217,0.0038705803,0.0012006006,0.0008962738,0.062883645],"category_scores_gemma":[0.0012021684,0.0007175301,0.0005080892,0.0048959996,0.0006986993,0.0052144183,0.0017214294,0.0018383521,0.07619277],"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":[0.00001234493,0.000049280832,0.00011167078,0.00023827347,0.000011189652,0.000050094142,0.00015999732,0.00035194782,0.0021652167,0.040167373,0.37052426,0.5861584],"study_design_scores_gemma":[0.0000024910703,0.0000052721825,0.0001796523,0.00009805978,0.0000059446575,0.0001382924,0.000031216292,0.0009205432,0.00088152406,0.01465379,0.9830747,0.00000849792],"about_ca_topic_score_codex":0.0018266264,"about_ca_topic_score_gemma":0.0025712473,"teacher_disagreement_score":0.062883645,"about_ca_system_score_codex":0.00085283525,"about_ca_system_score_gemma":0.00087766774,"threshold_uncertainty_score":0.21036673},"labels":[],"label_agreement":null},{"id":"W1586953409","doi":"10.5109/13505","title":"INFORMATIONAL REPRESENTABILITY FOR CONTEXTS IN DEDEKIND CATEGORIES","year":2002,"lang":"en","type":"article","venue":"Bulletin of informatics and cybernetics","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Francis Xavier University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Dedekind cut; Mathematics; Dedekind sum; Statistics; Combinatorics","score_opus":0.013735807197872969,"score_gpt":0.22621016962729043,"score_spread":0.21247436242941747,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1586953409","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":[0.087472506,0.0015484752,0.85860896,0.002628319,0.00023345393,0.00013822802,0.00062211294,0.0003556139,0.04839227],"genre_scores_gemma":[0.8126887,0.001057818,0.1761353,0.00072432513,0.00029820102,0.00030586743,0.0008748088,0.00011327451,0.0078016804],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99536467,0.001398808,0.00045371606,0.00084724673,0.0013122024,0.0006233321],"domain_scores_gemma":[0.99503446,0.0025079416,0.000312513,0.00092876976,0.0009594431,0.00025684244],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0039138068,0.0006048794,0.0007076164,0.0027292753,0.0030991177,0.0047627725,0.0015717989,0.0016985622,0.004702894],"category_scores_gemma":[0.0070335353,0.0006409865,0.002112568,0.0017951388,0.004909129,0.011320247,0.0048935325,0.003929589,0.0007666116],"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":[0.000008637866,0.000005431062,0.00008465573,0.00002351881,0.0000032141022,0.000052225758,0.00026579248,0.00034826586,0.0003017366,0.99626017,0.00020508298,0.002441199],"study_design_scores_gemma":[0.0000073594824,0.00001272467,0.00009514397,0.000018074696,0.00000967263,0.00009663646,0.00012240202,0.002507269,0.000762378,0.9904936,0.0058593727,0.000015415071],"about_ca_topic_score_codex":0.0015068062,"about_ca_topic_score_gemma":0.0010316628,"teacher_disagreement_score":0.0047627725,"about_ca_system_score_codex":0.0020137308,"about_ca_system_score_gemma":0.0011021575,"threshold_uncertainty_score":0.020698428},"labels":[],"label_agreement":null},{"id":"W1589843944","doi":"10.1007/11687238_86","title":"Querying Mediated Geographic Data Sources","year":2006,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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":"Saint Paul University","funders":"","keywords":"Computer science; Geographic information system; The Internet; Publication; World Wide Web; Data science; Database; Geography; Remote sensing; Business","score_opus":0.022745212040741536,"score_gpt":0.2476046827282162,"score_spread":0.22485947068747467,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1589843944","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":[0.030175265,0.0020483804,0.9109677,0.0014116246,0.00025800325,0.0002181331,0.0029349755,0.011490275,0.040495522],"genre_scores_gemma":[0.37804106,0.0044383914,0.52840585,0.00065929285,0.00031454497,0.00030616813,0.016613951,0.0019939952,0.06922682],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99779296,0.0003966991,0.00016836444,0.00030521333,0.0012405032,0.000096355965],"domain_scores_gemma":[0.99829084,0.00065636483,0.0000593491,0.0006637678,0.00027615522,0.000053400516],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018218359,0.00080949825,0.0012404432,0.0027603174,0.0009492253,0.007108356,0.0032460252,0.0017535007,0.012113754],"category_scores_gemma":[0.0068717655,0.000792643,0.0010351796,0.0050685857,0.0012119903,0.0073391325,0.0047608786,0.0012356091,0.0047202483],"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":[0.00032080276,0.00019384715,0.004164084,0.0011118056,0.00036199254,0.0015040735,0.0033061407,0.024772696,0.024790162,0.41929758,0.05440097,0.46577573],"study_design_scores_gemma":[0.00008438266,0.00009299796,0.00156361,0.00027935876,0.00025650734,0.002053485,0.0017952747,0.23005742,0.05290432,0.3137391,0.39702564,0.00014790733],"about_ca_topic_score_codex":0.0038568398,"about_ca_topic_score_gemma":0.0057444316,"teacher_disagreement_score":0.012113754,"about_ca_system_score_codex":0.0011404179,"about_ca_system_score_gemma":0.0008190548,"threshold_uncertainty_score":0.040524542},"labels":[],"label_agreement":null},{"id":"W1590056848","doi":"10.5555/1784489.1784510","title":"An ontological metamodel of classifiers and its application to conceptual modelling and database design","year":2007,"lang":"en","type":"article","venue":"International Conference on Conceptual Modeling","topic":"Advanced Database Systems and Queries","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":"Memorial University of Newfoundland","funders":"","keywords":"Metamodeling; Computer science; Conceptual model; Representation (politics); Ontology; Software engineering; Database; Data science; Artificial intelligence","score_opus":0.18754182472760933,"score_gpt":0.34967970205772386,"score_spread":0.16213787733011453,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1590056848","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":[0.0035425713,0.00008092073,0.99291694,0.00045428987,0.000037718364,0.00009057645,0.00034528415,0.00050357386,0.0020281605],"genre_scores_gemma":[0.07351961,0.0003000535,0.9222864,0.00021524583,0.000054665747,0.00026453607,0.0010629946,0.00019559203,0.0021008991],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99784446,0.00067024207,0.00041128998,0.0003154327,0.000639799,0.000118644166],"domain_scores_gemma":[0.9962012,0.0012316396,0.00026279638,0.0012087169,0.0008862428,0.0002093352],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0045406036,0.00045420788,0.00064457854,0.0023939188,0.0014570131,0.004055919,0.0018513456,0.0015582318,0.0025120466],"category_scores_gemma":[0.009091096,0.00075220363,0.0020513593,0.0025003096,0.0016293941,0.006916269,0.0018833589,0.0024206948,0.00093251735],"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":[0.00004143464,0.00007102581,0.0011881053,0.00012338356,0.00003407641,0.00019135991,0.0010347277,0.011912271,0.0032171798,0.93325984,0.0035924925,0.04533424],"study_design_scores_gemma":[0.000028428269,0.00005620767,0.0006102528,0.00024329199,0.00014624224,0.00039595892,0.00045375506,0.2571295,0.004831041,0.62775767,0.108290374,0.000057293866],"about_ca_topic_score_codex":0.0070461286,"about_ca_topic_score_gemma":0.009373939,"teacher_disagreement_score":0.0070461286,"about_ca_system_score_codex":0.0016506866,"about_ca_system_score_gemma":0.0026410287,"threshold_uncertainty_score":0.02401334},"labels":[],"label_agreement":null},{"id":"W1590183325","doi":"10.1016/b978-155860869-6/50074-3","title":"Quotient Cube","year":2002,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":187,"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":"Cube (algebra); Online analytical processing; Data cube; Monotone polygon; Computer science; Theoretical computer science; Algorithm; Quotient; Mathematics; Data mining; Data warehouse; Combinatorics","score_opus":0.01896972886198495,"score_gpt":0.22520496368360027,"score_spread":0.20623523482161532,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1590183325","genre_codex":"other","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":[0.018844103,0.003287412,0.1322472,0.0025136063,0.0014693168,0.00015174513,0.0038065335,0.0017797834,0.83590037],"genre_scores_gemma":[0.2640299,0.006598547,0.14402233,0.0013799856,0.0010428586,0.00038627998,0.014145944,0.0013912335,0.567003],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995297,0.000052130494,0.000031448682,0.00009953944,0.00023097993,0.000056130586],"domain_scores_gemma":[0.9996445,0.00006757781,0.000016913296,0.00010080324,0.00012638509,0.00004378173],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003114993,0.0007961782,0.00086870417,0.0012228767,0.0012773826,0.0035278043,0.001125007,0.0005540839,0.06466211],"category_scores_gemma":[0.0013841031,0.00031934847,0.0006739445,0.0022703076,0.0010516895,0.00519811,0.0024867544,0.0018065881,0.017089322],"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":[0.00008756357,0.0000354819,0.0001644658,0.00015162068,0.000013237922,0.0000879264,0.000107050975,0.001310615,0.0010480497,0.7816617,0.07700401,0.13832821],"study_design_scores_gemma":[0.000017147338,0.000017542296,0.00013138352,0.000040682673,0.000013481194,0.00019097805,0.00009562668,0.0031831693,0.0010420759,0.8076725,0.18758532,0.00001010399],"about_ca_topic_score_codex":0.0020231504,"about_ca_topic_score_gemma":0.00176022,"teacher_disagreement_score":0.06466211,"about_ca_system_score_codex":0.0011601858,"about_ca_system_score_gemma":0.00094767957,"threshold_uncertainty_score":0.21631628},"labels":[],"label_agreement":null},{"id":"W1592178743","doi":"10.1007/978-3-540-25957-2_33","title":"Flexible User Interface for Converting Relational Data into XML","year":2004,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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":"University of Calgary","funders":"","keywords":"Computer science; XML validation; XML Schema Editor; XML database; Document Structure Description; Efficient XML Interchange; Streaming XML; XML Encryption; XML; XML Schema (W3C); Information retrieval; RELAX NG; Relational database; Database; Programming language; World Wide Web","score_opus":0.045171638871911175,"score_gpt":0.3006949604193496,"score_spread":0.25552332154743845,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1592178743","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":[0.0042419764,0.00027123856,0.72501117,0.0002687925,0.00023600971,0.0002781342,0.0041081524,0.2554377,0.010146842],"genre_scores_gemma":[0.11013229,0.00070442795,0.6836963,0.0020694972,0.00023279978,0.0017017799,0.026443532,0.077562205,0.09745707],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989483,0.00016883321,0.00014335988,0.0001882052,0.00044765134,0.000103705],"domain_scores_gemma":[0.9971214,0.0014065874,0.000076105076,0.0007675932,0.0004789949,0.00014925883],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002236865,0.0018746662,0.0011736512,0.0018247518,0.00073012756,0.0026650387,0.0030928424,0.001857037,0.07259313],"category_scores_gemma":[0.006053848,0.0013377041,0.0010983177,0.0016160941,0.00054780446,0.0035550792,0.003672483,0.0018631571,0.023786604],"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":[0.0021848704,0.00031336036,0.0017807853,0.00085966144,0.0001367285,0.0016115125,0.0014093238,0.0021836685,0.061098814,0.020441985,0.36324766,0.54473174],"study_design_scores_gemma":[0.00075778936,0.00039119224,0.0032549885,0.0004565348,0.00026751336,0.003091929,0.0004313457,0.11329623,0.20009437,0.024942134,0.6525533,0.00046272445],"about_ca_topic_score_codex":0.0016661255,"about_ca_topic_score_gemma":0.0020851495,"teacher_disagreement_score":0.07259313,"about_ca_system_score_codex":0.00053240685,"about_ca_system_score_gemma":0.0005323338,"threshold_uncertainty_score":0.24284822},"labels":[],"label_agreement":null},{"id":"W1592716016","doi":"10.1007/bfb0027525","title":"Database management systems for statistical and scientific applications: Are commercially available DBMS good enough?","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","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":"Statistics Canada","funders":"","keywords":"Computer science; Database; Relation (database); Relational database; Data science; Set (abstract data type); Information system; Relational database management system; Engineering","score_opus":0.023796753880219425,"score_gpt":0.2627817110291686,"score_spread":0.23898495714894916,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1592716016","genre_codex":"commentary","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":[0.011741832,0.35429484,0.08716561,0.38693437,0.016538462,0.0001748537,0.0011618629,0.005051086,0.13693707],"genre_scores_gemma":[0.17327839,0.3770371,0.2138473,0.070889816,0.024928091,0.00033203317,0.0023783841,0.003292434,0.13401647],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9949765,0.001203805,0.00035343633,0.00037844686,0.0027017335,0.00038608277],"domain_scores_gemma":[0.9784555,0.011738777,0.0011533238,0.0022342568,0.0049587497,0.0014594153],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015378787,0.0007251536,0.0012326027,0.001611896,0.0008190856,0.010062581,0.0025220672,0.0039301324,0.017016955],"category_scores_gemma":[0.02498741,0.0006991013,0.0007490983,0.0029225894,0.0027267248,0.02662312,0.0019150586,0.004071814,0.011554837],"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":[0.00011124635,0.00014642843,0.0011906285,0.0015764228,0.0000802416,0.00012908407,0.0004537632,0.00043110317,0.0017947386,0.10504876,0.33551276,0.55352485],"study_design_scores_gemma":[0.00005270842,0.00014905572,0.0014665795,0.001338662,0.00008102466,0.00046634965,0.0005266531,0.001421278,0.0018117586,0.10406494,0.8885684,0.000052653806],"about_ca_topic_score_codex":0.0009073128,"about_ca_topic_score_gemma":0.001186223,"teacher_disagreement_score":0.017016955,"about_ca_system_score_codex":0.0013307692,"about_ca_system_score_gemma":0.002384329,"threshold_uncertainty_score":0.08133179},"labels":[],"label_agreement":null},{"id":"W1595032544","doi":"10.1109/icppw.2014.24","title":"Soft Real-Time OLAP: Exploiting Modern Hardware without Breaking the Bank","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Online analytical processing; Computer science; Tuple; Partition (number theory); Analytics; Query optimization; Stream processing; Big data; Database; Distributed computing; Real-time computing; Data mining; Data warehouse","score_opus":0.014496174513038296,"score_gpt":0.23961465935067172,"score_spread":0.22511848483763341,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1595032544","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":[0.06735889,0.0019135628,0.9133819,0.0008589986,0.00023383419,0.0001758235,0.00030663493,0.010241915,0.0055284845],"genre_scores_gemma":[0.40461567,0.0010123944,0.58894783,0.0005195818,0.00020969438,0.00015645266,0.0007424944,0.0008491348,0.0029468078],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9979201,0.00032011463,0.00015575289,0.00042903714,0.00087614806,0.00029886575],"domain_scores_gemma":[0.9935681,0.0009499055,0.00044103232,0.0042830687,0.00047103374,0.00028683536],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002077732,0.0015439631,0.00083740475,0.0011307267,0.00114886,0.0042352905,0.004791198,0.000833195,0.0028658283],"category_scores_gemma":[0.005145671,0.0010915331,0.0009025894,0.0023520656,0.0019315593,0.009341586,0.005340674,0.0023385778,0.0016092835],"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":[0.0013411324,0.0005118745,0.006932829,0.00045852113,0.0002140318,0.00042451877,0.0010892894,0.07067839,0.08378262,0.042243026,0.025419671,0.7669041],"study_design_scores_gemma":[0.00020620093,0.00065135316,0.0033722492,0.00010928287,0.00018901484,0.0009303321,0.00084342586,0.77119166,0.08474272,0.08640614,0.05113705,0.00022060593],"about_ca_topic_score_codex":0.00465852,"about_ca_topic_score_gemma":0.004714832,"teacher_disagreement_score":0.004791198,"about_ca_system_score_codex":0.0008766384,"about_ca_system_score_gemma":0.0019051913,"threshold_uncertainty_score":0.0109882355},"labels":[],"label_agreement":null},{"id":"W1595062593","doi":"","title":"Simulated annealing for materialized view selection in data warehousing environment","year":2006,"lang":"en","type":"article","venue":"Griffith Research Online (Griffith University, Queensland, Australia)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Materialized view; Computer science; Data warehouse; Simulated annealing; Data mining; Heuristic; Set (abstract data type); Database; Selection (genetic algorithm); Data processing; Quality (philosophy); Query optimization; Information retrieval; View; Machine learning; Artificial intelligence","score_opus":0.22404386161164952,"score_gpt":0.3931044109613604,"score_spread":0.16906054934971088,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1595062593","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":[0.04205381,0.00039118243,0.954172,0.00020347221,0.000027513976,0.00010559101,0.00004487271,0.00033961603,0.0026619907],"genre_scores_gemma":[0.57536745,0.00037230985,0.4216275,0.00011220799,0.000029603592,0.0004101893,0.00014653099,0.00011611505,0.0018181613],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992956,0.00039646795,0.000026291631,0.00008792029,0.00013891982,0.00005482558],"domain_scores_gemma":[0.99874556,0.0009793849,0.00006612582,0.00008181288,0.00008646595,0.000040750518],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009864682,0.0005552997,0.00073188863,0.0004678852,0.00047387445,0.00076557056,0.000765665,0.00096665067,0.0014337895],"category_scores_gemma":[0.0025282814,0.00050643773,0.0008822746,0.00046845173,0.00087737176,0.00072511355,0.0007279627,0.0009241583,0.0001957288],"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":[0.000054141765,0.000022889677,0.00025299028,0.00003010111,0.000022164117,0.000032349635,0.000065005195,0.97948,0.0023618785,0.0072481968,0.00026760215,0.010162644],"study_design_scores_gemma":[0.0000123069085,0.000028668395,0.00007690909,0.000003228016,0.0000062584363,0.0000066704565,0.000008621681,0.9950282,0.0007835276,0.0035448412,0.00049677654,0.0000040514115],"about_ca_topic_score_codex":0.003360984,"about_ca_topic_score_gemma":0.002697138,"teacher_disagreement_score":0.003360984,"about_ca_system_score_codex":0.0011582176,"about_ca_system_score_gemma":0.00091054174,"threshold_uncertainty_score":0.00840354},"labels":[],"label_agreement":null},{"id":"W1596342849","doi":"10.1007/11575771_28","title":"Containment of Conjunctive Queries with Arithmetic Expressions","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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":"Concordia University","funders":"","keywords":"Containment (computer programming); Conjunctive query; Rewriting; Computer science; Boolean conjunctive query; Theoretical computer science; Arithmetic; Database; Mathematics; Sargable; Information retrieval; Programming language; Web search query; Relational database; Search engine","score_opus":0.01088078553244383,"score_gpt":0.23339617650563524,"score_spread":0.2225153909731914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1596342849","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":[0.056073427,0.0021556069,0.892833,0.0018166725,0.0002731542,0.0002503343,0.0011580718,0.004805534,0.040634133],"genre_scores_gemma":[0.49774948,0.0024458517,0.46845278,0.0012326532,0.0012992149,0.0005339463,0.0075984886,0.0021262132,0.018561356],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9813417,0.0047228253,0.001704942,0.0020447618,0.008904805,0.0012809896],"domain_scores_gemma":[0.9486814,0.042507295,0.001708114,0.003187117,0.00341339,0.00050266425],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007480474,0.0013721538,0.0024671096,0.0033935292,0.0023612215,0.008918568,0.004479083,0.0020668309,0.0085561825],"category_scores_gemma":[0.033531774,0.003023445,0.0021132694,0.0057352097,0.0058138077,0.019233143,0.0064143334,0.0044892966,0.0024167579],"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":[0.00046761532,0.00017624904,0.0013703302,0.0007110305,0.00008249251,0.0009862849,0.0034931328,0.008836596,0.00925374,0.8684285,0.014355988,0.091838114],"study_design_scores_gemma":[0.00014184,0.00009424194,0.0007080738,0.0001695598,0.00017357782,0.0010408849,0.0009050721,0.082156,0.020178743,0.8717153,0.022620017,0.00009658085],"about_ca_topic_score_codex":0.0032015473,"about_ca_topic_score_gemma":0.0017881027,"teacher_disagreement_score":0.008918568,"about_ca_system_score_codex":0.0023957666,"about_ca_system_score_gemma":0.0021058565,"threshold_uncertainty_score":0.039560974},"labels":[],"label_agreement":null},{"id":"W1596568456","doi":"","title":"Statistical learning techniques for costing XML queries","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":66,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Comet; XML database; Information retrieval; Data mining; XML validation; Query optimization; Streaming XML; Database; XML; World Wide Web","score_opus":0.014801109867619575,"score_gpt":0.28921304832496086,"score_spread":0.2744119384573413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1596568456","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":[0.004120448,0.0006530594,0.99375385,0.00031575852,0.000026403819,0.0000474827,0.0001306414,0.00028543986,0.000666924],"genre_scores_gemma":[0.35140628,0.0038073885,0.6372101,0.000504429,0.00057154085,0.0007983471,0.0017676383,0.00041363135,0.0035207632],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99512637,0.0018683394,0.0003481118,0.0006083482,0.0018365663,0.0002122124],"domain_scores_gemma":[0.98058033,0.015114173,0.0013683926,0.0012423513,0.0015077346,0.00018711282],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0064681736,0.0015634937,0.0017138256,0.0033893292,0.00054090226,0.0020218974,0.0024018097,0.001425678,0.0019374691],"category_scores_gemma":[0.026084261,0.00082401594,0.0014500673,0.004907282,0.0011285347,0.0051206043,0.001469133,0.0029952999,0.00053079054],"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":[0.00005370503,0.000111266774,0.0021068773,0.0001505896,0.00012774415,0.000047828875,0.000052813546,0.78671414,0.00056836795,0.08642035,0.0029487598,0.12069752],"study_design_scores_gemma":[0.000004536502,0.000019639383,0.00014086155,0.000006334627,0.000010103763,0.0000150822125,0.0000071096038,0.9665168,0.0002181902,0.032327984,0.000726598,0.0000067783144],"about_ca_topic_score_codex":0.0046135667,"about_ca_topic_score_gemma":0.0045153447,"teacher_disagreement_score":0.0064681736,"about_ca_system_score_codex":0.0026885697,"about_ca_system_score_gemma":0.0017012083,"threshold_uncertainty_score":0.034207404},"labels":[],"label_agreement":null},{"id":"W1599200063","doi":"10.1007/s10115-015-0871-2","title":"Partial materialization for online analytical processing over multi-tagged document collections","year":2015,"lang":"en","type":"article","venue":"Knowledge and Information Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"University of Waterloo; Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Computer science; Centroid; Information retrieval; Medoid; Document clustering; Digital library; Data mining; Artificial intelligence; Cluster analysis","score_opus":0.04078338301597355,"score_gpt":0.3180951839573361,"score_spread":0.27731180094136254,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1599200063","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":[0.031239547,0.0004666232,0.954784,0.00035311055,0.000071345836,0.00044748856,0.0013761518,0.009003701,0.002257974],"genre_scores_gemma":[0.21575274,0.00050695206,0.7720177,0.00018624983,0.00014075254,0.0007977035,0.004886377,0.0008160646,0.004895428],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978696,0.00040304978,0.00035559133,0.0004327748,0.0007509559,0.000187995],"domain_scores_gemma":[0.99222845,0.0021749125,0.00069840776,0.0029066931,0.0017104524,0.00028093957],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002305905,0.0010386108,0.0013090145,0.0038835816,0.0016125975,0.004334277,0.0026177135,0.0007460133,0.0068416586],"category_scores_gemma":[0.012569184,0.00069117325,0.0012608279,0.0078025176,0.0013569426,0.0056377854,0.0047327313,0.00088155956,0.0045478106],"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":[0.0012372271,0.0002480588,0.0029594293,0.0005707243,0.000105318155,0.00060482736,0.0016574,0.027705882,0.04573967,0.03069949,0.018357761,0.87011427],"study_design_scores_gemma":[0.00030811617,0.0015100654,0.005626458,0.00017335157,0.00030136414,0.0026976755,0.0037671686,0.6165429,0.17494333,0.09046786,0.103354685,0.00030704378],"about_ca_topic_score_codex":0.002478098,"about_ca_topic_score_gemma":0.0030295064,"teacher_disagreement_score":0.0068416586,"about_ca_system_score_codex":0.0011350607,"about_ca_system_score_gemma":0.0025492616,"threshold_uncertainty_score":0.022887647},"labels":[],"label_agreement":null},{"id":"W1599579342","doi":"10.1007/bfb0024361","title":"Temporal extensions to a uniform behavioral object model","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":24,"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; Construct (python library); Inheritance (genetic algorithm); Set (abstract data type); Semantics (computer science); Object (grammar); Behavioral modeling; Extensibility; Programming language; Behavioral pattern; Theoretical computer science; Temporal logic; Artificial intelligence","score_opus":0.030477589399131148,"score_gpt":0.2854319055532071,"score_spread":0.25495431615407593,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1599579342","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":[0.018862974,0.00016963226,0.96682703,0.00031974414,0.000108353226,0.00005485348,0.00019370635,0.0009652869,0.012498372],"genre_scores_gemma":[0.44603166,0.0005998986,0.5192158,0.0004824883,0.00032222053,0.0004033977,0.00085838663,0.00067360763,0.031412546],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983139,0.0004333517,0.00024631896,0.00035652675,0.00043700216,0.00021291326],"domain_scores_gemma":[0.99542737,0.0011924707,0.00033263885,0.0021459078,0.0006716347,0.00022994659],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028946951,0.00071143813,0.0005017158,0.0008354859,0.000924968,0.0022454038,0.0019200833,0.0010470833,0.0060365056],"category_scores_gemma":[0.005954009,0.0008350095,0.0016516187,0.0011735052,0.001910235,0.0079334965,0.002749031,0.0026225122,0.0009821234],"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":[0.000042725882,0.000026737376,0.00012806052,0.000027438158,0.000007028467,0.000057461068,0.00014383341,0.0037451051,0.0013051104,0.9840567,0.0006733418,0.009786415],"study_design_scores_gemma":[0.000044414865,0.00006357562,0.00014658843,0.000042734548,0.00006141755,0.00014379072,0.000074097276,0.07926924,0.0028915848,0.8973711,0.019868806,0.000022717151],"about_ca_topic_score_codex":0.0021002847,"about_ca_topic_score_gemma":0.0021009254,"teacher_disagreement_score":0.0060365056,"about_ca_system_score_codex":0.0011701199,"about_ca_system_score_gemma":0.0009579485,"threshold_uncertainty_score":0.020194173},"labels":[],"label_agreement":null},{"id":"W1599776405","doi":"10.4018/978-1-93177-747-6.ch005","title":"Building Signature-Trees on Path Signatures in Document Databases","year":2011,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Computer science; Signature (topology); XML; Path (computing); Simple API for XML; Search engine indexing; Implementation; Database; Path expression; Object (grammar); Java; Information retrieval; XML database; Document Object Model; Data mining; XML Signature; Programming language; Efficient XML Interchange; World Wide Web; Artificial intelligence","score_opus":0.02156527490541609,"score_gpt":0.2647388258782904,"score_spread":0.2431735509728743,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1599776405","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":[0.0062449267,0.0025175049,0.9764212,0.00028044233,0.00011877326,0.00014091686,0.00041276545,0.0030828572,0.010780623],"genre_scores_gemma":[0.047773175,0.004815753,0.93211704,0.00019680987,0.000095019845,0.00014923736,0.0013274851,0.000859474,0.012665926],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99869627,0.00025356747,0.00013870746,0.00015906438,0.00065900804,0.00009342453],"domain_scores_gemma":[0.99865973,0.00059796637,0.000062392326,0.0003625067,0.00025549182,0.00006188235],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014145129,0.0005545906,0.0007652773,0.0017316607,0.00089913665,0.003137822,0.001394164,0.00082898507,0.0042080963],"category_scores_gemma":[0.0042078085,0.0008063475,0.00095737743,0.0047894744,0.0009724031,0.0083753,0.0023606129,0.001780887,0.0036412422],"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":[0.00009455021,0.00007293618,0.0005968644,0.00045607335,0.000037302852,0.00026330835,0.00073829404,0.013693858,0.006958156,0.36817044,0.019848123,0.5890701],"study_design_scores_gemma":[0.000039289513,0.00010805931,0.0003955926,0.00028633687,0.0000504029,0.0008637661,0.000329307,0.14272715,0.017872995,0.51549345,0.32176617,0.00006758491],"about_ca_topic_score_codex":0.0017226205,"about_ca_topic_score_gemma":0.0021090284,"teacher_disagreement_score":0.0042080963,"about_ca_system_score_codex":0.001085298,"about_ca_system_score_gemma":0.0013204865,"threshold_uncertainty_score":0.014077485},"labels":[],"label_agreement":null},{"id":"W1600707517","doi":"","title":"ToX, the Toronto XML Server.","year":2002,"lang":"en","type":"article","venue":"International Database Engineering and Applications Symposium","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; XML; World Wide Web; Database","score_opus":0.008685978233737922,"score_gpt":0.2176949170160104,"score_spread":0.20900893878227247,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1600707517","genre_codex":"software","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":[0.0056953323,0.0029776022,0.10744119,0.0035363778,0.0011012506,0.00061760074,0.2244003,0.4467827,0.20744766],"genre_scores_gemma":[0.051751085,0.0053357715,0.07223327,0.001616249,0.00037320636,0.00053344405,0.5528194,0.037258502,0.27807915],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989974,0.000093270355,0.00008254213,0.0001777654,0.00048003887,0.00016901453],"domain_scores_gemma":[0.99768853,0.0002517875,0.0001262892,0.00062407996,0.00075517787,0.0005540205],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010959352,0.0019980615,0.0008775624,0.0021589827,0.0015493562,0.0046276683,0.0038975244,0.0014990061,0.16138113],"category_scores_gemma":[0.0042300206,0.0015541087,0.00044514734,0.0034003141,0.0008226364,0.00493967,0.002742264,0.0020686728,0.15056807],"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":[0.00028778493,0.00002500692,0.00065164844,0.00022378049,0.000019211395,0.00010246717,0.00014234314,0.00072338426,0.0027746344,0.009791007,0.9397495,0.04550922],"study_design_scores_gemma":[0.00015403952,0.000041058895,0.0017427529,0.00016703761,0.000042870957,0.00023026978,0.00024307377,0.008117851,0.0082722595,0.0117437085,0.96915185,0.00009318552],"about_ca_topic_score_codex":0.131789,"about_ca_topic_score_gemma":0.12600723,"teacher_disagreement_score":0.16138113,"about_ca_system_score_codex":0.004382778,"about_ca_system_score_gemma":0.0070854067,"threshold_uncertainty_score":0.53987366},"labels":[],"label_agreement":null},{"id":"W1601989522","doi":"10.1007/978-3-540-75288-2_4","title":"Fast Answering of XPath Query Workloads on Web Collections","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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":"University of Toronto","funders":"","keywords":"XPath; Computer science; XML; Information retrieval; RSS; World Wide Web; XML database; XSLT; Web application; Database","score_opus":0.02087373953241594,"score_gpt":0.2583137001842508,"score_spread":0.23743996065183487,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1601989522","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":[0.7419427,0.0030350517,0.20044774,0.0014849128,0.00057544623,0.000472258,0.005607248,0.039136834,0.00729778],"genre_scores_gemma":[0.802028,0.0010254899,0.17208269,0.00040253584,0.0004976244,0.000268508,0.012986009,0.0017252881,0.008983803],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9955205,0.0007183523,0.00038853538,0.00084726216,0.0019602173,0.00056524685],"domain_scores_gemma":[0.9869571,0.0073768813,0.0005455961,0.0023743305,0.0020446214,0.0007015362],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029691672,0.001619015,0.0023495995,0.0021462587,0.0013140129,0.0028113946,0.0033080336,0.0013837913,0.005166263],"category_scores_gemma":[0.0121139195,0.0012049021,0.00092353206,0.0041398164,0.0005218693,0.005280317,0.0020538177,0.001503064,0.002144505],"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":[0.005897687,0.0010546788,0.019780053,0.0013141823,0.00038357405,0.00095830025,0.0012982028,0.066397,0.097385995,0.0065609836,0.08612283,0.7128466],"study_design_scores_gemma":[0.0002944349,0.00049768074,0.005942699,0.000034907847,0.00014332322,0.00054352614,0.00091368426,0.9397558,0.034584012,0.01121267,0.0060245222,0.00005271923],"about_ca_topic_score_codex":0.0073395283,"about_ca_topic_score_gemma":0.011941537,"teacher_disagreement_score":0.0073395283,"about_ca_system_score_codex":0.0012807692,"about_ca_system_score_gemma":0.0019762698,"threshold_uncertainty_score":0.017282844},"labels":[],"label_agreement":null},{"id":"W1602598615","doi":"10.1109/tools.1997.654697","title":"A framework for temporal data models: exploiting object-oriented technology","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Temporal database; Computer science; Data modeling; Set (abstract data type); Relational database; Object (grammar); Relational model; Data model (GIS); Temporal logic; Data mining; Artificial intelligence; Theoretical computer science; Database; Programming language","score_opus":0.1262307217843581,"score_gpt":0.31198290731501316,"score_spread":0.18575218553065506,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1602598615","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":[0.00042920376,0.0007499816,0.99520445,0.000596269,0.00012884378,0.000096842494,0.00012081081,0.00066823774,0.002005416],"genre_scores_gemma":[0.012239116,0.0017321716,0.98307884,0.0002869955,0.00031311077,0.00030450072,0.00039197004,0.00024280802,0.001410408],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9937453,0.002212933,0.00089131546,0.0008701365,0.0019420335,0.0003382239],"domain_scores_gemma":[0.99202543,0.003480656,0.00079736864,0.0023023698,0.00096617796,0.00042787718],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010703649,0.0016873009,0.0015372253,0.003826155,0.0025307958,0.011420691,0.005412134,0.0029603946,0.0031692567],"category_scores_gemma":[0.01491708,0.0017494231,0.0041827504,0.005058333,0.0053089685,0.017294697,0.005597381,0.0065576355,0.001921761],"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":[0.00002845259,0.000039626982,0.00026383612,0.00019279885,0.000052766212,0.00030532177,0.00076574803,0.008624139,0.00083690276,0.9397881,0.005201307,0.0439009],"study_design_scores_gemma":[0.000042991764,0.00005438432,0.00012116125,0.00038708403,0.00010907346,0.00061479816,0.00023462782,0.079934776,0.0015251536,0.70471644,0.21216644,0.00009308449],"about_ca_topic_score_codex":0.007258715,"about_ca_topic_score_gemma":0.0059881923,"teacher_disagreement_score":0.011420691,"about_ca_system_score_codex":0.0023815448,"about_ca_system_score_gemma":0.0040401607,"threshold_uncertainty_score":0.056607008},"labels":[],"label_agreement":null},{"id":"W1603847311","doi":"","title":"Query processing and optimization in native xml databases","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Path expression; XPath; XQuery; XML; Query language; XML database; Path (computing); Query optimization; Database; Theoretical computer science; Information retrieval; Programming language; World Wide Web","score_opus":0.015957522069428264,"score_gpt":0.25893715495818204,"score_spread":0.24297963288875377,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1603847311","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":[0.12794478,0.0010436197,0.8594548,0.0005810859,0.00006925117,0.0001604214,0.00030562424,0.004168593,0.0062717767],"genre_scores_gemma":[0.5943501,0.0005156143,0.39946246,0.00023927396,0.000065905595,0.00019050439,0.00066664635,0.00026834162,0.0042411755],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9967064,0.0011402251,0.00032004656,0.00040570318,0.0011714734,0.00025605774],"domain_scores_gemma":[0.9975036,0.0014419759,0.00012446943,0.0002861704,0.00058326777,0.000060565715],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032313815,0.0003626575,0.0006314086,0.00070971507,0.0006055246,0.0031237716,0.0012452655,0.0004458406,0.0012095078],"category_scores_gemma":[0.0056246594,0.00035655178,0.00056305085,0.0013070244,0.00074133,0.0020972816,0.0016416361,0.00053663965,0.00027663383],"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":[0.00089144695,0.0004120787,0.0053440453,0.00055322284,0.0001717983,0.00075585453,0.0010173806,0.49462065,0.022987608,0.14733268,0.015631258,0.31028196],"study_design_scores_gemma":[0.00003939266,0.000042286505,0.00035790732,0.000010317314,0.000020410036,0.00009340551,0.00018481156,0.9637367,0.008269138,0.023890836,0.003345585,0.000009158068],"about_ca_topic_score_codex":0.0047821524,"about_ca_topic_score_gemma":0.00463703,"teacher_disagreement_score":0.0047821524,"about_ca_system_score_codex":0.0011729096,"about_ca_system_score_gemma":0.0013147459,"threshold_uncertainty_score":0.017089367},"labels":[],"label_agreement":null},{"id":"W1604005737","doi":"","title":"Identifying Objects Over Time with Description Logics.","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Theoretical computer science; Path (computing); Function (biology); Reduction (mathematics); Temporal logic; Boolean function; Programming language; Algorithm; Mathematics","score_opus":0.03187294018422622,"score_gpt":0.22801359048354333,"score_spread":0.1961406502993171,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1604005737","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":[0.0012256618,0.0022250675,0.9849241,0.0018024696,0.00015249068,0.00013622119,0.0006532677,0.000700007,0.008180731],"genre_scores_gemma":[0.083182044,0.005486171,0.89619833,0.0017396242,0.0007470135,0.0008615802,0.0022786015,0.00037463993,0.009132071],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98872036,0.004621264,0.0015424367,0.0017981754,0.0028133467,0.0005044546],"domain_scores_gemma":[0.9825836,0.011720282,0.0011022441,0.0032563545,0.0009010898,0.0004364023],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01170702,0.0022110813,0.0014237644,0.0047493065,0.002025956,0.009217432,0.0041811876,0.0030471236,0.009924585],"category_scores_gemma":[0.019312957,0.0020253062,0.0044413423,0.00658716,0.0070975707,0.025738394,0.0068344567,0.006591586,0.0023536885],"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":[0.000029612576,0.000025549167,0.0001972654,0.00024610225,0.000042802145,0.00011340472,0.00050260767,0.003779496,0.00030541085,0.963032,0.0028353683,0.028890315],"study_design_scores_gemma":[0.000023364033,0.00001608613,0.00005735667,0.00012239158,0.000031046326,0.00015617277,0.00014836538,0.015372301,0.0005729039,0.94026786,0.043209776,0.000022457147],"about_ca_topic_score_codex":0.0054013636,"about_ca_topic_score_gemma":0.003919183,"teacher_disagreement_score":0.01170702,"about_ca_system_score_codex":0.0051191757,"about_ca_system_score_gemma":0.003029027,"threshold_uncertainty_score":0.06191337},"labels":[],"label_agreement":null},{"id":"W1607479644","doi":"10.1007/978-3-540-77581-2_4","title":"On Enhancing Query Optimization in the Oracle Database System by Utilizing Attribute Cardinality Maps","year":2008,"lang":"en","type":"book-chapter","venue":"Lecture notes in business information processing","topic":"Advanced Database Systems and Queries","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":"Carleton University","funders":"","keywords":"Cardinality (data modeling); Oracle; Computer science; Oracle database; Query optimization; Database; View; Information retrieval; Data mining; Database design; Programming language","score_opus":0.0172197967255125,"score_gpt":0.23611736588297313,"score_spread":0.21889756915746064,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1607479644","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":[0.060923334,0.0017844294,0.92641455,0.0006613285,0.00010602023,0.00013701626,0.00019571424,0.0041168123,0.0056607816],"genre_scores_gemma":[0.4539723,0.0014005259,0.53864384,0.00028914455,0.00017874409,0.00009697381,0.000539712,0.0005994555,0.004279307],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9968688,0.0010261142,0.00018232777,0.00021846723,0.0013877599,0.00031661204],"domain_scores_gemma":[0.9955318,0.0028608325,0.00012683934,0.0009810689,0.0004235143,0.000075900905],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026473338,0.0010862806,0.0015609337,0.0009785062,0.00077532895,0.0022205547,0.0017830603,0.0006033668,0.002627902],"category_scores_gemma":[0.008076938,0.00044349846,0.00061838474,0.0028362076,0.00092678826,0.005841082,0.0019961398,0.0013998009,0.00052985887],"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":[0.0022733929,0.0006119057,0.0040142424,0.00042201305,0.00014822728,0.0002162989,0.0005080778,0.24643086,0.045826916,0.06498898,0.0152215045,0.61933756],"study_design_scores_gemma":[0.000050846906,0.00015047133,0.0006823208,0.000014768955,0.000066221255,0.00013706686,0.00013419698,0.9473833,0.019668937,0.027340062,0.00433829,0.000033440287],"about_ca_topic_score_codex":0.0065907207,"about_ca_topic_score_gemma":0.008403301,"teacher_disagreement_score":0.0065907207,"about_ca_system_score_codex":0.0007380814,"about_ca_system_score_gemma":0.0012311272,"threshold_uncertainty_score":0.014000654},"labels":[],"label_agreement":null},{"id":"W1607663644","doi":"10.1002/0471643505.ch2","title":"Probability and Random Processess Review","year":2004,"lang":"en","type":"other","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Random variable; Joint probability distribution; Algebra of random variables; Sum of normally distributed random variables; Probability-generating function; Random function; Probability theory; Random element; Mathematics; Probability density function; Random variate; Moment-generating function; Marginal distribution; Probability mass function; Multivariate random variable; Probability distribution; Conditional probability; Independence (probability theory); Markov chain; Convergence of random variables; Statistics","score_opus":0.02050735325975299,"score_gpt":0.2617336500231508,"score_spread":0.2412262967633978,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1607663644","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":[0.0008593647,0.81643665,0.03914129,0.014670121,0.008968281,0.00008932515,0.00057862635,0.00021944173,0.11903692],"genre_scores_gemma":[0.02127665,0.8587883,0.020663297,0.007947796,0.016452707,0.00020782961,0.0008683575,0.00027794368,0.07351714],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978635,0.0006132623,0.00017048951,0.0003815471,0.0008677565,0.000103486236],"domain_scores_gemma":[0.99619436,0.002382424,0.00015952298,0.00031538235,0.00084091653,0.00010745121],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019715633,0.0013781198,0.0017416443,0.0037203545,0.0010676571,0.0040649744,0.0016069768,0.002342116,0.019500278],"category_scores_gemma":[0.0061216583,0.0006110534,0.0009930619,0.0050581982,0.0029541885,0.006105242,0.0013917219,0.00472493,0.013462834],"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":[0.000015048374,0.000047387162,0.000304395,0.0021602148,0.0000435342,0.0002489214,0.0002990055,0.0019853648,0.00043235783,0.6191614,0.21056886,0.16473354],"study_design_scores_gemma":[0.0000024619935,0.000017476632,0.00036167452,0.00059012533,0.00000895138,0.000497975,0.00007239187,0.0005231597,0.000082751176,0.1258242,0.87200284,0.000016074038],"about_ca_topic_score_codex":0.0031497243,"about_ca_topic_score_gemma":0.0021958882,"teacher_disagreement_score":0.019500278,"about_ca_system_score_codex":0.003126682,"about_ca_system_score_gemma":0.002860477,"threshold_uncertainty_score":0.06523496},"labels":[],"label_agreement":null},{"id":"W1649866788","doi":"10.1007/978-3-642-00958-7_73","title":"Representing User Navigation in XML Retrieval with Structural Summaries","year":2009,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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 Toronto","funders":"","keywords":"Computer science; XML; Information retrieval; Document Structure Description; XML framework; XML database; World Wide Web","score_opus":0.012522114379109937,"score_gpt":0.24998162660355874,"score_spread":0.2374595122244488,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1649866788","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":[0.078808464,0.0013942284,0.8818623,0.000555723,0.00016426889,0.00019798952,0.0033277906,0.026216729,0.00747267],"genre_scores_gemma":[0.376425,0.0013378776,0.6025212,0.00015272136,0.000101803176,0.00013952315,0.0064714476,0.0017376005,0.011112742],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99921393,0.00025615023,0.00011560172,0.00013997403,0.00020746014,0.00006672354],"domain_scores_gemma":[0.9983033,0.0009566104,0.0001221744,0.00031430484,0.000245869,0.000057690024],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013967309,0.0007045755,0.0009388371,0.0020986553,0.0007340778,0.0036637974,0.0012269001,0.0013851917,0.007494404],"category_scores_gemma":[0.005348428,0.0005772147,0.00083537685,0.002410082,0.00065031426,0.005967571,0.0016754303,0.0006853378,0.0020486864],"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":[0.0021466366,0.0003353306,0.0076507046,0.0014690459,0.00014662494,0.0009342781,0.003965643,0.102328286,0.023973422,0.1715947,0.038585074,0.64687026],"study_design_scores_gemma":[0.00013493195,0.0003732748,0.0012449075,0.00021298038,0.00026798286,0.00048314538,0.0009207806,0.80917853,0.037968133,0.08524865,0.06384053,0.00012618791],"about_ca_topic_score_codex":0.008229872,"about_ca_topic_score_gemma":0.010416028,"teacher_disagreement_score":0.008229872,"about_ca_system_score_codex":0.00079699454,"about_ca_system_score_gemma":0.0008660371,"threshold_uncertainty_score":0.025071204},"labels":[],"label_agreement":null},{"id":"W1650112140","doi":"10.1007/3-540-45813-1_45","title":"A Method for Detecting Context-Specific Independence in Conditional Probability Tables","year":2002,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","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 Regina","funders":"","keywords":"Computer science; Independence (probability theory); Conditional independence; Context (archaeology); Bayesian network; Inference; Artificial intelligence; Bayesian probability; Machine learning; Data mining; Algorithm; Statistics; Mathematics","score_opus":0.03918470606948292,"score_gpt":0.2806212904622083,"score_spread":0.24143658439272536,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1650112140","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":[0.004071,0.000086604996,0.9928784,0.00002697079,0.000024205943,0.000065852255,0.00031783708,0.0021764284,0.0003528333],"genre_scores_gemma":[0.08405891,0.00010803086,0.9125822,0.00006985535,0.00007117845,0.0002309827,0.0014129253,0.00029688506,0.0011691125],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9953052,0.0009240243,0.0003682304,0.0010016806,0.002168218,0.00023261593],"domain_scores_gemma":[0.97933495,0.01464686,0.0007578232,0.0031240373,0.0017756214,0.00036074538],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003267013,0.0011008799,0.0013977222,0.0036192483,0.0012210709,0.0021773395,0.0026276445,0.0016106747,0.004796637],"category_scores_gemma":[0.02245487,0.0014524464,0.0016458005,0.0033639579,0.0009849886,0.003952016,0.0026302037,0.0024300413,0.0019138304],"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":[0.0009650444,0.00038554665,0.013551236,0.00046464754,0.000495199,0.00074175297,0.00055671623,0.039056916,0.029820802,0.073498115,0.013634575,0.8268295],"study_design_scores_gemma":[0.00017225806,0.00014865061,0.004682491,0.00007608348,0.0003198428,0.0016412943,0.00012006826,0.8123243,0.03579111,0.12896964,0.015578339,0.00017592161],"about_ca_topic_score_codex":0.0021505358,"about_ca_topic_score_gemma":0.003215561,"teacher_disagreement_score":0.004796637,"about_ca_system_score_codex":0.0004813436,"about_ca_system_score_gemma":0.0017590089,"threshold_uncertainty_score":0.017277837},"labels":[],"label_agreement":null},{"id":"W167180509","doi":"","title":"Exploiting Schema Information for Efficient Streaming Queries.","year":2010,"lang":"en","type":"article","venue":"Software Engineering and Data Engineering","topic":"Advanced Database Systems and Queries","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 Alberta","funders":"","keywords":"Computer science; Schema (genetic algorithms); Streaming data; Information retrieval; Data mining","score_opus":0.010549608556253563,"score_gpt":0.22412563717463432,"score_spread":0.21357602861838076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W167180509","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":[0.073246695,0.002583743,0.89325815,0.0015685504,0.00030002845,0.00038567165,0.005098045,0.016743941,0.0068151453],"genre_scores_gemma":[0.41714373,0.0016832754,0.5620608,0.00047644821,0.00027630434,0.00021696044,0.013148344,0.001169548,0.0038246578],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9970444,0.00077706587,0.000344048,0.0004250081,0.0011837562,0.00022565154],"domain_scores_gemma":[0.98717064,0.0061995834,0.0005490526,0.0044637686,0.0013146127,0.00030232346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038237695,0.00088784343,0.0012781511,0.0023607204,0.0008079739,0.0029979611,0.002006037,0.001199702,0.0043738857],"category_scores_gemma":[0.017234545,0.0007386214,0.00087841484,0.0046047284,0.0006459225,0.008981918,0.0026535427,0.0017438276,0.0018188227],"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":[0.002505891,0.00057502266,0.010625912,0.00082362385,0.00033038476,0.00068190164,0.0013717492,0.030040722,0.066595525,0.07838292,0.07155204,0.73651433],"study_design_scores_gemma":[0.00028457821,0.00037792142,0.0021225489,0.00013014002,0.00025360446,0.0011282419,0.0007726968,0.72606057,0.05287082,0.17063066,0.0452675,0.00010065509],"about_ca_topic_score_codex":0.0035772214,"about_ca_topic_score_gemma":0.005031225,"teacher_disagreement_score":0.0043738857,"about_ca_system_score_codex":0.0007868884,"about_ca_system_score_gemma":0.0015787851,"threshold_uncertainty_score":0.020222306},"labels":[],"label_agreement":null},{"id":"W1681014725","doi":"","title":"A multi-dimensional histogram for selectivity estimation and fast approximate query answering","year":2003,"lang":"en","type":"article","venue":"Conference of the Centre for Advanced Studies on Collaborative Research","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Histogram; Computer science; Online analytical processing; Data mining; Query optimization; Oracle; Histogram matching; Set (abstract data type); SQL; Database; Information retrieval; Artificial intelligence; Data warehouse; Image (mathematics)","score_opus":0.10531800682429066,"score_gpt":0.39342699649642365,"score_spread":0.288108989672133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1681014725","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":[0.007220343,0.00033066503,0.98864347,0.000097041666,0.000053019794,0.000066515546,0.00037887692,0.0025262148,0.0006838597],"genre_scores_gemma":[0.26205495,0.0006041104,0.73365563,0.000159684,0.00018071786,0.00028768348,0.0016801181,0.00037859177,0.0009986059],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9972562,0.0006395974,0.00017921769,0.00040714128,0.001307155,0.00021063081],"domain_scores_gemma":[0.9908708,0.003931103,0.0005690723,0.0021800254,0.0021850823,0.00026388664],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002008965,0.00065242,0.0011454336,0.0032210231,0.00085209886,0.0020405613,0.0020510773,0.0009546176,0.003656732],"category_scores_gemma":[0.015404534,0.0005077851,0.00062302715,0.0059444974,0.0006870869,0.0052189864,0.0015558026,0.0014662057,0.0012648985],"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":[0.0009011786,0.00020794065,0.007920323,0.00033486533,0.00009340898,0.0001436256,0.0002876088,0.065902725,0.026451193,0.037569903,0.016175348,0.84401196],"study_design_scores_gemma":[0.00010236152,0.0002497986,0.0028586984,0.000041108015,0.000049039365,0.00069155666,0.00020225045,0.92053944,0.0291008,0.02861506,0.017398324,0.0001516159],"about_ca_topic_score_codex":0.003772925,"about_ca_topic_score_gemma":0.002663977,"teacher_disagreement_score":0.003772925,"about_ca_system_score_codex":0.0009892385,"about_ca_system_score_gemma":0.0013853743,"threshold_uncertainty_score":0.012233019},"labels":[],"label_agreement":null},{"id":"W1682128552","doi":"10.3233/fi-2000-42101","title":"A Proof System for Dependencies for Information Relations","year":2000,"lang":"en","type":"article","venue":"Fundamenta Informaticae","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Francis Xavier University; Natural Sciences and Engineering Research Council of Canada","funders":"","keywords":"Computer science; Dependency theory (database theory); Theoretical computer science; Data mining; Functional dependency; Relational database","score_opus":0.012313270662353644,"score_gpt":0.23672250789099755,"score_spread":0.22440923722864392,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1682128552","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":[0.002652671,0.0005630456,0.9835686,0.0014142181,0.00031521317,0.00020246633,0.00067010114,0.0020144624,0.008599229],"genre_scores_gemma":[0.09887301,0.0011004338,0.88573503,0.0011671876,0.00050655927,0.00048477252,0.0017342037,0.0006630214,0.009735723],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.995812,0.0011024739,0.00050052296,0.00079895515,0.0014823431,0.00030367257],"domain_scores_gemma":[0.989665,0.007042762,0.00039854783,0.0010371297,0.0016055306,0.0002510433],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005870749,0.0009556131,0.00094493636,0.002459834,0.002716659,0.004557424,0.002156648,0.001815059,0.015030001],"category_scores_gemma":[0.012302194,0.0012448499,0.0024297752,0.0017705626,0.0027586047,0.008897413,0.0054426375,0.0047006314,0.004051341],"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":[0.00004025575,0.000039862527,0.00017163252,0.00033999773,0.000038842645,0.00035628126,0.0004363572,0.0037022948,0.0032858357,0.9303625,0.0113876285,0.0498386],"study_design_scores_gemma":[0.00009595595,0.00004788498,0.00013878962,0.00013801378,0.000089933186,0.00035946525,0.00008612846,0.03618415,0.0067200684,0.8673382,0.08873936,0.00006205688],"about_ca_topic_score_codex":0.0025811105,"about_ca_topic_score_gemma":0.0027366818,"teacher_disagreement_score":0.015030001,"about_ca_system_score_codex":0.0024216268,"about_ca_system_score_gemma":0.003927587,"threshold_uncertainty_score":0.050280333},"labels":[],"label_agreement":null},{"id":"W173713730","doi":"10.5220/0001690301730178","title":"TREE EMBEDDING AND XML QUERY EVALUATION","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","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 Winnipeg","funders":"","keywords":"Computer science; XML; Information retrieval; Embedding; Query optimization; Database; XML database; Streaming XML; World Wide Web; Artificial intelligence","score_opus":0.0393342954977898,"score_gpt":0.2922452776143189,"score_spread":0.25291098211652907,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W173713730","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":[0.11612568,0.0041260985,0.863725,0.0018537655,0.00028358013,0.00020672294,0.0009192835,0.0056928396,0.007066978],"genre_scores_gemma":[0.7046084,0.0010520311,0.28436247,0.00031698617,0.00023992884,0.00011771979,0.0019097436,0.00072318135,0.0066695097],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99129957,0.0036097113,0.0006630888,0.0006556749,0.0032645098,0.00050745497],"domain_scores_gemma":[0.9859865,0.009040002,0.00054517033,0.0017406647,0.0023925765,0.00029509925],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0059192255,0.00079221785,0.00165273,0.0025545196,0.00061019295,0.0030691407,0.0014023434,0.0014617731,0.005026756],"category_scores_gemma":[0.024615215,0.0005398963,0.0008087638,0.0033491387,0.0010703385,0.009073999,0.0019685586,0.0013975711,0.0009354282],"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":[0.002647011,0.0005078206,0.007030265,0.0006869678,0.00018248428,0.00035091,0.0005657811,0.09098393,0.017494317,0.16446133,0.022836525,0.69225264],"study_design_scores_gemma":[0.00008571006,0.00026024316,0.0011296597,0.000064221116,0.00009303552,0.00029927277,0.00020884897,0.82936186,0.016437696,0.1445722,0.0074448828,0.00004241382],"about_ca_topic_score_codex":0.003505645,"about_ca_topic_score_gemma":0.0032064614,"teacher_disagreement_score":0.0059192255,"about_ca_system_score_codex":0.001449805,"about_ca_system_score_gemma":0.0011845975,"threshold_uncertainty_score":0.0313043},"labels":[],"label_agreement":null},{"id":"W1759713541","doi":"10.1007/3-540-45017-3_5","title":"Query Processing and Optimization for Regular Path Expressions","year":2003,"lang":"en","type":"book-chapter","venue":"Notes on numerical fluid mechanics and multidisciplinary design","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":16,"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":"Path expression; Path (computing); Joins; Computer science; Expression (computer science); Fast path; Longest path problem; Shortest path problem; Algorithm; XML; Theoretical computer science; Computer network; Programming language; World Wide Web; Graph","score_opus":0.036016215496402215,"score_gpt":0.26724035591998196,"score_spread":0.23122414042357975,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1759713541","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":[0.006840101,0.00086071825,0.98486716,0.0003659884,0.000058057354,0.0001257646,0.00043517922,0.002972246,0.0034747105],"genre_scores_gemma":[0.10027607,0.0009942541,0.88646597,0.00024487733,0.0001735639,0.00032727825,0.0024856252,0.001213146,0.007819219],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99365604,0.0014211849,0.0007060251,0.0009614458,0.0027076043,0.00054782594],"domain_scores_gemma":[0.993923,0.0037443296,0.00024906182,0.0012195166,0.00074785034,0.000116204676],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00399798,0.00129387,0.0025964219,0.0018301534,0.0012278523,0.0046421257,0.0030839997,0.0012364838,0.009065959],"category_scores_gemma":[0.014908653,0.0010889745,0.0019991933,0.0045510666,0.0021931066,0.0075666565,0.00265674,0.002810637,0.002791313],"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":[0.00084027107,0.00022924528,0.0009839066,0.00072807324,0.00014680528,0.00015714247,0.00056600996,0.14621715,0.006964947,0.35911018,0.03895469,0.4451016],"study_design_scores_gemma":[0.000074793716,0.000074068426,0.00019062235,0.000038887378,0.000056262368,0.000110506655,0.00012007389,0.68226194,0.0051843636,0.29962575,0.012229364,0.00003333006],"about_ca_topic_score_codex":0.0063611926,"about_ca_topic_score_gemma":0.005863512,"teacher_disagreement_score":0.009065959,"about_ca_system_score_codex":0.0020771923,"about_ca_system_score_gemma":0.0022006158,"threshold_uncertainty_score":0.030328631},"labels":[],"label_agreement":null},{"id":"W1760622754","doi":"10.1007/3-540-44503-x_24","title":"Reasoning about Summarizability in Heterogeneous Multidimensional Schemas","year":2001,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":62,"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; Artificial intelligence; Theoretical computer science; Human–computer interaction","score_opus":0.01505834220825383,"score_gpt":0.2520948302424129,"score_spread":0.23703648803415908,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1760622754","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":[0.15386525,0.001506169,0.8289179,0.0027184442,0.00013818202,0.00043665114,0.0020917987,0.004936888,0.0053886655],"genre_scores_gemma":[0.6280546,0.00096477993,0.36126518,0.0006093246,0.00027566197,0.00025535154,0.005637917,0.00058084825,0.0023563681],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9881142,0.0036317417,0.0021050365,0.001701613,0.0036891869,0.0007583213],"domain_scores_gemma":[0.95347387,0.03458663,0.0031045757,0.0051847673,0.003142235,0.00050792383],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0107404655,0.0010562605,0.0016330571,0.004138244,0.0019086393,0.006411411,0.0035735825,0.003149045,0.005001829],"category_scores_gemma":[0.05076087,0.0019922622,0.002680073,0.005708074,0.0028735197,0.026672937,0.0069332025,0.0030725538,0.0004816187],"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":[0.0012916274,0.00043804484,0.02483951,0.0028488103,0.0012808116,0.0052805175,0.009771824,0.10380298,0.019599628,0.5613454,0.021169852,0.24833101],"study_design_scores_gemma":[0.00027289733,0.00018311582,0.002577858,0.00042279524,0.0010640105,0.0012968008,0.0033737023,0.37367272,0.025579572,0.575635,0.015783777,0.00013772189],"about_ca_topic_score_codex":0.0034975787,"about_ca_topic_score_gemma":0.003378054,"teacher_disagreement_score":0.0107404655,"about_ca_system_score_codex":0.0018125994,"about_ca_system_score_gemma":0.00075055746,"threshold_uncertainty_score":0.056801677},"labels":[],"label_agreement":null},{"id":"W1767402579","doi":"","title":"Data sharing in the Hyperion peer database system","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":74,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa; University of Toronto","funders":"","keywords":"Computer science; Metadata; Data sharing; Relational database; Key (lock); Peer-to-peer; Distributed database; Database; Data management; Information retrieval; World Wide Web; Computer security","score_opus":0.07876823438720297,"score_gpt":0.3097147354873283,"score_spread":0.23094650110012532,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1767402579","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":[0.1836499,0.002194155,0.70104516,0.0023264536,0.0005337457,0.0009776962,0.00087521144,0.037298363,0.07109933],"genre_scores_gemma":[0.667379,0.0011393153,0.29292288,0.00068673905,0.0002731534,0.0005296434,0.0018591789,0.0007366078,0.034473475],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9964018,0.00082030415,0.00026408574,0.0006614253,0.001534091,0.00031838604],"domain_scores_gemma":[0.9979255,0.00039200348,0.00011700311,0.0009272304,0.00034220773,0.0002959133],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003249744,0.00040225126,0.0007631981,0.00093099935,0.0012331735,0.0040997383,0.0032616605,0.0011114442,0.005913521],"category_scores_gemma":[0.0040965294,0.00052078627,0.00049507513,0.0011300961,0.0012161627,0.0072703594,0.0054253247,0.001049635,0.0018668842],"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":[0.0038609025,0.0006820164,0.011601377,0.00067854807,0.00044876419,0.005305477,0.007995529,0.060934644,0.050123043,0.27521348,0.0683924,0.5147638],"study_design_scores_gemma":[0.00085984013,0.0009544508,0.0027252506,0.00021614286,0.00029160772,0.0024286918,0.0014595384,0.35486105,0.05678368,0.10065676,0.4784639,0.00029912288],"about_ca_topic_score_codex":0.003214137,"about_ca_topic_score_gemma":0.0017665447,"teacher_disagreement_score":0.005913521,"about_ca_system_score_codex":0.00085606053,"about_ca_system_score_gemma":0.0013088437,"threshold_uncertainty_score":0.019782722},"labels":[],"label_agreement":null},{"id":"W177538432","doi":"","title":"Proceedings of the 16th International Database Engineering & Applications Sysmposium","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Library science; Quality (philosophy); Computer science; Database; Operations research; Engineering","score_opus":0.007238045602608491,"score_gpt":0.2164243034666619,"score_spread":0.2091862578640534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W177538432","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.032866266,0.17446676,0.22175768,0.05764682,0.20682666,0.0039484953,0.013362422,0.007855616,0.28126928],"genre_scores_gemma":[0.04197078,0.061259888,0.10538258,0.006817683,0.05088221,0.0022911092,0.028675817,0.0039553475,0.6987646],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9917441,0.002409885,0.00088766555,0.0010013388,0.0034977836,0.00045921712],"domain_scores_gemma":[0.9887473,0.003222525,0.0006242358,0.0016848863,0.0034839348,0.0022371945],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.014053085,0.0016913201,0.0020801083,0.004156542,0.0019912526,0.010867274,0.002253489,0.0022842644,0.07863578],"category_scores_gemma":[0.01016807,0.0008882639,0.0018487356,0.0033846935,0.0017988656,0.0053345426,0.0048525543,0.003721491,0.04047553],"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":[0.0003432142,0.00027464493,0.00092703453,0.00095138105,0.0001041291,0.000299238,0.00047324278,0.00037675764,0.0032766971,0.0068847914,0.71421736,0.27187148],"study_design_scores_gemma":[0.00003786641,0.00014584658,0.0017056885,0.00029124046,0.00003854766,0.00041733176,0.0001369361,0.00087892887,0.0012963745,0.0039562625,0.99106807,0.000026894926],"about_ca_topic_score_codex":0.0012917755,"about_ca_topic_score_gemma":0.0016665077,"teacher_disagreement_score":0.07863578,"about_ca_system_score_codex":0.0028856667,"about_ca_system_score_gemma":0.0043182434,"threshold_uncertainty_score":0.2630629},"labels":[],"label_agreement":null},{"id":"W1779637050","doi":"10.5555/957289.957326","title":"Pedagogical tools for database design, development and use","year":2003,"lang":"en","type":"article","venue":"Principles and Practice of Programming in Java","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Computer science; Database schema; Database design; Database; View; Relational database; Database model; Database application; Java; Database testing; Database theory; SQL; World Wide Web; Programming language","score_opus":0.2950972804691166,"score_gpt":0.3791942475242312,"score_spread":0.0840969670551146,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1779637050","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":[0.00047815812,0.0024463292,0.938564,0.0050727054,0.00083632226,0.0005101236,0.00044277977,0.009013874,0.042635698],"genre_scores_gemma":[0.008142796,0.005182616,0.9433185,0.0021727597,0.0007557879,0.0012590695,0.0009728982,0.002169241,0.036026224],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99372673,0.0018190768,0.0009247911,0.0005945926,0.0026794448,0.00025527933],"domain_scores_gemma":[0.97856605,0.00944592,0.00090566743,0.0046837837,0.0047559915,0.0016425337],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0074436576,0.0016227771,0.0010069136,0.003224859,0.0014221978,0.0061996994,0.0035476477,0.002833512,0.03210545],"category_scores_gemma":[0.031952906,0.0018621597,0.0012181092,0.0033463973,0.0022053018,0.008553679,0.0050239833,0.009527317,0.045396037],"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":[0.000038936938,0.0003154318,0.0005196808,0.0011703908,0.00002829356,0.00034786094,0.0020091622,0.0013514094,0.0047079003,0.24428886,0.22299378,0.52222836],"study_design_scores_gemma":[0.0000435975,0.000044167395,0.0002642584,0.0007089887,0.000017061926,0.000803368,0.00022935159,0.0029411453,0.0020252005,0.12638082,0.866506,0.000036087386],"about_ca_topic_score_codex":0.00065972214,"about_ca_topic_score_gemma":0.00086486817,"teacher_disagreement_score":0.03210545,"about_ca_system_score_codex":0.0015603631,"about_ca_system_score_gemma":0.0033756834,"threshold_uncertainty_score":0.1074034},"labels":[],"label_agreement":null},{"id":"W1782020131","doi":"10.11575/prism/30818","title":"Optimizing In-Order Execution of Continuous Queries over Streamed Sensor Data","year":2004,"lang":"en","type":"article","venue":"PRISM (University of Calgary)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Order (exchange); Out-of-order execution; Real-time computing; Parallel computing","score_opus":0.014554161343858316,"score_gpt":0.21861918812887643,"score_spread":0.20406502678501812,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1782020131","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":[0.61660403,0.00040972585,0.37674943,0.00023756595,0.000039005423,0.00019792952,0.00013754626,0.0040159877,0.0016088159],"genre_scores_gemma":[0.85806006,0.00015640423,0.14051597,0.00004361818,0.000025187417,0.00007862999,0.000205716,0.00018044782,0.00073397456],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981414,0.0005029422,0.00017350297,0.00029515228,0.00063851645,0.00024846633],"domain_scores_gemma":[0.9947573,0.0031622767,0.0004662944,0.0006544505,0.0006209606,0.00033885892],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002592255,0.00087781704,0.0008991362,0.0004256583,0.00056778226,0.0014135863,0.001356451,0.0004631344,0.00062874745],"category_scores_gemma":[0.0057560233,0.00042717674,0.0003380147,0.000770088,0.0007940952,0.0013809418,0.00077048363,0.0008717763,0.00014318421],"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":[0.003568387,0.0010801364,0.018161234,0.00034634446,0.0001774897,0.00044792637,0.0011957166,0.5941737,0.15897991,0.009383327,0.0035610679,0.20892482],"study_design_scores_gemma":[0.00007977441,0.00019607489,0.0009572651,0.0000032249654,0.00001947795,0.00004541349,0.000108591325,0.97326636,0.023233458,0.0015371685,0.00054104876,0.000012197385],"about_ca_topic_score_codex":0.00525241,"about_ca_topic_score_gemma":0.005667983,"teacher_disagreement_score":0.00525241,"about_ca_system_score_codex":0.0008886394,"about_ca_system_score_gemma":0.0019185515,"threshold_uncertainty_score":0.013709307},"labels":[],"label_agreement":null},{"id":"W179587921","doi":"","title":"First Look at Microsoft SQL Server Yukon Beta for Developers","year":2004,"lang":"en","type":"book","venue":"Addison-Wesley Longman Publishing Co., Inc. eBooks","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Data Transformation Services; Business Intelligence Markup Language; User-defined function; SQL injection; Database; Language Integrated Query; Stored procedure; Log shipping; SQL/PSM; World Wide Web; Operating system; Application server; Internet Authentication Service; Query by Example; Web search query","score_opus":0.020438089033593426,"score_gpt":0.23870199907078146,"score_spread":0.21826391003718804,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W179587921","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003449067,0.0043450175,0.074834354,0.025743157,0.007373435,0.0011480285,0.011815569,0.2868687,0.5844227],"genre_scores_gemma":[0.010944757,0.002614165,0.03992172,0.016526524,0.0015706478,0.0006411018,0.011893657,0.07114197,0.84474546],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980703,0.00015876755,0.00014572444,0.00029142873,0.0011240965,0.00020969476],"domain_scores_gemma":[0.988913,0.0012966939,0.0004452245,0.0013919498,0.0063255513,0.0016275498],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0024355461,0.0017874152,0.0007546232,0.0019261508,0.0012752691,0.0058394237,0.0016186739,0.002024524,0.33192256],"category_scores_gemma":[0.015671944,0.0013465853,0.00063663704,0.0016378523,0.0004685723,0.0076779337,0.002527987,0.0041308794,0.4502555],"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":[0.00004037433,0.000034584944,0.00019428902,0.00006652978,0.0000026676755,0.00009327371,0.00011831339,0.000029201958,0.0005908631,0.0014545887,0.93995786,0.05741745],"study_design_scores_gemma":[0.000027074198,0.00004191127,0.00054188096,0.00011483934,0.0000043161685,0.00025393345,0.00018376388,0.00014500892,0.0006660503,0.001242829,0.9967526,0.00002574046],"about_ca_topic_score_codex":0.003081519,"about_ca_topic_score_gemma":0.003463982,"teacher_disagreement_score":0.33192256,"about_ca_system_score_codex":0.0011726309,"about_ca_system_score_gemma":0.002402963,"threshold_uncertainty_score":0.9529314},"labels":[],"label_agreement":null},{"id":"W180446144","doi":"","title":"Constructions Of Graphs Without Nowhere-Zero Flows From Boolean Formulas.","year":2004,"lang":"en","type":"article","venue":"Ars Combinatoria","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Mathematics; Zero (linguistics); Nowhere dense set; Combinatorics; Discrete mathematics; Computer science; Linguistics; Philosophy","score_opus":0.009344297948319143,"score_gpt":0.2303565491186145,"score_spread":0.22101225117029535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W180446144","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":[0.04440227,0.001663905,0.8406371,0.0033847345,0.0008118023,0.00027072604,0.0024818464,0.0040071877,0.10234049],"genre_scores_gemma":[0.48002854,0.0023584615,0.45610186,0.001969842,0.000342109,0.00048158356,0.004402704,0.002177712,0.05213722],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9987669,0.00039236728,0.000118882446,0.00024545362,0.00028269106,0.00019382327],"domain_scores_gemma":[0.99534214,0.002626435,0.00030861632,0.00092182826,0.0005244021,0.00027660019],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015523346,0.0009255141,0.00071628665,0.0020841972,0.0024164647,0.00390625,0.0021755842,0.0014257595,0.01134885],"category_scores_gemma":[0.0071447166,0.0010554439,0.0015760297,0.0024317375,0.0025762292,0.0096995495,0.0034815758,0.0032673948,0.0030854663],"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":[0.000052103835,0.000036322897,0.00015995493,0.00012018383,0.00001568304,0.00015129794,0.00025235218,0.00070797175,0.0013326998,0.9771987,0.0056310846,0.014341502],"study_design_scores_gemma":[0.000018596025,0.000008959997,0.00009549331,0.00006194603,0.000028384744,0.0001543591,0.00011937872,0.002331368,0.0021275438,0.97627366,0.018761916,0.00001848456],"about_ca_topic_score_codex":0.0016146577,"about_ca_topic_score_gemma":0.0027735033,"teacher_disagreement_score":0.01134885,"about_ca_system_score_codex":0.0017381699,"about_ca_system_score_gemma":0.0011378841,"threshold_uncertainty_score":0.037965655},"labels":[],"label_agreement":null},{"id":"W1805455758","doi":"10.1007/3-540-47984-8_33","title":"An Empirical Study with Metrics for Object-Relational Databases","year":2002,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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":"Université de Montréal","funders":"","keywords":"Computer science; Relational database; Schema (genetic algorithms); Granularity; Relational calculus; Semi-structured model; Relational model; Empirical research; Information schema; Database schema; Table (database); Data mining; Database; Theoretical computer science; Database model; Information retrieval; Database design; Programming language; Mathematics; Statistics","score_opus":0.05567951139443925,"score_gpt":0.3146619773778031,"score_spread":0.25898246598336383,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1805455758","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":[0.96775514,0.0034810253,0.022150464,0.00094079913,0.00007117746,0.00018192916,0.0008078168,0.00007057043,0.004541065],"genre_scores_gemma":[0.9894154,0.00038133678,0.008656403,0.00007613949,0.000057796788,0.0001384928,0.00069155527,0.000049567927,0.0005333467],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.92963976,0.054504383,0.0038015773,0.0027609519,0.008220041,0.0010732417],"domain_scores_gemma":[0.34220782,0.60537565,0.014576291,0.014958768,0.020615447,0.0022660196],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04285949,0.00078268844,0.00079152663,0.0036804006,0.0012988182,0.0031923328,0.0021381562,0.0013408259,0.0031562964],"category_scores_gemma":[0.40106875,0.00043192826,0.0011451805,0.010651671,0.0025515908,0.0114313075,0.0023728972,0.002203024,0.00058955257],"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":[0.0018360039,0.002630897,0.842396,0.0009878321,0.00068185246,0.0003185466,0.009062243,0.0038276883,0.0008363829,0.030115781,0.0069344696,0.10037225],"study_design_scores_gemma":[0.00049718306,0.010476795,0.7504178,0.0009827487,0.002061263,0.0044225566,0.042639375,0.10053564,0.004563627,0.05738774,0.02578801,0.00022721394],"about_ca_topic_score_codex":0.0045395736,"about_ca_topic_score_gemma":0.0038710765,"teacher_disagreement_score":0.04285949,"about_ca_system_score_codex":0.0017966024,"about_ca_system_score_gemma":0.0012705481,"threshold_uncertainty_score":0.22666538},"labels":[],"label_agreement":null},{"id":"W1809049220","doi":"10.1007/978-3-540-76843-2_22","title":"Sidera: A Cluster-Based Server for Online Analytical Processing","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","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":"Concordia University","funders":"","keywords":"Online analytical processing; Computer science; Server; Robustness (evolution); Database; Computer cluster; Data warehouse; Cluster (spacecraft); Operating system","score_opus":0.04094772496917243,"score_gpt":0.30988234587392244,"score_spread":0.26893462090475,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1809049220","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":[0.015054843,0.0009628297,0.5446571,0.00040813332,0.0004856452,0.0007125606,0.006553179,0.40556774,0.025597943],"genre_scores_gemma":[0.23285526,0.0013889554,0.5847415,0.0013872713,0.0008140212,0.0011277437,0.036042143,0.040005185,0.10163794],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99815315,0.00021673096,0.000118155505,0.0003877456,0.00090731354,0.00021694125],"domain_scores_gemma":[0.9965295,0.00058148225,0.00013320532,0.0012636362,0.0010135616,0.0004785937],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014788869,0.0020250278,0.0023212458,0.0024737078,0.0010531232,0.0032332775,0.0059541445,0.0013990193,0.041116327],"category_scores_gemma":[0.0039872434,0.0013366472,0.00082886143,0.0038602396,0.0006754842,0.0030741857,0.002541354,0.0020225258,0.039436404],"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":[0.0027636094,0.0006801663,0.002841402,0.0005598223,0.00033867586,0.00038693607,0.00038523,0.012178781,0.06586098,0.009831705,0.49971715,0.4044555],"study_design_scores_gemma":[0.0009001852,0.00055330375,0.0047488096,0.000117447096,0.00028874562,0.0011470445,0.00031919888,0.52862245,0.121474184,0.0262782,0.31510505,0.0004453769],"about_ca_topic_score_codex":0.004099569,"about_ca_topic_score_gemma":0.0034078003,"teacher_disagreement_score":0.041116327,"about_ca_system_score_codex":0.00088076317,"about_ca_system_score_gemma":0.0022499592,"threshold_uncertainty_score":0.13754779},"labels":[],"label_agreement":null},{"id":"W181731857","doi":"10.4018/978-1-59140-553-5.ch555","title":"XML Schema Integration and E-Commerce","year":2005,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Laurentian University","funders":"","keywords":"XML Schema Editor; Document Structure Description; Computer science; XML validation; RELAX NG; Information retrieval; Efficient XML Interchange; XML Schema (W3C); Streaming XML; XML database; Schema (genetic algorithms); XML; Document type definition; Database; Programming language; World Wide Web","score_opus":0.018699003705967103,"score_gpt":0.2526335297195642,"score_spread":0.2339345260135971,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W181731857","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":[0.0030778015,0.19621626,0.22391945,0.010811967,0.003116274,0.00040784257,0.0009547732,0.002431145,0.5590645],"genre_scores_gemma":[0.04671148,0.23588952,0.41001222,0.008737525,0.0024547118,0.00070854457,0.009378984,0.001885476,0.28422156],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99821645,0.00058166747,0.00018579901,0.0001982116,0.00072894717,0.00008889689],"domain_scores_gemma":[0.9986767,0.0007125919,0.000073955474,0.000250826,0.00021239326,0.00007350728],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025379234,0.0010725786,0.0009976076,0.0044573974,0.00093438104,0.007890305,0.0018848196,0.0032855696,0.022957832],"category_scores_gemma":[0.0036447954,0.000899554,0.0011727292,0.0136386,0.0019736295,0.011962451,0.0028985387,0.0033737188,0.012495076],"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":[0.00003234666,0.00010078996,0.00025918116,0.00088952476,0.000054565706,0.00044470173,0.0008612534,0.0020440007,0.0009818629,0.5675712,0.08343945,0.34332108],"study_design_scores_gemma":[0.000014327207,0.00001542567,0.00022623195,0.0007849218,0.000019081577,0.00093113416,0.00021160523,0.00311609,0.0004047647,0.1588044,0.8354538,0.00001811621],"about_ca_topic_score_codex":0.0021912488,"about_ca_topic_score_gemma":0.0017308706,"teacher_disagreement_score":0.022957832,"about_ca_system_score_codex":0.0021326463,"about_ca_system_score_gemma":0.0018711427,"threshold_uncertainty_score":0.0768016},"labels":[],"label_agreement":null},{"id":"W1817601911","doi":"10.17487/rfc3075","title":"XML-Signature Syntax and Processing","year":2001,"lang":"en","type":"report","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":283,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"XML Signature; Computer science; XML Encryption; Syntax; XML; Streaming XML; XML validation; Document type definition; Digital signature; Signature (topology); Efficient XML Interchange; Programming language; RuleML; Markup language; World Wide Web; Natural language processing; Mathematics","score_opus":0.027232234611274195,"score_gpt":0.29118528863170057,"score_spread":0.26395305402042635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1817601911","genre_codex":"methods","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":[0.004309723,0.0015837819,0.58093286,0.0041029006,0.0019580442,0.0031750414,0.077521734,0.12592888,0.20048694],"genre_scores_gemma":[0.048871145,0.0023444574,0.5500349,0.004020178,0.00091678323,0.0022080797,0.18210877,0.018048592,0.19144711],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99527365,0.0008830737,0.0008174039,0.00042316693,0.0022306445,0.00037213892],"domain_scores_gemma":[0.993487,0.000799244,0.00043217657,0.0020482002,0.0029243298,0.0003090038],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004279076,0.00143638,0.00075869716,0.0025329948,0.0011341587,0.0067815348,0.0023284624,0.0027203423,0.07052202],"category_scores_gemma":[0.0089853825,0.0009657775,0.0008687845,0.0033294905,0.0009921773,0.0077032754,0.0035381971,0.0025879042,0.12853178],"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":[0.00035055325,0.00017942404,0.0007773282,0.0006669496,0.000027489183,0.00034169902,0.00042012165,0.0015111462,0.010992499,0.1951115,0.56090456,0.22871675],"study_design_scores_gemma":[0.00006709814,0.000060963874,0.00035442415,0.00018130254,0.000016214493,0.0005814904,0.00007090937,0.003075405,0.01816433,0.023256216,0.9541119,0.000059827846],"about_ca_topic_score_codex":0.0020509055,"about_ca_topic_score_gemma":0.0012426641,"teacher_disagreement_score":0.07052202,"about_ca_system_score_codex":0.0013065371,"about_ca_system_score_gemma":0.0034572068,"threshold_uncertainty_score":0.23591965},"labels":[],"label_agreement":null},{"id":"W1819449330","doi":"10.1109/icde.1998.655768","title":"Query folding with inclusion dependencies","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":63,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Computer science; Set (abstract data type); Folding (DSP implementation); Functional dependency; Query language; Extension (predicate logic); Query optimization; Inclusion (mineral); Materialized view; Theoretical computer science; Dependency theory (database theory); Data mining; View; Relational database; Programming language; Chemistry; Database design","score_opus":0.016664665192995413,"score_gpt":0.2018180985975105,"score_spread":0.18515343340451507,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1819449330","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":[0.018061863,0.00029195994,0.9744598,0.00036017926,0.000047959344,0.00024993552,0.0003145222,0.0031596606,0.0030540687],"genre_scores_gemma":[0.25734764,0.0004848512,0.7338337,0.00048749754,0.00010608399,0.00029641538,0.0017472164,0.001054859,0.0046417164],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9916358,0.002105431,0.0010808613,0.001313115,0.003105863,0.0007589905],"domain_scores_gemma":[0.97638434,0.009013085,0.0011736449,0.0089266235,0.004064655,0.00043772275],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006805169,0.0011560974,0.0013744452,0.0018209422,0.0019988671,0.0025844183,0.0021423234,0.0014177503,0.0027485157],"category_scores_gemma":[0.021790948,0.0009474729,0.001999673,0.002987319,0.0020691296,0.0076777446,0.0053541544,0.0021322619,0.0010573852],"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":[0.0011554919,0.00048331651,0.014020981,0.0008255739,0.00025774175,0.001616386,0.003223369,0.059981592,0.036949594,0.23247752,0.020258872,0.62874955],"study_design_scores_gemma":[0.000078924575,0.00044827003,0.002512387,0.00019231364,0.0002914677,0.0023171783,0.0009059368,0.44631153,0.08548264,0.37902865,0.08226744,0.000163323],"about_ca_topic_score_codex":0.0033553662,"about_ca_topic_score_gemma":0.0023276939,"teacher_disagreement_score":0.006805169,"about_ca_system_score_codex":0.0011033798,"about_ca_system_score_gemma":0.0024088682,"threshold_uncertainty_score":0.035989583},"labels":[],"label_agreement":null},{"id":"W1819934925","doi":"10.7302/24323","title":"Query optimization in multidatabase systems","year":2024,"lang":"en","type":"article","venue":"Deep Blue (University of Michigan)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Query optimization; Computer science; Sargable; Query expansion; Query language; Web search query; View; Query by Example; Distributed database; Online aggregation; Database; RDF query language; Web query classification; Information retrieval; Distributed computing; Data mining; Search engine; Database design","score_opus":0.00728528310605132,"score_gpt":0.19193684382861143,"score_spread":0.18465156072256012,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1819934925","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":[0.05208314,0.0028102468,0.93929636,0.0007890684,0.000035933266,0.0001295644,0.00013349835,0.0013027337,0.003419491],"genre_scores_gemma":[0.67206544,0.0012974854,0.32180467,0.0002814215,0.000089625755,0.00019833434,0.00041066625,0.0003378675,0.0035144978],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9951331,0.0016904688,0.00034183872,0.00081492745,0.0016247454,0.00039490237],"domain_scores_gemma":[0.99757105,0.0013371786,0.00016624968,0.00040175198,0.00041235145,0.00011147231],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003762029,0.0007679511,0.0014853616,0.0008691516,0.000982643,0.0031670702,0.0018185222,0.0009314447,0.0014469574],"category_scores_gemma":[0.0053632474,0.0006112794,0.0007094435,0.0023439461,0.0010939649,0.0034850913,0.0025230052,0.0013573768,0.00032915646],"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":[0.00046136798,0.00023365965,0.004221629,0.0005132868,0.00020525864,0.00042928598,0.0007079168,0.65724975,0.02443329,0.07177648,0.008648497,0.23111962],"study_design_scores_gemma":[0.000031873726,0.00008027357,0.0007075007,0.000012804988,0.000034742396,0.00012503644,0.00022785914,0.9591103,0.006678424,0.027523154,0.0054470478,0.000020905652],"about_ca_topic_score_codex":0.004771453,"about_ca_topic_score_gemma":0.0042324397,"teacher_disagreement_score":0.004771453,"about_ca_system_score_codex":0.0017670391,"about_ca_system_score_gemma":0.0011681576,"threshold_uncertainty_score":0.019895732},"labels":[],"label_agreement":null},{"id":"W1820584689","doi":"10.1109/icde.1998.655769","title":"On querying spreadsheets","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Online analytical processing; Interoperability; Data warehouse; Schema (genetic algorithms); Software engineering; Database; Generality; Programming language; World Wide Web; Information retrieval","score_opus":0.022706953118206637,"score_gpt":0.22201191751204957,"score_spread":0.19930496439384293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1820584689","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":[0.008378706,0.0038621116,0.97413707,0.0034409794,0.0002638981,0.00022914879,0.00042277868,0.002126038,0.0071391244],"genre_scores_gemma":[0.08264311,0.007642217,0.88833624,0.003366415,0.0016081785,0.0005467858,0.0023642322,0.0012715656,0.012221205],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9781495,0.0047661737,0.0025445386,0.0032775775,0.010335031,0.0009272097],"domain_scores_gemma":[0.96520066,0.02188828,0.0017542039,0.0062594935,0.004043353,0.000854005],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009416516,0.00237644,0.0029306,0.0064971033,0.0037605553,0.009258105,0.0077529247,0.008042822,0.0070121144],"category_scores_gemma":[0.05343757,0.0022573296,0.003510851,0.01371374,0.008134995,0.036046527,0.009301462,0.0060517164,0.002790575],"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":[0.00044100682,0.00019261173,0.0025617185,0.0016863839,0.00017604225,0.0012239926,0.0029202183,0.040534563,0.0061309654,0.6627784,0.024496514,0.25685763],"study_design_scores_gemma":[0.00013825181,0.00019586121,0.00070031453,0.0005093784,0.00014291122,0.001885805,0.0009555446,0.15430532,0.0068628113,0.67353,0.1605674,0.00020644222],"about_ca_topic_score_codex":0.010157976,"about_ca_topic_score_gemma":0.006009722,"teacher_disagreement_score":0.010157976,"about_ca_system_score_codex":0.0037433822,"about_ca_system_score_gemma":0.0024110451,"threshold_uncertainty_score":0.04979992},"labels":[],"label_agreement":null},{"id":"W1824279275","doi":"10.1007/978-3-642-39995-4_6","title":"Intelligence for the Personal Web","year":2013,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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":"IBM (Canada); Queen's University","funders":"","keywords":"Computer science; Analytics; Predictive analytics; Web analytics; World Wide Web; Web service; Web intelligence; Human–computer interaction; Data science; Web modeling","score_opus":0.025402356010516335,"score_gpt":0.2593559191106855,"score_spread":0.23395356310016918,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1824279275","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":[0.002862689,0.031523336,0.02878422,0.009943747,0.0009263087,0.000033054686,0.00023387269,0.0006750681,0.9250177],"genre_scores_gemma":[0.17111465,0.06462621,0.036815744,0.004295945,0.0031110572,0.000099563214,0.0015880264,0.0006729852,0.7176758],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995394,0.00008939532,0.000024546933,0.000071635775,0.00022937749,0.00004575386],"domain_scores_gemma":[0.99953437,0.00014142739,0.000024550252,0.00016611823,0.00007276844,0.000060706385],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00058380875,0.0004487254,0.00039489605,0.001516171,0.0010909131,0.0062696976,0.00065718027,0.0014238558,0.027573785],"category_scores_gemma":[0.001469755,0.00038787062,0.0003736891,0.001925095,0.001852377,0.009813866,0.0022904617,0.0024707727,0.010100241],"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":[0.00001601376,0.000028914501,0.00020118167,0.00015944843,0.00001362729,0.00009048548,0.0004791521,0.0004371886,0.0005983056,0.69785345,0.11535018,0.18477203],"study_design_scores_gemma":[0.0000035166793,0.0000050822773,0.00024161604,0.0001395128,0.0000075444295,0.0001667956,0.00021722466,0.0010724111,0.00037793771,0.3361347,0.6616279,0.0000057186826],"about_ca_topic_score_codex":0.0017976254,"about_ca_topic_score_gemma":0.0023440376,"teacher_disagreement_score":0.027573785,"about_ca_system_score_codex":0.00097419234,"about_ca_system_score_gemma":0.0006760406,"threshold_uncertainty_score":0.09224355},"labels":[],"label_agreement":null},{"id":"W1827701859","doi":"10.1109/icde.1992.213143","title":"An abstraction mechanism for modeling generation","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Abstraction; Formalism (music); Mechanism (biology); Computer science; Generative grammar; Theoretical computer science; Programming language; Generative model; Artificial intelligence; Epistemology; Philosophy","score_opus":0.053159144401813234,"score_gpt":0.29271929888382975,"score_spread":0.2395601544820165,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1827701859","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":[0.0009790291,0.00013457735,0.995331,0.00021132613,0.000056988203,0.000043810574,0.00006427037,0.00069567806,0.002483235],"genre_scores_gemma":[0.101836756,0.0009021003,0.88683796,0.00032191677,0.00018454788,0.0005760066,0.00055009115,0.0006996105,0.008091103],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9977149,0.0006451995,0.000278941,0.0004238959,0.000734464,0.00020274028],"domain_scores_gemma":[0.99740857,0.00096965523,0.00018263033,0.00094785413,0.0003391177,0.00015221197],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004397989,0.0011818537,0.0008583353,0.001434219,0.001917948,0.0044476846,0.0039178277,0.0022500984,0.007145816],"category_scores_gemma":[0.005417344,0.0010000236,0.0034602305,0.0015739676,0.004162355,0.009261369,0.004558543,0.004181926,0.0018784881],"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":[0.000015971113,0.000013803629,0.00013825453,0.000059563507,0.000014662839,0.00011274153,0.000322055,0.014219181,0.0014850516,0.9716557,0.0013732897,0.01058984],"study_design_scores_gemma":[0.00004197178,0.000059448903,0.000094836876,0.00012157384,0.00008203409,0.0003338831,0.00009437871,0.19368708,0.00448724,0.7098499,0.0910819,0.00006566852],"about_ca_topic_score_codex":0.0033604328,"about_ca_topic_score_gemma":0.002136941,"teacher_disagreement_score":0.007145816,"about_ca_system_score_codex":0.0016051679,"about_ca_system_score_gemma":0.0024745446,"threshold_uncertainty_score":0.023905158},"labels":[],"label_agreement":null},{"id":"W1837482209","doi":"10.1109/iwsm.1998.668140","title":"A data warehouse for performance management of distributed systems","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Data warehouse; Computer science; Database; Distributed database; Online analytical processing; Data management; Warehouse; Data modeling; Distributed computing","score_opus":0.08340784418873476,"score_gpt":0.2673270814762634,"score_spread":0.18391923728752863,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1837482209","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":[0.002558604,0.0019181177,0.9366397,0.0016295802,0.00064309465,0.0006614746,0.005528767,0.04357398,0.0068466635],"genre_scores_gemma":[0.026130758,0.0024876564,0.93827873,0.0007289756,0.0006975052,0.0010539715,0.020128723,0.004021509,0.0064721587],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9930588,0.0011744954,0.0017050342,0.00081769744,0.0029742308,0.00026974623],"domain_scores_gemma":[0.9918298,0.0014962325,0.0004812591,0.0036684787,0.0018587054,0.0006656045],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008715441,0.0019636976,0.002466644,0.004488489,0.0021657199,0.009696825,0.005093614,0.0020002772,0.009574015],"category_scores_gemma":[0.012638771,0.0016599338,0.002315936,0.008463139,0.00099545,0.010637862,0.0041084737,0.0050280034,0.007161649],"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":[0.0006984307,0.0004972509,0.0029477077,0.0021583398,0.00056981936,0.0013737238,0.0018412757,0.018229483,0.019119717,0.2404651,0.25298625,0.4591129],"study_design_scores_gemma":[0.00039591608,0.0003236639,0.0022716485,0.0006429488,0.00034130536,0.0012007592,0.00034668116,0.15849449,0.014630485,0.1342744,0.6867651,0.00031268894],"about_ca_topic_score_codex":0.0028279352,"about_ca_topic_score_gemma":0.0022225608,"teacher_disagreement_score":0.009696825,"about_ca_system_score_codex":0.001591873,"about_ca_system_score_gemma":0.0026130402,"threshold_uncertainty_score":0.046092153},"labels":[],"label_agreement":null},{"id":"W1851849126","doi":"10.1007/978-3-540-30464-7_22","title":"Merging of XML Documents","year":2004,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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":"Carleton University","funders":"","keywords":"Computer science; XML validation; XML Schema Editor; XML Encryption; Streaming XML; Efficient XML Interchange; Document Structure Description; Merge (version control); XML database; XML Signature; Information retrieval; XML; XML Schema (W3C); Database; Programming language; World Wide Web","score_opus":0.012158246283899872,"score_gpt":0.2523578509546292,"score_spread":0.24019960467072934,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1851849126","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":[0.04580779,0.0021012046,0.8761941,0.00086920825,0.0006568084,0.0006097434,0.0032798012,0.02235632,0.04812494],"genre_scores_gemma":[0.17079052,0.0015538064,0.75958914,0.0004926396,0.00021790928,0.0002758313,0.01725594,0.005467909,0.044356193],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9974446,0.00047472003,0.0002599079,0.0006077821,0.0010073265,0.0002055331],"domain_scores_gemma":[0.99633574,0.0011166263,0.00018419065,0.0014535699,0.00078508037,0.00012475366],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023971198,0.0009517129,0.0009385635,0.002878455,0.0013495621,0.0039756596,0.0022005455,0.001353142,0.022426005],"category_scores_gemma":[0.006060911,0.0012698439,0.0018291918,0.004610721,0.00067828223,0.005421955,0.003262454,0.0015226986,0.009369464],"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":[0.00096643256,0.00026780923,0.003189205,0.0010267484,0.00024017785,0.0010855206,0.0018519379,0.00609606,0.08781241,0.06183457,0.038045306,0.79758394],"study_design_scores_gemma":[0.000118479096,0.00039308393,0.0037874086,0.0003106301,0.0005433629,0.001820101,0.0011871838,0.048764326,0.42912617,0.049754966,0.46401432,0.00017990018],"about_ca_topic_score_codex":0.0014007477,"about_ca_topic_score_gemma":0.0014684602,"teacher_disagreement_score":0.022426005,"about_ca_system_score_codex":0.00086499675,"about_ca_system_score_gemma":0.0011660857,"threshold_uncertainty_score":0.07502246},"labels":[],"label_agreement":null},{"id":"W1853645231","doi":"10.1007/11901181_50","title":"iQL: A Query Language for the Instance-Based Data Model","year":2006,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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":"Memorial University of Newfoundland","funders":"","keywords":"Computer science; Query language; Exploit; Class (philosophy); Query optimization; Sargable; Data control language; Data model (GIS); RDF query language; Programming language; Relational database; Query by Example; Object (grammar); Information retrieval; Artificial intelligence; Web query classification; Web search query; Search engine","score_opus":0.035230106636358866,"score_gpt":0.2768388598100966,"score_spread":0.24160875317373773,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1853645231","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":[0.00080330676,0.0002978729,0.94445205,0.0006533479,0.0001296927,0.00022433842,0.007033462,0.04340086,0.0030050334],"genre_scores_gemma":[0.04629199,0.0012999376,0.87540615,0.003053776,0.0003466692,0.0014775238,0.036735658,0.02583212,0.009556242],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9949774,0.0009335712,0.0010057897,0.0006145892,0.002110994,0.000357572],"domain_scores_gemma":[0.99497545,0.0022220958,0.00037971282,0.0013071428,0.0008471892,0.000268377],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0055289185,0.001772767,0.002362255,0.002972335,0.0010945069,0.0069919894,0.0063009067,0.0026757494,0.018131508],"category_scores_gemma":[0.012969942,0.002271009,0.0028613147,0.0037264514,0.002221026,0.013201884,0.006051599,0.0059016505,0.011825557],"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":[0.00073183735,0.00023410018,0.0017273619,0.0026611846,0.00020770758,0.0005928815,0.001592149,0.012674785,0.017732084,0.38372245,0.32416221,0.25396124],"study_design_scores_gemma":[0.00031602613,0.00014583072,0.0005016887,0.000528561,0.00019587527,0.0008693517,0.00030982142,0.109259844,0.031175764,0.26785997,0.5885126,0.00032471778],"about_ca_topic_score_codex":0.0044777314,"about_ca_topic_score_gemma":0.0037384504,"teacher_disagreement_score":0.018131508,"about_ca_system_score_codex":0.0022170846,"about_ca_system_score_gemma":0.0026915797,"threshold_uncertainty_score":0.060655892},"labels":[],"label_agreement":null},{"id":"W1858879794","doi":"10.1007/978-3-642-34002-4_8","title":"Sliced Column-Store (SCS): Ontological Foundations and Practical Implications","year":2012,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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":"Memorial University of Newfoundland","funders":"","keywords":"Column (typography); Computer science; Basis (linear algebra); Database; Mathematics","score_opus":0.04392375029413948,"score_gpt":0.3138288031854855,"score_spread":0.26990505289134603,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1858879794","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":[0.04385076,0.0076791127,0.8344547,0.018070247,0.0008608104,0.0002142743,0.004191234,0.003101154,0.08757762],"genre_scores_gemma":[0.4153117,0.008091802,0.54491425,0.0027488575,0.0007177398,0.0002893631,0.0041474695,0.0010533889,0.022725424],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99840134,0.00037290095,0.00018250989,0.00035614354,0.00050203264,0.00018516737],"domain_scores_gemma":[0.9927182,0.0026668063,0.0003794551,0.002415848,0.0013584895,0.0004613333],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025560085,0.0005888649,0.000691275,0.0013465899,0.00239488,0.009534727,0.0030747352,0.0022641046,0.009656644],"category_scores_gemma":[0.007528374,0.00095083966,0.00085404643,0.006940248,0.008978001,0.02258148,0.0039114314,0.0030704117,0.0019575376],"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":[0.00002623052,0.00001505017,0.00029821927,0.00008584947,0.0000043280547,0.00003254109,0.00040615373,0.00088495604,0.0002838543,0.97479236,0.005400396,0.017770028],"study_design_scores_gemma":[0.000022486403,0.00002679469,0.00031344383,0.00019249138,0.000027864357,0.0003029951,0.0008400901,0.011469038,0.0018525568,0.8924337,0.09247566,0.000042899377],"about_ca_topic_score_codex":0.019901017,"about_ca_topic_score_gemma":0.014706204,"teacher_disagreement_score":0.019901017,"about_ca_system_score_codex":0.0024690502,"about_ca_system_score_gemma":0.005383618,"threshold_uncertainty_score":0.03957033},"labels":[],"label_agreement":null},{"id":"W1865928316","doi":"","title":"On Order Dependencies for the Semantic Web","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; OWL-S; Semantic Web; Web service; Ontology; Web Ontology Language; Semantic Web Stack; Description logic; Social Semantic Web; Ontology language; Plan (archaeology); Order (exchange); Semantic Web Rule Language; Information retrieval; World Wide Web; Theoretical computer science; Semantic analytics","score_opus":0.01627099205929031,"score_gpt":0.2613462749511629,"score_spread":0.2450752828918726,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1865928316","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":[0.01167104,0.0012116557,0.9574042,0.0063416627,0.00055250723,0.000120560646,0.0007393029,0.00070529507,0.021253748],"genre_scores_gemma":[0.3631939,0.0033662189,0.6094535,0.0029748708,0.0016938815,0.00050361466,0.0026441086,0.0007906591,0.015379271],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99486035,0.0020167045,0.0003886527,0.0006341054,0.0017275469,0.0003725906],"domain_scores_gemma":[0.9817467,0.013498982,0.00061282434,0.0020718712,0.001694992,0.00037468487],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006217039,0.00087034586,0.0009807518,0.0026340154,0.0023103599,0.0027969275,0.0016562964,0.0021006633,0.0076801577],"category_scores_gemma":[0.021748284,0.0011656248,0.0018835947,0.0034174593,0.0039637364,0.012578776,0.0043229903,0.0056692823,0.001143583],"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":[0.000030345765,0.000024113457,0.00019811341,0.00007008591,0.0000124274675,0.00013837853,0.00011664337,0.014018827,0.00021033264,0.96512824,0.004605021,0.0154473735],"study_design_scores_gemma":[0.000011544845,0.000004405797,0.00004564564,0.000029194493,0.000007828375,0.000034577686,0.000020774758,0.038055137,0.00027619384,0.9519878,0.009518515,0.000008362775],"about_ca_topic_score_codex":0.0071862997,"about_ca_topic_score_gemma":0.006780006,"teacher_disagreement_score":0.0076801577,"about_ca_system_score_codex":0.002594167,"about_ca_system_score_gemma":0.00182043,"threshold_uncertainty_score":0.032879233},"labels":[],"label_agreement":null},{"id":"W186600092","doi":"","title":"SgmlQL + XGQL = powerful XML pattern-matching and data-manipulation in a single language","year":2000,"lang":"en","type":"article","venue":"RIAO Conference","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer science; XML; Document Structure Description; Efficient XML Interchange; Information retrieval; XML validation; Streaming XML; XML Schema Editor; SGML; Matching (statistics); XML Schema (W3C); Pattern matching; Natural language processing; XML Encryption; Programming language; World Wide Web","score_opus":0.039022575776509104,"score_gpt":0.28710745746104543,"score_spread":0.24808488168453632,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W186600092","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":[0.004699572,0.00018050047,0.94846517,0.0006241437,0.000077770484,0.00024243796,0.0011047233,0.038099002,0.0065066274],"genre_scores_gemma":[0.09939634,0.00086861156,0.8659316,0.0016041786,0.0002379317,0.00060383504,0.0074416837,0.008088737,0.015827166],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9974987,0.0008834377,0.00032064476,0.0003117306,0.0008153307,0.00017009983],"domain_scores_gemma":[0.9984534,0.0005521146,0.00013008532,0.0006072914,0.00018585144,0.00007127944],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0040205587,0.0008267156,0.0007599019,0.0006686246,0.00048137407,0.0029237724,0.0017334784,0.0009980686,0.009061411],"category_scores_gemma":[0.0033907404,0.0006491161,0.0010737343,0.0011269109,0.0015860376,0.0048066108,0.0028857547,0.0015828777,0.0048585883],"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":[0.00079479604,0.00021864523,0.0029427544,0.0012673509,0.00015082929,0.0009782248,0.0020276569,0.011230601,0.042279143,0.39690742,0.10425262,0.43694994],"study_design_scores_gemma":[0.00041589446,0.0002936598,0.0012507882,0.00017453043,0.00011771697,0.0014725727,0.00030686686,0.11427193,0.05136945,0.21788545,0.61230797,0.00013320621],"about_ca_topic_score_codex":0.0019178697,"about_ca_topic_score_gemma":0.0012913704,"teacher_disagreement_score":0.009061411,"about_ca_system_score_codex":0.0005141652,"about_ca_system_score_gemma":0.0012049703,"threshold_uncertainty_score":0.030313492},"labels":[],"label_agreement":null},{"id":"W1878146358","doi":"10.1007/978-3-540-30192-9_12","title":"XML Query Processing and Optimization","year":2004,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Computer science; XML; Component (thermodynamics); Relational algebra; Query optimization; Theoretical computer science; Relational database; Programming language; Algebra over a field; Information retrieval; Mathematics; World Wide Web","score_opus":0.012734684969691695,"score_gpt":0.23850048064553828,"score_spread":0.2257657956758466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1878146358","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":[0.002806179,0.008689365,0.9395455,0.001554962,0.00040746207,0.00010706598,0.0004998597,0.002740433,0.043649085],"genre_scores_gemma":[0.06560718,0.012354782,0.79674584,0.0009836089,0.0012235305,0.00031907752,0.0032227251,0.0017779716,0.11776528],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9975909,0.00047130286,0.00019749113,0.0004189057,0.0012067844,0.00011456844],"domain_scores_gemma":[0.99921405,0.00031872335,0.000029920351,0.00027815433,0.00013732444,0.000021859238],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017568935,0.0012458747,0.0015433509,0.0012348603,0.0006790387,0.003330666,0.0020001403,0.00087478646,0.018481791],"category_scores_gemma":[0.0028994593,0.00094484864,0.0011918254,0.0035899319,0.0011060964,0.004017274,0.001759931,0.0021608018,0.008479677],"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":[0.00011490172,0.00011244187,0.0002754068,0.00043754355,0.00007497869,0.00007747181,0.00014723143,0.018298851,0.0043587517,0.31863183,0.077234045,0.58023655],"study_design_scores_gemma":[0.000048392452,0.00007973189,0.00056215754,0.0001259458,0.00007621876,0.00048053588,0.000100702644,0.19791497,0.013249358,0.5002822,0.28702596,0.00005381287],"about_ca_topic_score_codex":0.0017293757,"about_ca_topic_score_gemma":0.0016559267,"teacher_disagreement_score":0.018481791,"about_ca_system_score_codex":0.0011985285,"about_ca_system_score_gemma":0.00087817543,"threshold_uncertainty_score":0.06182778},"labels":[],"label_agreement":null},{"id":"W1884435899","doi":"10.1007/3-540-45140-4_4","title":"Towards Extensible Information Brokers Based on XML","year":2000,"lang":"en","type":"book-chapter","venue":"Notes on numerical fluid mechanics and multidisciplinary design","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":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Government of Canada","keywords":"Computer science; XML; Personalization; The Internet; World Wide Web; XML Schema (W3C); Database; Information retrieval; XML validation; XML Encryption","score_opus":0.026004889454211907,"score_gpt":0.24989840999228155,"score_spread":0.22389352053806966,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1884435899","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":[0.0068803467,0.0012362964,0.9645037,0.0009557349,0.00034650924,0.0003467732,0.00048109418,0.020083182,0.0051663313],"genre_scores_gemma":[0.061008174,0.0023824626,0.9107647,0.00080595555,0.0002151804,0.0005393336,0.0052221436,0.0037011902,0.01536094],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9948138,0.0011957715,0.001117314,0.00072490657,0.0017409069,0.00040725202],"domain_scores_gemma":[0.9911773,0.002776966,0.00041706127,0.0039731795,0.0011757241,0.00047978648],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.014093584,0.0012907437,0.0026374664,0.0033805752,0.0018579547,0.010787228,0.005843176,0.0036465393,0.0076928367],"category_scores_gemma":[0.016615523,0.003490045,0.0022141899,0.005236725,0.0022406634,0.021122081,0.009895358,0.0063330736,0.0051896465],"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":[0.0010687903,0.0005536866,0.0024491607,0.0008084948,0.00029319507,0.00084472273,0.0030586463,0.018483233,0.01727232,0.54698616,0.050658274,0.3575232],"study_design_scores_gemma":[0.0004862935,0.00023111026,0.00053355086,0.000633849,0.00041512976,0.0005840778,0.0009823708,0.23045035,0.033037864,0.4407983,0.29164833,0.00019882653],"about_ca_topic_score_codex":0.0042050323,"about_ca_topic_score_gemma":0.0032598083,"teacher_disagreement_score":0.014093584,"about_ca_system_score_codex":0.0013274527,"about_ca_system_score_gemma":0.0017319517,"threshold_uncertainty_score":0.07453483},"labels":[],"label_agreement":null},{"id":"W1890359884","doi":"10.1109/tai.1993.633975","title":"Evaluating logical queries by means of communicating processes","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Computer science; Predicate (mathematical logic); Petri net; Heuristics; Theoretical computer science; Computation; Deductive database; Message passing; Extensional definition; Database theory; Query language; Programming language; Database; Relational database","score_opus":0.11391959810348125,"score_gpt":0.3405884453056424,"score_spread":0.22666884720216118,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1890359884","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":[0.026020762,0.00019398872,0.96907425,0.00024913347,0.000029620413,0.00018723693,0.000029698675,0.0011007276,0.003114601],"genre_scores_gemma":[0.32987353,0.0002504839,0.6679308,0.0001335113,0.00007555851,0.00021757129,0.00010413987,0.000118325755,0.0012961591],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9944957,0.0019530632,0.0003820352,0.00073069154,0.0020436668,0.0003949689],"domain_scores_gemma":[0.99486274,0.0031283298,0.00036348574,0.0007410086,0.0007283462,0.00017614702],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00605067,0.0007541979,0.0009687985,0.0012568514,0.0017620802,0.003798663,0.0025181954,0.0014248061,0.0018313513],"category_scores_gemma":[0.011927142,0.0006611613,0.0013382133,0.0011255012,0.0033772336,0.004948965,0.0024168107,0.0016051633,0.00035172954],"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":[0.00054268254,0.00021981377,0.0023360583,0.00031787512,0.000113276445,0.0007756528,0.0019149337,0.09836306,0.020241972,0.7579817,0.0016081728,0.11558477],"study_design_scores_gemma":[0.00016349496,0.00020355078,0.00028738624,0.00005553651,0.00020764743,0.0002387358,0.0002715091,0.6457949,0.027947433,0.3110591,0.013709143,0.00006162587],"about_ca_topic_score_codex":0.0032369415,"about_ca_topic_score_gemma":0.0024845446,"teacher_disagreement_score":0.00605067,"about_ca_system_score_codex":0.0016127325,"about_ca_system_score_gemma":0.0022886938,"threshold_uncertainty_score":0.03199941},"labels":[],"label_agreement":null},{"id":"W1910577028","doi":"10.1109/cmpcmm.1993.659092","title":"The OSIRIS ATM Interface: Experience and Insights","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","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":"Bell (Canada)","funders":"","keywords":"Osiris; Interface (matter); Computer science; Human–computer interaction; Operating system","score_opus":0.009655738437953509,"score_gpt":0.2603533038630014,"score_spread":0.25069756542504784,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1910577028","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":[0.5720759,0.0430829,0.18930978,0.016756095,0.0008269853,0.00037370773,0.0009028122,0.0022901043,0.17438179],"genre_scores_gemma":[0.8410492,0.023616824,0.100111924,0.0025106764,0.0007636329,0.00010013177,0.0014679974,0.00078911014,0.029590575],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9960406,0.0014111224,0.00016310847,0.0003303266,0.0016579473,0.00039690128],"domain_scores_gemma":[0.991104,0.0042741476,0.00029129357,0.0006018051,0.0030103317,0.00071849674],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.016512683,0.0008961965,0.0006158618,0.0009528879,0.0006614298,0.004798645,0.0034494924,0.0017606339,0.0071365763],"category_scores_gemma":[0.015640197,0.00037620906,0.00035507692,0.0013698589,0.0015555345,0.0066000465,0.0015719,0.002788515,0.0017287353],"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":[0.0032328756,0.0022599583,0.036161456,0.0011451775,0.00015548227,0.00086051354,0.008874072,0.011927001,0.02935219,0.03401189,0.032381188,0.8396381],"study_design_scores_gemma":[0.0008348313,0.010018865,0.03436642,0.0017441594,0.00060493115,0.005445136,0.01947437,0.093278944,0.12149519,0.03205194,0.6801033,0.0005819969],"about_ca_topic_score_codex":0.0029893266,"about_ca_topic_score_gemma":0.0035156105,"teacher_disagreement_score":0.016512683,"about_ca_system_score_codex":0.0009621154,"about_ca_system_score_gemma":0.0010150447,"threshold_uncertainty_score":0.087328434},"labels":[],"label_agreement":null},{"id":"W1920747368","doi":"10.1109/icde.1998.655823","title":"ROL: a prototype for deductive object-oriented databases","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Database schema; Deductive database; Programming language; Database; Query language; Semantics (computer science); Schema (genetic algorithms); Object (grammar); Set (abstract data type); Database design; Class (philosophy); Information retrieval; Artificial intelligence","score_opus":0.043247365703811186,"score_gpt":0.2805278945717235,"score_spread":0.23728052886791232,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1920747368","genre_codex":"methods","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0045419806,0.00067481253,0.82596946,0.0010181697,0.0003002538,0.001097228,0.0015121341,0.14850232,0.016383674],"genre_scores_gemma":[0.03853589,0.0011179682,0.9102356,0.001335147,0.00025549834,0.0010093738,0.007896227,0.00834835,0.031265993],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9976921,0.0003785331,0.00028268463,0.00042023632,0.0010294882,0.00019695252],"domain_scores_gemma":[0.99699223,0.0010074094,0.00019930553,0.0008603913,0.00060407654,0.00033649927],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003955969,0.000709107,0.00095067656,0.0012053421,0.00070163596,0.0042108167,0.00653267,0.0016379576,0.023640312],"category_scores_gemma":[0.0069345194,0.0011486685,0.00092624367,0.0013541481,0.0011086699,0.0073454236,0.0027766651,0.0020170943,0.01580513],"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":[0.0013838075,0.00091456715,0.0020954555,0.0021606367,0.00018197326,0.0025958891,0.001639391,0.008139835,0.043346114,0.11018161,0.20074798,0.6266128],"study_design_scores_gemma":[0.0008768043,0.00046824405,0.0006300528,0.00046492153,0.00017275207,0.0018568311,0.0002840236,0.06864358,0.029875714,0.043538973,0.85300523,0.00018284193],"about_ca_topic_score_codex":0.00147942,"about_ca_topic_score_gemma":0.0012105255,"teacher_disagreement_score":0.023640312,"about_ca_system_score_codex":0.0006576722,"about_ca_system_score_gemma":0.0012152281,"threshold_uncertainty_score":0.079084694},"labels":[],"label_agreement":null},{"id":"W193394673","doi":"10.5220/0001336100610068","title":"ON DIGITAL SEARCH TREES - A Simple Method for Constructing Balanced Binary Trees","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","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 Toronto","funders":"","keywords":"Binary search tree; Simple (philosophy); Ternary search tree; Computer science; Optimal binary search tree; Weight-balanced tree; Binary tree; Binary number; Random binary tree; Theoretical computer science; Algorithm; Mathematics; Arithmetic; K-ary tree; Tree structure; Interval tree","score_opus":0.02787745641179899,"score_gpt":0.33281239717838634,"score_spread":0.30493494076658734,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W193394673","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":[0.0048245066,0.00034883228,0.9878033,0.00018480957,0.00010021079,0.00019681489,0.00060090673,0.0014607522,0.0044799754],"genre_scores_gemma":[0.046973914,0.000559103,0.9442921,0.00016053236,0.00011687514,0.00036292948,0.001648412,0.00057230407,0.0053137],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99822575,0.00032523015,0.00017205357,0.0002711627,0.00086337945,0.00014243474],"domain_scores_gemma":[0.9965145,0.0015760547,0.00015909104,0.00086356467,0.0007417661,0.00014503981],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001578767,0.0007675831,0.0010943064,0.003845971,0.0013097615,0.0024718177,0.0015085571,0.0009360513,0.011119993],"category_scores_gemma":[0.011475383,0.00071837404,0.0009772144,0.006280202,0.0011132838,0.0055169864,0.0026608026,0.0015634699,0.0036989723],"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":[0.00025183428,0.000100737314,0.00096500304,0.00037095023,0.000043047417,0.00009580537,0.00032265682,0.020399008,0.010898629,0.17405725,0.020695362,0.77179974],"study_design_scores_gemma":[0.00020748662,0.00015511758,0.00093469577,0.0001959254,0.00012776305,0.0006374472,0.0002540529,0.324094,0.020965043,0.54073226,0.11160069,0.000095506766],"about_ca_topic_score_codex":0.0021610763,"about_ca_topic_score_gemma":0.004184765,"teacher_disagreement_score":0.011119993,"about_ca_system_score_codex":0.0011022661,"about_ca_system_score_gemma":0.0014712303,"threshold_uncertainty_score":0.037200093},"labels":[],"label_agreement":null},{"id":"W1941705215","doi":"10.1109/ccece.2001.933606","title":"The use of conceptual models during the design of new telecommunication services","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Telecommunications service; Conceptual model; Computer science; Conceptual design; Telecommunications; Process (computing); Service (business); Software deployment; Conceptual framework; Telos; Knowledge management; Software engineering; Process management; Business","score_opus":0.12493096564169302,"score_gpt":0.24874883364871778,"score_spread":0.12381786800702475,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1941705215","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":[0.0049768537,0.0010860987,0.98481363,0.0018767454,0.00009339725,0.00021602566,0.00007004557,0.00020767775,0.0066594994],"genre_scores_gemma":[0.08558759,0.0026255108,0.9078189,0.00034485728,0.000095918425,0.00051167444,0.00031935933,0.00016905383,0.0025270428],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.97628754,0.016273763,0.0014936078,0.0011214532,0.00417375,0.0006498786],"domain_scores_gemma":[0.9625194,0.027746785,0.0023877793,0.0043985513,0.0023761657,0.0005713372],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.023681719,0.0014876929,0.0007264616,0.0031761397,0.0020021687,0.0083707785,0.0029564772,0.003143178,0.00344189],"category_scores_gemma":[0.04055681,0.0020056132,0.002062822,0.002869323,0.005778219,0.01646758,0.0039706817,0.005551765,0.0012354943],"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":[0.000075662094,0.0000950178,0.00054955785,0.00077366375,0.00005345409,0.0004791457,0.010261268,0.026510997,0.003593375,0.8657381,0.0024818538,0.08938788],"study_design_scores_gemma":[0.00010398371,0.00023497448,0.000581538,0.0017757072,0.00016455867,0.001073172,0.0046612923,0.10076805,0.008216654,0.57943696,0.30277622,0.00020688405],"about_ca_topic_score_codex":0.0039308695,"about_ca_topic_score_gemma":0.0042900653,"teacher_disagreement_score":0.023681719,"about_ca_system_score_codex":0.004551108,"about_ca_system_score_gemma":0.005172423,"threshold_uncertainty_score":0.12524235},"labels":[],"label_agreement":null},{"id":"W1941844167","doi":"10.1109/adl.1998.670397","title":"Query optimization for structured documents based on knowledge on the document type definition","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":30,"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 Alberta","funders":"","keywords":"Computer science; Information retrieval; Exploit; Query optimization; Query language; Document type definition; Transformation (genetics); Sargable; Web search query; Document Structure Description; XML; World Wide Web; Search engine","score_opus":0.038085631121421694,"score_gpt":0.26534032707521366,"score_spread":0.22725469595379197,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1941844167","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":[0.01990825,0.00017600479,0.97542953,0.00018832831,0.00002503777,0.00017546864,0.0001860116,0.0025712429,0.0013401095],"genre_scores_gemma":[0.15222706,0.00045203234,0.8428177,0.00015441087,0.000068383095,0.00019558903,0.0016575769,0.0006558035,0.001771372],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99467504,0.0014268667,0.00064885104,0.00079372944,0.002146626,0.00030880648],"domain_scores_gemma":[0.99130064,0.005612948,0.0004790627,0.0016302428,0.00078110886,0.00019600963],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0039272774,0.00068238,0.0017393337,0.0013305385,0.00073441816,0.0038049025,0.0016988234,0.00091937324,0.0014007343],"category_scores_gemma":[0.013125181,0.0005334266,0.0018373346,0.0023427121,0.001484757,0.004583374,0.0022009527,0.002131931,0.0008710519],"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":[0.001155721,0.00066501246,0.005400842,0.00067427586,0.00026770166,0.0006814103,0.0013260609,0.2063859,0.05721548,0.20114435,0.008985811,0.5160974],"study_design_scores_gemma":[0.00008106856,0.00016111865,0.00051241944,0.00002705706,0.000094160176,0.00034292252,0.00020805253,0.86298203,0.03304485,0.09513187,0.0073578325,0.000056556666],"about_ca_topic_score_codex":0.0038299246,"about_ca_topic_score_gemma":0.0035559882,"teacher_disagreement_score":0.0039272774,"about_ca_system_score_codex":0.0010602999,"about_ca_system_score_gemma":0.0015253577,"threshold_uncertainty_score":0.020769656},"labels":[],"label_agreement":null},{"id":"W194356895","doi":"10.1007/978-1-4613-0103-5_19","title":"Data-Acquisition Systems","year":2001,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Database Systems and Queries","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":"Wilfrid Laurier University","funders":"","keywords":"Chassis; Data acquisition; Computer science; Context (archaeology); Power (physics); Engineering; Operating system; Mechanical engineering","score_opus":0.05744161309112771,"score_gpt":0.2699059203684437,"score_spread":0.21246430727731597,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W194356895","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003901707,0.008116949,0.35826093,0.0018010804,0.0013613148,0.0008483105,0.0063884454,0.037690643,0.5816306],"genre_scores_gemma":[0.03482988,0.008156258,0.1642934,0.0021953757,0.0007884385,0.00053098996,0.011725583,0.0028198797,0.7746602],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99918956,0.000081971266,0.000050432882,0.00020464566,0.0004169945,0.000056398505],"domain_scores_gemma":[0.99910766,0.00017387925,0.000028103932,0.00029078472,0.00034558293,0.00005392495],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00093845703,0.0011727118,0.00074115547,0.002202962,0.0008703127,0.0035484317,0.001741977,0.0010435247,0.12966228],"category_scores_gemma":[0.0017251018,0.00070311327,0.00043666517,0.0032224965,0.00053370174,0.0041477913,0.0019822055,0.001406485,0.106886834],"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":[0.00010458526,0.000081444094,0.000415095,0.0005017891,0.000021814649,0.000097564916,0.00020059632,0.0005408462,0.011089451,0.06353236,0.28525364,0.6381609],"study_design_scores_gemma":[0.000016976557,0.000030958963,0.00041038162,0.00008841577,0.000016951642,0.00023034113,0.000036840873,0.0019683125,0.009963144,0.009268515,0.9779515,0.000017698407],"about_ca_topic_score_codex":0.0012181572,"about_ca_topic_score_gemma":0.0011232685,"teacher_disagreement_score":0.12966228,"about_ca_system_score_codex":0.00068866875,"about_ca_system_score_gemma":0.00093900436,"threshold_uncertainty_score":0.4337635},"labels":[],"label_agreement":null},{"id":"W1947850017","doi":"10.1109/dexa.1998.707505","title":"Design and implementation of the Relationlog deductive database system","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Deductive database; Datalog; Programming language; Database design; Data control language; Database; Query language; Data manipulation language; Database theory; Information retrieval; Query by Example","score_opus":0.027621916630388505,"score_gpt":0.2596567370838326,"score_spread":0.23203482045344406,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1947850017","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":[0.0131890355,0.0004333702,0.94652754,0.0005493275,0.0001718393,0.00086417265,0.00058611896,0.025628729,0.012049864],"genre_scores_gemma":[0.14096476,0.00058591994,0.8455231,0.000643428,0.00009302154,0.0005918115,0.0016196594,0.00080729125,0.009171057],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99871075,0.00018518677,0.0001314786,0.00023503532,0.0006089455,0.00012859923],"domain_scores_gemma":[0.9989755,0.00027240065,0.00007567756,0.00028468555,0.0002956272,0.000096236676],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016692589,0.00028967217,0.0004774377,0.0007344378,0.0006228568,0.0024066258,0.002600129,0.00090432743,0.0072970106],"category_scores_gemma":[0.0031015025,0.0005788808,0.0004506954,0.0005794048,0.00085558876,0.0027021475,0.001262482,0.0013719688,0.003901872],"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":[0.0008881655,0.0011288355,0.004355418,0.0014795151,0.00013489605,0.0016752667,0.0016261246,0.04041762,0.08642035,0.23114468,0.036832206,0.5938969],"study_design_scores_gemma":[0.0006445275,0.000848518,0.0015990363,0.00021497274,0.00029429843,0.002000569,0.00039519297,0.34405527,0.16931765,0.07119824,0.40924132,0.00019046364],"about_ca_topic_score_codex":0.0016469801,"about_ca_topic_score_gemma":0.0016362601,"teacher_disagreement_score":0.0072970106,"about_ca_system_score_codex":0.0006983518,"about_ca_system_score_gemma":0.0022897949,"threshold_uncertainty_score":0.024410903},"labels":[],"label_agreement":null},{"id":"W1948089873","doi":"10.1109/case.1995.465295","title":"Interactive object-oriented schema development","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Conceptual schema; Semantic reasoner; Schema (genetic algorithms); Programming language; Star schema; Database schema; Schema migration; Semi-structured model; Theoretical computer science; Information retrieval; Artificial intelligence; Database design","score_opus":0.018638566117340223,"score_gpt":0.23686410624588844,"score_spread":0.21822554012854822,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1948089873","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":[0.004153247,0.00011524167,0.9748458,0.0002491263,0.00006049209,0.00025031104,0.0003199549,0.012024708,0.007981067],"genre_scores_gemma":[0.049654562,0.0004600782,0.9369074,0.00019982456,0.000031549123,0.00047272112,0.0019996972,0.0021273282,0.008146857],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99713093,0.0010014864,0.0002992475,0.00030968853,0.0011258543,0.00013284576],"domain_scores_gemma":[0.99346644,0.004109898,0.00015726483,0.0011667053,0.0008475347,0.0002521829],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0064694053,0.00078603363,0.0005726314,0.001369975,0.0007891539,0.0039880523,0.0024699806,0.0011692401,0.010844566],"category_scores_gemma":[0.0118190395,0.0009784596,0.0013575268,0.001046844,0.0010541687,0.0038803974,0.0043227933,0.0014633142,0.002712887],"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":[0.0004548681,0.0004214102,0.0025123446,0.0009588046,0.0001933748,0.001749701,0.0063776243,0.021462442,0.03121093,0.44823247,0.044184193,0.44224182],"study_design_scores_gemma":[0.0003176708,0.00009695956,0.00056988304,0.00027223496,0.00011892123,0.001185224,0.0007159109,0.17538893,0.044377677,0.22351076,0.5533396,0.000106263426],"about_ca_topic_score_codex":0.0009758719,"about_ca_topic_score_gemma":0.0011955098,"teacher_disagreement_score":0.010844566,"about_ca_system_score_codex":0.0007855862,"about_ca_system_score_gemma":0.0011946122,"threshold_uncertainty_score":0.036278665},"labels":[],"label_agreement":null},{"id":"W1949546175","doi":"10.1109/hicss.1990.205201","title":"Transforming from flat algebra to nested algebra","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Relational algebra; Joins; Relation algebra; Algebra over a field; Computer science; Redundancy (engineering); Universal algebra; Nested loop join; Selection (genetic algorithm); Boolean algebra; Relation (database); Nesting (process); Mathematics; Pure mathematics; Programming language; Algorithm; Database; Relational database; Two-element Boolean algebra; Filtered algebra; Artificial intelligence","score_opus":0.02100975472547761,"score_gpt":0.23064715124755508,"score_spread":0.20963739652207747,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1949546175","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":[0.03128583,0.0001391679,0.9443165,0.00073967356,0.0001359385,0.000108645785,0.000110512374,0.00094831473,0.02221539],"genre_scores_gemma":[0.4063889,0.00042265162,0.58271307,0.0007675884,0.00014597189,0.00011118721,0.00033783604,0.0002436925,0.008869151],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.998425,0.00035561557,0.000109511915,0.0002219145,0.0007045316,0.00018354825],"domain_scores_gemma":[0.9986249,0.0003925215,0.000090916445,0.00044474457,0.0003561513,0.00009068395],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015525336,0.00025843922,0.00025525453,0.00056216394,0.00082487625,0.0019507582,0.0009797072,0.0005568837,0.00329857],"category_scores_gemma":[0.0044864547,0.0003448785,0.00075562164,0.000601998,0.0022878589,0.0057997517,0.0023595977,0.0014385079,0.0008011143],"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":[0.000035103065,0.000043289492,0.00026022512,0.00003653296,0.000007235048,0.0002654186,0.00072068,0.0036559994,0.005001416,0.9553641,0.0016249405,0.032984972],"study_design_scores_gemma":[0.000021998545,0.00006167286,0.00020044533,0.000019819387,0.000009989545,0.00028357934,0.0003505507,0.041486565,0.006871158,0.9214979,0.029172612,0.000023824898],"about_ca_topic_score_codex":0.0063604927,"about_ca_topic_score_gemma":0.0038037861,"teacher_disagreement_score":0.0063604927,"about_ca_system_score_codex":0.0010468295,"about_ca_system_score_gemma":0.0011741304,"threshold_uncertainty_score":0.012646973},"labels":[],"label_agreement":null},{"id":"W1952702272","doi":"10.1109/ast.1996.506488","title":"Object-oriented modeling in Metaview","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta; Nortel (Canada)","funders":"","keywords":"Computer science; Object-oriented programming; Object (grammar); Feature (linguistics); Object-oriented modeling; Object-oriented analysis and design; Mechanism (biology); Object model; Software engineering; Artificial intelligence; Programming language; Unified Modeling Language","score_opus":0.051840339282909965,"score_gpt":0.2520056713440065,"score_spread":0.20016533206109652,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1952702272","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":[0.0018742731,0.00056060863,0.987611,0.00069045764,0.00011087213,0.00006969941,0.000052480635,0.00043408113,0.00859652],"genre_scores_gemma":[0.06378074,0.0017574849,0.9271428,0.0004399847,0.0003097814,0.0004814048,0.00024348969,0.00035306843,0.005491279],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99598277,0.0022366021,0.00028567793,0.00034276058,0.00090138544,0.000250802],"domain_scores_gemma":[0.99420446,0.0032794527,0.00060224696,0.0011700873,0.00044049,0.0003032749],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008942006,0.0010843755,0.00091381575,0.0022458525,0.0011800841,0.0083478205,0.0033636543,0.0020925147,0.003935529],"category_scores_gemma":[0.00794054,0.0012252611,0.0021164797,0.0022325316,0.0031164377,0.009068333,0.0034263555,0.0034020385,0.0012517578],"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":[0.0000164777,0.000031733383,0.0003110484,0.000089875364,0.000030713403,0.00020372127,0.0008757682,0.010128239,0.00063437445,0.9708981,0.0014026959,0.015377353],"study_design_scores_gemma":[0.00006259306,0.00007457998,0.00022402656,0.00028596545,0.00006422663,0.00044656076,0.00030832578,0.092196435,0.0026602675,0.755317,0.14831127,0.0000487605],"about_ca_topic_score_codex":0.0018062483,"about_ca_topic_score_gemma":0.0022316077,"teacher_disagreement_score":0.008942006,"about_ca_system_score_codex":0.0015303239,"about_ca_system_score_gemma":0.0015931309,"threshold_uncertainty_score":0.047290444},"labels":[],"label_agreement":null},{"id":"W1964417640","doi":"10.1504/ijiids.2010.035772","title":"Processing exact results for sliding window joins over data streams using disk storage","year":2010,"lang":"en","type":"article","venue":"International Journal of Intelligent Information and Database Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Joins; Computer science; Sliding window protocol; Window (computing); Data stream mining; Data stream; Real-time computing; Algorithm; Data mining; Distributed computing; Parallel computing; Operating system","score_opus":0.047514629237544494,"score_gpt":0.32993797029605587,"score_spread":0.28242334105851136,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1964417640","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":[0.053793732,0.0005948474,0.9426183,0.0002180707,0.00007220766,0.00008790492,0.00014907894,0.0015798964,0.0008859483],"genre_scores_gemma":[0.36178902,0.00044697526,0.6353143,0.00006392366,0.00018743395,0.00010962493,0.0006049075,0.00037191677,0.0011118893],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9938572,0.00087843684,0.00084577483,0.0008020532,0.0032989061,0.00031757052],"domain_scores_gemma":[0.9780939,0.013783609,0.0017783641,0.0035587554,0.0023487315,0.00043656433],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0072143762,0.0013027393,0.002545513,0.0018358339,0.0012411121,0.0042993166,0.002002687,0.0011613558,0.001979275],"category_scores_gemma":[0.02568882,0.000798733,0.0009144429,0.002731628,0.0017371336,0.0064401953,0.0026989742,0.0012616448,0.000630229],"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":[0.002537001,0.00036604182,0.0070694285,0.001079876,0.0002679626,0.0010554789,0.0015611685,0.43330273,0.043290373,0.055793703,0.0039299573,0.4497463],"study_design_scores_gemma":[0.000055308712,0.00018137433,0.00030925428,0.000024366778,0.000026438514,0.00018938982,0.00015677835,0.9508636,0.015916344,0.03113069,0.0011223699,0.000024008139],"about_ca_topic_score_codex":0.0011832335,"about_ca_topic_score_gemma":0.0014819991,"teacher_disagreement_score":0.0072143762,"about_ca_system_score_codex":0.00074439246,"about_ca_system_score_gemma":0.0014006824,"threshold_uncertainty_score":0.038153768},"labels":[],"label_agreement":null},{"id":"W1964597053","doi":"10.3166/isi.9.3-4.83-108","title":"Extraction itérative de requêtes fréquentes","year":2004,"lang":"fr","type":"article","venue":"Ingénierie des systèmes d information","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Extraction (chemistry); Chemistry; Chromatography","score_opus":0.022117163446725627,"score_gpt":0.26768201530844254,"score_spread":0.24556485186171692,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1964597053","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":[0.049977243,0.0010685966,0.9417796,0.00033441465,0.00008432256,0.0004939892,0.0008331081,0.0033295862,0.0020991678],"genre_scores_gemma":[0.18136121,0.000854669,0.8088293,0.0002136589,0.00020050525,0.00046089324,0.0042122165,0.0007863616,0.003081193],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9797092,0.0042080823,0.0021226709,0.003809441,0.009176905,0.00097372854],"domain_scores_gemma":[0.94238985,0.037825454,0.0026320065,0.009092984,0.007457569,0.0006021061],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007919732,0.0020229002,0.0030336801,0.0064891917,0.0017693402,0.005586859,0.003553745,0.002391881,0.00385712],"category_scores_gemma":[0.05387001,0.0017903305,0.0043834457,0.0056457003,0.0020421087,0.007524531,0.004837247,0.0028372325,0.0021938821],"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":[0.0011677587,0.00046812935,0.017375333,0.0014550659,0.00064368895,0.0019178656,0.0029791621,0.020607438,0.039647188,0.064684495,0.0063546244,0.8426993],"study_design_scores_gemma":[0.00040620525,0.00094441144,0.015404292,0.0005163131,0.00095991243,0.00792332,0.002297082,0.5743202,0.1319422,0.1952472,0.069628105,0.00041078817],"about_ca_topic_score_codex":0.002373752,"about_ca_topic_score_gemma":0.0030123275,"teacher_disagreement_score":0.007919732,"about_ca_system_score_codex":0.0011690736,"about_ca_system_score_gemma":0.0025530863,"threshold_uncertainty_score":0.041884005},"labels":[],"label_agreement":null},{"id":"W1965783511","doi":"10.5555/2486788.2486965","title":"Supporting application development with structured queries in the cloud","year":2013,"lang":"en","type":"article","venue":"International Conference on Software Engineering","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Computer science; Cloud computing; Ontology; SQL; Terminology; Abstraction; World Wide Web; Database; Set (abstract data type); Information retrieval; Software engineering; Data science; Programming language","score_opus":0.012885609363114872,"score_gpt":0.2518800112637012,"score_spread":0.23899440190058632,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1965783511","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":[0.018075762,0.000089538866,0.96746504,0.00064952485,0.000027252112,0.00037845102,0.00024249063,0.010242691,0.0028291778],"genre_scores_gemma":[0.22301058,0.0003276839,0.76926386,0.00064458326,0.00007187867,0.00044940965,0.0012022835,0.0021195293,0.0029101274],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.98966366,0.0041541606,0.0015869439,0.00096099515,0.0028379073,0.00079629075],"domain_scores_gemma":[0.9744564,0.014841548,0.001491925,0.0052990527,0.0030123633,0.00089867786],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012123893,0.00090653595,0.0009610197,0.001374815,0.00127897,0.006624496,0.0031746197,0.0015259375,0.001938694],"category_scores_gemma":[0.021953348,0.0010316422,0.0014485961,0.0016153844,0.0025338153,0.008741247,0.0058305613,0.0025104817,0.0012205365],"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":[0.0016985378,0.0010100979,0.016696872,0.0013874517,0.000304974,0.005326018,0.022231143,0.0717954,0.09025477,0.4861845,0.03544251,0.26766774],"study_design_scores_gemma":[0.00041451745,0.00037828548,0.0018698712,0.00039182295,0.00015087979,0.001581764,0.003197347,0.6063372,0.071132496,0.18868643,0.12563036,0.00022897711],"about_ca_topic_score_codex":0.0051435158,"about_ca_topic_score_gemma":0.004771199,"teacher_disagreement_score":0.012123893,"about_ca_system_score_codex":0.0013030525,"about_ca_system_score_gemma":0.0040057134,"threshold_uncertainty_score":0.06411809},"labels":[],"label_agreement":null},{"id":"W1967675407","doi":"10.1093/logcom/exl010","title":"A Logic of Type Relations and its Applications to Relational Databases","year":2006,"lang":"en","type":"article","venue":"Journal of Logic and Computation","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Francis Xavier University","funders":"","keywords":"Relational database; Computer science; Nondeterministic algorithm; Relational model; Rough set; Relational calculus; Type (biology); Set (abstract data type); Relational algebra; Theoretical computer science; Database; Programming language; Algebra over a field; Mathematics; Artificial intelligence; Pure mathematics","score_opus":0.052531346816544776,"score_gpt":0.31014090831566865,"score_spread":0.2576095614991239,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1967675407","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":[0.003832071,0.008715205,0.96005565,0.0036031606,0.0013913643,0.00012776535,0.00031976862,0.00067191146,0.021283101],"genre_scores_gemma":[0.105503365,0.014203819,0.8584025,0.0018742867,0.002494012,0.00039786845,0.0004562557,0.00037157975,0.016296288],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9972066,0.00080975995,0.0003431701,0.00048821664,0.0009554343,0.00019682402],"domain_scores_gemma":[0.9966948,0.0018249451,0.0002882516,0.00042549876,0.00047754278,0.00028900307],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004265331,0.0010153494,0.0011595788,0.0031043151,0.003155317,0.009101949,0.0028914858,0.0023938548,0.0063689123],"category_scores_gemma":[0.008932077,0.0013222925,0.0032435562,0.007160053,0.0068992497,0.012692233,0.0044314945,0.006014111,0.002243265],"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":[0.000013850877,0.00001487,0.000066262604,0.00007745295,0.000012108587,0.00017577369,0.00020693807,0.001598277,0.00034316725,0.9797071,0.002185439,0.015598801],"study_design_scores_gemma":[0.000011833929,0.000014454266,0.000044713583,0.000073903684,0.000019492958,0.0002834731,0.000076595825,0.008150815,0.00041334814,0.9618162,0.029068716,0.000026431886],"about_ca_topic_score_codex":0.0035456123,"about_ca_topic_score_gemma":0.0024087525,"teacher_disagreement_score":0.009101949,"about_ca_system_score_codex":0.002530247,"about_ca_system_score_gemma":0.0026082252,"threshold_uncertainty_score":0.022557557},"labels":[],"label_agreement":null},{"id":"W1967714462","doi":"10.1145/1463788.1463794","title":"Synchronized tag clouds for exploring semi-structured clinical trial data","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Canada Research Chairs","keywords":"Computer science","score_opus":0.38888680116015406,"score_gpt":0.3990731893879223,"score_spread":0.01018638822776824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1967714462","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":[0.04101915,0.00066419045,0.9419704,0.00048896996,0.000080758226,0.0007240912,0.0024694805,0.0108939735,0.0016888806],"genre_scores_gemma":[0.15577652,0.0003478927,0.83980876,0.00014038687,0.00006069081,0.0007048409,0.0017779714,0.0006277396,0.00075512816],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99436814,0.0027896652,0.00067259365,0.00066037185,0.001269545,0.00023967799],"domain_scores_gemma":[0.9538432,0.036090266,0.0023561383,0.005092444,0.0015711199,0.001046923],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010058041,0.0015615156,0.0014087799,0.0068429387,0.0011634423,0.0053766514,0.0021130736,0.0018830076,0.004502439],"category_scores_gemma":[0.036455657,0.0010982545,0.0015683067,0.0072506173,0.0011646637,0.007424011,0.005210871,0.0013232582,0.0013107006],"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":[0.006743212,0.0007463008,0.013261385,0.0048000864,0.00076078303,0.0030569048,0.029946832,0.04801111,0.09015177,0.05544222,0.025339397,0.72174007],"study_design_scores_gemma":[0.0010819025,0.001623517,0.010996029,0.0007832311,0.00063329097,0.0031215644,0.009552961,0.57514656,0.07005361,0.19603032,0.13023037,0.00074670673],"about_ca_topic_score_codex":0.002823429,"about_ca_topic_score_gemma":0.006021418,"teacher_disagreement_score":0.010058041,"about_ca_system_score_codex":0.0012001399,"about_ca_system_score_gemma":0.0021634817,"threshold_uncertainty_score":0.053192675},"labels":[],"label_agreement":null},{"id":"W1968879741","doi":"10.1023/b:isfi.0000037881.10525.07","title":"Supporting Semantic Diversity in the Relational Data Model: The Case of Multi-Face Attributes","year":2004,"lang":"en","type":"article","venue":"Information Systems Frontiers","topic":"Advanced Database Systems and Queries","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":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Relational model; Relational database; Flexibility (engineering); Database design; Database model; Semantic data model; Data model (GIS); Entity–relationship model; Face (sociological concept); Extension (predicate logic); Data science; Information retrieval; Artificial intelligence; Programming language","score_opus":0.06447404967572654,"score_gpt":0.28930652533963985,"score_spread":0.22483247566391332,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1968879741","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":[0.14026897,0.0010502167,0.8435898,0.0046933694,0.00017771922,0.00011958902,0.0004022346,0.00094114343,0.008756874],"genre_scores_gemma":[0.7917806,0.0005050434,0.20370756,0.00070413447,0.0002621825,0.000101963255,0.00043600868,0.00025912208,0.0022434432],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9794676,0.0077169836,0.0017337515,0.0021364002,0.0066897497,0.002255518],"domain_scores_gemma":[0.90509355,0.052063514,0.0037114825,0.03074719,0.005753275,0.0026308855],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02579645,0.0006674665,0.0025477344,0.0017708096,0.003958433,0.010658739,0.0056659337,0.004938597,0.0024253502],"category_scores_gemma":[0.069694005,0.0013561726,0.0022577893,0.003399167,0.007507223,0.04601459,0.016363896,0.00592827,0.0006289869],"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":[0.0010625102,0.00030050654,0.0077021103,0.00033234188,0.00018396445,0.0018288867,0.0045083184,0.06634775,0.005243927,0.8146755,0.0055604405,0.092253745],"study_design_scores_gemma":[0.000093776995,0.00011305506,0.00037938452,0.00009670933,0.00011430027,0.00092628435,0.0012637001,0.19663568,0.0051632742,0.78706896,0.008036076,0.00010876902],"about_ca_topic_score_codex":0.002874524,"about_ca_topic_score_gemma":0.003472248,"teacher_disagreement_score":0.02579645,"about_ca_system_score_codex":0.0019836833,"about_ca_system_score_gemma":0.0023454865,"threshold_uncertainty_score":0.13642633},"labels":[],"label_agreement":null},{"id":"W1968925642","doi":"10.1145/1995441.1995445","title":"Towards highly parallel event processing through reconfigurable hardware","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Field-programmable gate array; Complex event processing; Scalability; Reconfigurable computing; Computer architecture; Event (particle physics); Adaptability; Stream processing; Embedded system; Parallel computing; Process (computing); Programming language; Operating system","score_opus":0.0510924020436313,"score_gpt":0.27047954041472705,"score_spread":0.21938713837109575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1968925642","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":[0.033705894,0.00061693863,0.9510309,0.00033947936,0.0001566203,0.0000984106,0.00008176424,0.004654675,0.009315375],"genre_scores_gemma":[0.38834554,0.0009949035,0.60006493,0.00036013263,0.00014698245,0.00011695832,0.0003698578,0.00033863707,0.009262062],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994023,0.00010505074,0.000055160126,0.00010582743,0.0002510365,0.000080602375],"domain_scores_gemma":[0.9995727,0.00016985959,0.00004680597,0.00013069075,0.0000572172,0.000022784969],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006378757,0.00045652018,0.00025369762,0.00039180025,0.00035212157,0.0017028856,0.0012076821,0.00044026095,0.003384618],"category_scores_gemma":[0.0009869791,0.00030185934,0.00043421888,0.00055950024,0.00069845835,0.0015362083,0.00071313453,0.0008739025,0.0010299368],"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":[0.0011654373,0.0002439427,0.0021014996,0.0006199846,0.00013661063,0.0010408992,0.00039152836,0.10812284,0.20753029,0.24513765,0.014972315,0.418537],"study_design_scores_gemma":[0.00023110666,0.00042105073,0.00053105206,0.000054550823,0.00011344348,0.0006588453,0.00008418706,0.6715731,0.18910503,0.060286116,0.07686677,0.000074727424],"about_ca_topic_score_codex":0.001171919,"about_ca_topic_score_gemma":0.0016489123,"teacher_disagreement_score":0.003384618,"about_ca_system_score_codex":0.0004612463,"about_ca_system_score_gemma":0.00052334176,"threshold_uncertainty_score":0.011322677},"labels":[],"label_agreement":null},{"id":"W1969565828","doi":"10.1109/icde.2007.368972","title":"Increasing Buffer-Locality for Multiple Relational Table Scans through Grouping and Throttling","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada)","funders":"","keywords":"Computer science; Workload; Bandwidth throttling; Reuse; Table (database); Locality; Latency (audio); Bandwidth (computing); Database index; Operating system; Database; Distributed computing; Real-time computing; Computer network; Information retrieval; Search engine indexing","score_opus":0.03873612830546713,"score_gpt":0.28508616792948255,"score_spread":0.24635003962401542,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1969565828","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":[0.72855586,0.00215874,0.2454178,0.0005143792,0.00007965485,0.00033087976,0.0001366786,0.017866062,0.004939964],"genre_scores_gemma":[0.8850197,0.00022704691,0.112905554,0.00010353165,0.00006033168,0.000119251046,0.00018179175,0.0004565779,0.00092620513],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981839,0.00040208857,0.00018668972,0.00039681082,0.0005229223,0.00030751558],"domain_scores_gemma":[0.99192274,0.002612547,0.001132149,0.0031445331,0.0006440289,0.00054415653],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017274134,0.0008451669,0.0011822708,0.0018189133,0.001168709,0.0014604193,0.0030798845,0.0008061074,0.001284127],"category_scores_gemma":[0.0072035957,0.0008411518,0.0003880866,0.0017626272,0.00087908417,0.0032676093,0.002349041,0.00085880933,0.0006232261],"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":[0.002371989,0.0010439325,0.024699287,0.00038143448,0.00013839075,0.0004735494,0.001949038,0.043426897,0.49986205,0.0039277594,0.0050497875,0.41667596],"study_design_scores_gemma":[0.00046440415,0.002315473,0.019336646,0.00008182485,0.00033089865,0.001271913,0.0012413511,0.62882686,0.32063797,0.0072432063,0.017980143,0.0002693026],"about_ca_topic_score_codex":0.002781327,"about_ca_topic_score_gemma":0.004034357,"teacher_disagreement_score":0.0030798845,"about_ca_system_score_codex":0.00073264685,"about_ca_system_score_gemma":0.0010257243,"threshold_uncertainty_score":0.009135544},"labels":[],"label_agreement":null},{"id":"W1971778458","doi":"10.1145/773153.773155","title":"An information-theoretic approach to normal forms for relational and XML data","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Relational database; XML; Normalization (sociology); Relational model; Information retrieval; Database normalization; Data mining; Measure (data warehouse); XML validation; Set (abstract data type); Theoretical computer science; Programming language; Artificial intelligence; Cluster analysis; World Wide Web","score_opus":0.028231308012105216,"score_gpt":0.26193153741412817,"score_spread":0.23370022940202295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1971778458","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":[0.0029352254,0.00058951415,0.98894066,0.0016296096,0.00015243041,0.00014475435,0.000179827,0.00022880857,0.0051991954],"genre_scores_gemma":[0.0877354,0.0012413845,0.90326834,0.0010244973,0.00081053143,0.000983374,0.0005125411,0.00029747377,0.004126426],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.95522094,0.018410098,0.006335588,0.0053585023,0.0136642065,0.0010107136],"domain_scores_gemma":[0.9386058,0.03600722,0.0040116394,0.012951757,0.0076193823,0.0008042024],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.030521836,0.001525278,0.0017750359,0.006629996,0.0023904138,0.011113217,0.0042649424,0.0037895255,0.0053263237],"category_scores_gemma":[0.08920021,0.0014053488,0.0030493885,0.010279317,0.019909458,0.02760584,0.005579777,0.0085553415,0.0019016702],"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":[0.000012973324,0.000014011358,0.00014056334,0.00005503306,0.0000085289275,0.000034233854,0.00022569342,0.0019270912,0.00026308117,0.9844737,0.0007517502,0.012093363],"study_design_scores_gemma":[0.0000081664175,0.000021429229,0.000047978257,0.000039996754,0.000006777375,0.00010705248,0.000060927192,0.0090360865,0.000714998,0.9812688,0.008669474,0.00001840013],"about_ca_topic_score_codex":0.0014655573,"about_ca_topic_score_gemma":0.0010507796,"teacher_disagreement_score":0.030521836,"about_ca_system_score_codex":0.005378297,"about_ca_system_score_gemma":0.0030324531,"threshold_uncertainty_score":0.16141683},"labels":[],"label_agreement":null},{"id":"W1972149001","doi":"10.1145/2463676.2465337","title":"Data stream warehousing","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Citation; Computer science; Library science; World Wide Web; Database","score_opus":0.048580890745774014,"score_gpt":0.2763698588857756,"score_spread":0.22778896814000157,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1972149001","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":[0.0039056267,0.013786188,0.7849908,0.005743618,0.0040038554,0.0013174126,0.016977075,0.07022338,0.09905205],"genre_scores_gemma":[0.028775744,0.033068176,0.57064646,0.0031121906,0.0054339664,0.0014105878,0.062842,0.011784363,0.2829265],"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9992754,0.000075382646,0.00006354609,0.00010992719,0.00041338126,0.000062463965],"domain_scores_gemma":[0.9981065,0.0004929371,0.000054989294,0.00029537198,0.0008011773,0.00024893697],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014583368,0.0017027144,0.0007593261,0.0021445304,0.00066054316,0.0025979609,0.0013064941,0.00081351853,0.12220529],"category_scores_gemma":[0.003300436,0.0009340664,0.0011098741,0.0033233897,0.0002673492,0.00406744,0.0021808168,0.0019324153,0.06913901],"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":[0.0000708278,0.00012511565,0.00026279432,0.00050850323,0.000030418356,0.00005079679,0.00007972578,0.002305949,0.0020296762,0.006655824,0.5099775,0.4779029],"study_design_scores_gemma":[0.00004250028,0.00008253238,0.0009534026,0.00024151387,0.000017343602,0.0002620961,0.00009051469,0.01620832,0.0027378006,0.021394042,0.9579296,0.000040208346],"about_ca_topic_score_codex":0.0019832237,"about_ca_topic_score_gemma":0.0025328503,"teacher_disagreement_score":0.12220529,"about_ca_system_score_codex":0.0005688347,"about_ca_system_score_gemma":0.0016298154,"threshold_uncertainty_score":0.4088174},"labels":[],"label_agreement":null},{"id":"W1972300062","doi":"","title":"Proceedings of the 5th ACM international workshop on Data Warehousing and OLAP","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Online analytical processing; Data warehouse; Computer science; Business intelligence; Data science; Database; Quality (philosophy); Data quality; Business","score_opus":0.08902000189135288,"score_gpt":0.2958453347821053,"score_spread":0.2068253328907524,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1972300062","genre_codex":"methods","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":[0.01638705,0.11070847,0.5795931,0.053543065,0.06679268,0.0015908892,0.007821287,0.014023618,0.14953975],"genre_scores_gemma":[0.05409965,0.084055595,0.48377174,0.012243631,0.014251253,0.0012529106,0.048823856,0.0046096467,0.29689175],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99437463,0.0012894832,0.0006780556,0.00082350697,0.0023194465,0.00051493064],"domain_scores_gemma":[0.99376196,0.0012717785,0.00018913507,0.0015176096,0.0022344398,0.0010251229],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0068043405,0.0020315496,0.0021092573,0.0025965602,0.0017645059,0.010093621,0.0036170701,0.0028110151,0.04476156],"category_scores_gemma":[0.009368586,0.0012759537,0.0020617328,0.003399406,0.0018247709,0.011070396,0.006466969,0.0066588344,0.022930028],"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":[0.0003269371,0.00032931688,0.00086238876,0.00062506297,0.00015204785,0.0003864556,0.0009620852,0.0013692903,0.0043538436,0.01646926,0.609088,0.3650753],"study_design_scores_gemma":[0.00003243431,0.000074930926,0.0007589416,0.0003182841,0.0000468047,0.00030818162,0.0003919833,0.00405442,0.0011546516,0.013504479,0.97931105,0.000043857468],"about_ca_topic_score_codex":0.006325789,"about_ca_topic_score_gemma":0.007973321,"teacher_disagreement_score":0.04476156,"about_ca_system_score_codex":0.0012757909,"about_ca_system_score_gemma":0.004173648,"threshold_uncertainty_score":0.14974236},"labels":[],"label_agreement":null},{"id":"W1973020953","doi":"10.1145/2554850.2554891","title":"LittleD","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; SQL; Joins; In-Memory Processing; Relational database; Parsing; Database; Stored procedure; Memory management; Query optimization; Relational database management system; Programming language; Query by Example; Information retrieval; Search engine","score_opus":0.0051199551664739135,"score_gpt":0.2038580278109582,"score_spread":0.1987380726444843,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1973020953","genre_codex":"methods","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":[0.01088182,0.008260791,0.3867421,0.0074948696,0.002850735,0.0011671333,0.044329844,0.18313342,0.35513934],"genre_scores_gemma":[0.10053005,0.007849532,0.37928334,0.009251112,0.0015919508,0.0014401681,0.16204157,0.03613461,0.30187774],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9948349,0.00064881233,0.0005905333,0.00101766,0.0025203978,0.00038778267],"domain_scores_gemma":[0.9888454,0.0019578957,0.00045389205,0.0043916665,0.0035614932,0.00078968506],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0032641261,0.0011077505,0.0011875519,0.0028953226,0.0012016229,0.008294881,0.0056878403,0.0018999433,0.1074779],"category_scores_gemma":[0.013499535,0.0012552172,0.0010961451,0.003783694,0.0010430764,0.009273768,0.005823669,0.0024250778,0.08411778],"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":[0.00088039914,0.00022228071,0.0022153514,0.0013235736,0.000083839994,0.000334994,0.00039434538,0.0015211324,0.009671103,0.073803745,0.49032056,0.4192286],"study_design_scores_gemma":[0.000084179206,0.00008324723,0.00050650345,0.00012263395,0.000025593368,0.00043073515,0.00007740477,0.0049981815,0.0065444275,0.012361954,0.9747181,0.000047141515],"about_ca_topic_score_codex":0.0022729966,"about_ca_topic_score_gemma":0.0024743562,"teacher_disagreement_score":0.8925221,"about_ca_system_score_codex":0.0016555878,"about_ca_system_score_gemma":0.0024610735,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W1973214928","doi":"10.3166/isi.11.6.55-82","title":"Sélection de schéma de fragmentation horizontale dans les entrepôts de données. Formalisation et algorithmes","year":2006,"lang":"fr","type":"article","venue":"Ingénierie des systèmes d information","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Partition (number theory); Simulated annealing; Fragmentation (computing); Algorithm; Mathematics; Combinatorics; Operating system","score_opus":0.021845779939214726,"score_gpt":0.25377326974556125,"score_spread":0.23192748980634653,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1973214928","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":[0.013039599,0.0003517788,0.98446935,0.00017201292,0.000011628463,0.00016382606,0.00008488224,0.00075905357,0.00094791566],"genre_scores_gemma":[0.11063411,0.00037667726,0.88707757,0.00007113009,0.000015750971,0.00019547304,0.00036269342,0.00009580605,0.0011707713],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9981686,0.0006260145,0.00017618929,0.00038449198,0.00051255996,0.00013199933],"domain_scores_gemma":[0.9967631,0.0020620679,0.00038941344,0.00035944756,0.0003485404,0.00007741697],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034849886,0.00072865875,0.0009174245,0.0017224719,0.0006776875,0.0031335352,0.0013323076,0.0016387478,0.0021128403],"category_scores_gemma":[0.007425009,0.0008020729,0.0014169964,0.0020224075,0.0012877518,0.0022449072,0.0012554373,0.001117294,0.0005494218],"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":[0.00028600614,0.00025748712,0.0053768256,0.0006126095,0.00021157623,0.00023406783,0.0007551329,0.383025,0.022802165,0.06241114,0.0023736882,0.5216543],"study_design_scores_gemma":[0.000092885115,0.00013785266,0.0013593619,0.0001456342,0.00007723179,0.00041877324,0.00024267171,0.9445769,0.014807525,0.030490525,0.0076110205,0.000039595994],"about_ca_topic_score_codex":0.004419572,"about_ca_topic_score_gemma":0.003112341,"teacher_disagreement_score":0.004419572,"about_ca_system_score_codex":0.001234541,"about_ca_system_score_gemma":0.0012712864,"threshold_uncertainty_score":0.01843065},"labels":[],"label_agreement":null},{"id":"W1974717772","doi":"10.1145/1966357.1966360","title":"Closed world chasing","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Semantics (computer science); Computer science; Monotonic function; Data exchange; Theoretical computer science; Trough (economics); Chase; Algorithm; Programming language; Mathematics; Database","score_opus":0.05580742758565782,"score_gpt":0.232871795204453,"score_spread":0.17706436761879518,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1974717772","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":[0.0069836923,0.00020888649,0.9792612,0.0009079328,0.00014576872,0.00012275764,0.00024067693,0.00063126406,0.011497806],"genre_scores_gemma":[0.36285344,0.000971924,0.6103322,0.0014601148,0.00041426223,0.0011149844,0.0015768497,0.00084870186,0.020427598],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9927543,0.0021872981,0.0006464865,0.0014787867,0.0022130224,0.00072000205],"domain_scores_gemma":[0.9912469,0.0041829734,0.00038698,0.0021287769,0.0016938044,0.00036056814],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0060706763,0.0010095706,0.0012382523,0.0023105785,0.002890954,0.0061457213,0.0029883832,0.0027991496,0.010137055],"category_scores_gemma":[0.016579187,0.00081956456,0.0029452075,0.0026857415,0.007070678,0.019881006,0.00893095,0.006298885,0.0016387523],"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":[0.000021651878,0.000018614031,0.00005595221,0.00003637076,0.000010602244,0.00005429211,0.00023186435,0.0016776037,0.0006179398,0.9887354,0.0009369087,0.007602779],"study_design_scores_gemma":[0.000026338463,0.00003432727,0.000033489636,0.00003819264,0.00002252313,0.00010100956,0.00012000171,0.018744726,0.0035748777,0.9572118,0.020061582,0.000031175638],"about_ca_topic_score_codex":0.0017116087,"about_ca_topic_score_gemma":0.0012980315,"teacher_disagreement_score":0.010137055,"about_ca_system_score_codex":0.0018347821,"about_ca_system_score_gemma":0.0027759483,"threshold_uncertainty_score":0.033911824},"labels":[],"label_agreement":null},{"id":"W1975270911","doi":"10.1145/601858.601873","title":"Toward autonomic computing with DB2 universal database","year":2002,"lang":"en","type":"article","venue":"ACM SIGMOD Record","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":50,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada)","funders":"","keywords":"Computer science; Total cost of ownership; Database; IBM; Unix; Scale (ratio); Software; Operating system","score_opus":0.03708365375936235,"score_gpt":0.23390888169402854,"score_spread":0.1968252279346662,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975270911","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":[0.039123118,0.010466701,0.84916884,0.01760706,0.0019519456,0.0002561576,0.00015704543,0.009308469,0.07196065],"genre_scores_gemma":[0.33965477,0.008156983,0.62361217,0.007203508,0.0016411956,0.0003936905,0.0005742595,0.0007842967,0.017979153],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99750274,0.00056259846,0.00014621801,0.0002932248,0.0011366556,0.00035851562],"domain_scores_gemma":[0.99782723,0.00025049248,0.00009885786,0.00064746285,0.0006324946,0.0005434373],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0051236027,0.0005104946,0.0006559832,0.0010167995,0.0012242607,0.0051694815,0.0026147072,0.0014357175,0.0020404826],"category_scores_gemma":[0.00582315,0.00063363614,0.0006900451,0.0015140099,0.0012700411,0.00826508,0.004906474,0.0040711393,0.001164829],"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":[0.00044188273,0.00037097474,0.0060883677,0.00028923078,0.00011534182,0.0005086645,0.0014545096,0.010207325,0.010946211,0.5670201,0.0546818,0.3478756],"study_design_scores_gemma":[0.00012267477,0.00030625684,0.0019034671,0.00025803162,0.00012112479,0.0011056408,0.000737482,0.16552995,0.010842292,0.3697217,0.4492526,0.000098711265],"about_ca_topic_score_codex":0.0021234148,"about_ca_topic_score_gemma":0.0021088135,"teacher_disagreement_score":0.0051694815,"about_ca_system_score_codex":0.00089875935,"about_ca_system_score_gemma":0.0016096529,"threshold_uncertainty_score":0.02709651},"labels":[],"label_agreement":null},{"id":"W1976311617","doi":"10.1108/17440080780000298","title":"Sibling‐First Data Organization for Parse‐Free XML Data Processing","year":2006,"lang":"en","type":"article","venue":"International Journal of Web Information Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"Hamilton Health Sciences Foundation","keywords":"Computer science; XPath; Streaming XML; Simple API for XML; XML database; Parsing; Information retrieval; XML validation; Efficient XML Interchange; XML Schema (W3C); Database; XML; XML Signature; Instruction prefetch; XML Encryption; Data mining; Programming language; World Wide Web; Operating system","score_opus":0.03634770499622808,"score_gpt":0.2846657076760225,"score_spread":0.24831800267979443,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1976311617","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":[0.019595698,0.0006717554,0.96499866,0.0002767649,0.00017888313,0.0003054016,0.0011335149,0.0100322245,0.0028071704],"genre_scores_gemma":[0.104785435,0.00046988513,0.8855614,0.00030622497,0.00006757406,0.0003292513,0.0038203562,0.0008908983,0.0037689041],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99847776,0.00025175465,0.000292863,0.00023803646,0.0006107154,0.00012893256],"domain_scores_gemma":[0.9954066,0.00071621436,0.00028516384,0.002232955,0.001191036,0.00016812059],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017233135,0.0005370974,0.0007029129,0.0015390327,0.0008232437,0.0016667846,0.0021517107,0.00065305864,0.0036301042],"category_scores_gemma":[0.0055228025,0.0005547873,0.0008502403,0.0030435508,0.00064460555,0.003733144,0.0019897637,0.0008931822,0.0014770714],"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":[0.00087670237,0.0002827378,0.008237114,0.0008268146,0.00015984043,0.00060967205,0.0013869919,0.017747767,0.07696751,0.07133517,0.049583495,0.77198625],"study_design_scores_gemma":[0.00035707303,0.0010191543,0.00577915,0.00017859998,0.00021702092,0.00240974,0.0006528985,0.33134484,0.26904714,0.06800556,0.32064867,0.00034022992],"about_ca_topic_score_codex":0.003902033,"about_ca_topic_score_gemma":0.005220165,"teacher_disagreement_score":0.003902033,"about_ca_system_score_codex":0.0013398303,"about_ca_system_score_gemma":0.0021219603,"threshold_uncertainty_score":0.01214391},"labels":[],"label_agreement":null},{"id":"W1976808588","doi":"10.2168/lmcs-2(3:2)2006","title":"Logics for Unranked Trees: An Overview","year":2006,"lang":"en","type":"article","venue":"Logical Methods in Computer Science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":67,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; University of Pennsylvania","keywords":"Computer science; Automaton; Tree automaton; XML; Tree (set theory); Theoretical computer science; Mathematics; Combinatorics; World Wide Web","score_opus":0.16511784447448183,"score_gpt":0.4470196305774615,"score_spread":0.28190178610297967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1976808588","genre_codex":"methods","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006113023,0.10856461,0.85389674,0.0024132417,0.00039909178,0.00014859549,0.00055168394,0.0008710198,0.027041927],"genre_scores_gemma":[0.18955746,0.1464625,0.6403632,0.0032334954,0.0024769395,0.0005992062,0.0017160767,0.0005074709,0.015083578],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99671197,0.0009397167,0.00040447715,0.0005090817,0.0012559663,0.00017878435],"domain_scores_gemma":[0.9968431,0.00212807,0.00028428246,0.00027902573,0.00033504647,0.00013058119],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035751194,0.0009253439,0.0008695812,0.004996594,0.0011388714,0.005425214,0.002604565,0.001356637,0.0035617526],"category_scores_gemma":[0.0035440424,0.0009357236,0.0015573365,0.006195283,0.003370176,0.01171357,0.0021464354,0.002563103,0.0010712291],"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":[0.000046986843,0.00006749009,0.0005308025,0.001005527,0.000040806724,0.00022742631,0.0005429115,0.005918942,0.0012286991,0.85552573,0.0059522516,0.12891231],"study_design_scores_gemma":[0.000023912153,0.00006166328,0.0003730554,0.0004791223,0.000044753437,0.00071537314,0.00020468027,0.022450669,0.0017185467,0.83570427,0.13816416,0.000059799968],"about_ca_topic_score_codex":0.0030814104,"about_ca_topic_score_gemma":0.002375582,"teacher_disagreement_score":0.005425214,"about_ca_system_score_codex":0.0033291262,"about_ca_system_score_gemma":0.0019943453,"threshold_uncertainty_score":0.024154603},"labels":[],"label_agreement":null},{"id":"W1977283395","doi":"10.1016/j.artint.2002.02.001","title":"A formal analysis of why heuristic functions work","year":2005,"lang":"en","type":"article","venue":"Artificial Intelligence","topic":"Advanced Database Systems and Queries","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":"University of Windsor; Carleton University","funders":"","keywords":"Heuristics; Computer science; Heuristic; Mathematical proof; Range (aeronautics); Mathematical optimization; Theoretical computer science; Algorithm; Mathematics; Artificial intelligence","score_opus":0.042325289150734316,"score_gpt":0.28950778667921073,"score_spread":0.24718249752847643,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1977283395","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":[0.015393456,0.00072253466,0.93108445,0.005883921,0.00014785018,0.000099121055,0.00015277551,0.00040414577,0.046111856],"genre_scores_gemma":[0.5805014,0.0011566813,0.40134823,0.0014327419,0.00039210697,0.0003979814,0.0003504612,0.00055547,0.013864923],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9956949,0.0018921292,0.00026216806,0.0004627084,0.0011294972,0.00055857643],"domain_scores_gemma":[0.97929984,0.016113212,0.0007294028,0.0021743677,0.0014481582,0.00023497666],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0051214956,0.0008065635,0.0008068675,0.0020470698,0.001994948,0.0063383663,0.0032497374,0.0030495508,0.0155815035],"category_scores_gemma":[0.034424905,0.0011076708,0.0020552755,0.0022512248,0.008193957,0.016621696,0.0022897513,0.003758226,0.0017050438],"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":[0.00000912275,0.000014264838,0.00008543734,0.00003837786,0.0000067380593,0.00003226231,0.00015152387,0.0019308969,0.00012725842,0.9925237,0.0008340345,0.004246317],"study_design_scores_gemma":[0.000012296434,0.00000745778,0.00005890929,0.000026034457,0.000010107442,0.00006932194,0.00010941552,0.012725548,0.00032581936,0.983163,0.0034823439,0.000009713856],"about_ca_topic_score_codex":0.0029519463,"about_ca_topic_score_gemma":0.002416136,"teacher_disagreement_score":0.0155815035,"about_ca_system_score_codex":0.0026315113,"about_ca_system_score_gemma":0.0023314187,"threshold_uncertainty_score":0.052125394},"labels":[],"label_agreement":null},{"id":"W1979020588","doi":"10.1145/1096967.1096972","title":"Answering queries with arithmetic expressions in heterogeneous systems","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Rewriting; Conjunctive query; Query language; Data integration; Context (archaeology); Information retrieval; Query expansion; Question answering; Information integration; Theoretical computer science; Spatial query; Database; Sargable; Web search query; Programming language; Relational database; Search engine","score_opus":0.008992971030348127,"score_gpt":0.2215752563469889,"score_spread":0.21258228531664078,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979020588","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":[0.053623408,0.00039275218,0.9396714,0.0010185682,0.000051118135,0.00018512129,0.00022177934,0.0019564438,0.002879451],"genre_scores_gemma":[0.49560517,0.0006171235,0.49820042,0.0006304227,0.00022539667,0.00027046748,0.00095119386,0.00048270726,0.003017063],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.98392093,0.0070869797,0.0014233813,0.0023410476,0.0044078375,0.00081982487],"domain_scores_gemma":[0.98264503,0.012064547,0.00094704697,0.0025030645,0.0015799274,0.0002603284],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010180915,0.0007583321,0.0015884498,0.0015387015,0.0013999529,0.005710836,0.0027511155,0.0020568909,0.0019590782],"category_scores_gemma":[0.029266436,0.0008002182,0.001988746,0.002538446,0.0029319962,0.011016911,0.0046463753,0.0021686452,0.0006390026],"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":[0.0007183993,0.00033488148,0.004979815,0.00060122827,0.00023770772,0.0015966385,0.0054147346,0.14576022,0.022160841,0.62206364,0.007892722,0.18823917],"study_design_scores_gemma":[0.00017138408,0.00012071551,0.00054011337,0.00005557122,0.00017832345,0.0003606323,0.001152243,0.5556222,0.020767087,0.40725076,0.013686708,0.00009416147],"about_ca_topic_score_codex":0.00597241,"about_ca_topic_score_gemma":0.0042173616,"teacher_disagreement_score":0.010180915,"about_ca_system_score_codex":0.0018120368,"about_ca_system_score_gemma":0.0012638049,"threshold_uncertainty_score":0.053842485},"labels":[],"label_agreement":null},{"id":"W1979393344","doi":"10.1504/ijiids.2012.045113","title":"Handling sharable queries in both streaming and stored XML documents","year":2012,"lang":"en","type":"article","venue":"International Journal of Intelligent Information and Database Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; XML; Information retrieval; Query plan; Streaming XML; Matching (statistics); Database; World Wide Web; Web search query; Sargable; Search engine","score_opus":0.015045293442884248,"score_gpt":0.27302186299650716,"score_spread":0.2579765695536229,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979393344","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":[0.13485421,0.0001976017,0.850773,0.00040622838,0.000086409804,0.00043526114,0.0001908446,0.008474621,0.0045818384],"genre_scores_gemma":[0.6488092,0.00024991797,0.34544477,0.00016852243,0.0001287555,0.00021757899,0.0004693778,0.00041757882,0.004094322],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99619067,0.00082712737,0.00044035295,0.00054563757,0.0018001233,0.00019611674],"domain_scores_gemma":[0.99148667,0.0035977769,0.00081838993,0.0031327487,0.00068498414,0.00027950868],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004569479,0.00042485326,0.00084510166,0.0006231543,0.0012339825,0.0028541163,0.0020275398,0.0007694514,0.0022156623],"category_scores_gemma":[0.007536373,0.00035048104,0.00051757926,0.0012046075,0.0012971936,0.0050816615,0.0018119203,0.0010631654,0.00054146687],"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":[0.002150624,0.0010163367,0.019614656,0.00071061985,0.00027222908,0.0027739126,0.004828518,0.090279676,0.2686625,0.16192755,0.010294344,0.4374691],"study_design_scores_gemma":[0.00023116215,0.00074139336,0.0035568054,0.00005007468,0.00015527666,0.0013100825,0.0013333486,0.6907441,0.17159157,0.08557016,0.044598255,0.0001177364],"about_ca_topic_score_codex":0.001725299,"about_ca_topic_score_gemma":0.0017997255,"teacher_disagreement_score":0.004569479,"about_ca_system_score_codex":0.00072382763,"about_ca_system_score_gemma":0.0013930657,"threshold_uncertainty_score":0.024166048},"labels":[],"label_agreement":null},{"id":"W1980161931","doi":"10.4018/jdwm.2008010103","title":"Dynamic View Selection for OLAP","year":2008,"lang":"en","type":"article","venue":"International Journal of Data Warehousing and Mining","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Materialized view; Online analytical processing; Computer science; Data warehouse; Aggregate (composite); Selection (genetic algorithm); Task (project management); Set (abstract data type); Information retrieval; Order (exchange); Data mining; Database; View; Machine learning","score_opus":0.06588151749652649,"score_gpt":0.3408887644985445,"score_spread":0.275007247002018,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1980161931","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":[0.017603071,0.0021621557,0.9746303,0.0003548902,0.00010552826,0.0001608273,0.00033944726,0.0025562479,0.0020874152],"genre_scores_gemma":[0.3728464,0.0015348651,0.6208139,0.00031608992,0.00027469336,0.00031294976,0.0015342864,0.00055045786,0.0018163802],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9964971,0.0012093423,0.00020984576,0.00061374594,0.0012144299,0.00025547593],"domain_scores_gemma":[0.9929894,0.0035527449,0.0004466083,0.0017563243,0.0008297048,0.0004252328],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002851802,0.0009862328,0.0013233154,0.0012259831,0.0010706246,0.0023734504,0.0023361272,0.0008436125,0.0024076046],"category_scores_gemma":[0.008921787,0.00066607265,0.00097085757,0.002275297,0.00083511136,0.0033625641,0.0025897413,0.002040235,0.0008734288],"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":[0.0012440501,0.0004345915,0.0056979638,0.00040007243,0.00024501295,0.0006448752,0.0006093242,0.20661318,0.028351393,0.060259536,0.024292324,0.6712076],"study_design_scores_gemma":[0.000084373394,0.00018420901,0.000910592,0.00004372928,0.000067230234,0.00045032395,0.0002131816,0.89554673,0.007907673,0.0766967,0.01782746,0.00006768184],"about_ca_topic_score_codex":0.0022704925,"about_ca_topic_score_gemma":0.0023612035,"teacher_disagreement_score":0.002851802,"about_ca_system_score_codex":0.00068468536,"about_ca_system_score_gemma":0.00095016405,"threshold_uncertainty_score":0.015081942},"labels":[],"label_agreement":null},{"id":"W1981807005","doi":"10.1117/12.543826","title":"XML algebras for data mining","year":2004,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":10,"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 Regina","funders":"","keywords":"XML Schema Editor; Efficient XML Interchange; XML validation; Streaming XML; Computer science; XML Encryption; Document Structure Description; XML Schema (W3C); Information retrieval; XML Signature; XML database; XML; World Wide Web","score_opus":0.022090178716028294,"score_gpt":0.2540251880028885,"score_spread":0.23193500928686017,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1981807005","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":[0.0011614355,0.012518466,0.9574286,0.0039096614,0.00068880565,0.00029328003,0.0009927507,0.0013686372,0.021638395],"genre_scores_gemma":[0.04501615,0.017848145,0.915913,0.0035363382,0.0026404867,0.0010326464,0.0036678535,0.00042140746,0.009923981],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98970246,0.0042562406,0.0016937657,0.001195254,0.0028573263,0.00029500877],"domain_scores_gemma":[0.990983,0.0047015445,0.0007129601,0.0018457406,0.0014248497,0.00033190392],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012263002,0.0014488437,0.0013637559,0.0055641043,0.0018128625,0.006604156,0.0026649816,0.0018654703,0.008924672],"category_scores_gemma":[0.015142371,0.00086581067,0.0031427643,0.006634281,0.003848482,0.012955243,0.004300084,0.0055044536,0.0053042513],"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":[0.000024174919,0.000031962732,0.00019896055,0.00041409244,0.000060553113,0.00013897689,0.0002889643,0.00195939,0.0004687693,0.9362334,0.009818952,0.050361898],"study_design_scores_gemma":[0.000013836647,0.000016212849,0.00009333002,0.00020121905,0.000024357272,0.00016950209,0.00008921866,0.0072653852,0.00050996034,0.9114666,0.08012709,0.00002331998],"about_ca_topic_score_codex":0.0020858292,"about_ca_topic_score_gemma":0.001465958,"teacher_disagreement_score":0.012263002,"about_ca_system_score_codex":0.00237735,"about_ca_system_score_gemma":0.0032366477,"threshold_uncertainty_score":0.06485373},"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":"W1982859232","doi":"10.1007/s10844-008-0074-3","title":"The Multi-Tree Cubing algorithm for computing iceberg cubes","year":2008,"lang":"en","type":"article","venue":"Journal of Intelligent Information Systems","topic":"Advanced Database Systems and Queries","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; Data cube; Computation; Algorithm; Partition (number theory); Online analytical processing; Pruning; Tree (set theory); Sorting; Trie; Data mining; Data structure; Data warehouse; Mathematics","score_opus":0.0363375668273497,"score_gpt":0.2791748354478105,"score_spread":0.24283726862046082,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1982859232","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":[0.014023702,0.0006638715,0.9814461,0.00022234854,0.00007277284,0.00006407761,0.00028733123,0.0009869918,0.0022328873],"genre_scores_gemma":[0.09821608,0.00039336833,0.89817923,0.000096721364,0.000035633995,0.00012862067,0.0008298377,0.00025807496,0.0018624427],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993319,0.00013231912,0.000057728652,0.00010675331,0.00026917705,0.00010196697],"domain_scores_gemma":[0.9986313,0.00053057895,0.00006990236,0.00027985408,0.00040599098,0.0000823937],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010658797,0.0006495422,0.0017704901,0.0016685971,0.0012084909,0.0022376273,0.0022029297,0.0010447397,0.0042915056],"category_scores_gemma":[0.0042237225,0.0006795896,0.0009652439,0.0028009284,0.00071801164,0.0036459058,0.0021542595,0.0017282828,0.0010373667],"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":[0.0005881116,0.00013829986,0.0017707844,0.00039166203,0.00011616067,0.000087264816,0.00030158504,0.34363765,0.0051165638,0.0868113,0.01854429,0.5424963],"study_design_scores_gemma":[0.00003448939,0.00004090302,0.00016871652,0.00002732027,0.000016099848,0.00005265126,0.000057710677,0.9502225,0.002175291,0.041986305,0.005201642,0.000016446065],"about_ca_topic_score_codex":0.012045475,"about_ca_topic_score_gemma":0.011414453,"teacher_disagreement_score":0.012045475,"about_ca_system_score_codex":0.0011034906,"about_ca_system_score_gemma":0.0018909808,"threshold_uncertainty_score":0.023950696},"labels":[],"label_agreement":null},{"id":"W1983304353","doi":"10.1145/974750.974757","title":"A normal form for XML documents","year":2004,"lang":"en","type":"article","venue":"ACM Transactions on Database Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":285,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Functional dependency; XML validation; Document Structure Description; XML; Information retrieval; XML database; XML Schema Editor; Relational database; Theoretical computer science; Programming language; World Wide Web","score_opus":0.02221699491570806,"score_gpt":0.2760328890509727,"score_spread":0.2538158941352646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1983304353","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":[0.0037814195,0.0003703671,0.9838071,0.00095297786,0.00037209695,0.00020241308,0.0008956241,0.0016569823,0.007961028],"genre_scores_gemma":[0.071618274,0.0009324224,0.9108495,0.00051492685,0.00034423286,0.000592833,0.0025330936,0.0007806217,0.011834062],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99445254,0.0011183302,0.0012037047,0.0011861986,0.0017997772,0.00023936525],"domain_scores_gemma":[0.99478215,0.0016989767,0.00044212784,0.0013324145,0.0015884856,0.0001559346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0040671197,0.0008807774,0.0006523783,0.00217742,0.001047653,0.004094907,0.0011244082,0.0013282045,0.004795743],"category_scores_gemma":[0.010869498,0.00066681317,0.00094288087,0.0022937646,0.0030745335,0.0089872675,0.0020935973,0.003126266,0.0027727343],"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":[0.000047891368,0.000025450003,0.00032219273,0.00014150486,0.000010369835,0.0001340775,0.00053770276,0.0023209485,0.0027929647,0.90567094,0.008598844,0.07939696],"study_design_scores_gemma":[0.000030248097,0.0000650839,0.00015700402,0.00012182789,0.000018772856,0.0007831081,0.00018971885,0.023255708,0.0057443245,0.68327665,0.28631026,0.000047303733],"about_ca_topic_score_codex":0.0019024407,"about_ca_topic_score_gemma":0.0015462369,"teacher_disagreement_score":0.004795743,"about_ca_system_score_codex":0.0017783416,"about_ca_system_score_gemma":0.0018667502,"threshold_uncertainty_score":0.02150923},"labels":[],"label_agreement":null},{"id":"W198356505","doi":"","title":"Object-oriented programming in C# with dynamic classification.","year":2004,"lang":"en","type":"article","venue":"Scholarship at UWindsor (University of Windsor)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Artificial intelligence; Object (grammar); Programming language","score_opus":0.013374496718259587,"score_gpt":0.22231467715967665,"score_spread":0.20894018044141707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W198356505","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":[0.00061780476,0.0005081621,0.95693195,0.00074784254,0.00031265736,0.0003367658,0.0005005491,0.019223798,0.020820452],"genre_scores_gemma":[0.008957193,0.0011950051,0.962152,0.0012067737,0.0002522664,0.0009190347,0.0015993215,0.0065026656,0.01721569],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99532735,0.00084685587,0.00064892403,0.0006885149,0.002052062,0.00043632393],"domain_scores_gemma":[0.9951846,0.0019006202,0.00043660807,0.0011791376,0.0010554984,0.00024356353],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036313378,0.0021393509,0.0011105594,0.0016963788,0.0013630281,0.004948643,0.0043751565,0.002001834,0.01762075],"category_scores_gemma":[0.010690394,0.0017265584,0.0025221186,0.003386304,0.0023824559,0.0060331593,0.003948301,0.0055695106,0.018599931],"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":[0.00019105051,0.0001256615,0.00063391647,0.0012869268,0.00009355674,0.0006349711,0.0008948121,0.010639405,0.005591709,0.46330962,0.1724974,0.34410098],"study_design_scores_gemma":[0.00014961378,0.000058518348,0.0004533487,0.0006822355,0.00007194297,0.00084843737,0.00009438281,0.052171513,0.007318642,0.20616822,0.7318305,0.00015266042],"about_ca_topic_score_codex":0.0068368195,"about_ca_topic_score_gemma":0.006574684,"teacher_disagreement_score":0.01762075,"about_ca_system_score_codex":0.0015287378,"about_ca_system_score_gemma":0.004570156,"threshold_uncertainty_score":0.058947265},"labels":[],"label_agreement":null},{"id":"W1983768816","doi":"10.1016/s0169-023x(02)00133-7","title":"Optimizing temporal queries: efficient handling of duplicates","year":2002,"lang":"en","type":"article","venue":"Data & Knowledge Engineering","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":5,"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 Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; SQL; Query language; Query optimization; Query by Example; Relational database; Temporal database; Semantics (computer science); Expressive power; Context (archaeology); Sargable; Information retrieval; Programming language; Database; Web search query; Search engine","score_opus":0.038932829926481824,"score_gpt":0.24963580992641615,"score_spread":0.21070297999993431,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1983768816","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":[0.12335644,0.003768716,0.8495,0.0013058537,0.000471572,0.0002952661,0.0016716305,0.012356844,0.007273614],"genre_scores_gemma":[0.42385888,0.0013905487,0.5616745,0.0005689126,0.0004344936,0.00021471365,0.003538725,0.0020316404,0.006287615],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.991804,0.0017881871,0.0009356915,0.0010807771,0.0036944286,0.0006969456],"domain_scores_gemma":[0.9838435,0.007553881,0.0010466847,0.00454368,0.0026548652,0.00035741914],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0053675915,0.0012552501,0.0023585754,0.0018615174,0.001633156,0.0039922534,0.00483478,0.0017365152,0.0031667405],"category_scores_gemma":[0.020735139,0.0011909095,0.0012032223,0.004802144,0.0013147503,0.008217559,0.0034673344,0.0015249257,0.001405733],"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":[0.0039443593,0.000632574,0.0064471005,0.0010276762,0.00040683575,0.00097196875,0.0013367884,0.07599457,0.04906671,0.04932555,0.06717879,0.7436671],"study_design_scores_gemma":[0.0006721465,0.00043692297,0.0014538608,0.00008640213,0.00043631924,0.0013192982,0.0007997855,0.8034211,0.06544702,0.09697572,0.028797667,0.00015383071],"about_ca_topic_score_codex":0.005861953,"about_ca_topic_score_gemma":0.006236839,"teacher_disagreement_score":0.005861953,"about_ca_system_score_codex":0.0012579113,"about_ca_system_score_gemma":0.0030307958,"threshold_uncertainty_score":0.02838689},"labels":[],"label_agreement":null},{"id":"W1985795626","doi":"10.1145/371920.371979","title":"A unified constraint model for XML","year":2001,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bell (Canada)","funders":"","keywords":"Computer science; Data integrity; XML; Consistency (knowledge bases); XML Schema (W3C); Programming language; Schema (genetic algorithms); XML validation; Constraint (computer-aided design); Document Structure Description; RELAX NG; XML Schema Editor; Theoretical computer science; Database; Information retrieval; Artificial intelligence; XML Encryption; World Wide Web; Mathematics","score_opus":0.04297505834151318,"score_gpt":0.27942794125195014,"score_spread":0.23645288291043695,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1985795626","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":[0.0016288173,0.0017918556,0.9759862,0.0017481652,0.0002099136,0.00023150294,0.0016385283,0.00067970925,0.016085412],"genre_scores_gemma":[0.04674253,0.0029138396,0.9324057,0.0007841031,0.00033340356,0.0008769098,0.00331509,0.00024469467,0.012383725],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9956585,0.0012949961,0.00061626255,0.0006633523,0.0015025112,0.0002643991],"domain_scores_gemma":[0.99746895,0.000923598,0.0002864059,0.00065857806,0.0005465366,0.00011589901],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0044343607,0.0011695805,0.0010509489,0.002717047,0.0020369194,0.0069446866,0.0038579009,0.0028154561,0.007844154],"category_scores_gemma":[0.0074439812,0.0008734468,0.0024523258,0.0056637395,0.002220728,0.009634262,0.0034650927,0.0032325904,0.002334776],"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":[0.000015864993,0.000015748241,0.000080314996,0.00009955218,0.00001722891,0.0001459928,0.0001931147,0.009865187,0.0005131268,0.9676077,0.0043171095,0.017128918],"study_design_scores_gemma":[0.00004921705,0.00003328433,0.00011416057,0.00016252635,0.000052410018,0.00034131162,0.00013339901,0.107482165,0.0010979583,0.6576079,0.23287486,0.00005081105],"about_ca_topic_score_codex":0.011326039,"about_ca_topic_score_gemma":0.013620401,"teacher_disagreement_score":0.011326039,"about_ca_system_score_codex":0.0025397216,"about_ca_system_score_gemma":0.0037830954,"threshold_uncertainty_score":0.026241302},"labels":[],"label_agreement":null},{"id":"W1987077754","doi":"10.3166/isi.10.2.9-37","title":"Un modèle de stockage de données XML basé sur les séquences","year":2005,"lang":"fr","type":"article","venue":"Ingénierie des systèmes d information","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Humanities; Computer science; Art","score_opus":0.04017213379063617,"score_gpt":0.23594330216939174,"score_spread":0.19577116837875558,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1987077754","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":[0.014153607,0.0005255153,0.9759161,0.0009550359,0.000096532094,0.0001444649,0.0012479231,0.00218995,0.004770808],"genre_scores_gemma":[0.23554543,0.003230166,0.7302575,0.0004204241,0.0002323499,0.0011046977,0.004636244,0.00048605123,0.024087172],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99809617,0.0004109334,0.00023950933,0.00038499062,0.0007781535,0.00009023549],"domain_scores_gemma":[0.9974552,0.0013768594,0.00017815997,0.00047420766,0.0004100359,0.00010569238],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024149294,0.0012410022,0.0011350292,0.0020267747,0.0011609016,0.0077645793,0.0027891728,0.002725589,0.007874993],"category_scores_gemma":[0.006502997,0.0013685335,0.0019243144,0.003227127,0.0021558222,0.009543421,0.0015625436,0.002091375,0.0022461046],"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":[0.00044227907,0.00015810128,0.0019758337,0.0004915407,0.00013993926,0.000905939,0.0008006245,0.54775256,0.007180832,0.3708506,0.0050908974,0.06421091],"study_design_scores_gemma":[0.00013027425,0.00011109957,0.00020122466,0.000068252084,0.00006457623,0.0002913679,0.00007708864,0.904428,0.0038093214,0.06499343,0.02577318,0.000052102117],"about_ca_topic_score_codex":0.022640334,"about_ca_topic_score_gemma":0.014223636,"teacher_disagreement_score":0.022640334,"about_ca_system_score_codex":0.0022213145,"about_ca_system_score_gemma":0.0028574374,"threshold_uncertainty_score":0.045017123},"labels":[],"label_agreement":null},{"id":"W1987552238","doi":"10.1145/373626.373697","title":"Constraints for semistructured data and XML","year":2001,"lang":"en","type":"article","venue":"ACM SIGMOD Record","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":107,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bell (Canada)","funders":"","keywords":"Computer science; Data integrity; XML database; Database; XML; Programming language; World Wide Web","score_opus":0.04716285210807767,"score_gpt":0.3007392847096654,"score_spread":0.2535764326015877,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1987552238","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":[0.0041223494,0.06307293,0.83961034,0.017699817,0.0040367623,0.00041636062,0.0038067389,0.00083586277,0.066398926],"genre_scores_gemma":[0.107598625,0.09722275,0.73301554,0.0069488715,0.009230489,0.0014757301,0.007854723,0.00067187153,0.035981424],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99187976,0.002309519,0.001538803,0.0010038845,0.0029676766,0.00030043913],"domain_scores_gemma":[0.98884434,0.0067701763,0.0012149531,0.0013411975,0.0014834495,0.00034593305],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0056467066,0.0011454512,0.0011105235,0.0033817512,0.0019914764,0.0067334925,0.0023073656,0.0027061314,0.011041507],"category_scores_gemma":[0.016371144,0.0008024803,0.0013228782,0.00832441,0.00446942,0.0137761235,0.0030442148,0.0042237886,0.0033559422],"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":[0.000017036102,0.00001303192,0.000112917536,0.0005866311,0.000020133884,0.0003109178,0.00037919392,0.0017800432,0.0005785097,0.93819827,0.015715735,0.042287517],"study_design_scores_gemma":[0.000012270519,0.000018264373,0.00014655088,0.00044723184,0.000018015848,0.0007137829,0.00022577861,0.004314009,0.0008362781,0.7099551,0.28327197,0.000040700364],"about_ca_topic_score_codex":0.0040536025,"about_ca_topic_score_gemma":0.0031748868,"teacher_disagreement_score":0.011041507,"about_ca_system_score_codex":0.002177354,"about_ca_system_score_gemma":0.0021189142,"threshold_uncertainty_score":0.036937475},"labels":[],"label_agreement":null},{"id":"W1988668397","doi":"10.1007/s00778-007-0058-x","title":"Temporal XML: modeling, indexing, and query processing","year":2007,"lang":"en","type":"article","venue":"The VLDB Journal","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":98,"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; XPath; Information retrieval; Search engine indexing; Query language; XML database; XML validation; Streaming XML; XML; Temporal database; Document Structure Description; Data mining; World Wide Web","score_opus":0.01980670494016319,"score_gpt":0.2688788118537077,"score_spread":0.24907210691354453,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1988668397","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":[0.017008528,0.007450273,0.9620278,0.0022558053,0.00021629011,0.00014846728,0.0017987369,0.0037515324,0.005342662],"genre_scores_gemma":[0.3203615,0.012326392,0.6507199,0.00053749594,0.0007260865,0.00040962858,0.006692308,0.00085629564,0.0073704296],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.995899,0.0015210522,0.00061132107,0.00053811754,0.0012395278,0.00019092529],"domain_scores_gemma":[0.9939814,0.0033880812,0.0005122092,0.0012474614,0.0006882609,0.00018248093],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0062094964,0.0008504153,0.0011465591,0.0033310333,0.0008235184,0.007952701,0.0035226904,0.00188221,0.0030003067],"category_scores_gemma":[0.0148278875,0.0010706129,0.001386147,0.007056882,0.0017812762,0.012049731,0.0013911374,0.0016035532,0.0013076545],"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":[0.0003808387,0.00028042294,0.0056759226,0.0008557687,0.0001243745,0.000439146,0.0010801698,0.11784529,0.00411377,0.5937322,0.020431349,0.25504076],"study_design_scores_gemma":[0.000045407145,0.00009833643,0.00096645684,0.0001606011,0.00012432146,0.0006240569,0.00033326467,0.6637654,0.004334326,0.28496847,0.04450912,0.000070272785],"about_ca_topic_score_codex":0.011803828,"about_ca_topic_score_gemma":0.0075916336,"teacher_disagreement_score":0.011803828,"about_ca_system_score_codex":0.0020443061,"about_ca_system_score_gemma":0.0022571438,"threshold_uncertainty_score":0.032839358},"labels":[],"label_agreement":null},{"id":"W1990080312","doi":"10.1142/s1793351x09000677","title":"A PEER DATA SHARING SYSTEM COMBINING SCHEMA AND DATA LEVEL MAPPINGS","year":2009,"lang":"en","type":"article","venue":"International Journal of Semantic Computing","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Schema (genetic algorithms); Data sharing; Theoretical computer science; Information retrieval; Data mining","score_opus":0.11366102391904716,"score_gpt":0.3523066023592655,"score_spread":0.23864557844021833,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1990080312","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":[0.027032133,0.00018133358,0.9587834,0.00052166905,0.000079322424,0.00043263313,0.00022250683,0.0053848457,0.007362093],"genre_scores_gemma":[0.31071657,0.00030446216,0.67497766,0.00027124438,0.00009677139,0.0004003874,0.0008281639,0.0004997207,0.011905135],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9961953,0.0010896252,0.00038979115,0.0007212313,0.0013882198,0.00021579197],"domain_scores_gemma":[0.99617493,0.00087301293,0.00018177496,0.0015386136,0.00087931735,0.0003522113],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037045993,0.0006072807,0.0011965533,0.0017418906,0.0018232681,0.0037304177,0.0025112138,0.0016336387,0.00401673],"category_scores_gemma":[0.006719901,0.0006641339,0.00083917566,0.0027703703,0.0013768977,0.008494009,0.0051254476,0.0011576313,0.002024788],"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":[0.00077987456,0.0006358213,0.006155957,0.00065133465,0.00046977022,0.002166777,0.0044168117,0.05404191,0.07730647,0.40763664,0.021873256,0.42386538],"study_design_scores_gemma":[0.00027961272,0.00081598514,0.0012263918,0.000115650546,0.00031021851,0.0030045356,0.0017500065,0.459189,0.06977968,0.27782702,0.18542457,0.00027730243],"about_ca_topic_score_codex":0.0023233525,"about_ca_topic_score_gemma":0.0015128634,"teacher_disagreement_score":0.00401673,"about_ca_system_score_codex":0.0011411987,"about_ca_system_score_gemma":0.0027496468,"threshold_uncertainty_score":0.019591987},"labels":[],"label_agreement":null},{"id":"W1990424408","doi":"10.1016/j.tcs.2011.05.047","title":"Rewriting of visibly pushdown languages for XML data integration","year":2011,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Advanced Database Systems and Queries","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 Victoria","funders":"","keywords":"Computer science; Programming language; XML validation; Document Structure Description; XML Schema Editor; XPath; XML Schema (W3C); Streaming XML; Efficient XML Interchange; RELAX NG; XML; XML Encryption; World Wide Web","score_opus":0.04928169162103819,"score_gpt":0.3136043105700699,"score_spread":0.2643226189490317,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1990424408","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":[0.033647068,0.00033501236,0.9532768,0.00033456838,0.00018592991,0.00013306136,0.00036089544,0.0041742157,0.0075523965],"genre_scores_gemma":[0.47887507,0.0004629534,0.49910983,0.00046453802,0.00017139081,0.00025375315,0.0015889002,0.0032275543,0.015845947],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9967771,0.0009860608,0.00042486316,0.0005015913,0.0009904664,0.0003199734],"domain_scores_gemma":[0.99492115,0.0021912854,0.00031715768,0.001548352,0.0008295908,0.00019247118],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027187774,0.00065326714,0.0007805538,0.0008154736,0.0011437743,0.003355891,0.0017006918,0.0011089451,0.0045650844],"category_scores_gemma":[0.006916489,0.0009845213,0.0017245132,0.0010673307,0.0019396029,0.0046637566,0.0029602267,0.0027118202,0.0012236987],"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":[0.00043401358,0.00021208567,0.0010664059,0.00045743017,0.000113589515,0.0010992694,0.0026343893,0.032105677,0.046071514,0.7897888,0.007941583,0.118075155],"study_design_scores_gemma":[0.00010417426,0.00015993211,0.00033376928,0.000106581654,0.0001564766,0.00042783687,0.00038747926,0.15993552,0.056816995,0.7389628,0.042466223,0.00014213807],"about_ca_topic_score_codex":0.00212522,"about_ca_topic_score_gemma":0.0027807187,"teacher_disagreement_score":0.0045650844,"about_ca_system_score_codex":0.0010364737,"about_ca_system_score_gemma":0.00094909273,"threshold_uncertainty_score":0.015271723},"labels":[],"label_agreement":null},{"id":"W1990557166","doi":"10.1145/1891719.1891725","title":"Comparing XML processing performance in middleware and database","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada)","funders":"","keywords":"Computer science; Streaming XML; Efficient XML Interchange; XML database; XML Signature; XML Schema Editor; XML validation; XML Encryption; XML framework; Database; Middleware (distributed applications); XML; XML Schema (W3C); Document Structure Description; World Wide Web","score_opus":0.023269641840046224,"score_gpt":0.24637712708911563,"score_spread":0.2231074852490694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1990557166","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":[0.9332668,0.0060464437,0.029083414,0.0009945194,0.00045682926,0.00019391492,0.00061454956,0.01033928,0.019004267],"genre_scores_gemma":[0.95777124,0.0019043282,0.03041829,0.00026019278,0.00015218493,0.000105665844,0.0021114897,0.0010997411,0.006176895],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9802203,0.0040787198,0.0019677961,0.0022663863,0.009254081,0.0022126911],"domain_scores_gemma":[0.96786726,0.017228503,0.0014274897,0.0053112386,0.0069033396,0.001262235],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010125172,0.0011422879,0.0013479391,0.0031472624,0.0013058429,0.005354091,0.0030487073,0.0024967445,0.003317483],"category_scores_gemma":[0.03617967,0.00081779755,0.0008077283,0.0075421026,0.001018698,0.006557738,0.0023509078,0.0014264671,0.0020606106],"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":[0.023001637,0.0018554062,0.05532941,0.0027419687,0.0009311728,0.0010009748,0.0028527111,0.09905428,0.18956068,0.015363184,0.01946183,0.58884674],"study_design_scores_gemma":[0.0010135511,0.007076021,0.09297889,0.00025890968,0.00077330257,0.0015454161,0.004019531,0.32519227,0.519082,0.008434021,0.03916257,0.0004635669],"about_ca_topic_score_codex":0.0069889575,"about_ca_topic_score_gemma":0.003842602,"teacher_disagreement_score":0.010125172,"about_ca_system_score_codex":0.0027662907,"about_ca_system_score_gemma":0.0015468546,"threshold_uncertainty_score":0.05354768},"labels":[],"label_agreement":null},{"id":"W1991368089","doi":"10.1145/543613.543636","title":"OLAP dimension constraints","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":63,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Online analytical processing; Dimension (graph theory); Heuristics; Computer science; Theoretical computer science; Class (philosophy); Intrinsic dimension; Set (abstract data type); Aggregate (composite); Space (punctuation); Curse of dimensionality; Mathematics; Data mining; Artificial intelligence; Data warehouse; Combinatorics; Programming language","score_opus":0.021910008873901855,"score_gpt":0.22386910770609347,"score_spread":0.20195909883219162,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1991368089","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":[0.02482232,0.0014915805,0.94527376,0.0029397402,0.00028418517,0.00090615975,0.008353211,0.0032782226,0.012650787],"genre_scores_gemma":[0.18959408,0.0011356723,0.7943435,0.0015067513,0.00020393977,0.0006136679,0.008728686,0.00053435937,0.0033393067],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.989077,0.0025481393,0.0013653054,0.0019041614,0.0044180164,0.0006875139],"domain_scores_gemma":[0.97650945,0.011522179,0.002230245,0.0047185025,0.0045822836,0.0004371939],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0056397286,0.0014319931,0.0011448365,0.002092673,0.0024296206,0.006653569,0.0036044645,0.0016317298,0.007695276],"category_scores_gemma":[0.03176184,0.0009968284,0.0022185706,0.004398348,0.0015321757,0.012401655,0.0053898464,0.0038045195,0.0011982773],"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":[0.0005670324,0.00023152312,0.012245605,0.0016937358,0.0004215921,0.0013640813,0.001837106,0.07739713,0.008432784,0.46837857,0.048619125,0.3788116],"study_design_scores_gemma":[0.000070903385,0.00012820703,0.0019425141,0.00047718146,0.00020215582,0.0013664088,0.0018750826,0.2614272,0.018865902,0.5688524,0.14465035,0.00014161886],"about_ca_topic_score_codex":0.0045851455,"about_ca_topic_score_gemma":0.005575138,"teacher_disagreement_score":0.007695276,"about_ca_system_score_codex":0.0015698263,"about_ca_system_score_gemma":0.0026123768,"threshold_uncertainty_score":0.029826105},"labels":[],"label_agreement":null},{"id":"W1991438431","doi":"10.1007/s10619-006-6575-6","title":"The cgmCUBE project: Optimizing parallel data cube generation for ROLAP","year":2006,"lang":"en","type":"article","venue":"Distributed and Parallel Databases","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":52,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; Concordia University; Carleton University","funders":"","keywords":"Online analytical processing; Computer science; Data cube; Data warehouse; Cube (algebra); Very large database; Database; Data structure; Data mining; Programming language","score_opus":0.07826883404703516,"score_gpt":0.31089565877940334,"score_spread":0.23262682473236818,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1991438431","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":[0.124522574,0.002088694,0.65030843,0.0024927973,0.001159609,0.0010779529,0.0125628095,0.1819978,0.023789389],"genre_scores_gemma":[0.17595337,0.0005217138,0.7820124,0.00047740282,0.00014717704,0.00083414675,0.020949084,0.010721168,0.008383492],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99781835,0.0005991581,0.00009332442,0.00033819923,0.0008870298,0.00026385306],"domain_scores_gemma":[0.99742234,0.0006357193,0.00007392431,0.00081805384,0.000834422,0.0002154405],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021921853,0.0024395392,0.0017856633,0.0014434205,0.0012924671,0.0021700913,0.0041486816,0.0013092596,0.0138794985],"category_scores_gemma":[0.00558696,0.0009932668,0.0014769455,0.0029446757,0.0011895683,0.0027504012,0.002956788,0.0022022275,0.0036423423],"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":[0.0026571823,0.0008101522,0.0024170063,0.0007650937,0.00044830397,0.00032660112,0.00042881272,0.16359143,0.01839018,0.018209651,0.3368922,0.4550634],"study_design_scores_gemma":[0.001088609,0.0002558173,0.0006389589,0.00003160577,0.00011478155,0.00009585804,0.00017997019,0.93155736,0.026174337,0.013440469,0.026348047,0.00007417494],"about_ca_topic_score_codex":0.027344162,"about_ca_topic_score_gemma":0.023391921,"teacher_disagreement_score":0.027344162,"about_ca_system_score_codex":0.0018802277,"about_ca_system_score_gemma":0.004020597,"threshold_uncertainty_score":0.054369986},"labels":[],"label_agreement":null},{"id":"W1993188540","doi":"10.1142/s0218194007003446","title":"XML SCHEMA MATCHING","year":2007,"lang":"en","type":"article","venue":"International Journal of Software Engineering and Knowledge Engineering","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; Open Text (Canada); University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Schema matching; Document Structure Description; RELAX NG; XML Schema Editor; XML validation; XML Schema (W3C); XML; Star schema; Efficient XML Interchange; Information retrieval; XML database; Matching (statistics); Schema (genetic algorithms); Data mining; Streaming XML; Database; Data integration; Document type definition; Mathematics; World Wide Web","score_opus":0.006121626440767754,"score_gpt":0.24008975644408093,"score_spread":0.23396813000331318,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1993188540","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":[0.0069004414,0.0015935494,0.9424831,0.0018680919,0.0005284267,0.0013716466,0.008072061,0.009445755,0.027736915],"genre_scores_gemma":[0.05533796,0.0018941157,0.89400023,0.0014615078,0.00015980071,0.0005926528,0.026906166,0.0016045645,0.018042931],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9910477,0.0021353848,0.0015443552,0.0018012362,0.002990623,0.00048065768],"domain_scores_gemma":[0.9907109,0.0027093748,0.00060362316,0.0032772732,0.002411025,0.00028776017],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0058957706,0.0011336645,0.0016433265,0.00529923,0.0020932984,0.0055236355,0.003969609,0.0033056792,0.026102195],"category_scores_gemma":[0.023933152,0.0008464036,0.002828695,0.009383951,0.000927681,0.011217493,0.005568805,0.0019959717,0.012762329],"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":[0.00037209154,0.00038476803,0.0031295489,0.001424306,0.0003719883,0.00086175685,0.0010079505,0.014379292,0.009873381,0.23470019,0.11568326,0.61781156],"study_design_scores_gemma":[0.00014227277,0.00015607008,0.0011720276,0.00046544752,0.0002071678,0.0018680131,0.0011720369,0.10681486,0.022324942,0.28025964,0.58530754,0.000109997556],"about_ca_topic_score_codex":0.00352963,"about_ca_topic_score_gemma":0.0027830668,"teacher_disagreement_score":0.026102195,"about_ca_system_score_codex":0.0018394355,"about_ca_system_score_gemma":0.0037168586,"threshold_uncertainty_score":0.08732051},"labels":[],"label_agreement":null},{"id":"W1996827442","doi":"10.1300/j104v40n03_03","title":"Metadata and Bibliographic Control: Soul-Mates or Two Solitudes?","year":2005,"lang":"en","type":"article","venue":"Cataloging & Classification Quarterly","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Metadata; Soul; Cataloging; Computer science; Library science; Dewey Decimal Classification; Information retrieval; Control (management); World Wide Web; Philosophy; Library classification; Theology; Artificial intelligence","score_opus":0.030785095144832655,"score_gpt":0.29084233401196236,"score_spread":0.2600572388671297,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1996827442","genre_codex":"review","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":[0.018641109,0.39538604,0.040724374,0.33859745,0.007908241,0.00004925578,0.00024925577,0.00035116335,0.19809313],"genre_scores_gemma":[0.65654886,0.2312193,0.017603796,0.03346202,0.021659086,0.00016059303,0.00026160263,0.00024167789,0.038843084],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.996734,0.001464309,0.00030765485,0.00037078816,0.0008601316,0.00026318856],"domain_scores_gemma":[0.9875194,0.007355569,0.0008740967,0.0016143977,0.0019895704,0.00064693124],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0066393674,0.00046131073,0.0007842215,0.00561291,0.0031575435,0.016100805,0.0013532921,0.0022461945,0.0069811516],"category_scores_gemma":[0.009088605,0.0002916808,0.00040248927,0.0066477475,0.027043521,0.030103287,0.004957588,0.0041734083,0.0008601463],"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":[0.000028851651,0.000018011668,0.00059728476,0.00026315125,0.000011655643,0.00004547095,0.0017805068,0.00016298161,0.00009356881,0.9396435,0.012059985,0.04529501],"study_design_scores_gemma":[0.00000999039,0.000034782737,0.00085228565,0.0007833848,0.000019224319,0.00021189335,0.0052045966,0.000484706,0.00021648285,0.791778,0.20036276,0.00004184925],"about_ca_topic_score_codex":0.004642487,"about_ca_topic_score_gemma":0.004687728,"teacher_disagreement_score":0.9838992,"about_ca_system_score_codex":0.004514224,"about_ca_system_score_gemma":0.0033423048,"threshold_uncertainty_score":0.03511274},"labels":[],"label_agreement":null},{"id":"W1997164579","doi":"10.1145/1321440.1321507","title":"Mapgraph","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Online analytical processing; Computer science; Granularity; Hierarchy; Overhead (engineering); Dimension (graph theory); Cube (algebra); Data cube; Representation (politics); Theoretical computer science; Data warehouse; Distributed computing; Database; Data mining; Programming language; Mathematics","score_opus":0.007811217787833087,"score_gpt":0.24306129342936153,"score_spread":0.23525007564152844,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997164579","genre_codex":"methods","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":[0.016583132,0.0018112115,0.6043375,0.0018586023,0.00069194613,0.00095737865,0.060660046,0.13186131,0.18123877],"genre_scores_gemma":[0.20847201,0.0038219977,0.46890667,0.00128451,0.0002485353,0.0015825244,0.1777471,0.0119106155,0.12602605],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995184,0.00005654726,0.00002632369,0.00010279627,0.00022178811,0.00007417815],"domain_scores_gemma":[0.9991026,0.00015967483,0.000053568496,0.00037510155,0.0002193706,0.00008968391],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031316737,0.0008154888,0.0005391905,0.0017262159,0.0009616132,0.0025368326,0.001975255,0.0007962252,0.0545437],"category_scores_gemma":[0.0020162554,0.0005902284,0.00079974555,0.002915786,0.00038479414,0.0028619939,0.0029280735,0.0009158977,0.01874917],"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":[0.00034167367,0.00018461465,0.0017534845,0.0010868093,0.00014949832,0.00051374687,0.00059103937,0.0152354855,0.0070151594,0.10441104,0.49840787,0.3703096],"study_design_scores_gemma":[0.00004397409,0.000056155124,0.0006695507,0.00006793235,0.00004232974,0.00038055226,0.00017719244,0.03505637,0.006357553,0.04457468,0.91253155,0.000042174805],"about_ca_topic_score_codex":0.00635498,"about_ca_topic_score_gemma":0.008537232,"teacher_disagreement_score":0.0545437,"about_ca_system_score_codex":0.00076248863,"about_ca_system_score_gemma":0.0014643164,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W1997533292","doi":"10.1145/503099.503102","title":"SchemaSQL","year":2001,"lang":"en","type":"article","venue":"ACM Transactions on Database Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":94,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; SQL; Data definition language; Relational database; Schema (genetic algorithms); Database schema; Programming language; Database; Conceptual schema; Semi-structured model; Database model; Information retrieval; Database design","score_opus":0.03070971332297829,"score_gpt":0.26929298189477086,"score_spread":0.23858326857179257,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997533292","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":[0.0027523173,0.0021437951,0.6742128,0.00398384,0.001196718,0.0016733913,0.06256807,0.17475957,0.07670942],"genre_scores_gemma":[0.046233952,0.004812209,0.5766754,0.008545077,0.000719474,0.002589094,0.27213436,0.035607494,0.052682918],"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99209315,0.0017938126,0.0013899966,0.0010258692,0.0030110178,0.0006861448],"domain_scores_gemma":[0.99287766,0.0018569377,0.0004363914,0.0022184642,0.002177951,0.00043252858],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007928503,0.0016373199,0.0013677296,0.0028632581,0.001608906,0.008521542,0.0077120685,0.0026352196,0.05195415],"category_scores_gemma":[0.016723096,0.0020172133,0.0036713977,0.003119037,0.001317966,0.010766727,0.007945903,0.0044160215,0.033685356],"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":[0.0005714045,0.00022105538,0.0022787577,0.0019597958,0.00031936404,0.0005276238,0.0008744594,0.0053454535,0.004737686,0.2642291,0.56247634,0.15645906],"study_design_scores_gemma":[0.00010456918,0.00003734294,0.00024640956,0.00017030197,0.00005001328,0.00039460234,0.00016016769,0.01058917,0.0039696572,0.05993186,0.9242697,0.00007622639],"about_ca_topic_score_codex":0.0075289584,"about_ca_topic_score_gemma":0.005942179,"teacher_disagreement_score":0.05195415,"about_ca_system_score_codex":0.0018060249,"about_ca_system_score_gemma":0.0051471824,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W1998014869","doi":"10.1145/335191.335476","title":"Of XML and databases (panel session)","year":2000,"lang":"en","type":"article","venue":"ACM SIGMOD Record","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Resverlogix (Canada)","funders":"","keywords":"Computer science; XML database; Database; Session (web analytics); XML; XML Schema Editor; Efficient XML Interchange; World Wide Web; XML Base; Streaming XML; XML validation; Information retrieval; XML Encryption","score_opus":0.04303868654853697,"score_gpt":0.2752964978959816,"score_spread":0.2322578113474446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1998014869","genre_codex":"commentary","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":[0.0013899531,0.10971872,0.0111874,0.36726278,0.23189595,0.0006362856,0.0015295406,0.0006510946,0.2757283],"genre_scores_gemma":[0.0081395125,0.06961299,0.004834391,0.09356745,0.18970487,0.00079339405,0.001831316,0.0005896195,0.63092655],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99822015,0.0004579907,0.00007771046,0.00034993896,0.00061673013,0.0002774325],"domain_scores_gemma":[0.9951515,0.0016509837,0.00020437804,0.00036579225,0.0012563376,0.0013710129],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0070897657,0.0013984931,0.0010701795,0.0017934965,0.0034162495,0.008237874,0.0017418799,0.00979725,0.09609054],"category_scores_gemma":[0.0058942,0.0007952493,0.0013471338,0.0025679034,0.0018360881,0.011965331,0.005426606,0.011214568,0.03380161],"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":[0.000020496733,0.00002519401,0.0000909416,0.00006755925,0.000005363894,0.000037508154,0.000063358515,0.000026623453,0.00016209466,0.00543918,0.977371,0.016690645],"study_design_scores_gemma":[0.000013164781,0.000017648777,0.00042383187,0.0002299069,0.0000070860283,0.000055377983,0.000119735596,0.00005825777,0.000079846875,0.004386899,0.99459803,0.000010134318],"about_ca_topic_score_codex":0.004291974,"about_ca_topic_score_gemma":0.013715043,"teacher_disagreement_score":0.09609054,"about_ca_system_score_codex":0.0019885644,"about_ca_system_score_gemma":0.0026874845,"threshold_uncertainty_score":0.32145488},"labels":[],"label_agreement":null},{"id":"W1998219992","doi":"10.1017/s0960129511000442","title":"Lenses, fibrations and universal translations","year":2011,"lang":"en","type":"article","venue":"Mathematical Structures in Computer Science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; Mount Allison University","funders":"","keywords":"Categorical variable; Lens (geology); Complement (music); Through-the-lens metering; Constant (computer programming); Computer science; Variation (astronomy); Mathematics; Pure mathematics; Algebra over a field; Physics; Programming language; Optics","score_opus":0.028088432010136718,"score_gpt":0.24475460419808934,"score_spread":0.21666617218795262,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1998219992","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":[0.16831367,0.00624278,0.694536,0.0032554974,0.00057263754,0.00009732902,0.00034676885,0.0010306532,0.1256048],"genre_scores_gemma":[0.88937706,0.0024600197,0.08794256,0.0005994167,0.00046766925,0.00011626053,0.00026898817,0.00031876913,0.018449204],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.997421,0.0006084321,0.00019953315,0.0006597144,0.00066144177,0.0004499174],"domain_scores_gemma":[0.9966323,0.0013034502,0.00035841667,0.0006047177,0.00062720745,0.00047395902],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024879966,0.00064775284,0.00052129384,0.0021334754,0.0023322338,0.004134017,0.0006815523,0.0012342334,0.0053698476],"category_scores_gemma":[0.0043357736,0.0005613618,0.001071375,0.0011940269,0.008239608,0.014549779,0.005081705,0.0020588192,0.0007489649],"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":[0.000010940375,0.000004481865,0.00016444818,0.000021709324,0.0000034550364,0.00009814088,0.00046766354,0.00016006085,0.00044179845,0.9941658,0.00033647218,0.0041249855],"study_design_scores_gemma":[0.000012554774,0.000031743275,0.00037530638,0.000029637633,0.000014279898,0.0005198584,0.00061848364,0.0020562124,0.0019510686,0.97085637,0.023509808,0.00002470121],"about_ca_topic_score_codex":0.0021410997,"about_ca_topic_score_gemma":0.0013362215,"teacher_disagreement_score":0.0053698476,"about_ca_system_score_codex":0.0017047281,"about_ca_system_score_gemma":0.0008535396,"threshold_uncertainty_score":0.017963886},"labels":[],"label_agreement":null},{"id":"W1998415522","doi":"10.4018/ijdwm.2015010102","title":"Parallel Real-Time OLAP on Multi-Core Processors","year":2015,"lang":"en","type":"article","venue":"International Journal of Data Warehousing and Mining","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Online analytical processing; Computer science; Data warehouse; Data cube; Benchmark (surveying); Database; Xeon Phi; Decision support system; Data mining; Parallel computing","score_opus":0.1509179829619319,"score_gpt":0.365363937577586,"score_spread":0.2144459546156541,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1998415522","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":[0.24890155,0.0019986078,0.6961772,0.00070058374,0.0005171573,0.0009849616,0.0008947384,0.033571474,0.016253728],"genre_scores_gemma":[0.5474951,0.00050447613,0.44272637,0.00031755297,0.00009078665,0.00062955415,0.0015784722,0.00083648035,0.0058212527],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973355,0.00045890594,0.0002546275,0.0006351964,0.00091519015,0.00040046722],"domain_scores_gemma":[0.9971942,0.0006625103,0.00020699557,0.00071859994,0.0009952649,0.00022248464],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015937666,0.0017658694,0.0010610431,0.0009539651,0.0010517391,0.002147226,0.0027986427,0.00055339094,0.004445226],"category_scores_gemma":[0.0035867624,0.0007543004,0.0007339564,0.0017219352,0.0007757273,0.0021954023,0.0015905602,0.001420671,0.0014872546],"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":[0.005167157,0.0011075162,0.0074336627,0.0011662476,0.0005957607,0.0013132278,0.0009803212,0.3656594,0.10539413,0.014188039,0.046450887,0.45054373],"study_design_scores_gemma":[0.0003035973,0.00047589332,0.001108623,0.000032329586,0.000079815676,0.00019806088,0.00017500829,0.9418256,0.03960007,0.005385316,0.0107489,0.00006679561],"about_ca_topic_score_codex":0.0064040064,"about_ca_topic_score_gemma":0.0056600613,"teacher_disagreement_score":0.0064040064,"about_ca_system_score_codex":0.001136629,"about_ca_system_score_gemma":0.0026240193,"threshold_uncertainty_score":0.014870763},"labels":[],"label_agreement":null},{"id":"W1998597078","doi":"10.1145/1670243.1670248","title":"An information-theoretic analysis of worst-case redundancy in database design","year":2008,"lang":"en","type":"article","venue":"ACM Transactions on Database Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Seventh Framework Programme; Engineering and Physical Sciences Research Council","keywords":"Computer science; Redundancy (engineering); Schema (genetic algorithms); Functional dependency; Database schema; Theoretical computer science; Data integrity; Relational database; Data mining; Database design; Information retrieval; Database","score_opus":0.03518479320693964,"score_gpt":0.27502739543239096,"score_spread":0.23984260222545134,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1998597078","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":[0.034553234,0.0010741426,0.9562877,0.0009785042,0.00004430057,0.00007382144,0.0001312122,0.00020760063,0.0066494253],"genre_scores_gemma":[0.67349154,0.0015437064,0.32092574,0.0003375761,0.00032304626,0.00038394096,0.00034143857,0.00020104113,0.0024519188],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9830073,0.006897724,0.0011155807,0.0014044441,0.006760076,0.00081481994],"domain_scores_gemma":[0.9477338,0.036994893,0.0034103545,0.0076716146,0.0037428993,0.0004464647],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012243633,0.0012807553,0.0011139945,0.0032944838,0.00094956625,0.0043771984,0.002695252,0.0014210612,0.0023861444],"category_scores_gemma":[0.051508173,0.0010819343,0.0012415366,0.00375176,0.005014334,0.010851688,0.0018904309,0.0024880618,0.0004928748],"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":[0.0001770875,0.00008537819,0.0011470986,0.00032096967,0.00009803643,0.00019272356,0.00040425957,0.3119412,0.004790825,0.62018377,0.0014717194,0.059186947],"study_design_scores_gemma":[0.00002261202,0.00015723029,0.00036575968,0.000054682354,0.000062079926,0.00030502104,0.00007572305,0.41109473,0.004040639,0.5806116,0.0031694162,0.0000405118],"about_ca_topic_score_codex":0.00070240634,"about_ca_topic_score_gemma":0.000611911,"teacher_disagreement_score":0.012243633,"about_ca_system_score_codex":0.003522623,"about_ca_system_score_gemma":0.0015650146,"threshold_uncertainty_score":0.06475127},"labels":[],"label_agreement":null},{"id":"W1999812853","doi":"10.1145/1866480.1866484","title":"LTIX","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Joins; XML; Search engine indexing; Path (computing); Pruning; Path expression; Data mining; Scheme (mathematics); Index (typography); XPath; Tree (set theory); Tree structure; Twig; Data structure; Information retrieval; Theoretical computer science; XML database; Query language; Mathematics","score_opus":0.004661640029444121,"score_gpt":0.2231415807463154,"score_spread":0.2184799407168713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1999812853","genre_codex":"methods","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":[0.010322255,0.0009251155,0.78326315,0.00085086835,0.0003914127,0.00078218477,0.017404264,0.101717256,0.084343456],"genre_scores_gemma":[0.16169417,0.001940784,0.6203045,0.0016937846,0.00044346272,0.001403293,0.09118973,0.01000163,0.11132859],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.998563,0.00021064469,0.00021073934,0.00024326559,0.00059991755,0.00017245294],"domain_scores_gemma":[0.99860173,0.0002795484,0.00013175356,0.0005346758,0.00036178943,0.00009053364],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0011768596,0.0006703911,0.0006016785,0.0019033263,0.00082052965,0.0032271792,0.0017148384,0.00093673344,0.0414281],"category_scores_gemma":[0.0043710126,0.00046376165,0.00067175523,0.002961937,0.00043733296,0.0049362215,0.0028041133,0.0012762054,0.026411595],"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":[0.00070044934,0.0001877405,0.002594951,0.0010067802,0.0000862382,0.00044520956,0.000526343,0.005236681,0.028283952,0.13013043,0.20868197,0.6221193],"study_design_scores_gemma":[0.0001237151,0.00032947396,0.0014270265,0.00017974092,0.0000654533,0.00094940775,0.00029024418,0.054809548,0.03869893,0.06385903,0.8391782,0.00008930534],"about_ca_topic_score_codex":0.0021575573,"about_ca_topic_score_gemma":0.0021007962,"teacher_disagreement_score":0.9585719,"about_ca_system_score_codex":0.0012051964,"about_ca_system_score_gemma":0.0015187502,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W1999968379","doi":"10.1007/s00778-010-0180-z","title":"Streaming multiple aggregations using phantoms","year":2010,"lang":"en","type":"article","venue":"The VLDB Journal","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":26,"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; Granularity; Data stream mining; Aggregate (composite); Petabyte; Computation; Volume (thermodynamics); Distributed computing; Set (abstract data type); Data mining; The Internet; Service (business); Computer network; Real-time computing; Big data; Algorithm","score_opus":0.020176654432361135,"score_gpt":0.26893277961267065,"score_spread":0.2487561251803095,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1999968379","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":[0.052246884,0.0007239908,0.90245265,0.00076687796,0.0006949221,0.00020437443,0.0006936922,0.033837155,0.008379376],"genre_scores_gemma":[0.42196855,0.00034519492,0.56570524,0.0003026213,0.0004156815,0.00022213891,0.001879816,0.0018680898,0.0072926795],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9966425,0.00078180694,0.0003015049,0.0005887366,0.0013388112,0.0003465448],"domain_scores_gemma":[0.9837992,0.0055707395,0.000496161,0.006867094,0.00231849,0.00094824075],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0043046186,0.0012525951,0.0022546174,0.002089137,0.0016196512,0.003337681,0.0029954354,0.0014735726,0.01048976],"category_scores_gemma":[0.018938025,0.0015393625,0.0009351251,0.0033979185,0.0012382346,0.006386018,0.0044755023,0.0022327937,0.0022083342],"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":[0.008996285,0.0010104608,0.005625395,0.00050151005,0.00039044512,0.0014511453,0.0012863266,0.10324994,0.0805121,0.099446505,0.05910219,0.6384276],"study_design_scores_gemma":[0.00034541613,0.00028252238,0.0005153343,0.00004502426,0.00007915028,0.00039048295,0.00012575509,0.9110613,0.025496865,0.043921914,0.01765995,0.00007632569],"about_ca_topic_score_codex":0.0024266925,"about_ca_topic_score_gemma":0.0023682772,"teacher_disagreement_score":0.01048976,"about_ca_system_score_codex":0.0013606164,"about_ca_system_score_gemma":0.0017330601,"threshold_uncertainty_score":0.035091758},"labels":[],"label_agreement":null},{"id":"W2000480185","doi":"10.1016/j.tcs.2007.06.004","title":"Fibrations and universal view updatability","year":2007,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mount Allison University","funders":"","keywords":"Computer science; Mathematics; Theoretical computer science; Programming language; Algebra over a field; Pure mathematics","score_opus":0.007948658562605852,"score_gpt":0.25337003983349854,"score_spread":0.2454213812708927,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2000480185","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":[0.2249213,0.0012114536,0.73722196,0.0026224933,0.00027787857,0.00010954579,0.0004904719,0.0031666977,0.029978154],"genre_scores_gemma":[0.9045833,0.0007341921,0.08185142,0.00045609157,0.00032991255,0.00012879581,0.0005693082,0.0011215654,0.010225378],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99284583,0.0014251572,0.00092525786,0.0023760537,0.0013459239,0.001081685],"domain_scores_gemma":[0.96923894,0.015918883,0.0022328098,0.008433551,0.0026655262,0.0015101486],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006179074,0.00086957036,0.001635282,0.0029205934,0.0038241895,0.0061629754,0.001829318,0.0021673949,0.008109905],"category_scores_gemma":[0.019710746,0.0022341202,0.0025528471,0.0026468567,0.010317401,0.03283239,0.010034727,0.0045856987,0.0010099909],"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":[0.000116377996,0.000038455757,0.0015038323,0.00006109759,0.000030573876,0.00044009316,0.0023461173,0.0007165859,0.0014086526,0.97990215,0.00097294926,0.01246319],"study_design_scores_gemma":[0.00003533961,0.000024115845,0.00044060138,0.000029408362,0.000057698006,0.00053619465,0.00033663728,0.0039699953,0.0022301532,0.98644316,0.00586313,0.000033586366],"about_ca_topic_score_codex":0.0016028084,"about_ca_topic_score_gemma":0.0010685088,"teacher_disagreement_score":0.008109905,"about_ca_system_score_codex":0.0012795836,"about_ca_system_score_gemma":0.0008487493,"threshold_uncertainty_score":0.032678485},"labels":[],"label_agreement":null},{"id":"W2002963734","doi":"10.1007/s10844-006-0036-6","title":"Is it DSS or OLTP: automatically identifying DBMS workloads","year":2007,"lang":"en","type":"article","venue":"Journal of Intelligent Information Systems","topic":"Advanced Database Systems and Queries","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":"IBM (Canada); Queen's University","funders":"Microsoft; International Business Machines Corporation","keywords":"Online transaction processing; Computer science; Workload; Online analytical processing; Database; Benchmark (surveying); Decision support system; Construct (python library); Transaction processing; Data mining; Operating system; Database transaction; Data warehouse; Programming language","score_opus":0.05905425229981971,"score_gpt":0.33796667652316315,"score_spread":0.27891242422334345,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2002963734","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":[0.9114044,0.0012369666,0.05955266,0.00086122344,0.00031478985,0.00012184507,0.0064971894,0.014430455,0.005580438],"genre_scores_gemma":[0.9512878,0.0004074608,0.04001266,0.00017364685,0.00014098366,0.000038686772,0.0062137875,0.00024356609,0.0014815264],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995443,0.00005677936,0.000060311242,0.00009360557,0.00017490027,0.000070058144],"domain_scores_gemma":[0.99804497,0.00069824985,0.00027013954,0.00026881575,0.00045644146,0.0002613759],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00060481514,0.00047974265,0.0003814186,0.0021601191,0.0002776617,0.0013580357,0.000470782,0.0004836812,0.0014698587],"category_scores_gemma":[0.0035083196,0.00020823065,0.00019737934,0.001565947,0.00013748385,0.0021234874,0.00046121876,0.00032447762,0.00096912717],"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":[0.0017522557,0.00030539633,0.3345341,0.00043644328,0.00018625017,0.00040881804,0.00047858048,0.0049581905,0.08515031,0.0023553444,0.040397175,0.5290371],"study_design_scores_gemma":[0.00023391178,0.0010311423,0.1928604,0.00014066591,0.00037011364,0.0019322981,0.00210705,0.6271382,0.10988965,0.012362397,0.051843904,0.00009020863],"about_ca_topic_score_codex":0.002277089,"about_ca_topic_score_gemma":0.0040440597,"teacher_disagreement_score":0.002277089,"about_ca_system_score_codex":0.00024446438,"about_ca_system_score_gemma":0.0005532512,"threshold_uncertainty_score":0.004917145},"labels":[],"label_agreement":null},{"id":"W200421997","doi":"10.4018/978-1-59140-041-7.ch002","title":"Towards Semistructured Data Integration","year":2011,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Data integration; Consistency (knowledge bases); Information integration; IDEF1X; Graph; Data mining; Tree (set theory); Information retrieval; Theoretical computer science; Semantic Web; Ontology-based data integration; Artificial intelligence; Mathematics","score_opus":0.04397183008164761,"score_gpt":0.2688901659396014,"score_spread":0.2249183358579538,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W200421997","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":[0.0030623355,0.0014835373,0.98907834,0.0010934261,0.00017776854,0.0001348096,0.00022219883,0.00076691096,0.0039805095],"genre_scores_gemma":[0.022887798,0.001881884,0.9707136,0.00055182085,0.000118182405,0.00022079822,0.0010640115,0.0002425438,0.0023193331],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99333644,0.0021735507,0.0008837638,0.0008994356,0.0025118385,0.00019505306],"domain_scores_gemma":[0.99145985,0.003033839,0.00046967712,0.0031910795,0.0014573208,0.0003882234],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008533169,0.00086225977,0.0013878796,0.0034122225,0.0012700683,0.008006141,0.0034458095,0.0021281615,0.002438631],"category_scores_gemma":[0.012717888,0.0012548198,0.0026313763,0.0067896843,0.0037269474,0.0173834,0.010022381,0.005520852,0.0015180461],"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":[0.00008962389,0.00015334866,0.0009365862,0.0006591241,0.00008800515,0.0005360062,0.0032826392,0.007308119,0.0067234174,0.737879,0.009722777,0.23262137],"study_design_scores_gemma":[0.00002825543,0.00005482073,0.00022071652,0.0004336081,0.000043379754,0.0007092229,0.00088189886,0.064636774,0.0044803047,0.76549864,0.16296008,0.00005224529],"about_ca_topic_score_codex":0.0014536357,"about_ca_topic_score_gemma":0.0012619705,"teacher_disagreement_score":0.008533169,"about_ca_system_score_codex":0.0016412665,"about_ca_system_score_gemma":0.002432022,"threshold_uncertainty_score":0.045128226},"labels":[],"label_agreement":null},{"id":"W2005064346","doi":"10.1115/detc2004-57739","title":"Handling Imprecise and Uncertain Engineering Information in IDEF1X and Relational Data Models","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Computer science; Database design; Relational database; Database model; Conceptual schema; Logical data model; Relational model; Data modeling; Database schema; IDEF1X; Entity–relationship model; Database theory; Fuzzy logic; Database; Information engineering; Data mining; Information system; Software engineering; Artificial intelligence; Engineering; Ontology-based data integration","score_opus":0.035328132374007955,"score_gpt":0.23886447944186406,"score_spread":0.20353634706785612,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2005064346","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":[0.010621961,0.0006708694,0.9835053,0.0007967702,0.000055504956,0.00006160443,0.00019955992,0.0001906018,0.0038978276],"genre_scores_gemma":[0.31084523,0.0024639308,0.6776266,0.00048566185,0.00024275787,0.0003402149,0.0010059798,0.00008302089,0.0069065643],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9929396,0.0022639188,0.00080994645,0.00080773875,0.0027891516,0.0003895975],"domain_scores_gemma":[0.9937504,0.003155198,0.000758304,0.001406788,0.00078472454,0.0001445614],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0072233193,0.0006313241,0.0009647401,0.0023201539,0.0010333871,0.006531002,0.0021896358,0.0018092608,0.0014331582],"category_scores_gemma":[0.014561201,0.0005697517,0.0013109253,0.0028169402,0.0023647433,0.011237607,0.0030785147,0.0021323347,0.0005297693],"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":[0.000069317575,0.000039921688,0.0010936661,0.000115977105,0.000025648238,0.00075009273,0.0011415465,0.040868554,0.0011602987,0.90353745,0.0018375216,0.049360007],"study_design_scores_gemma":[0.00003096461,0.000084970525,0.00046517822,0.00018491215,0.000056014564,0.0012085215,0.0007193451,0.3392535,0.0032604996,0.6141774,0.04048539,0.00007332326],"about_ca_topic_score_codex":0.003840606,"about_ca_topic_score_gemma":0.002520772,"teacher_disagreement_score":0.0072233193,"about_ca_system_score_codex":0.0014338434,"about_ca_system_score_gemma":0.0011881102,"threshold_uncertainty_score":0.038201034},"labels":[],"label_agreement":null},{"id":"W2006315879","doi":"10.1145/1093382.1093388","title":"Capturing summarizability with integrity constraints in OLAP","year":2005,"lang":"en","type":"article","venue":"ACM Transactions on Database Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":93,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Online analytical processing; Computer science; Heuristics; Dimension (graph theory); Theoretical computer science; Set (abstract data type); Data integrity; Aggregate (composite); Intrinsic dimension; Class (philosophy); Space (punctuation); Data mining; Curse of dimensionality; Data warehouse; Database; Artificial intelligence; Mathematics; Programming language","score_opus":0.025716485551273413,"score_gpt":0.2608755870518358,"score_spread":0.23515910150056235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2006315879","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":[0.040597126,0.00040571202,0.9543814,0.000977661,0.00003952698,0.00028467,0.00058458536,0.0013283198,0.0014010004],"genre_scores_gemma":[0.3083235,0.00037472707,0.68846494,0.00025959924,0.00010451922,0.000260051,0.0012502891,0.00025169863,0.0007107307],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98962605,0.0036393735,0.0010369365,0.0014146612,0.0036239058,0.00065898435],"domain_scores_gemma":[0.9549343,0.030995954,0.0041351155,0.005306885,0.0041178036,0.0005098787],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0058784573,0.0013108379,0.001289405,0.002267622,0.0018945255,0.0046996167,0.003100541,0.002210974,0.0018602543],"category_scores_gemma":[0.056476925,0.0013270716,0.0015704788,0.004584523,0.002596858,0.015227198,0.0045639146,0.0041152826,0.00035042156],"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":[0.0006044139,0.00034751283,0.008910788,0.0008833761,0.00027045608,0.001265886,0.0024500298,0.45767266,0.013429612,0.22160663,0.006796409,0.28576216],"study_design_scores_gemma":[0.000040652074,0.00008267761,0.0007452574,0.00007559753,0.00006857922,0.00026292712,0.00054226496,0.7197083,0.009812639,0.26353425,0.0050631105,0.00006373149],"about_ca_topic_score_codex":0.0074467794,"about_ca_topic_score_gemma":0.0070249117,"teacher_disagreement_score":0.0074467794,"about_ca_system_score_codex":0.0017874858,"about_ca_system_score_gemma":0.0020804398,"threshold_uncertainty_score":0.03108865},"labels":[],"label_agreement":null},{"id":"W2006616981","doi":"10.1145/1835449.1835644","title":"A framework for BM25F-based XML retrieval","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Element (criminal law); Information retrieval; XML; Field (mathematics); XML framework; Document Structure Description; XML validation; Weighting; XML Schema (W3C); XML Signature; World Wide Web; Mathematics; Physics","score_opus":0.02058687536043164,"score_gpt":0.29838085536171366,"score_spread":0.277793980001282,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2006616981","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":[0.0028904201,0.0016756156,0.9863283,0.00032870925,0.00015109878,0.000489452,0.0005703029,0.0060106246,0.0015555035],"genre_scores_gemma":[0.0401208,0.000679686,0.95434046,0.00024863693,0.00017275629,0.0007137934,0.0018764485,0.00037633878,0.0014710601],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9892959,0.003915473,0.0008807718,0.0016875874,0.003702013,0.0005182659],"domain_scores_gemma":[0.99348986,0.0025712624,0.00037219035,0.0010358909,0.0022717535,0.0002589695],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.014753379,0.0027301162,0.0027360846,0.009986186,0.0021292688,0.004449446,0.005063137,0.004187218,0.0050920434],"category_scores_gemma":[0.026593687,0.0007699692,0.0025313196,0.007461198,0.0013137789,0.0049613644,0.0027156428,0.002793561,0.004678555],"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":[0.0006017098,0.00045435637,0.0008894366,0.0006371605,0.00045990167,0.00013634904,0.00025936047,0.08395119,0.012271924,0.026164655,0.02883235,0.8453416],"study_design_scores_gemma":[0.000180588,0.0004882875,0.0011731015,0.00011291073,0.00019362444,0.00040346867,0.00012769521,0.9192431,0.013104578,0.037730552,0.027007272,0.00023487349],"about_ca_topic_score_codex":0.03517458,"about_ca_topic_score_gemma":0.02575341,"teacher_disagreement_score":0.03517458,"about_ca_system_score_codex":0.0030300324,"about_ca_system_score_gemma":0.0034009444,"threshold_uncertainty_score":0.07802427},"labels":[],"label_agreement":null},{"id":"W2006849827","doi":"10.3166/isi.19.4.118-143","title":"Exécution sécurisée de requêtes avec agrégats sur des données distribuées","year":2014,"lang":"fr","type":"article","venue":"Ingénierie des systèmes d information","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Political science; Humanities; Philosophy","score_opus":0.026364222658299085,"score_gpt":0.2314857114338765,"score_spread":0.20512148877557743,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2006849827","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":[0.64276445,0.0009267037,0.2927087,0.0008484906,0.00027729827,0.0002609081,0.00114877,0.05088796,0.010176651],"genre_scores_gemma":[0.8703557,0.00051990536,0.104935035,0.00026496127,0.00016917428,0.00015854744,0.0020546613,0.003170704,0.018371316],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9961708,0.000676447,0.00034584937,0.000639213,0.0018189169,0.00034880915],"domain_scores_gemma":[0.99175185,0.0049272547,0.00032603243,0.0013998062,0.0012856583,0.00030926766],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030360073,0.0018466155,0.0010977053,0.0015697291,0.0010921707,0.0028958018,0.001115876,0.0015027435,0.0057435436],"category_scores_gemma":[0.010603854,0.0008694822,0.0012980192,0.0010259618,0.001554154,0.0019420099,0.0015846194,0.0016830828,0.0014169653],"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":[0.0113972,0.0012237026,0.03612761,0.0012258915,0.00060779654,0.0029463486,0.003545094,0.16723005,0.28218642,0.016075619,0.016348634,0.46108568],"study_design_scores_gemma":[0.00052856334,0.0006479748,0.014498438,0.0000753844,0.00017330717,0.00048305248,0.0004908502,0.83430535,0.13052534,0.0031030688,0.01507642,0.000092263246],"about_ca_topic_score_codex":0.022608228,"about_ca_topic_score_gemma":0.013852597,"teacher_disagreement_score":0.022608228,"about_ca_system_score_codex":0.0015142413,"about_ca_system_score_gemma":0.0018824977,"threshold_uncertainty_score":0.044953227},"labels":[],"label_agreement":null},{"id":"W2007045316","doi":"10.1145/2630729.2630735","title":"Massachusetts Economy and Technology Index System","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"United States Agency for International Development; Ministry of Economy, Trade and Industry; National Science Foundation","keywords":"Metis; Big data; Fidelity; Index (typography); Census; Data science; Key (lock); Computer science; Knowledge management; Business; World Wide Web; Telecommunications; Data mining; Sociology; Computer security","score_opus":0.004610163935724667,"score_gpt":0.19483708784151027,"score_spread":0.1902269239057856,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007045316","genre_codex":"dataset","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":[0.002059962,0.0008855393,0.0019953442,0.0007017104,0.00027681838,0.00013651016,0.91946,0.0024258823,0.07205828],"genre_scores_gemma":[0.012212327,0.0015909615,0.0031139308,0.00027326535,0.00025024323,0.00068243925,0.948616,0.0005027025,0.032758027],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99824905,0.00016037973,0.00048242224,0.00028943637,0.00066289486,0.00015583647],"domain_scores_gemma":[0.99459606,0.0009112779,0.0010416792,0.00063781586,0.0023718784,0.00044119963],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010318451,0.0012310288,0.0013005871,0.01901745,0.0008835584,0.004671661,0.0017282612,0.00095546007,0.13399051],"category_scores_gemma":[0.013599277,0.00042592277,0.0005108146,0.034530703,0.00024396354,0.0046164165,0.0018570784,0.0013309668,0.10351827],"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":[0.00005815849,0.000024585048,0.0032409073,0.00050868513,0.000037838498,0.00010167329,0.00014190674,0.00043589014,0.00020521184,0.023603538,0.94692075,0.024720896],"study_design_scores_gemma":[0.000016148386,0.000011286741,0.0050335624,0.00011077692,0.000015141445,0.00007401613,0.000081567814,0.00039666842,0.00016851384,0.0033825901,0.99069107,0.000018627814],"about_ca_topic_score_codex":0.025716737,"about_ca_topic_score_gemma":0.015303797,"teacher_disagreement_score":0.13399051,"about_ca_system_score_codex":0.0024579954,"about_ca_system_score_gemma":0.0032649066,"threshold_uncertainty_score":0.4482429},"labels":[],"label_agreement":null},{"id":"W2007644552","doi":"10.3166/isi.7.3.11-38","title":"Langage pour bases multidimensionnelles : OLAP-SQL","year":2002,"lang":"fr","type":"article","venue":"Ingénierie des systèmes d information","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Online analytical processing; Computer science; SQL; Database; Data warehouse","score_opus":0.0375928310123485,"score_gpt":0.23732211699825811,"score_spread":0.1997292859859096,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007644552","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":[0.007914538,0.0009743537,0.9302365,0.0007771489,0.00026682197,0.00030932357,0.0024557735,0.048866242,0.0081993],"genre_scores_gemma":[0.11607856,0.0025184595,0.83626485,0.0013609387,0.00053903734,0.0009789235,0.010299635,0.009448111,0.022511523],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99627775,0.0009687684,0.0006045995,0.0004650048,0.001497738,0.00018608566],"domain_scores_gemma":[0.99378777,0.0033861906,0.00027825142,0.0011118462,0.001157386,0.0002784585],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004723668,0.0014075836,0.0009365473,0.0012522665,0.0009036117,0.00542709,0.0013365606,0.0013628704,0.014303296],"category_scores_gemma":[0.007829723,0.0008757097,0.0009411286,0.0011733801,0.0010548799,0.0050921957,0.0023280038,0.00366456,0.007116134],"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":[0.002386821,0.0004951811,0.0050652274,0.0022902512,0.00024639058,0.0022904042,0.0051307394,0.024296597,0.06601241,0.27448425,0.0957433,0.52155846],"study_design_scores_gemma":[0.00036827466,0.00041874067,0.0020608623,0.00056758523,0.00013867301,0.0021652747,0.0007844644,0.120393485,0.086937055,0.0904306,0.69547015,0.00026477053],"about_ca_topic_score_codex":0.0029944968,"about_ca_topic_score_gemma":0.0013805979,"teacher_disagreement_score":0.014303296,"about_ca_system_score_codex":0.00087211485,"about_ca_system_score_gemma":0.0012061077,"threshold_uncertainty_score":0.047849298},"labels":[],"label_agreement":null},{"id":"W2008340931","doi":"10.1145/1458082.1458152","title":"Rewriting of visibly pushdown languages for xml data integration","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; XML Schema Editor; Streaming XML; XML validation; Programming language; Document Structure Description; XPath; XML Schema (W3C); Efficient XML Interchange; XML; RELAX NG; XML database; XML Encryption; World Wide Web","score_opus":0.08009445811931618,"score_gpt":0.3330191870290265,"score_spread":0.2529247289097103,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008340931","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":[0.033472873,0.0006563368,0.9567681,0.0005382425,0.00009380243,0.00011082234,0.00011680561,0.00045840145,0.0077846018],"genre_scores_gemma":[0.5823452,0.0011771285,0.4030583,0.0005239022,0.00023815437,0.0005262698,0.0007224129,0.00049646455,0.010912241],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99600524,0.0013306449,0.00050658215,0.0006826836,0.001260245,0.0002145769],"domain_scores_gemma":[0.99322045,0.0043291403,0.0006308372,0.00088616065,0.00076496066,0.00016842895],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023530729,0.0006658961,0.00053144206,0.0008344778,0.0009552576,0.0026506116,0.0010900742,0.0011205882,0.0031839225],"category_scores_gemma":[0.009360845,0.0006277957,0.0019520341,0.00090295414,0.0023488586,0.0043957974,0.0022037642,0.0022596603,0.000654375],"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":[0.000050385814,0.000045658395,0.00045179404,0.00017948291,0.0000436735,0.0005644523,0.00088212837,0.044072103,0.008597949,0.9244015,0.00085287483,0.019858077],"study_design_scores_gemma":[0.000020655129,0.00003703404,0.00012652186,0.000022790739,0.000030583215,0.00023870089,0.00010943112,0.13671641,0.0052524586,0.85022765,0.0071824095,0.00003532829],"about_ca_topic_score_codex":0.0014607273,"about_ca_topic_score_gemma":0.0010613858,"teacher_disagreement_score":0.0031839225,"about_ca_system_score_codex":0.0018481269,"about_ca_system_score_gemma":0.000833948,"threshold_uncertainty_score":0.013409197},"labels":[],"label_agreement":null},{"id":"W2008970532","doi":"10.1145/1188966.1188985","title":"Peer-to-peer data integration with distributed bridges","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Peer-to-peer; Computer science; Data integration; Distributed computing; Database","score_opus":0.023262748752188724,"score_gpt":0.266157444194721,"score_spread":0.24289469544253225,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008970532","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":[0.008984469,0.00027368686,0.9862148,0.00036853855,0.000050578285,0.00022242371,0.000035231904,0.0012718781,0.0025783218],"genre_scores_gemma":[0.1796704,0.00045753195,0.81378627,0.00031005224,0.00011929357,0.00041107307,0.00044091057,0.0002559638,0.0045485026],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9922963,0.0018831854,0.0005960131,0.0011622661,0.0037351758,0.00032697013],"domain_scores_gemma":[0.9930883,0.0019045193,0.00048649582,0.002820157,0.0013852607,0.00031539996],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0064216373,0.0005518876,0.0011762555,0.0018198002,0.00196727,0.0040576914,0.0048948033,0.0021749828,0.001910546],"category_scores_gemma":[0.012523077,0.00086416677,0.0010531342,0.0033332852,0.0013004991,0.008260157,0.008569238,0.0022590668,0.0012412817],"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":[0.00042031932,0.0006616992,0.005868828,0.00082463835,0.0004405585,0.0013599904,0.005046031,0.07280248,0.033452913,0.20257486,0.011668142,0.66487956],"study_design_scores_gemma":[0.00021710448,0.00062128465,0.0015708554,0.00028874545,0.00035065648,0.001540157,0.0013974548,0.5267772,0.04959735,0.24711986,0.17030846,0.00021083668],"about_ca_topic_score_codex":0.0015619195,"about_ca_topic_score_gemma":0.0013895888,"teacher_disagreement_score":0.0064216373,"about_ca_system_score_codex":0.0006885575,"about_ca_system_score_gemma":0.0020126137,"threshold_uncertainty_score":0.033961296},"labels":[],"label_agreement":null},{"id":"W2009853803","doi":"10.1016/j.scico.2010.12.001","title":"Partial evaluation of Maple","year":2010,"lang":"en","type":"article","venue":"Science of Computer Programming","topic":"Advanced Database Systems and Queries","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":"McMaster University","funders":"","keywords":"Maple; Computer science; Partial evaluation; Code (set theory); Programming language","score_opus":0.02531060812568823,"score_gpt":0.30938040908148295,"score_spread":0.2840698009557947,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2009853803","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":[0.29053107,0.003953395,0.5429453,0.0029070608,0.0009900284,0.00023666884,0.0027278385,0.024465015,0.13124354],"genre_scores_gemma":[0.8839461,0.00045337278,0.08997916,0.00039029244,0.00035623295,0.00012434232,0.0016987559,0.0012665462,0.021785172],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9974884,0.0008299273,0.000112407375,0.00026253657,0.0009081839,0.0003985484],"domain_scores_gemma":[0.99468166,0.0019212322,0.00020665486,0.0016931045,0.0012802199,0.00021702128],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001726284,0.0006427333,0.0009787206,0.00095473893,0.0008741336,0.0024765215,0.0011284862,0.0006989058,0.01724239],"category_scores_gemma":[0.009650841,0.00035556435,0.0007033012,0.0011522004,0.001121559,0.0039201416,0.0025278965,0.0008801286,0.0028104086],"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":[0.004051702,0.00027045218,0.005921274,0.0010656363,0.00026479707,0.00055861386,0.0004960529,0.045292057,0.015669838,0.36179778,0.06792848,0.49668333],"study_design_scores_gemma":[0.0003159618,0.00082597346,0.0024605873,0.00018511589,0.00030668257,0.000697582,0.0002822381,0.30680937,0.0481272,0.55340636,0.086469255,0.00011372987],"about_ca_topic_score_codex":0.001364262,"about_ca_topic_score_gemma":0.0020947324,"teacher_disagreement_score":0.01724239,"about_ca_system_score_codex":0.0008489956,"about_ca_system_score_gemma":0.0013927872,"threshold_uncertainty_score":0.05768156},"labels":[],"label_agreement":null},{"id":"W2011820176","doi":"10.1109/edoc.2014.12","title":"A Formalization of Complex Event Stream Processing","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Computer science; Complex event processing; Event (particle physics); Set (abstract data type); Programming language; Computation; Stream processing; Theoretical computer science; Code (set theory); Data mining; Distributed computing; Process (computing)","score_opus":0.017694577325448622,"score_gpt":0.2666752352905432,"score_spread":0.24898065796509458,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2011820176","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":[0.0013864964,0.00024453006,0.99337053,0.0005105809,0.00006999219,0.00010376236,0.000304937,0.00074842037,0.0032607054],"genre_scores_gemma":[0.10656217,0.0011634562,0.8828083,0.0007245653,0.00042494293,0.0006558562,0.001194792,0.00042658942,0.006039297],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.996326,0.0007332605,0.00059693865,0.0006920867,0.0013504125,0.00030121056],"domain_scores_gemma":[0.9955161,0.0021634842,0.00042665933,0.0008156339,0.00088380073,0.00019439221],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0053628995,0.001111051,0.00069205154,0.0014290771,0.0010916288,0.005027326,0.0031191914,0.0016567586,0.005286269],"category_scores_gemma":[0.007835085,0.00093390705,0.002080224,0.001739285,0.004565793,0.006471652,0.0028041159,0.0040304866,0.0016336481],"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":[0.000039716884,0.00005955641,0.0003077552,0.00020259891,0.000022292968,0.00030635283,0.0005012757,0.017539443,0.0023549546,0.95846003,0.0027416872,0.017464394],"study_design_scores_gemma":[0.00008282422,0.00009649034,0.00027957332,0.00024702595,0.00007863259,0.0007219356,0.00019545229,0.2058299,0.005994825,0.6829687,0.10342733,0.000077327175],"about_ca_topic_score_codex":0.0050724847,"about_ca_topic_score_gemma":0.003146151,"teacher_disagreement_score":0.0053628995,"about_ca_system_score_codex":0.0014213922,"about_ca_system_score_gemma":0.003031215,"threshold_uncertainty_score":0.028362036},"labels":[],"label_agreement":null},{"id":"W2012602264","doi":"10.1145/956699.956721","title":"Partial answers in information integration systems","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Concordia University","funders":"","keywords":"Citation; Library science; World Wide Web; Computer science","score_opus":0.010095854802269493,"score_gpt":0.22456011690282532,"score_spread":0.21446426210055583,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2012602264","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":[0.030769873,0.055958923,0.41595277,0.11156906,0.0050495546,0.0005875472,0.0018636889,0.0032849335,0.37496364],"genre_scores_gemma":[0.58742,0.028582986,0.18246774,0.011022788,0.0065260753,0.0009676677,0.0052726655,0.0012575627,0.17648253],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9808702,0.009774542,0.0018536565,0.0021237254,0.0044919793,0.0008858891],"domain_scores_gemma":[0.97614324,0.013357437,0.0010393322,0.00477059,0.0037800982,0.0009092126],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012289923,0.0010393818,0.0013601661,0.0045203157,0.0047283308,0.015127736,0.0019182146,0.0053371745,0.03785211],"category_scores_gemma":[0.045653813,0.0011614559,0.0013806742,0.00811614,0.009832357,0.05032277,0.011017217,0.0039312467,0.0081892535],"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":[0.000054458997,0.000039248393,0.00067644136,0.00038735225,0.000031035925,0.00021776951,0.0020798796,0.0010056356,0.0001777939,0.89254993,0.031232052,0.071548395],"study_design_scores_gemma":[0.000023628212,0.000029867717,0.00019562984,0.00021319505,0.000023313638,0.00021940301,0.000882344,0.0022914486,0.00025166367,0.8368147,0.15903366,0.000021142736],"about_ca_topic_score_codex":0.0029841622,"about_ca_topic_score_gemma":0.0023437089,"teacher_disagreement_score":0.03785211,"about_ca_system_score_codex":0.0041137193,"about_ca_system_score_gemma":0.0037656303,"threshold_uncertainty_score":0.12662792},"labels":[],"label_agreement":null},{"id":"W2013380293","doi":"10.1145/958220.958261","title":"Set-at-a-time access to XML through DOM","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; University of Waterloo","keywords":"Computer science; Document Object Model; XML; Interface (matter); Overhead (engineering); Set (abstract data type); Filter (signal processing); Code (set theory); Application programming interface; Simple API for XML; Database; Distributed computing; Programming language; Efficient XML Interchange; Operating system; XML Signature","score_opus":0.03509056860356404,"score_gpt":0.30540656512002834,"score_spread":0.2703159965164643,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013380293","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":[0.02069938,0.00032855693,0.9615285,0.00021699227,0.000090786496,0.00020191367,0.00025863358,0.011534017,0.0051412424],"genre_scores_gemma":[0.19744797,0.00055700215,0.78926265,0.0006166857,0.00012962698,0.0003555723,0.0013222565,0.0021447637,0.008163458],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9970728,0.0010845215,0.00044921853,0.00031487842,0.0007725304,0.000306183],"domain_scores_gemma":[0.9907141,0.0023926124,0.00033027167,0.0049529294,0.0011687258,0.00044139358],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003535604,0.0006303888,0.0011822568,0.0009516123,0.0011401469,0.0036954593,0.0024643687,0.0015997665,0.0022279297],"category_scores_gemma":[0.00910628,0.0007732187,0.0012394334,0.0009825923,0.0014083345,0.0063870554,0.0048776297,0.0024665382,0.0019301551],"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":[0.0029327923,0.00065929326,0.008281613,0.0008726665,0.00019436459,0.002010815,0.0038266527,0.024703292,0.08910415,0.4084755,0.029623203,0.4293157],"study_design_scores_gemma":[0.00036424032,0.00059899304,0.0021511833,0.00030712623,0.00016082673,0.0023463047,0.00052526593,0.34816304,0.10403871,0.1790222,0.36195567,0.00036643606],"about_ca_topic_score_codex":0.0013651333,"about_ca_topic_score_gemma":0.0024012101,"teacher_disagreement_score":0.0036954593,"about_ca_system_score_codex":0.00061298214,"about_ca_system_score_gemma":0.0011505893,"threshold_uncertainty_score":0.018698275},"labels":[],"label_agreement":null},{"id":"W2014465906","doi":"10.1109/icde.2008.4497606","title":"Hierarchical Indexing Approach to Support XPath Queries","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"XPath; Search engine indexing; Computer science; Index (typography); Path expression; Information retrieval; XML; Data mining; Theoretical computer science; Query language; XML database; World Wide Web","score_opus":0.035453499669332214,"score_gpt":0.25563149039249544,"score_spread":0.22017799072316324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2014465906","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":[0.013896938,0.0010890204,0.9711149,0.00045143696,0.00011262775,0.00036637046,0.0007519133,0.0072749783,0.0049417815],"genre_scores_gemma":[0.12635821,0.0012982918,0.8600838,0.0004957981,0.00023776812,0.00053148094,0.003716747,0.000825428,0.0064525628],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9966366,0.0004627116,0.00049552746,0.0005533267,0.0015357438,0.0003159846],"domain_scores_gemma":[0.9946337,0.0014025617,0.00035112113,0.002076032,0.0013358294,0.00020082913],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001975242,0.00076597853,0.0008608806,0.0025477912,0.0009970673,0.0022723868,0.0028968484,0.00090098305,0.0034463282],"category_scores_gemma":[0.0054086545,0.00056770945,0.0012509474,0.004545587,0.00086800545,0.0074429666,0.0022401796,0.0019980425,0.0014862509],"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":[0.0005143933,0.0007851764,0.007336427,0.0011860237,0.00024832957,0.000615404,0.0018687488,0.045880776,0.056813132,0.14651465,0.04730308,0.69093394],"study_design_scores_gemma":[0.00024512134,0.0007007754,0.0033206518,0.00015247388,0.0003765721,0.0014909937,0.00067805214,0.6390722,0.06844609,0.12531793,0.15997978,0.00021930027],"about_ca_topic_score_codex":0.008129714,"about_ca_topic_score_gemma":0.0055185906,"teacher_disagreement_score":0.008129714,"about_ca_system_score_codex":0.0012357614,"about_ca_system_score_gemma":0.0021937788,"threshold_uncertainty_score":0.01616478},"labels":[],"label_agreement":null},{"id":"W2015071642","doi":"10.1145/1030397.1030401","title":"Querying XML documents by dynamic shredding","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; XML Schema Editor; Streaming XML; Efficient XML Interchange; XML validation; XML database; XQuery; Document Structure Description; Information retrieval; XML Schema (W3C); XML Encryption; XML; Database; World Wide Web","score_opus":0.005008996265919023,"score_gpt":0.24840605666567453,"score_spread":0.2433970603997555,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015071642","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":[0.1023189,0.00275539,0.8454575,0.0015754934,0.00022449407,0.00051568507,0.0030373975,0.02986992,0.014245266],"genre_scores_gemma":[0.28277895,0.0020336655,0.6908772,0.0010285908,0.0001981346,0.00029716507,0.008999675,0.0038140872,0.009972473],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9943956,0.0013011266,0.0008637439,0.0010201047,0.0021618179,0.00025768168],"domain_scores_gemma":[0.9919119,0.0036840988,0.0005473387,0.0026091281,0.0010790387,0.00016854811],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0042728633,0.00084269646,0.0013673245,0.0031516068,0.00078889105,0.0042734235,0.0023620978,0.0013113861,0.0034610445],"category_scores_gemma":[0.014693557,0.00091719197,0.001445468,0.0030251949,0.0016298176,0.0068074577,0.0054383283,0.0015042116,0.0016625894],"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":[0.0018174181,0.0003993545,0.012473223,0.0015693075,0.00042461144,0.0036081478,0.009344206,0.05709594,0.08110496,0.121690966,0.042831946,0.6676399],"study_design_scores_gemma":[0.00022598554,0.00030769221,0.0027017188,0.00044440644,0.00027855343,0.0030443002,0.0022740797,0.43501842,0.15459031,0.13916786,0.26167482,0.00027179753],"about_ca_topic_score_codex":0.0028215891,"about_ca_topic_score_gemma":0.003200782,"teacher_disagreement_score":0.0042734235,"about_ca_system_score_codex":0.0010618849,"about_ca_system_score_gemma":0.0008793435,"threshold_uncertainty_score":0.022597313},"labels":[],"label_agreement":null},{"id":"W20171450","doi":"10.1016/s0167-4943(10)70006-6","title":"Querying Business Processes Under Models of Uncertainty.","year":2008,"lang":"en","type":"article","venue":"Archives of Gerontology and Geriatrics","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science","score_opus":0.038530439109520094,"score_gpt":0.25267276602062216,"score_spread":0.21414232691110208,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W20171450","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":[0.107282504,0.006841022,0.8494295,0.010117167,0.00024966235,0.0005349531,0.0090353275,0.005177268,0.011332645],"genre_scores_gemma":[0.8039289,0.0029863724,0.18021664,0.00072436436,0.00030123317,0.0003861122,0.008571164,0.00028675995,0.002598483],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.977839,0.010158591,0.0023648394,0.0037863038,0.0049365456,0.0009147511],"domain_scores_gemma":[0.89776975,0.082290255,0.0073156203,0.0069087055,0.0043437197,0.0013719837],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0208656,0.0013463855,0.0019709892,0.0043154317,0.0014634131,0.008890271,0.0025290162,0.0028645545,0.004699766],"category_scores_gemma":[0.096183725,0.0013459366,0.0030688958,0.0057423785,0.001813218,0.013952221,0.0047527454,0.0022506132,0.0011568415],"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":[0.0009106988,0.00030942252,0.03630101,0.0010606569,0.00068465644,0.0015056317,0.0020742347,0.4954901,0.0011084741,0.3103785,0.011802352,0.1383742],"study_design_scores_gemma":[0.00007342435,0.00005306462,0.0011088988,0.000065335924,0.000069660324,0.0002753375,0.00032764874,0.76321447,0.00034292115,0.22757,0.0068649016,0.000034337176],"about_ca_topic_score_codex":0.02016192,"about_ca_topic_score_gemma":0.013961604,"teacher_disagreement_score":0.0208656,"about_ca_system_score_codex":0.0040006526,"about_ca_system_score_gemma":0.004255906,"threshold_uncertainty_score":0.11034918},"labels":[],"label_agreement":null},{"id":"W2017988065","doi":"10.1145/1951365.1951374","title":"GPX-matcher","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"XPath; Computer science; XML; Regular expression; Matching (statistics); Encoding (memory); Automaton; Path expression; XML database; Theoretical computer science; Information retrieval; Programming language; World Wide Web; Artificial intelligence","score_opus":0.0458915072464365,"score_gpt":0.21460782157730507,"score_spread":0.16871631433086856,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2017988065","genre_codex":"methods","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020068828,0.0005188228,0.8530591,0.0006129304,0.0004650449,0.0005454636,0.0032718624,0.09954245,0.021915415],"genre_scores_gemma":[0.21720615,0.0005760276,0.6949042,0.0014615769,0.0001753057,0.00076790055,0.014405488,0.0076803714,0.062822975],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989367,0.00015106279,0.000082472216,0.0003763176,0.00034041225,0.00011295979],"domain_scores_gemma":[0.99905187,0.00023237421,0.000052982123,0.00044905243,0.00017765086,0.00003603717],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008312901,0.00092596695,0.00074210996,0.0010675458,0.0008033576,0.0018001015,0.0024739737,0.001669847,0.035338845],"category_scores_gemma":[0.0035227875,0.00055465405,0.0007043398,0.0015653446,0.0005932847,0.0032636733,0.0024277386,0.0011329224,0.016725307],"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":[0.0014682263,0.00035595708,0.003333287,0.0007092428,0.00014527535,0.0006309866,0.00035538757,0.021796735,0.03135876,0.07974591,0.1549827,0.7051175],"study_design_scores_gemma":[0.00034813047,0.0005050973,0.002264133,0.000120999684,0.000113038885,0.0013150102,0.0002732721,0.3723506,0.121597275,0.13308695,0.36791003,0.00011548492],"about_ca_topic_score_codex":0.0018109728,"about_ca_topic_score_gemma":0.001367596,"teacher_disagreement_score":0.035338845,"about_ca_system_score_codex":0.0008824781,"about_ca_system_score_gemma":0.001063521,"threshold_uncertainty_score":0.11822021},"labels":[],"label_agreement":null},{"id":"W2019933064","doi":"10.2200/s00363ed1v01y201105dtm018","title":"Fundamentals of Physical Design and Query Compilation","year":2011,"lang":"en","type":"article","venue":"Synthesis lectures on data management","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":29,"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 Institute of Informatics","keywords":"Computer science; Query optimization; Information retrieval","score_opus":0.09803155566453071,"score_gpt":0.27762418553492446,"score_spread":0.17959262987039376,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2019933064","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":[0.001517181,0.0071446104,0.96026534,0.0012173298,0.0007855681,0.00006543807,0.0001561899,0.0016818217,0.027166663],"genre_scores_gemma":[0.15326074,0.018807538,0.7662249,0.00087311346,0.0020389147,0.00071342534,0.0007022375,0.00139086,0.05598826],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983286,0.00024213073,0.00011884876,0.00029690366,0.0008739234,0.00013950236],"domain_scores_gemma":[0.9986564,0.0005766683,0.00006952296,0.0003407844,0.0003090922,0.000047555404],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014221119,0.0014966854,0.000982614,0.0010875543,0.0007895465,0.004520024,0.0021538988,0.0011579577,0.016083961],"category_scores_gemma":[0.0045547644,0.001253599,0.001059538,0.0017894785,0.002445603,0.0043200874,0.0013432526,0.0025772576,0.0059283986],"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":[0.00007274147,0.00006783795,0.0002506881,0.00063141866,0.000043435746,0.000061200975,0.0002261512,0.017193269,0.0048631844,0.6680764,0.030258711,0.27825493],"study_design_scores_gemma":[0.000053202675,0.000062492465,0.00042743707,0.00024119983,0.000056898578,0.00023916822,0.00008014586,0.067639105,0.007044692,0.6951364,0.22896962,0.000049719198],"about_ca_topic_score_codex":0.0017753113,"about_ca_topic_score_gemma":0.0014514888,"teacher_disagreement_score":0.016083961,"about_ca_system_score_codex":0.0018801553,"about_ca_system_score_gemma":0.0018834146,"threshold_uncertainty_score":0.053806186},"labels":[],"label_agreement":null},{"id":"W2019940097","doi":"10.1016/s0304-3975(02)00736-3","title":"Expressive power of SQL","year":2003,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":68,"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; University of New Brunswick","funders":"Institut national de recherche en informatique et en automatique (INRIA)","keywords":"SQL; Computer science; Relational algebra; Mathematical proof; Programming language; Theoretical computer science; Reachability; Relational database; Database; Mathematics","score_opus":0.007096860504463824,"score_gpt":0.24190759469112036,"score_spread":0.23481073418665654,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2019940097","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":[0.07136263,0.006106877,0.6973356,0.015160126,0.00048376387,0.000107066146,0.0016795562,0.0031807094,0.20458364],"genre_scores_gemma":[0.87221044,0.0033543925,0.08876637,0.0025989448,0.0010265027,0.00020429975,0.001708753,0.0010936457,0.029036628],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9931554,0.002033841,0.000573761,0.0011959288,0.0025448145,0.0004961511],"domain_scores_gemma":[0.988117,0.0071023875,0.00035747085,0.0030899285,0.0010052413,0.00032799147],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0054329513,0.0009140365,0.001016292,0.0021072319,0.0017897136,0.0090131685,0.0023153478,0.001173494,0.008899666],"category_scores_gemma":[0.016362723,0.0013341417,0.0015468032,0.0021520548,0.0061286567,0.020793905,0.0056859152,0.0064178566,0.002152569],"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":[0.000051456318,0.000023046929,0.00018717081,0.000054971468,0.0000134145575,0.00003412491,0.00044937083,0.0012863036,0.0009603569,0.98237646,0.0019075088,0.012655822],"study_design_scores_gemma":[0.000012994385,0.000008119296,0.000067263034,0.000021642141,0.000022293967,0.0000472464,0.000058631336,0.0059784777,0.0011258161,0.9837143,0.008933257,0.000010008757],"about_ca_topic_score_codex":0.0012980581,"about_ca_topic_score_gemma":0.0008606386,"teacher_disagreement_score":0.0090131685,"about_ca_system_score_codex":0.0021062403,"about_ca_system_score_gemma":0.0013343081,"threshold_uncertainty_score":0.029772341},"labels":[],"label_agreement":null},{"id":"W20223991","doi":"10.20965/jaciii.2006.p0744","title":"Minimization of XML Tree Pattern Queries in the Presence of Integrity Constraints","year":2006,"lang":"en","type":"article","venue":"Journal of Advanced Computational Intelligence and Intelligent Informatics","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Computer science; Minification; XML; XPath; Tree (set theory); Complement (music); Query optimization; Algorithm; Key (lock); Spatial query; Time complexity; Theoretical computer science; Data mining; Sargable; Mathematics; Web search query; XML database; Information retrieval; Programming language","score_opus":0.02396197672208518,"score_gpt":0.27944266073935536,"score_spread":0.2554806840172702,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W20223991","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":[0.07804368,0.00020448212,0.9178577,0.00039143604,0.000014093879,0.00012698812,0.00021159832,0.0014853588,0.001664722],"genre_scores_gemma":[0.26732972,0.00017513006,0.72904825,0.00015295859,0.000031215648,0.000117263204,0.000830696,0.00046760976,0.0018470513],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99742377,0.00075880275,0.0002000762,0.00041644697,0.0009887784,0.00021213773],"domain_scores_gemma":[0.99479043,0.0035676165,0.00032641535,0.00065165065,0.0005637273,0.00010009531],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015951367,0.0006195578,0.0008893412,0.00058865733,0.00051442307,0.0011141808,0.0014400115,0.0006876224,0.0015098196],"category_scores_gemma":[0.007362134,0.000421947,0.00063301617,0.0012850453,0.00062330073,0.0026749517,0.0013781853,0.00091328914,0.0004280348],"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":[0.0012675725,0.0004064059,0.004289705,0.0008065095,0.00017991774,0.0009632943,0.0008156877,0.25409973,0.07999263,0.061382275,0.011067983,0.58472836],"study_design_scores_gemma":[0.000073257805,0.00017420767,0.00066260435,0.00002084262,0.00005636521,0.0008428476,0.0003009169,0.911258,0.042122856,0.03927016,0.0051928884,0.000025086443],"about_ca_topic_score_codex":0.001946719,"about_ca_topic_score_gemma":0.0028170336,"teacher_disagreement_score":0.001946719,"about_ca_system_score_codex":0.00055188994,"about_ca_system_score_gemma":0.0010362777,"threshold_uncertainty_score":0.008436024},"labels":[],"label_agreement":null},{"id":"W2022740398","doi":"10.14778/1880172.1880173","title":"Generating efficient execution plans for vertically partitioned XML databases","year":2010,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Query plan; Scalability; Database; Query optimization; XML database; Sargable; Distributed database; XML; Online aggregation; Relational database; Distributed computing; Information retrieval; Web search query; Search engine; Operating system","score_opus":0.0174271781966315,"score_gpt":0.25235560063649676,"score_spread":0.23492842243986525,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2022740398","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":[0.13633391,0.00029033067,0.85711056,0.000311742,0.000020726015,0.00031444378,0.0003685017,0.0026879637,0.0025618013],"genre_scores_gemma":[0.4294305,0.00018609212,0.56708044,0.000054913795,0.000016631795,0.000323542,0.0010214814,0.00039805076,0.0014884068],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990274,0.00030229814,0.000072885254,0.00014680155,0.00032346358,0.00012714954],"domain_scores_gemma":[0.9982217,0.00093797443,0.00021076215,0.00032100358,0.00022886266,0.0000797733],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012150742,0.00057277887,0.00037623366,0.00066852866,0.0005906887,0.0008605595,0.0007935427,0.0003827284,0.0014536434],"category_scores_gemma":[0.0037079505,0.00042291344,0.0005683462,0.00079701963,0.00058561086,0.0012739216,0.0011319348,0.00073952967,0.00026252551],"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":[0.00060768373,0.00032523225,0.008031659,0.00029639885,0.00008712615,0.00053792546,0.00074655964,0.5947072,0.052482765,0.052048355,0.00802385,0.28210527],"study_design_scores_gemma":[0.00007568761,0.0000978436,0.0008561987,0.000017022414,0.00002994678,0.00007342355,0.00021665113,0.956482,0.018001806,0.020793136,0.003337697,0.000018532452],"about_ca_topic_score_codex":0.00476395,"about_ca_topic_score_gemma":0.008089596,"teacher_disagreement_score":0.00476395,"about_ca_system_score_codex":0.00091860397,"about_ca_system_score_gemma":0.0013660417,"threshold_uncertainty_score":0.009472489},"labels":[],"label_agreement":null},{"id":"W2022769614","doi":"10.1109/bigdata.2013.6691776","title":"Managing massive graphs in relational DBMS","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Locality; SQL; Graph database; Relational database; Database; Graph; Theoretical computer science; Parallel computing","score_opus":0.013276665646162438,"score_gpt":0.22480636516710578,"score_spread":0.21152969952094333,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2022769614","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":[0.2223416,0.0026340976,0.73686814,0.0025421826,0.0002480903,0.00033139825,0.0020212254,0.02488662,0.008126641],"genre_scores_gemma":[0.60084665,0.0013476098,0.3901776,0.0004852795,0.000121332785,0.00016552291,0.0026634336,0.00084237027,0.0033502416],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99783474,0.00052925525,0.00022203344,0.00037427986,0.000863742,0.00017597774],"domain_scores_gemma":[0.99329454,0.0019055462,0.00046238577,0.0032877144,0.0007415952,0.00030819973],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020057647,0.0006799051,0.000858505,0.0016022461,0.0011271933,0.003294349,0.0030638974,0.0007151646,0.001982332],"category_scores_gemma":[0.007166771,0.0007043805,0.0006461457,0.0039337273,0.0010118874,0.008406078,0.0032666416,0.00096678187,0.0008099809],"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":[0.001484191,0.00059715577,0.014984697,0.0009189153,0.0004063078,0.0016351921,0.002214735,0.22947185,0.052820038,0.15990245,0.057204556,0.47836],"study_design_scores_gemma":[0.00021193971,0.0002741932,0.0027173155,0.00007491173,0.00019775951,0.00088649866,0.0013783968,0.7160512,0.040857926,0.19768685,0.039547786,0.00011519238],"about_ca_topic_score_codex":0.005180101,"about_ca_topic_score_gemma":0.0069880937,"teacher_disagreement_score":0.005180101,"about_ca_system_score_codex":0.000985051,"about_ca_system_score_gemma":0.0014113561,"threshold_uncertainty_score":0.01060766},"labels":[],"label_agreement":null},{"id":"W2023116400","doi":"10.1002/jae.1007","title":"Maxima: An open source computer algebra system","year":2008,"lang":"en","type":"article","venue":"Journal of Applied Econometrics","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Directory; Maxima; Computer science; Open source; Content (measure theory); Information retrieval; World Wide Web; Mathematics; Programming language; Operating system; History","score_opus":0.04164062374902375,"score_gpt":0.23737860302115307,"score_spread":0.19573797927212933,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2023116400","genre_codex":"methods","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0029101374,0.0006786901,0.44669947,0.0008954686,0.0004415623,0.00044752556,0.08108697,0.42876878,0.038071375],"genre_scores_gemma":[0.054726385,0.0014933306,0.6368459,0.0009356479,0.0006975541,0.0025222462,0.1593756,0.10215882,0.041244525],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978835,0.00054276694,0.000256074,0.0003885589,0.000741734,0.00018732023],"domain_scores_gemma":[0.9965803,0.0013428644,0.00017051063,0.0010596118,0.00065887667,0.00018781926],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.003230368,0.0011774652,0.0016305253,0.0031296962,0.00093185174,0.0041331477,0.004269331,0.00086554006,0.1837957],"category_scores_gemma":[0.011540773,0.0013558988,0.0021229147,0.004034468,0.0007513984,0.0051221712,0.00393591,0.0027024264,0.11273394],"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":[0.0007294885,0.00019223611,0.0011972889,0.0010305798,0.00023516025,0.00019128369,0.00021444363,0.005496266,0.0030169021,0.074829884,0.7265084,0.18635812],"study_design_scores_gemma":[0.00077443017,0.00010518562,0.0012503705,0.00023125869,0.000109093846,0.0003720348,0.00011776636,0.07324493,0.0106438715,0.18215944,0.7308628,0.00012881124],"about_ca_topic_score_codex":0.0017284638,"about_ca_topic_score_gemma":0.002129897,"teacher_disagreement_score":0.9957307,"about_ca_system_score_codex":0.00089306606,"about_ca_system_score_gemma":0.002024314,"threshold_uncertainty_score":0.6148579},"labels":[],"label_agreement":null},{"id":"W2024493099","doi":"10.1107/s0108767300026416","title":"An Environment for Searching and Mining Multiple Structural Databases","year":2000,"lang":"en","type":"article","venue":"Acta Crystallographica Section A Foundations of Crystallography","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Database; Computer science; Information retrieval","score_opus":0.019128609773460595,"score_gpt":0.2738990056233544,"score_spread":0.2547703958498938,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2024493099","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":[0.003767363,0.0076276595,0.4376566,0.0017958423,0.00059381325,0.002092365,0.1662277,0.37058762,0.0096510155],"genre_scores_gemma":[0.01356434,0.005261905,0.7064231,0.0006516422,0.00016048936,0.003367272,0.25305256,0.013951256,0.0035674968],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9910416,0.0024654013,0.0024423692,0.0016918879,0.0019986879,0.00036004512],"domain_scores_gemma":[0.9818942,0.010679089,0.0016902761,0.003197267,0.001472605,0.0010664281],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.016325464,0.0062496997,0.005961597,0.015944533,0.003628099,0.011609142,0.00927631,0.0041585653,0.041825205],"category_scores_gemma":[0.0416028,0.0050760405,0.0051886495,0.023805602,0.0018097173,0.013819448,0.01322001,0.005442036,0.040983863],"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":[0.0029906398,0.00056930335,0.004029582,0.019540735,0.002399339,0.0031878105,0.0021009005,0.009372048,0.009899968,0.04256866,0.5813752,0.32196587],"study_design_scores_gemma":[0.0016910627,0.00044107065,0.0042286045,0.0040141735,0.000808283,0.0026568805,0.0017989889,0.078341745,0.010317148,0.13808906,0.7570121,0.0006008626],"about_ca_topic_score_codex":0.0033961623,"about_ca_topic_score_gemma":0.0057257954,"teacher_disagreement_score":0.041825205,"about_ca_system_score_codex":0.0018582111,"about_ca_system_score_gemma":0.00556932,"threshold_uncertainty_score":0.13991922},"labels":[],"label_agreement":null},{"id":"W2025036269","doi":"10.1145/1923947.1923969","title":"Lightweight problem determination in DBMSs using data stream analysis techniques","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada); Queen's University","funders":"","keywords":"Computer science; Overhead (engineering); IBM; Task (project management); Set (abstract data type); Database; Data mining; Data stream; Stream processing; Real-time computing; Distributed computing; Operating system; Programming language","score_opus":0.028893490438080607,"score_gpt":0.3127612501953509,"score_spread":0.2838677597572703,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2025036269","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":[0.0829638,0.00082988007,0.88969535,0.000893182,0.00007891341,0.0005683112,0.0007198014,0.022169594,0.00208121],"genre_scores_gemma":[0.20994231,0.00032235036,0.7855686,0.00022686303,0.00006766497,0.00025403214,0.0012908644,0.000752074,0.0015752658],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99131304,0.0022997851,0.00094411534,0.0015276701,0.003409488,0.0005060319],"domain_scores_gemma":[0.97855157,0.0125412,0.0020606704,0.0038832393,0.0023481383,0.00061516673],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004630375,0.0018977805,0.002184309,0.0028964723,0.0019106723,0.0051358067,0.002929143,0.0014020744,0.0022327385],"category_scores_gemma":[0.02374493,0.0014467728,0.001774398,0.0034618522,0.0012038994,0.007188079,0.0038069873,0.0026092639,0.0012371653],"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":[0.0011361707,0.0012512845,0.022076083,0.0013615546,0.00048545547,0.0008012312,0.002403022,0.096347,0.039048824,0.01668109,0.017863743,0.8005447],"study_design_scores_gemma":[0.00020813156,0.000230776,0.0029089213,0.00008344327,0.000100167454,0.0004212902,0.0009842025,0.91925853,0.027534433,0.039990455,0.008202173,0.000077457604],"about_ca_topic_score_codex":0.004239181,"about_ca_topic_score_gemma":0.0075740037,"teacher_disagreement_score":0.0051358067,"about_ca_system_score_codex":0.0012384356,"about_ca_system_score_gemma":0.0031046295,"threshold_uncertainty_score":0.024488032},"labels":[],"label_agreement":null},{"id":"W2026132760","doi":"10.1145/1980002.1980005","title":"Interview with Frank Tompa","year":2011,"lang":"en","type":"article","venue":"ACM SIGWEB Newsletter","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; XML; Selection (genetic algorithm); Matching (statistics); World Wide Web; Information retrieval; Library science; Database; Artificial intelligence","score_opus":0.057525854295443594,"score_gpt":0.23013140306525812,"score_spread":0.17260554876981452,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2026132760","genre_codex":"commentary","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":[0.0028004623,0.009876249,0.00044064282,0.94219625,0.012988915,0.000033747405,0.00014066717,0.00007931817,0.03144382],"genre_scores_gemma":[0.042572454,0.011909854,0.001168345,0.77610034,0.0044944147,0.00019780459,0.00017646959,0.0002050923,0.1631751],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980792,0.0006554747,0.000051141375,0.00025856862,0.00042625313,0.000529336],"domain_scores_gemma":[0.9954964,0.0012901151,0.00016267101,0.00006295412,0.0010936187,0.0018943219],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026130353,0.0006095231,0.0007171343,0.0009362413,0.012135057,0.004487816,0.0009196913,0.0055026812,0.03137558],"category_scores_gemma":[0.011809564,0.0005204049,0.00033575945,0.0013264157,0.0026696066,0.0054882234,0.0022486965,0.013703218,0.009013917],"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":[0.000010813431,0.00001737362,0.00018521772,0.000026285623,0.0000010811909,0.00023442022,0.0025524457,0.000019096371,0.000054248132,0.0032627152,0.986384,0.007252297],"study_design_scores_gemma":[0.0000042733727,0.000016139513,0.00029263936,0.00009713119,0.0000014758765,0.0007266577,0.008824813,0.000043577384,0.000042118274,0.0010973215,0.9888405,0.000013297833],"about_ca_topic_score_codex":0.020624558,"about_ca_topic_score_gemma":0.026487801,"teacher_disagreement_score":0.03137558,"about_ca_system_score_codex":0.0047651734,"about_ca_system_score_gemma":0.009125986,"threshold_uncertainty_score":0.10496181},"labels":[],"label_agreement":null},{"id":"W2026139222","doi":"10.1016/j.jcss.2006.10.014","title":"Dependency-preserving normalization of relational and XML data","year":2006,"lang":"en","type":"article","venue":"Journal of Computer and System Sciences","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":49,"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; Functional dependency; Relational database; Redundancy (engineering); XML; Data integrity; Normalization (sociology); Data redundancy; Dependency (UML); XML validation; Data mining; Theoretical computer science; Database; Artificial intelligence","score_opus":0.03262459263909213,"score_gpt":0.2570799605490312,"score_spread":0.22445536790993909,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2026139222","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":[0.020520533,0.0008829713,0.95373243,0.0011438442,0.0005413071,0.00016519894,0.0026560728,0.011059416,0.009298194],"genre_scores_gemma":[0.23937547,0.0017611322,0.7151228,0.0011956155,0.0007372643,0.00043541592,0.0104417335,0.0076208166,0.023309743],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.990531,0.0020432633,0.0011644479,0.0015580021,0.004160445,0.000542885],"domain_scores_gemma":[0.9745746,0.0067233965,0.0015187712,0.011692479,0.0051514907,0.00033931684],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007141,0.0006804311,0.0011841034,0.0029902789,0.0014936023,0.003978079,0.0023876557,0.0008087095,0.00593703],"category_scores_gemma":[0.025274837,0.0012200199,0.0018376943,0.0054537165,0.0019176133,0.0073661953,0.003371988,0.0024409893,0.003204097],"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":[0.00064064446,0.00022997145,0.0054728836,0.00069762825,0.000251881,0.0007402862,0.0014485642,0.022548174,0.024007495,0.41579053,0.047981862,0.48019004],"study_design_scores_gemma":[0.00009259085,0.00011275728,0.0048594642,0.0002391499,0.00041805234,0.0011532233,0.00055798655,0.15792173,0.15401685,0.4796424,0.20080239,0.00018344707],"about_ca_topic_score_codex":0.0045303255,"about_ca_topic_score_gemma":0.005452336,"teacher_disagreement_score":0.007141,"about_ca_system_score_codex":0.0016999162,"about_ca_system_score_gemma":0.0039051494,"threshold_uncertainty_score":0.037765622},"labels":[],"label_agreement":null},{"id":"W2026485377","doi":"10.1007/s007780200061","title":"Locating and accessing data repositories with WebSemantics","year":2002,"lang":"en","type":"article","venue":"The VLDB Journal","topic":"Advanced Database Systems and Queries","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":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Metadata; Computer science; World Wide Web; Data element; Interoperability; Data discovery; Data sharing; Metadata repository; Data mapping; Linked data; Semantics (computer science); Data publishing; Information retrieval; Data science; Semantic Web; Publishing; Database","score_opus":0.059896002714666226,"score_gpt":0.26536957458185456,"score_spread":0.20547357186718834,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2026485377","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":[0.08839287,0.0011088651,0.8028378,0.00132935,0.00023119418,0.0006216089,0.0012440339,0.08112134,0.023112923],"genre_scores_gemma":[0.3168527,0.0011269987,0.6528541,0.0004948357,0.00018083402,0.00051342935,0.008023914,0.0055590416,0.014394166],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9948502,0.00094911514,0.0007356157,0.0005393928,0.002587179,0.00033850377],"domain_scores_gemma":[0.9892827,0.003245854,0.0006665177,0.005232651,0.0011261887,0.00044598305],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004102397,0.0010765612,0.0015358069,0.0067258333,0.0027090556,0.00693424,0.0028478696,0.0016100652,0.0061064577],"category_scores_gemma":[0.014703744,0.0015083302,0.001357951,0.01015719,0.0017234973,0.0121906875,0.008094511,0.001826221,0.0036386738],"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":[0.0013531387,0.00065647776,0.024043638,0.0008697966,0.0003143213,0.0016470123,0.004372249,0.008461107,0.028969942,0.07657515,0.06245535,0.79028183],"study_design_scores_gemma":[0.00047655008,0.0005964045,0.012523165,0.00064256485,0.0006170788,0.0051651876,0.005599478,0.36908078,0.10981565,0.21831119,0.27675486,0.00041709462],"about_ca_topic_score_codex":0.0045977114,"about_ca_topic_score_gemma":0.008527393,"teacher_disagreement_score":0.00693424,"about_ca_system_score_codex":0.0007165212,"about_ca_system_score_gemma":0.0021059697,"threshold_uncertainty_score":0.021695793},"labels":[],"label_agreement":null},{"id":"W2026984353","doi":"10.1145/1247480.1247567","title":"Optimal top-down join enumeration","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Leverage (statistics); Join (topology); Computer science; Enumeration; Transformational leadership; Graph; Dynamic programming; Top-down and bottom-up design; Theoretical computer science; Algorithm; Programming language; Artificial intelligence; Mathematics","score_opus":0.01174624350896088,"score_gpt":0.2568719753305507,"score_spread":0.24512573182158978,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2026984353","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":[0.03215099,0.0004083982,0.9501038,0.00024591037,0.00005004861,0.00021038562,0.0004911781,0.0036181025,0.012721239],"genre_scores_gemma":[0.3099544,0.00042889078,0.6757836,0.000250012,0.000049996746,0.00023118749,0.0025381693,0.0009228412,0.009840997],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.997638,0.00049040356,0.00017088458,0.00035891557,0.00094544346,0.00039632554],"domain_scores_gemma":[0.99766445,0.0009913,0.000099102246,0.0007529487,0.00041328967,0.00007893107],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012667973,0.00074443925,0.0012419447,0.0011520502,0.0010248135,0.0021522145,0.0014819856,0.0009348517,0.0097697405],"category_scores_gemma":[0.0055119502,0.0005792031,0.0011653228,0.002245361,0.0007701577,0.0029936016,0.0023100774,0.0013722982,0.0029616528],"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":[0.00059842813,0.00036873875,0.001991906,0.00061847264,0.000078620265,0.00021270229,0.00030923428,0.22809516,0.024882883,0.10560595,0.019382378,0.61785555],"study_design_scores_gemma":[0.00007140484,0.00014503986,0.00053690275,0.000038637572,0.000058461574,0.00023001303,0.00014396125,0.84079254,0.019830935,0.124441266,0.013672687,0.000038288366],"about_ca_topic_score_codex":0.0023523173,"about_ca_topic_score_gemma":0.004070302,"teacher_disagreement_score":0.0097697405,"about_ca_system_score_codex":0.00074136496,"about_ca_system_score_gemma":0.0022591162,"threshold_uncertainty_score":0.032683015},"labels":[],"label_agreement":null},{"id":"W2027705590","doi":"10.1007/s00778-012-0298-2","title":"Recommending XML physical designs for XML databases","year":2012,"lang":"en","type":"article","venue":"The VLDB Journal","topic":"Advanced Database Systems and Queries","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":"IBM (Canada); University of Waterloo","funders":"","keywords":"Computer science; XML database; Database; Materialized view; Efficient XML Interchange; XML Schema Editor; XML validation; XML; Relational database; Streaming XML; Information retrieval; Database design; XML Schema (W3C); XML framework; View; XML Encryption; World Wide Web","score_opus":0.13732934415176967,"score_gpt":0.35816510893963266,"score_spread":0.220835764787863,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2027705590","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":[0.10190032,0.0029175265,0.8792844,0.001441366,0.00037243543,0.0005017735,0.002557948,0.0026470546,0.0083770845],"genre_scores_gemma":[0.52217907,0.0018878435,0.46424368,0.00031546247,0.00013240748,0.00045671375,0.004435394,0.00024547,0.0061039305],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982161,0.00068768306,0.00015639157,0.00033322608,0.00051433145,0.00009227305],"domain_scores_gemma":[0.99497616,0.0024556906,0.00026619292,0.0009115022,0.0012148838,0.00017554474],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001569522,0.0009395137,0.0007952247,0.003338238,0.00066907844,0.001956584,0.0013484483,0.0015569445,0.008550234],"category_scores_gemma":[0.013102292,0.0009382434,0.00107509,0.002475245,0.0006605476,0.0035596208,0.001231397,0.0008642491,0.0019259682],"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":[0.0014342812,0.00064720854,0.0205264,0.0015768015,0.0002922962,0.00090488186,0.0007380189,0.13073581,0.01799577,0.049955867,0.06349501,0.7116977],"study_design_scores_gemma":[0.0002563069,0.00084156735,0.003155101,0.00024018384,0.00025650594,0.0007282255,0.0010281195,0.87480843,0.012102515,0.07128881,0.035215963,0.000078323355],"about_ca_topic_score_codex":0.0018270549,"about_ca_topic_score_gemma":0.0054848716,"teacher_disagreement_score":0.008550234,"about_ca_system_score_codex":0.00074879394,"about_ca_system_score_gemma":0.0010618824,"threshold_uncertainty_score":0.028603375},"labels":[],"label_agreement":null},{"id":"W2028156291","doi":"10.1145/1183512.1183527","title":"Computing closest common subexpressions for view selection problems","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada)","funders":"","keywords":"Materialized view; Computer science; Selection (genetic algorithm); Exploit; Set (abstract data type); Task (project management); Data warehouse; Space (punctuation); Relation (database); Data mining; Information retrieval; Theoretical computer science; Artificial intelligence; View","score_opus":0.01629554265453223,"score_gpt":0.2686786688748383,"score_spread":0.2523831262203061,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2028156291","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":[0.07784861,0.00077118026,0.9181264,0.00029180548,0.000041864536,0.00021219223,0.00038256156,0.00077612174,0.00154931],"genre_scores_gemma":[0.2733177,0.00054651755,0.7208507,0.00012158676,0.00010745211,0.0003097064,0.0025130194,0.0003248623,0.0019085617],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99451375,0.0013385495,0.0005245961,0.0010922255,0.0020614238,0.0004693927],"domain_scores_gemma":[0.9903438,0.006663386,0.00074097054,0.00095037994,0.0010052627,0.00029619707],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004689292,0.0014176861,0.002735244,0.0065701352,0.0014472634,0.003036901,0.002672106,0.001773178,0.0041208165],"category_scores_gemma":[0.0230247,0.00075423997,0.0023018387,0.0053581703,0.0015196885,0.0055940216,0.0031822324,0.001748414,0.0008170007],"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":[0.0007846137,0.00045910574,0.0108859725,0.00051613525,0.00028671362,0.0006367253,0.0009775265,0.28867006,0.009617838,0.072839685,0.008420018,0.60590553],"study_design_scores_gemma":[0.00010356842,0.00018538015,0.0011494862,0.000041050385,0.00009372103,0.00038407432,0.00045649963,0.86237264,0.007646057,0.1239854,0.0035345114,0.000047718655],"about_ca_topic_score_codex":0.00270228,"about_ca_topic_score_gemma":0.0031628474,"teacher_disagreement_score":0.0065701352,"about_ca_system_score_codex":0.0015953417,"about_ca_system_score_gemma":0.0018461902,"threshold_uncertainty_score":0.024799645},"labels":[],"label_agreement":null},{"id":"W2029487844","doi":"10.1007/s00778-010-0184-8","title":"Efficient evaluation of generalized tree-pattern queries on XML streams","year":2010,"lang":"en","type":"article","venue":"The VLDB Journal","topic":"Advanced Database Systems and Queries","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":"IBM (Canada)","funders":"","keywords":"XPath; Computer science; XML; Scalability; Query language; Fragment (logic); Spatial query; Theoretical computer science; Query optimization; Tree (set theory); Focus (optics); Node (physics); Time complexity; Data mining; XML database; Information retrieval; Algorithm; Web query classification; Web search query; Database; Search engine; Mathematics","score_opus":0.02671680487953133,"score_gpt":0.2935799402125482,"score_spread":0.26686313533301687,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2029487844","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":[0.4580931,0.0018364522,0.51040405,0.0007565229,0.00025618883,0.00042904928,0.0022300237,0.02071383,0.00528082],"genre_scores_gemma":[0.79427904,0.00044005577,0.1959776,0.000219876,0.0001657669,0.00015830777,0.0036216371,0.0011555803,0.0039821523],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9958715,0.00077417574,0.00037883333,0.0005125627,0.0020047773,0.00045810867],"domain_scores_gemma":[0.99434257,0.0030291048,0.00034185167,0.0010461418,0.0009890298,0.00025122013],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024268818,0.0012408054,0.0023985489,0.0014573704,0.00069444114,0.0029651031,0.0020632716,0.0011252402,0.003595418],"category_scores_gemma":[0.007969531,0.0005748042,0.00082604314,0.0026737994,0.00077724596,0.0042919153,0.0022730138,0.00090458465,0.0008253916],"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":[0.010309126,0.00061944366,0.0142402295,0.0010628671,0.00044966486,0.0016745393,0.0009585936,0.12881376,0.10375737,0.029076828,0.029679341,0.67935824],"study_design_scores_gemma":[0.0003347284,0.0003425186,0.0019008224,0.000027643946,0.000098006116,0.00036453927,0.00030090712,0.932673,0.038644392,0.021587238,0.0036868672,0.000039429757],"about_ca_topic_score_codex":0.004315688,"about_ca_topic_score_gemma":0.0063166,"teacher_disagreement_score":0.004315688,"about_ca_system_score_codex":0.0012699014,"about_ca_system_score_gemma":0.001485303,"threshold_uncertainty_score":0.012834728},"labels":[],"label_agreement":null},{"id":"W2029752352","doi":"10.1142/s0218843007001676","title":"SUPPORTING DISTRIBUTED EVENT-CONDITION-ACTION RULES IN A MULTIDATABASE ENVIRONMENT","year":2007,"lang":"en","type":"article","venue":"International Journal of Cooperative Information Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Wilfrid Laurier University; University of Ottawa","funders":"","keywords":"Computer science; Operand; Event (particle physics); Programming language; Semantics (computer science); Active database; Execution model; Set (abstract data type); Specification language; Database; Theoretical computer science; Distributed computing; Operating system","score_opus":0.0157671591098564,"score_gpt":0.3204777395311622,"score_spread":0.30471058042130583,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2029752352","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":[0.011476907,0.00013346734,0.97138566,0.00027816903,0.00006934675,0.0005078387,0.000102761594,0.01373445,0.0023114262],"genre_scores_gemma":[0.21332449,0.00012685999,0.7818511,0.0002642023,0.00011543047,0.00046427228,0.000401188,0.00078569254,0.0026667996],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9850713,0.0038507718,0.0019953477,0.002729669,0.0053536273,0.0009992578],"domain_scores_gemma":[0.9623103,0.018513095,0.0028810226,0.011485908,0.0031287554,0.0016809464],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.016945666,0.0011783094,0.001965666,0.0017025272,0.0018671855,0.006628043,0.0069467155,0.0026689682,0.0043825945],"category_scores_gemma":[0.025791075,0.0012630564,0.0013560292,0.0015913692,0.0025070417,0.0077528623,0.0037595567,0.0029856907,0.0015189216],"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":[0.0021265165,0.0035443918,0.012937436,0.0008798981,0.00066082634,0.004612355,0.0029129595,0.22276929,0.05785629,0.1856064,0.019396983,0.48669654],"study_design_scores_gemma":[0.00078652194,0.0004820152,0.0011865791,0.00011785858,0.00022378152,0.001160198,0.00022596275,0.82607216,0.05766405,0.06867608,0.04312233,0.00028250756],"about_ca_topic_score_codex":0.005831639,"about_ca_topic_score_gemma":0.0055131107,"teacher_disagreement_score":0.016945666,"about_ca_system_score_codex":0.0014566475,"about_ca_system_score_gemma":0.004108895,"threshold_uncertainty_score":0.089618266},"labels":[],"label_agreement":null},{"id":"W2031981104","doi":"10.1001/archsurg.2009.293","title":"What Do We Gain and Lose From Database Studies?","year":2010,"lang":"en","type":"letter","venue":"Archives of Surgery","topic":"Advanced Database Systems and Queries","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":"Ottawa Hospital","funders":"","keywords":"Medicine; Database; Surgery; Computer science","score_opus":0.04947215824883857,"score_gpt":0.27987629091586635,"score_spread":0.23040413266702778,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031981104","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00011344467,0.0016840624,0.00012249028,0.99356526,0.0038189755,0.0000020762031,0.000010496476,0.000008977829,0.00067417795],"genre_scores_gemma":[0.0047725425,0.0040049073,0.0006810988,0.95612484,0.03262577,0.000018624822,0.000022240263,0.000028140294,0.0017218149],"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.970242,0.013440018,0.003962783,0.001882285,0.008286802,0.0021860662],"domain_scores_gemma":[0.7328773,0.15890425,0.013032308,0.011911102,0.04155457,0.04172053],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.060242187,0.00088808715,0.0022943146,0.0028528585,0.007802466,0.014066808,0.0029396524,0.051594146,0.010496013],"category_scores_gemma":[0.25669768,0.0011958122,0.0014131798,0.0030367419,0.024389844,0.033449665,0.008155682,0.05302247,0.008376353],"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":[0.00012981641,0.000069900256,0.0028422263,0.00026547283,0.00006348875,0.0011769308,0.00047642682,0.00007610379,0.00011949297,0.015623142,0.9252602,0.053896867],"study_design_scores_gemma":[0.00026502777,0.000118082426,0.00398434,0.0024452098,0.0001047644,0.0053479956,0.0056019686,0.0005615041,0.00017306629,0.16869257,0.81243694,0.00026850216],"about_ca_topic_score_codex":0.0060885265,"about_ca_topic_score_gemma":0.015265193,"teacher_disagreement_score":0.9397578,"about_ca_system_score_codex":0.0074216463,"about_ca_system_score_gemma":0.012945765,"threshold_uncertainty_score":0.318595},"labels":[],"label_agreement":null},{"id":"W2032265428","doi":"10.1145/2002259.2002316","title":"fpga-ToPSS","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Complex event processing; Field-programmable gate array; Event (particle physics); Latency (audio); Predicate (mathematical logic); Computer architecture; Embedded system; Operating system; Programming language","score_opus":0.04151205478638785,"score_gpt":0.22792922152968717,"score_spread":0.18641716674329933,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2032265428","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":[0.0562548,0.0028188163,0.40844277,0.0012149643,0.0013664204,0.0007327627,0.007913354,0.1498305,0.3714257],"genre_scores_gemma":[0.6030639,0.0015490403,0.17729127,0.0016923329,0.00028945238,0.00037427104,0.015901655,0.005175924,0.19466221],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99947363,0.00005093781,0.000025808167,0.00008160997,0.00027176872,0.00009620939],"domain_scores_gemma":[0.99972624,0.00004343405,0.000015120402,0.0000936061,0.000093497605,0.000028026954],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023180684,0.00087373727,0.0003380194,0.0006082635,0.0002609939,0.0012179473,0.0011853543,0.00043453087,0.0819027],"category_scores_gemma":[0.00061103975,0.00034624684,0.0003104045,0.00046826515,0.00024310997,0.0010011084,0.0005801362,0.0006895524,0.018461771],"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":[0.0020965342,0.00020316489,0.0024651694,0.0007893598,0.00015960196,0.00093594537,0.00018419385,0.025198283,0.06800766,0.046668395,0.3587277,0.49456397],"study_design_scores_gemma":[0.00052686397,0.0006614584,0.0019263861,0.00010269494,0.00009481855,0.001404775,0.00009385144,0.13976562,0.093151785,0.013227296,0.74893016,0.000114259405],"about_ca_topic_score_codex":0.0049879886,"about_ca_topic_score_gemma":0.007233335,"teacher_disagreement_score":0.0819027,"about_ca_system_score_codex":0.00085111253,"about_ca_system_score_gemma":0.00045505402,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W2036224420","doi":"10.1145/1321211.1321231","title":"Window query processing for joining data streams with relations","year":2007,"lang":"en","type":"article","venue":"Proceedings of CASCON","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"IBM (Canada)","funders":"","keywords":"Joins; Computer science; Data stream mining; Query optimization; Semantics (computer science); Focus (optics); Data stream; Process (computing); Sliding window protocol; Database; Window (computing); Distributed computing; Theoretical computer science; Data mining; World Wide Web; Programming language","score_opus":0.033356415506022294,"score_gpt":0.2861722652909604,"score_spread":0.2528158497849381,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2036224420","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":[0.021021118,0.00024673025,0.977093,0.00008962529,0.000038304286,0.000102096936,0.000058143298,0.0006587343,0.00069228065],"genre_scores_gemma":[0.29147014,0.00049168454,0.70522416,0.00009506275,0.00015269301,0.00018393404,0.00059055176,0.00022394795,0.0015678029],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9955428,0.0008456424,0.00046984886,0.0007422014,0.0021436631,0.00025586734],"domain_scores_gemma":[0.9936039,0.0033211056,0.00054004625,0.0012918666,0.0009311465,0.00031207796],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004796027,0.0007692607,0.0011829354,0.0013651612,0.0009829684,0.002396031,0.0018603234,0.00080851885,0.00211925],"category_scores_gemma":[0.014314056,0.00047635738,0.0009672333,0.0023232708,0.00075408764,0.0050025126,0.0020808112,0.001540275,0.0006171253],"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":[0.0028031657,0.00058048905,0.007599423,0.0005777795,0.00021417941,0.0006444305,0.0017558432,0.19581188,0.075381495,0.11335009,0.008510987,0.59277016],"study_design_scores_gemma":[0.00005500945,0.00021985844,0.0005725896,0.000016682738,0.00004281326,0.00025290452,0.00018692487,0.94725317,0.01911801,0.026522707,0.005738415,0.000020872283],"about_ca_topic_score_codex":0.0016924042,"about_ca_topic_score_gemma":0.0015772884,"teacher_disagreement_score":0.004796027,"about_ca_system_score_codex":0.00076307193,"about_ca_system_score_gemma":0.0010827886,"threshold_uncertainty_score":0.025364101},"labels":[],"label_agreement":null},{"id":"W2037018161","doi":"10.4018/jdwm.2006010101","title":"Improved Data Partitioning for Building Large ROLAP Data Cubes in Parallel","year":2006,"lang":"en","type":"article","venue":"International Journal of Data Warehousing and Mining","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University; Carleton University; Dalhousie University","funders":"","keywords":"Computer science; Parallel computing; Speedup; Scalability; Data cube; Data warehouse; Cube (algebra); Representation (politics); Multiprocessing; Materialized view; Online analytical processing; Data structure; External Data Representation; Parallel algorithm; Data mining; Database; Operating system","score_opus":0.07509153115286228,"score_gpt":0.3572573266976316,"score_spread":0.28216579554476934,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2037018161","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":[0.013018137,0.000097551885,0.9841702,0.00007113008,0.000022855058,0.00007307163,0.000092216105,0.001276825,0.0011780214],"genre_scores_gemma":[0.06618385,0.00009087182,0.93156594,0.00004014394,0.000018224173,0.0002018255,0.00064541737,0.00026751333,0.0009862242],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991855,0.00016644571,0.00005308582,0.00012811746,0.00038378447,0.0000830346],"domain_scores_gemma":[0.9992137,0.00024246074,0.00004534511,0.0002625569,0.00020911852,0.00002669935],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005219598,0.0006420029,0.0006471712,0.0007262207,0.00069347885,0.0007445428,0.0014505044,0.00037069956,0.0018232437],"category_scores_gemma":[0.0017031148,0.00042904547,0.00083277904,0.0013784708,0.0005216955,0.00141836,0.0015882289,0.0009279091,0.0008961922],"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":[0.00048137683,0.00025528503,0.0016936775,0.000369519,0.00013186153,0.00041149298,0.0006680161,0.26406026,0.08053403,0.026234435,0.013650949,0.6115091],"study_design_scores_gemma":[0.0001314466,0.00011793836,0.0005297424,0.000013976208,0.000041656698,0.00027290164,0.00015050793,0.91526544,0.048612397,0.016172519,0.018649269,0.000042259384],"about_ca_topic_score_codex":0.0032896914,"about_ca_topic_score_gemma":0.0043121036,"teacher_disagreement_score":0.0032896914,"about_ca_system_score_codex":0.0004391073,"about_ca_system_score_gemma":0.00080420583,"threshold_uncertainty_score":0.0065410733},"labels":[],"label_agreement":null},{"id":"W2039389988","doi":"10.1007/s10959-007-0063-4","title":"Optimal Policies to Obtain the Most Join Results","year":2007,"lang":"en","type":"article","venue":"Journal of Theoretical Probability","topic":"Advanced Database Systems and Queries","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":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Join (topology); Probabilistic logic; Mathematics; Carry (investment); Object (grammar); Sample (material); Order (exchange); Integer (computer science); Discrete mathematics; Mathematical optimization; Combinatorics; Computer science; Statistics; Artificial intelligence","score_opus":0.016192202842402217,"score_gpt":0.2839616636669836,"score_spread":0.2677694608245814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2039389988","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":[0.23440693,0.0026721957,0.7257647,0.0134834135,0.00061174016,0.0007264255,0.0011772836,0.0048760925,0.016281297],"genre_scores_gemma":[0.7843885,0.00091633125,0.20793542,0.0014498688,0.00060264004,0.00041678676,0.0006911428,0.00073887967,0.0028605657],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99237883,0.0033413516,0.00055797485,0.001196976,0.0010185592,0.0015063081],"domain_scores_gemma":[0.93240666,0.051717833,0.001817074,0.008837526,0.0026467522,0.0025741511],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009655363,0.0017486804,0.0037059865,0.0032721425,0.0029459596,0.005181878,0.0031461439,0.0048504774,0.008864083],"category_scores_gemma":[0.060941633,0.0018274733,0.0017133566,0.0025399898,0.0030141112,0.008751633,0.00324171,0.005344323,0.0020090607],"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":[0.011362362,0.0041961977,0.013800776,0.0019235783,0.00083366403,0.0005713962,0.0016443637,0.29412326,0.033100452,0.33837909,0.05621851,0.24384634],"study_design_scores_gemma":[0.0009048833,0.00040435107,0.0011716706,0.00012102344,0.00024382723,0.00031276196,0.00050059886,0.59262973,0.016453667,0.3838697,0.0033030452,0.00008477862],"about_ca_topic_score_codex":0.00075208175,"about_ca_topic_score_gemma":0.0013566053,"teacher_disagreement_score":0.009655363,"about_ca_system_score_codex":0.002528267,"about_ca_system_score_gemma":0.0054821,"threshold_uncertainty_score":0.051063},"labels":[],"label_agreement":null},{"id":"W2040374677","doi":"10.1007/s00778-002-0081-x","title":"TIMBER: A native XML database","year":2002,"lang":"en","type":"article","venue":"The VLDB Journal","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":408,"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 British Columbia; University of British Columbia Hospital","funders":"","keywords":"Computer science; XPath; XML database; Streaming XML; XML validation; Efficient XML Interchange; XML Schema Editor; XML Encryption; Database; Query optimization; XML Schema (W3C); Information retrieval; XML; XML Signature; Document Structure Description; Rewriting; Relational database; Programming language; World Wide Web","score_opus":0.02968092915324465,"score_gpt":0.24349118944614273,"score_spread":0.21381026029289807,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2040374677","genre_codex":"software","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":[0.015473803,0.0011891719,0.3010935,0.0009803518,0.0007352425,0.0005334383,0.02184816,0.60033053,0.05781583],"genre_scores_gemma":[0.19683675,0.0022569122,0.39191404,0.0029009588,0.0005460267,0.0010649745,0.14005914,0.106766865,0.15765427],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989785,0.00011435006,0.00014141723,0.00018629052,0.0004653207,0.00011420033],"domain_scores_gemma":[0.9983242,0.00031779514,0.00007606765,0.00068349985,0.00039661667,0.00020179339],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001711137,0.00091522874,0.0008096745,0.0016800401,0.00081985036,0.0029518509,0.0033356862,0.0011155099,0.041982993],"category_scores_gemma":[0.0041506425,0.0009285269,0.0006353547,0.0017573026,0.00067813107,0.0051895455,0.0026393612,0.0015912486,0.026769951],"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":[0.0013673331,0.00041467423,0.0027853032,0.0007249621,0.00013691175,0.000646078,0.0005836682,0.002747043,0.028063811,0.035970483,0.629412,0.29714775],"study_design_scores_gemma":[0.0007072585,0.0002653515,0.0030055721,0.00018764487,0.00019598717,0.0014446724,0.0004483227,0.049103215,0.041971777,0.04970949,0.8527276,0.00023311705],"about_ca_topic_score_codex":0.0028970826,"about_ca_topic_score_gemma":0.003936544,"teacher_disagreement_score":0.041982993,"about_ca_system_score_codex":0.00047863182,"about_ca_system_score_gemma":0.0013399178,"threshold_uncertainty_score":0.14044708},"labels":[],"label_agreement":null},{"id":"W2040900238","doi":"10.4018/jdwm.2013040105","title":"An Envisioned Approach for Modeling and Supporting User-Centric Query Activities on Data Warehouses","year":2013,"lang":"en","type":"article","venue":"International Journal of Data Warehousing and Mining","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Computer science; Data warehouse; Online analytical processing; Metadata; Ontology; Information retrieval; Exploit; Knowledge extraction; Query optimization; Data mining; Data science; Database; World Wide Web","score_opus":0.09383134873528128,"score_gpt":0.3502786813204296,"score_spread":0.25644733258514835,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2040900238","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":[0.0023962269,0.0001814265,0.99288756,0.00090139813,0.000045911675,0.00015483254,0.00010787521,0.0009935311,0.0023312762],"genre_scores_gemma":[0.06582862,0.00047166712,0.9303591,0.00031897434,0.00008430107,0.00032149372,0.0003590356,0.00013232729,0.0021244676],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9948067,0.0017966189,0.0006697347,0.0009477164,0.0013624307,0.00041677678],"domain_scores_gemma":[0.9961618,0.0008643914,0.00022583528,0.0014792874,0.0008765207,0.00039218002],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009373072,0.0010584454,0.0010356092,0.0017686615,0.0014108724,0.010941811,0.0069570425,0.004270458,0.0024283817],"category_scores_gemma":[0.0067930515,0.0015207271,0.0026420876,0.0026869273,0.0030418395,0.01199247,0.0041209557,0.003159067,0.0013816126],"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":[0.00016065793,0.00029521505,0.001955799,0.00035493117,0.00015016567,0.0004706816,0.002735237,0.0695895,0.006601247,0.8610332,0.006085456,0.0505679],"study_design_scores_gemma":[0.00006722405,0.00018676766,0.00031768068,0.00020384052,0.00013633924,0.00034321737,0.0007206319,0.5640098,0.005820057,0.32672504,0.101361185,0.00010824127],"about_ca_topic_score_codex":0.005320027,"about_ca_topic_score_gemma":0.004906735,"teacher_disagreement_score":0.010941811,"about_ca_system_score_codex":0.002014504,"about_ca_system_score_gemma":0.0033266353,"threshold_uncertainty_score":0.049570143},"labels":[],"label_agreement":null},{"id":"W2041019860","doi":"10.1007/s10270-008-0104-1","title":"Generating relational database transactions from eb 3 attribute definitions","year":2008,"lang":"en","type":"article","venue":"Software & Systems Modeling","topic":"Advanced Database Systems and Queries","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":"Université de Sherbrooke","funders":"","keywords":"Computer science; Executable; SQL; TRACE (psycholinguistics); Programming language; Database transaction; Relational database; Representation (politics); Implementation; Function (biology); Database; Database design; Theoretical computer science","score_opus":0.10714857610450189,"score_gpt":0.24932410924979784,"score_spread":0.14217553314529596,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2041019860","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":[0.07970037,0.00028644054,0.89280117,0.00043235396,0.0001857656,0.0003966591,0.002348137,0.015456104,0.008392943],"genre_scores_gemma":[0.42697427,0.00026343914,0.5575455,0.00016447024,0.00007645871,0.00028410146,0.0069778403,0.002361226,0.0053527085],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982797,0.0003779339,0.00013469468,0.00027525765,0.0007607461,0.00017167555],"domain_scores_gemma":[0.9952285,0.0025978058,0.00018583403,0.0008737541,0.0010237593,0.00009041941],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012449323,0.00062466913,0.000630762,0.0012237862,0.000433863,0.0019876645,0.001559077,0.0009966148,0.009273637],"category_scores_gemma":[0.010447649,0.00067874236,0.0015255662,0.0017150727,0.00061308406,0.0023341142,0.0021198087,0.0013138521,0.0029728212],"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":[0.0015246986,0.00041551984,0.008704979,0.0010963841,0.00019813242,0.0016701592,0.0014466116,0.1137234,0.054269835,0.11742912,0.037173904,0.6623473],"study_design_scores_gemma":[0.00022904664,0.0003274443,0.0021363974,0.00012830645,0.00015173487,0.000660873,0.00081815576,0.7640589,0.08512794,0.112134926,0.03415157,0.000074726384],"about_ca_topic_score_codex":0.001461107,"about_ca_topic_score_gemma":0.0024195933,"teacher_disagreement_score":0.009273637,"about_ca_system_score_codex":0.00059146364,"about_ca_system_score_gemma":0.0009905555,"threshold_uncertainty_score":0.031023443},"labels":[],"label_agreement":null},{"id":"W2041764830","doi":"10.1109/icisa.2010.5480393","title":"Tree Reconstruction and Bottom-Up Evaluation of Tree Pattern Queries","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Computer science; XML; Tree (set theory); Theoretical computer science; Node (physics); Bounded function; Algorithm; Combinatorics; Information retrieval; Data mining; Mathematics; World Wide Web","score_opus":0.022194560183305977,"score_gpt":0.2712666110137672,"score_spread":0.24907205083046122,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2041764830","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":[0.056785665,0.00078340824,0.9134739,0.0005880646,0.00013343645,0.00038765435,0.0012879011,0.01751453,0.00904543],"genre_scores_gemma":[0.3492392,0.00037566535,0.63456297,0.0004014475,0.00006850132,0.00029500487,0.0051095793,0.001466602,0.008481034],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99680567,0.0004808494,0.00023320937,0.00048944657,0.001544155,0.00044660943],"domain_scores_gemma":[0.9973226,0.0009873549,0.00013584155,0.00064504234,0.0007944954,0.00011458733],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009878931,0.00093602284,0.0012342017,0.0016250482,0.00075868086,0.0027086383,0.0021392573,0.0012472103,0.00827805],"category_scores_gemma":[0.0067274612,0.0005868157,0.0011928264,0.0024339117,0.000835485,0.0049247537,0.0027946664,0.001225951,0.0033532018],"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":[0.0018420517,0.00041522304,0.0045212833,0.00063450745,0.00011305941,0.0008673085,0.0006984203,0.054521997,0.064620584,0.05467276,0.03245558,0.7846372],"study_design_scores_gemma":[0.00013981093,0.0002465903,0.0010831787,0.00007520636,0.0000758851,0.00044901454,0.0003716851,0.8714754,0.056993704,0.051574636,0.017446568,0.00006830196],"about_ca_topic_score_codex":0.0049684644,"about_ca_topic_score_gemma":0.0051210634,"teacher_disagreement_score":0.00827805,"about_ca_system_score_codex":0.0013037882,"about_ca_system_score_gemma":0.0017249582,"threshold_uncertainty_score":0.027692795},"labels":[],"label_agreement":null},{"id":"W2042315498","doi":"10.1145/581751.581752","title":"Searching for dependencies at multiple abstraction levels","year":2002,"lang":"en","type":"article","venue":"ACM Transactions on Database Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Functional dependency; Dependency (UML); Tuple; Online analytical processing; Dependency theory (database theory); Generalization; Abstraction; Scope (computer science); Data mining; Extension (predicate logic); Theoretical computer science; Database; Data warehouse; Relational database; Artificial intelligence; Programming language","score_opus":0.09694704259971397,"score_gpt":0.2879969122087368,"score_spread":0.19104986960902282,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2042315498","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":[0.29665953,0.0005798722,0.6925,0.00059160957,0.000033789227,0.00018875186,0.0018381963,0.0038118928,0.0037963416],"genre_scores_gemma":[0.7284258,0.0002298157,0.26670104,0.00011344503,0.00002280193,0.000087460445,0.0025494357,0.00019027208,0.00168001],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99852175,0.00018844106,0.00011762486,0.00036820048,0.0005274123,0.00027655886],"domain_scores_gemma":[0.99395156,0.0032364035,0.00062897796,0.0010570455,0.00086342485,0.00026266693],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014630222,0.0006634902,0.0007590489,0.0031319268,0.0012602,0.0014684391,0.0011683278,0.0008536466,0.002637543],"category_scores_gemma":[0.009311095,0.00078402204,0.0012519724,0.0017216491,0.0006713869,0.0038950837,0.0022272577,0.0014495861,0.0005226152],"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":[0.0008020498,0.00044229496,0.11373778,0.0008394884,0.00031726874,0.0032343115,0.0023241572,0.09193343,0.039309334,0.07596149,0.0128951315,0.6582033],"study_design_scores_gemma":[0.000044965298,0.0003082459,0.029141728,0.00017063605,0.0003204052,0.001496567,0.00105286,0.71309793,0.035868064,0.2005826,0.017787384,0.0001286964],"about_ca_topic_score_codex":0.004696145,"about_ca_topic_score_gemma":0.0077070603,"teacher_disagreement_score":0.004696145,"about_ca_system_score_codex":0.00069668697,"about_ca_system_score_gemma":0.0014138488,"threshold_uncertainty_score":0.009337604},"labels":[],"label_agreement":null},{"id":"W2042832124","doi":"10.1145/1361348.1361361","title":"Report on the First International Workshop on Ranking in Databases (DBRank'07)","year":2007,"lang":"en","type":"article","venue":"ACM SIGMOD Record","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Conjunction (astronomy); Ranking (information retrieval); Computer science; Database; World Wide Web; Information retrieval","score_opus":0.047223779236043414,"score_gpt":0.3079342729547288,"score_spread":0.2607104937186854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2042832124","genre_codex":"editorial","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":[0.014520988,0.08783008,0.26955542,0.10492078,0.2729503,0.0040705223,0.040776882,0.013563609,0.19181144],"genre_scores_gemma":[0.02419565,0.053649098,0.14657575,0.020539163,0.055474397,0.002247497,0.1228731,0.009033751,0.56541157],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9862146,0.004322113,0.0006615027,0.0016600188,0.005911164,0.0012305368],"domain_scores_gemma":[0.97160125,0.0051577585,0.0006521276,0.003245155,0.013159515,0.0061841584],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.019319301,0.0027524356,0.0034426257,0.004156297,0.0019223253,0.009959702,0.0029487312,0.0031269987,0.11849425],"category_scores_gemma":[0.022399683,0.0010010907,0.0021710857,0.0052142777,0.0010107644,0.010023492,0.006838918,0.007033009,0.08831723],"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":[0.00014490714,0.00019105447,0.00026467597,0.00020424117,0.000031274412,0.000052269952,0.00007996849,0.00036353196,0.00070271443,0.002142701,0.9227117,0.07311101],"study_design_scores_gemma":[0.00009291042,0.00021902741,0.0010443738,0.00024816403,0.0000611305,0.00015832079,0.0002128303,0.001632365,0.0016202003,0.0048833424,0.98976433,0.000063130385],"about_ca_topic_score_codex":0.005631926,"about_ca_topic_score_gemma":0.008499938,"teacher_disagreement_score":0.11849425,"about_ca_system_score_codex":0.0021317443,"about_ca_system_score_gemma":0.0048476933,"threshold_uncertainty_score":0.39640272},"labels":[],"label_agreement":null},{"id":"W2043353936","doi":"10.5555/381473.381639","title":"3/sup rd/ international workshop on net-centric computing (NCC 2001) Theme: migrating to the Web","year":2001,"lang":"en","type":"article","venue":"International Conference on Software Engineering","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; University of Alberta; University of Victoria","funders":"","keywords":"Business process reengineering; Theme (computing); Computer science; Focus (optics); Software engineering; User interface; World Wide Web; Legacy system; Modernization theory; Interface (matter); Process (computing); Engineering; Operating system; Software","score_opus":0.030852102244929305,"score_gpt":0.2780941211667981,"score_spread":0.2472420189218688,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2043353936","genre_codex":"methods","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":[0.03879072,0.024358973,0.48126534,0.06434361,0.060729098,0.0014613358,0.0015704661,0.0050211707,0.32245922],"genre_scores_gemma":[0.09087036,0.013567394,0.15365528,0.008174988,0.006610922,0.00063909293,0.0044084396,0.0018624569,0.72021115],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982309,0.00047744976,0.00011324863,0.0002808212,0.0006649374,0.00023267468],"domain_scores_gemma":[0.9961681,0.000697659,0.00010531076,0.00046132455,0.0016472416,0.0009203348],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005033653,0.0010250757,0.000752285,0.0010812351,0.0018992128,0.0071914415,0.0017458302,0.0028748342,0.03730856],"category_scores_gemma":[0.0040130597,0.00059346826,0.0007465592,0.0010764443,0.0011534957,0.0054344507,0.002411122,0.0039701858,0.013377554],"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":[0.00048417176,0.0002833051,0.0012062988,0.00034667263,0.000044668974,0.0005179802,0.0010055471,0.0019063269,0.010621531,0.03622206,0.5874136,0.35994777],"study_design_scores_gemma":[0.00005775184,0.0001695693,0.0012081898,0.0003426838,0.000038944774,0.0004637803,0.0005111104,0.01152204,0.0054285624,0.010131879,0.9700824,0.00004301176],"about_ca_topic_score_codex":0.008229565,"about_ca_topic_score_gemma":0.016477956,"teacher_disagreement_score":0.03730856,"about_ca_system_score_codex":0.0020749746,"about_ca_system_score_gemma":0.0031438952,"threshold_uncertainty_score":0.1248095},"labels":[],"label_agreement":null},{"id":"W2045841926","doi":"10.1016/s0890-5401(03)00017-8","title":"Incremental recomputation in local languages","year":2003,"lang":"en","type":"article","venue":"Information and Computation","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":21,"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":"Recursion (computer science); Computer science; Transitive closure; Closure (psychology); Property (philosophy); Impossibility; Locality; Relation (database); SQL; Transitive relation; Theoretical computer science; Aggregate (composite); Programming language; Mathematics; Discrete mathematics; Linguistics; Database; Combinatorics","score_opus":0.008492860012480948,"score_gpt":0.25872772695770957,"score_spread":0.2502348669452286,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045841926","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":[0.11719739,0.0010858322,0.8396054,0.0011699894,0.0001997173,0.00024023009,0.00061744574,0.0220681,0.017815936],"genre_scores_gemma":[0.62735873,0.0003525261,0.35064602,0.0004825867,0.00014302472,0.00029080425,0.0011524588,0.0038031272,0.015770813],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9948137,0.0017936528,0.00039324816,0.0006621015,0.0015849231,0.0007523995],"domain_scores_gemma":[0.97526383,0.011710326,0.0005872717,0.010388353,0.0015536714,0.00049654883],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0048042503,0.00082307233,0.001659635,0.0013678578,0.0019832293,0.004635688,0.0043274835,0.0013568837,0.013061224],"category_scores_gemma":[0.024551734,0.0012829835,0.0013280628,0.0029158234,0.00306971,0.013120987,0.006577821,0.002840217,0.0021948854],"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":[0.0024901864,0.00046846256,0.003997976,0.00083156396,0.0001708094,0.0007100294,0.0035523435,0.066707544,0.015583419,0.45424575,0.02792773,0.42331424],"study_design_scores_gemma":[0.0003908038,0.00018410166,0.00059725327,0.000102754726,0.0003008622,0.00032159188,0.0007751376,0.4630667,0.03380073,0.4748942,0.025458656,0.00010712493],"about_ca_topic_score_codex":0.0044848514,"about_ca_topic_score_gemma":0.0077170404,"teacher_disagreement_score":0.013061224,"about_ca_system_score_codex":0.0018123371,"about_ca_system_score_gemma":0.0021282446,"threshold_uncertainty_score":0.04369414},"labels":[],"label_agreement":null},{"id":"W2046619512","doi":"10.1016/j.ic.2004.07.003","title":"Towards an algebraic theory of information integration","year":2004,"lang":"en","type":"article","venue":"Information and Computation","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":15,"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; Algebraic number; Algebra over a field; Algebraic theory; Theoretical computer science; Calculus (dental); Mathematics; Pure mathematics","score_opus":0.01085730189325719,"score_gpt":0.24946845794978648,"score_spread":0.23861115605652927,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2046619512","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":[0.008413746,0.0019816535,0.95388675,0.004747496,0.0003687856,0.000051480212,0.00016668315,0.00026365925,0.030119766],"genre_scores_gemma":[0.33951962,0.004521733,0.63423306,0.002017439,0.002124922,0.0003532572,0.000553483,0.00026892003,0.01640746],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99676895,0.0011462496,0.000282696,0.0004939625,0.0010737347,0.00023445176],"domain_scores_gemma":[0.9958246,0.0018998809,0.00030710164,0.00075440307,0.00097494194,0.0002390203],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0043354747,0.00092682225,0.0013144573,0.0036904255,0.003014879,0.008552858,0.00292212,0.0022288137,0.0052852333],"category_scores_gemma":[0.008699295,0.0012494059,0.0022380766,0.0043051643,0.010481136,0.02101252,0.005367999,0.0064630215,0.0012302236],"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":[0.0000030087565,0.0000046348564,0.000032597094,0.0000132453615,0.000003024966,0.00001113882,0.00006284404,0.00045650156,0.00004167021,0.99709356,0.00045623147,0.0018214684],"study_design_scores_gemma":[0.0000047455696,0.0000034380348,0.0000176992,0.000008403508,0.000004539271,0.000020697533,0.000025881072,0.0035651904,0.000047359375,0.9925585,0.0037391034,0.000004434787],"about_ca_topic_score_codex":0.0028180773,"about_ca_topic_score_gemma":0.002480721,"teacher_disagreement_score":0.008552858,"about_ca_system_score_codex":0.0034617386,"about_ca_system_score_gemma":0.0021232844,"threshold_uncertainty_score":0.025116742},"labels":[],"label_agreement":null},{"id":"W2046904770","doi":"10.1016/s0306-4379(01)00054-0","title":"One-pass evaluation of region algebra expressions","year":2003,"lang":"en","type":"article","venue":"Information Systems","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Computer science; Operator (biology); Set (abstract data type); Simple (philosophy); Tree (set theory); Algorithm; Theoretical computer science; Algebra over a field; Programming language; Mathematics","score_opus":0.05425727120654508,"score_gpt":0.28254411237563026,"score_spread":0.22828684116908518,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2046904770","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":[0.08936387,0.000846025,0.8440689,0.0004295894,0.0002837818,0.00024937006,0.0007193638,0.013227869,0.05081132],"genre_scores_gemma":[0.66897064,0.0006122941,0.27086267,0.0003156308,0.00019920335,0.00015115966,0.0013596393,0.0053086937,0.052220143],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99716944,0.00053473236,0.00014809651,0.00041506818,0.0011592185,0.0005733658],"domain_scores_gemma":[0.9970306,0.0012061164,0.00015443134,0.0007553387,0.0007591929,0.00009430543],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024789176,0.0008546811,0.0011886746,0.0008652375,0.0009860975,0.0033125912,0.0020313999,0.0009422999,0.016997369],"category_scores_gemma":[0.0059226635,0.0005682213,0.0013007784,0.0011102558,0.0015292102,0.0060312375,0.0027480312,0.0010729653,0.003820585],"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":[0.0018553166,0.00022831734,0.0022029697,0.0009826524,0.00019835835,0.00080423214,0.0019209394,0.018955505,0.046596497,0.6153318,0.022251999,0.28867137],"study_design_scores_gemma":[0.00021803378,0.000411561,0.0014958235,0.00020086885,0.00045203915,0.00075008435,0.0007588132,0.1419546,0.23825125,0.53517723,0.08009383,0.00023592392],"about_ca_topic_score_codex":0.002252501,"about_ca_topic_score_gemma":0.0026289006,"teacher_disagreement_score":0.016997369,"about_ca_system_score_codex":0.0013901369,"about_ca_system_score_gemma":0.0012160253,"threshold_uncertainty_score":0.056861877},"labels":[],"label_agreement":null},{"id":"W2046909321","doi":"10.1145/1557626.1557634","title":"XPath query evaluation based on the stack encoding","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Computer science; Twig; XPath; Encoding (memory); Tree (set theory); Query optimization; Pruning; XML; Theoretical computer science; Pattern matching; Set (abstract data type); Redundancy (engineering); Data mining; Algorithm; Mathematics; XML database; Artificial intelligence","score_opus":0.04041330200351174,"score_gpt":0.2887081794239154,"score_spread":0.24829487742040368,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2046909321","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":[0.18371315,0.001295342,0.7821832,0.0005258342,0.000097292184,0.00038289782,0.0016431912,0.017408296,0.01275073],"genre_scores_gemma":[0.5802501,0.00069140794,0.40458032,0.00021966573,0.00007470835,0.00030508413,0.004204243,0.0012336081,0.00844099],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99826115,0.00033584132,0.00014602902,0.00018836942,0.0008837092,0.00018492449],"domain_scores_gemma":[0.9981775,0.00084809115,0.00007343257,0.0003869562,0.00046964205,0.000044333407],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013953567,0.0008339647,0.0009049541,0.0013912176,0.00059735443,0.0020522734,0.0012901218,0.0007535259,0.0053615384],"category_scores_gemma":[0.0041706543,0.00035952474,0.00053821516,0.0018638534,0.0005969771,0.005232903,0.0017128803,0.00093723246,0.0009705025],"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":[0.0042208526,0.0004421661,0.0052863155,0.0005520249,0.00015751595,0.0007331921,0.0006451142,0.050193995,0.069413885,0.052379064,0.026147295,0.78982854],"study_design_scores_gemma":[0.00034727427,0.00049974176,0.0022125132,0.000053952754,0.00012607295,0.0007209414,0.00039665942,0.8399264,0.1062381,0.03445547,0.014935668,0.000087202025],"about_ca_topic_score_codex":0.0037380795,"about_ca_topic_score_gemma":0.0024630341,"teacher_disagreement_score":0.0053615384,"about_ca_system_score_codex":0.00097319414,"about_ca_system_score_gemma":0.0010065056,"threshold_uncertainty_score":0.01793611},"labels":[],"label_agreement":null},{"id":"W2047502228","doi":"10.1016/j.jcss.2007.03.002","title":"View disassembly: A rewrite that extracts portions of views","year":2007,"lang":"en","type":"article","venue":"Journal of Computer and System Sciences","topic":"Advanced Database Systems and Queries","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":"York University","funders":"","keywords":"Computer science; Class (philosophy); Theoretical computer science; Task (project management); Cover (algebra); Cache; Materialized view; Matching (statistics); Table (database); Information retrieval; Artificial intelligence; Database; Mathematics; View; Parallel computing","score_opus":0.053639016463828626,"score_gpt":0.31413215651623083,"score_spread":0.2604931400524022,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2047502228","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":[0.019214163,0.0006668823,0.8362558,0.00045068856,0.0005634474,0.00049721147,0.003887656,0.12552129,0.012942852],"genre_scores_gemma":[0.17926782,0.0009028032,0.69960946,0.0012672113,0.00035643342,0.0003897488,0.015308427,0.0811729,0.021725222],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9977309,0.00030962998,0.0002489283,0.00045682339,0.0010007267,0.00025301237],"domain_scores_gemma":[0.9942368,0.0023253283,0.0002522283,0.0021634626,0.00085441564,0.00016768218],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013513506,0.0022975435,0.001718771,0.0016681603,0.0008052691,0.0025898744,0.0025917683,0.0017005961,0.015080063],"category_scores_gemma":[0.008658045,0.002116793,0.0022445119,0.0013339511,0.0012255196,0.005003581,0.0036219505,0.0028568057,0.006318441],"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":[0.0015050238,0.00045099916,0.004852667,0.0018259432,0.0005018797,0.0025477395,0.0027010795,0.006277617,0.117052175,0.0405992,0.22875947,0.59292626],"study_design_scores_gemma":[0.00048068582,0.00052041246,0.0037983826,0.00049491914,0.0010342438,0.00233925,0.0017659134,0.1173732,0.35337088,0.073550075,0.44480163,0.00047043734],"about_ca_topic_score_codex":0.004688462,"about_ca_topic_score_gemma":0.006126485,"teacher_disagreement_score":0.015080063,"about_ca_system_score_codex":0.00053935853,"about_ca_system_score_gemma":0.001462394,"threshold_uncertainty_score":0.05044782},"labels":[],"label_agreement":null},{"id":"W2048330777","doi":"10.1145/1111322.1111338","title":"Efficient and decentralized computation of approximate global state","year":2006,"lang":"en","type":"article","venue":"ACM SIGCOMM Computer Communication Review","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Robustness (evolution); Distributed computing; Computation; The Internet; Overhead (engineering); State (computer science); Algorithm","score_opus":0.015675238980428035,"score_gpt":0.28434182205246455,"score_spread":0.2686665830720365,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2048330777","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":[0.013025698,0.00018784314,0.9834495,0.00027386876,0.000043719116,0.000032685883,0.00007560298,0.00082053157,0.0020905104],"genre_scores_gemma":[0.73086435,0.00036945243,0.2655886,0.00013758677,0.00012137568,0.00019257012,0.00040491985,0.00021453819,0.0021066058],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99776614,0.00056760927,0.00013427202,0.0005077648,0.000824263,0.00019992168],"domain_scores_gemma":[0.99365836,0.0028388265,0.0005716123,0.0019919034,0.00077266194,0.00016661349],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023886645,0.00058746344,0.0014603204,0.0009825461,0.00096834486,0.0025506248,0.0020258971,0.0011800318,0.0019287734],"category_scores_gemma":[0.013036113,0.00064967683,0.0005337353,0.0010712086,0.0015816785,0.0043312698,0.002883825,0.0016958913,0.0006147947],"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":[0.0003278572,0.00009909263,0.0016333788,0.00012469057,0.00008179763,0.00009957577,0.00018381418,0.7861468,0.010396934,0.09044391,0.0038378169,0.10662433],"study_design_scores_gemma":[0.00002447661,0.000028403763,0.0001899264,0.00000639266,0.000009749112,0.000023793284,0.000026470168,0.96300626,0.002298727,0.033371754,0.0010036385,0.000010325346],"about_ca_topic_score_codex":0.0018332335,"about_ca_topic_score_gemma":0.002634112,"teacher_disagreement_score":0.0025506248,"about_ca_system_score_codex":0.0012019079,"about_ca_system_score_gemma":0.0017861079,"threshold_uncertainty_score":0.012632668},"labels":[],"label_agreement":null},{"id":"W2049257988","doi":"10.1145/2389686.2389693","title":"Exploring and analyzing documents with OLAP","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; University of Waterloo","keywords":"Online analytical processing; Computer science; Cluster (spacecraft); Information retrieval; Centroid; Data science; Data mining; World Wide Web; Data warehouse; Artificial intelligence","score_opus":0.06807361504051525,"score_gpt":0.25635729386357753,"score_spread":0.1882836788230623,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2049257988","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":[0.0563823,0.0017294679,0.91758823,0.001154731,0.00009216222,0.0008858051,0.0053741965,0.010551841,0.006241211],"genre_scores_gemma":[0.09400736,0.0009299414,0.8981354,0.000121342586,0.000053922427,0.00032845247,0.004865313,0.0003660148,0.0011923104],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99435633,0.0013055871,0.0007694337,0.0008507933,0.0023953156,0.0003226197],"domain_scores_gemma":[0.9917468,0.0032092945,0.0007931465,0.0018665707,0.0019855232,0.00039867894],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034241083,0.0019820961,0.0015008164,0.014223963,0.0023960082,0.00858911,0.002206154,0.0010072965,0.002164535],"category_scores_gemma":[0.013213368,0.00075339014,0.0015143818,0.022132318,0.0010228865,0.006524418,0.0044751875,0.0014390012,0.0019740665],"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":[0.0005327534,0.00039030972,0.015149171,0.001662572,0.00052864576,0.001400392,0.0057942257,0.025236383,0.020384159,0.014669881,0.017061146,0.8971904],"study_design_scores_gemma":[0.000098574295,0.0003247842,0.015508352,0.0005220432,0.000476739,0.002621093,0.020616038,0.57349265,0.056701083,0.19755742,0.13169964,0.00038170008],"about_ca_topic_score_codex":0.0066844397,"about_ca_topic_score_gemma":0.008996862,"teacher_disagreement_score":0.014223963,"about_ca_system_score_codex":0.0009906533,"about_ca_system_score_gemma":0.0023397985,"threshold_uncertainty_score":0.018108606},"labels":[],"label_agreement":null},{"id":"W2050021969","doi":"10.1142/s0218843000000144","title":"SUPPORTING DISTRIBUTED AUTONOMOUS INFORMATION SERVICES USING COORDINATION","year":2000,"lang":"en","type":"article","venue":"International Journal of Cooperative Information Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Architecture; Information system; Information quality; Information flow; Information architecture; Conceptual architecture; Quality (philosophy); Process (computing); Services computing; Information model; Software engineering; Knowledge management; Management information systems; World Wide Web; Web service","score_opus":0.010122640658273311,"score_gpt":0.2845225062339726,"score_spread":0.27439986557569934,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2050021969","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":[0.02939705,0.00035362932,0.9478847,0.0010352863,0.000096722164,0.0004899094,0.00009421382,0.0062099495,0.01443851],"genre_scores_gemma":[0.5245837,0.0005898837,0.4665826,0.0003639407,0.00013406177,0.00054810103,0.00054794835,0.00043590055,0.0062138843],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9961708,0.0013381044,0.00034122748,0.0006030685,0.0010943637,0.00045246942],"domain_scores_gemma":[0.99591786,0.0017494317,0.00032327056,0.0010522052,0.0005517929,0.0004053913],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0044673113,0.0008393143,0.0007139665,0.00087571045,0.0019460078,0.005206942,0.0024704929,0.0015755186,0.0020946686],"category_scores_gemma":[0.007873313,0.0005822906,0.0005902228,0.0012710571,0.0017931655,0.004037368,0.0046065035,0.0014883782,0.0009073763],"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":[0.0008834352,0.0005687767,0.0054132114,0.000707521,0.00018148465,0.0016592854,0.0044894135,0.121297896,0.041172292,0.48718238,0.024550578,0.3118938],"study_design_scores_gemma":[0.00044968267,0.00023601415,0.0009217878,0.00013064315,0.00014333463,0.0005747852,0.0006815784,0.69441795,0.02136872,0.15972391,0.12122097,0.0001305765],"about_ca_topic_score_codex":0.007381496,"about_ca_topic_score_gemma":0.0035395187,"teacher_disagreement_score":0.007381496,"about_ca_system_score_codex":0.0013547783,"about_ca_system_score_gemma":0.0032156329,"threshold_uncertainty_score":0.023625672},"labels":[],"label_agreement":null},{"id":"W2050265418","doi":"10.1145/1804669.1804698","title":"Data correspondence, exchange and repair","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Homomorphism; Computer science; Tuple; Data exchange; Generalization; Functional dependency; Class (philosophy); Theoretical computer science; Perspective (graphical); Database; Relational database; Mathematics; Discrete mathematics; Artificial intelligence","score_opus":0.03235578818536942,"score_gpt":0.28570564193136516,"score_spread":0.2533498537459957,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2050265418","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":[0.034900278,0.00012805326,0.95825475,0.0009936083,0.000052484185,0.00026571387,0.00044836098,0.0008837301,0.0040730713],"genre_scores_gemma":[0.47607604,0.00021227144,0.5157924,0.00041164455,0.00010602202,0.0005549845,0.0010716952,0.00029369575,0.00548119],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98901623,0.003519098,0.0011742694,0.002497801,0.003086653,0.0007059869],"domain_scores_gemma":[0.9599772,0.0202516,0.0022632806,0.014381719,0.002474803,0.0006513907],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010176433,0.0006849497,0.0012648393,0.0012127183,0.0019969,0.003941479,0.0033288258,0.0021683995,0.004581682],"category_scores_gemma":[0.043252867,0.00082323473,0.0017855272,0.0017558134,0.0043598767,0.014448002,0.005958896,0.0032314567,0.001067103],"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":[0.00029217676,0.00017266351,0.0037938945,0.00031487708,0.00006513223,0.00043024027,0.00089679734,0.03203735,0.00442675,0.86317736,0.0034802796,0.09091245],"study_design_scores_gemma":[0.000053849057,0.00016721073,0.0006283977,0.00006633902,0.0000644361,0.0007034241,0.0005649305,0.12711655,0.019237572,0.82833296,0.02300732,0.000057041234],"about_ca_topic_score_codex":0.0016364402,"about_ca_topic_score_gemma":0.0012395728,"teacher_disagreement_score":0.010176433,"about_ca_system_score_codex":0.0018052422,"about_ca_system_score_gemma":0.0042567533,"threshold_uncertainty_score":0.053818762},"labels":[],"label_agreement":null},{"id":"W2052341104","doi":"10.1108/10650750210430169","title":"XML and relational databases: uses and opportunities for libraries","year":2002,"lang":"en","type":"article","venue":"OCLC Systems & Services","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Relational database management system; Computer science; XML; XML database; Relational database; Database; XML Schema Editor; World Wide Web","score_opus":0.10383659856904978,"score_gpt":0.25033140704206114,"score_spread":0.14649480847301136,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2052341104","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":[0.0073365397,0.41183728,0.18366012,0.17998365,0.0052166986,0.0001523298,0.00068292563,0.0068522687,0.20427822],"genre_scores_gemma":[0.0774494,0.47589535,0.28679082,0.027168093,0.027752182,0.000296938,0.0017167385,0.0025809582,0.1003496],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9925694,0.0035437162,0.000650873,0.0006678959,0.0021366635,0.00043138932],"domain_scores_gemma":[0.9802377,0.009241669,0.0010043171,0.003203125,0.0035757185,0.0027373726],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01677947,0.0007973277,0.0009365794,0.005551925,0.0018800183,0.017181838,0.0032468645,0.00447788,0.016427115],"category_scores_gemma":[0.015551691,0.000958395,0.0010396835,0.010278395,0.004861291,0.053683676,0.0062818597,0.0040922225,0.009234229],"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":[0.00013586045,0.00007697498,0.0011867471,0.0008089208,0.000031920597,0.0004182863,0.0017987147,0.00034696484,0.00079231506,0.3966933,0.1155118,0.48219824],"study_design_scores_gemma":[0.000016402888,0.000024131086,0.000374121,0.00045634917,0.000019306619,0.0008388144,0.0009002496,0.001042786,0.00040824682,0.08405564,0.91181374,0.00005024422],"about_ca_topic_score_codex":0.0016412274,"about_ca_topic_score_gemma":0.0020294916,"teacher_disagreement_score":0.017181838,"about_ca_system_score_codex":0.0016619666,"about_ca_system_score_gemma":0.002784197,"threshold_uncertainty_score":0.088739395},"labels":[],"label_agreement":null},{"id":"W2052521912","doi":"10.1145/967900.968046","title":"ConvRel","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; XML validation; Cardinality (data modeling); XML database; XML; Document Structure Description; XML Schema (W3C); Theoretical computer science; Programming language; Database; Information retrieval; XML Encryption; World Wide Web","score_opus":0.008708561292173365,"score_gpt":0.22392504171984756,"score_spread":0.2152164804276742,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2052521912","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":[0.011530351,0.002160824,0.3379413,0.004310368,0.0015003004,0.0005314663,0.031617567,0.13190109,0.47850686],"genre_scores_gemma":[0.12019196,0.0023861926,0.30968416,0.0052427696,0.0006106818,0.0005840112,0.1353677,0.038143788,0.38778877],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99760085,0.00039742977,0.00016400195,0.00066837564,0.0009772624,0.00019205688],"domain_scores_gemma":[0.9970696,0.00059958996,0.00013719527,0.0014180805,0.00064097176,0.00013447639],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002314255,0.0011512992,0.00080659345,0.0018445723,0.0012822315,0.0036754224,0.003581711,0.0012532538,0.11417847],"category_scores_gemma":[0.005875869,0.0008023627,0.000996349,0.0017507309,0.00075182813,0.0056520402,0.003889844,0.0015068952,0.07588684],"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":[0.0004778854,0.00010764236,0.0015186645,0.0005812463,0.000068605965,0.00048870425,0.00028710323,0.0022886198,0.0029811065,0.056542855,0.56145793,0.3731996],"study_design_scores_gemma":[0.0000672719,0.000060588925,0.0006296717,0.00010667999,0.000028459435,0.0006052352,0.00017608293,0.009938977,0.005521356,0.034894466,0.9479345,0.000036767622],"about_ca_topic_score_codex":0.00597523,"about_ca_topic_score_gemma":0.010075227,"teacher_disagreement_score":0.11417847,"about_ca_system_score_codex":0.0011930485,"about_ca_system_score_gemma":0.0014720879,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W2053024197","doi":"10.1007/s10472-005-9016-8","title":"Regular path queries under approximate semantics","year":2006,"lang":"en","type":"article","venue":"Annals of Mathematics and Artificial Intelligence","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":26,"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; Concordia University","funders":"","keywords":"Containment (computer programming); Path (computing); Focus (optics); Semantics (computer science); Mathematics; Query language; Query optimization; Computer science; Polynomial; Automaton; Theoretical computer science; Algorithm; Database; Programming language","score_opus":0.07877425589486078,"score_gpt":0.3108494660789743,"score_spread":0.2320752101841135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2053024197","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":[0.0714914,0.0028021396,0.88791394,0.0070292335,0.0005519495,0.00011227247,0.0009967886,0.002245925,0.026856309],"genre_scores_gemma":[0.7860084,0.0027448556,0.18964083,0.0019024848,0.0018539988,0.00024248585,0.0022031085,0.0009042048,0.014499667],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9899239,0.002336141,0.0010822525,0.0017614275,0.0041860417,0.0007103049],"domain_scores_gemma":[0.97356546,0.016474744,0.0012049623,0.005421446,0.002720073,0.0006134396],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006116534,0.0008869358,0.0028392517,0.0026458397,0.0018162938,0.008839681,0.0027912373,0.0027544287,0.0060045524],"category_scores_gemma":[0.0315107,0.0013861166,0.0019319729,0.0045935214,0.005744459,0.03658773,0.0057389713,0.006387086,0.0014155088],"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":[0.00028536483,0.000052188923,0.0004583461,0.00011855696,0.00003856716,0.00008503702,0.00032644966,0.0053049526,0.00068516674,0.96454287,0.0031139916,0.02498848],"study_design_scores_gemma":[0.000026052967,0.00002000753,0.000059742793,0.000013010213,0.00003095959,0.00011555648,0.000056449204,0.014749676,0.00054372265,0.9813291,0.0030438649,0.0000119183305],"about_ca_topic_score_codex":0.0015853944,"about_ca_topic_score_gemma":0.0008791793,"teacher_disagreement_score":0.008839681,"about_ca_system_score_codex":0.0025036228,"about_ca_system_score_gemma":0.002160036,"threshold_uncertainty_score":0.03234774},"labels":[],"label_agreement":null},{"id":"W2053259448","doi":"10.1007/s11280-007-0029-6","title":"Clustered Chain Path Index for XML Document: Efficiently Processing Branch Queries","year":2007,"lang":"en","type":"article","venue":"World Wide Web","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":5,"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":"University of Waterloo; National University of Singapore","keywords":"Computer science; Cardinality (data modeling); XML; Path (computing); Scalability; Index (typography); Data mining; Path expression; Inverted index; XPath; Tree (set theory); Stream processing; Search engine indexing; XML database; Algorithm; Information retrieval; Database; Query language; Parallel computing; Programming language","score_opus":0.009802303416945914,"score_gpt":0.2593626724000832,"score_spread":0.2495603689831373,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2053259448","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":[0.2226836,0.0025521982,0.66005653,0.00096701283,0.0002793385,0.0008208477,0.017710166,0.07936734,0.015562994],"genre_scores_gemma":[0.29267928,0.0007405424,0.6591948,0.00028906687,0.00014888369,0.0004017955,0.030671472,0.0028978966,0.012976167],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993724,0.00006476043,0.00007046082,0.00010295255,0.0003190202,0.00007045833],"domain_scores_gemma":[0.9977539,0.00084585114,0.00015707592,0.0005427303,0.00054083846,0.00015951815],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006588795,0.0009162971,0.0010218142,0.0038435971,0.000961119,0.0017872185,0.00153392,0.0008327751,0.014467522],"category_scores_gemma":[0.0032751441,0.0005827664,0.0004753588,0.0057166545,0.00043667227,0.003309461,0.0017574799,0.000831819,0.0039163856],"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":[0.0019078731,0.00037544107,0.0072141765,0.00047617697,0.000101900776,0.00022359038,0.0004377084,0.009699319,0.034375727,0.0126765575,0.06756278,0.8649487],"study_design_scores_gemma":[0.0007508651,0.00073663116,0.0060517313,0.00014564981,0.00026980368,0.00061195524,0.0007649363,0.750352,0.10706277,0.051439095,0.08167011,0.00014441895],"about_ca_topic_score_codex":0.009215742,"about_ca_topic_score_gemma":0.017834993,"teacher_disagreement_score":0.014467522,"about_ca_system_score_codex":0.0011846296,"about_ca_system_score_gemma":0.0026350215,"threshold_uncertainty_score":0.048398614},"labels":[],"label_agreement":null},{"id":"W2053340216","doi":"10.1007/s10844-011-0166-3","title":"Tableaux-based optimization of schema mappings for data integration","year":2011,"lang":"en","type":"article","venue":"Journal of Intelligent Information Systems","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 Ottawa","funders":"","keywords":"Computer science; Schema (genetic algorithms); Assertion; Tuple; Conceptual schema; Star schema; Database schema; Data integration; Semi-structured model; Theoretical computer science; Information retrieval; Programming language; Data mining; Database design; Mathematics; Discrete mathematics","score_opus":0.0965137520039541,"score_gpt":0.282461807509628,"score_spread":0.18594805550567392,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2053340216","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":[0.033218045,0.0005687361,0.9547516,0.00042296472,0.00013500307,0.00019118506,0.0007958474,0.0041997307,0.00571693],"genre_scores_gemma":[0.25013015,0.00029812014,0.74167126,0.00020826962,0.00005615158,0.00021147917,0.0020799998,0.00096240686,0.0043821703],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99733776,0.00096292957,0.00022146893,0.00037052456,0.00085307413,0.00025420878],"domain_scores_gemma":[0.99636936,0.0020740803,0.00016087416,0.0007550134,0.00054305076,0.000097691496],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023396425,0.0008411811,0.0012518103,0.0014622785,0.00082563394,0.0026536337,0.0019668057,0.0010212488,0.007830597],"category_scores_gemma":[0.008368305,0.0007561611,0.0016423027,0.002696307,0.0008922236,0.0032497316,0.0021312665,0.0018348012,0.001380966],"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":[0.0011248958,0.00053943036,0.0020888022,0.00048368936,0.0002459977,0.00047552475,0.00058377645,0.22312109,0.023100907,0.20119794,0.028330395,0.5187076],"study_design_scores_gemma":[0.00013059727,0.00011588796,0.0004928257,0.000052226078,0.00009342877,0.00018870628,0.00019838111,0.8034242,0.014605084,0.1698562,0.010796462,0.0000460546],"about_ca_topic_score_codex":0.00452665,"about_ca_topic_score_gemma":0.008287015,"teacher_disagreement_score":0.007830597,"about_ca_system_score_codex":0.0014817379,"about_ca_system_score_gemma":0.0018270706,"threshold_uncertainty_score":0.026195943},"labels":[],"label_agreement":null},{"id":"W2053771722","doi":"10.1007/s10990-005-7006-5","title":"Least Reflexive Points of Relations","year":2005,"lang":"en","type":"article","venue":"LISP and Symbolic Computation","topic":"Advanced Database Systems and Queries","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":"Université Laval","funders":"","keywords":"Mathematics; Nondeterministic algorithm; Reflexivity; Generalization; Complete lattice; Algebraic number; Partially ordered set; Binary relation; Pure mathematics; Lattice (music); Fixed point; Discrete mathematics; Combinatorics; Mathematical analysis; Universality (dynamical systems)","score_opus":0.01226304771391825,"score_gpt":0.27104388238119,"score_spread":0.25878083466727175,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2053771722","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":[0.15416467,0.0016818733,0.6230549,0.002036965,0.0004353427,0.00018397864,0.0013528218,0.002915124,0.21417418],"genre_scores_gemma":[0.7730012,0.0012202831,0.15085125,0.0005441541,0.00059655897,0.00022838157,0.0015954486,0.0010045321,0.070958264],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99793917,0.00043746515,0.00016515549,0.0004738099,0.000687256,0.00029712284],"domain_scores_gemma":[0.9958264,0.0020591922,0.00026026095,0.00082557095,0.0007644354,0.00026419817],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015785889,0.0008925156,0.0012116567,0.0024046036,0.002702763,0.0048266468,0.0014845027,0.0015829742,0.015739465],"category_scores_gemma":[0.00550343,0.0011884017,0.0011126153,0.0019489708,0.004205234,0.0095104715,0.003045034,0.0052178977,0.0053798836],"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":[0.00012833854,0.000022883583,0.00014050324,0.000067232686,0.000016371434,0.00011467496,0.0006476022,0.0002656858,0.002845435,0.9823387,0.0013170209,0.012095526],"study_design_scores_gemma":[0.000049037124,0.000033467564,0.00013802061,0.000030395302,0.00002685701,0.00021363334,0.00020777243,0.0008492117,0.0065148682,0.9815694,0.010348382,0.00001889926],"about_ca_topic_score_codex":0.00059717626,"about_ca_topic_score_gemma":0.00078437326,"teacher_disagreement_score":0.015739465,"about_ca_system_score_codex":0.0010880107,"about_ca_system_score_gemma":0.000814896,"threshold_uncertainty_score":0.05265379},"labels":[],"label_agreement":null},{"id":"W2054103607","doi":"10.1109/iri.2014.7051977","title":"Using document space for relational search","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Computer science; Information retrieval; Search engine indexing; Relational database; Transformation (genetics); Keyword search; Search engine; Tuple; Space (punctuation); Mathematics","score_opus":0.0650871392210247,"score_gpt":0.3271971145017349,"score_spread":0.2621099752807102,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2054103607","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":[0.0046936176,0.0028955657,0.98024005,0.00076179917,0.00018039931,0.00009661956,0.0005554255,0.0015588879,0.009017669],"genre_scores_gemma":[0.113561355,0.0033883154,0.8713687,0.0005112806,0.00036478977,0.00027955257,0.0017006061,0.00041348697,0.008411845],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9955232,0.0014061937,0.0004230876,0.00087011064,0.0015886634,0.00018874688],"domain_scores_gemma":[0.9949462,0.0018749841,0.00031099847,0.0020779127,0.00062388706,0.00016607161],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002574026,0.0007082647,0.001228676,0.0033187664,0.0010788748,0.0061159427,0.0018429584,0.0009777085,0.0080675],"category_scores_gemma":[0.009293223,0.0003610949,0.0011927481,0.0063838637,0.0019392429,0.011293291,0.0040886365,0.0016912636,0.00396746],"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":[0.000106633015,0.00005258262,0.0005131801,0.00031615686,0.00005785159,0.000082099024,0.00040163056,0.007905027,0.0031715024,0.7371139,0.008507178,0.24177232],"study_design_scores_gemma":[0.000046867695,0.000109181194,0.0002870537,0.000118608456,0.00007270435,0.0005486168,0.000253458,0.09125022,0.008110277,0.74169236,0.15743613,0.00007444871],"about_ca_topic_score_codex":0.0026665817,"about_ca_topic_score_gemma":0.0018937142,"teacher_disagreement_score":0.0080675,"about_ca_system_score_codex":0.001358218,"about_ca_system_score_gemma":0.0013516222,"threshold_uncertainty_score":0.026988447},"labels":[],"label_agreement":null},{"id":"W2054655669","doi":"10.1145/383891.383892","title":"Querying ATSQL databases with temporal logic","year":2001,"lang":"en","type":"article","venue":"ACM Transactions on Database Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":66,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; SQL; Temporal logic; Expressive power; Temporal database; Extension (predicate logic); Database; Translation (biology); Programming language; Representation (politics); Theoretical computer science","score_opus":0.05051783123629092,"score_gpt":0.2832165114231688,"score_spread":0.23269868018687787,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2054655669","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":[0.021816252,0.00018842761,0.9672636,0.00061631174,0.00007785459,0.00009233407,0.000753834,0.003816975,0.0053743753],"genre_scores_gemma":[0.47757867,0.0007945401,0.5091717,0.0010111053,0.00031091797,0.00036441867,0.0039546015,0.00089132594,0.005922742],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9956501,0.0011407754,0.00069717254,0.0004340682,0.0018463063,0.00023146595],"domain_scores_gemma":[0.9949386,0.002177153,0.0005139877,0.001131729,0.0011009211,0.00013755982],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002744949,0.0005990789,0.00058518205,0.00084578927,0.00065524905,0.0031168598,0.0015705588,0.00062208076,0.0031290401],"category_scores_gemma":[0.007968815,0.0004623743,0.0010913615,0.0013556501,0.00089986477,0.0062528457,0.0022128979,0.0015121073,0.00066832744],"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":[0.0008290342,0.00024559663,0.0031128346,0.0006475863,0.00015044239,0.0012511491,0.0012773202,0.05012334,0.04116383,0.71939915,0.017952897,0.16384676],"study_design_scores_gemma":[0.0001269976,0.00021442222,0.0005331871,0.00014452344,0.00014878891,0.001196719,0.0004936118,0.5247963,0.05065151,0.33673665,0.08487537,0.00008191195],"about_ca_topic_score_codex":0.0020707618,"about_ca_topic_score_gemma":0.0017258255,"teacher_disagreement_score":0.0031290401,"about_ca_system_score_codex":0.00072468835,"about_ca_system_score_gemma":0.0010716353,"threshold_uncertainty_score":0.01451683},"labels":[],"label_agreement":null},{"id":"W2054681294","doi":"10.1145/1247480.1247611","title":"ConEx","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Query optimization; Sargable; Query plan; Query expansion; Query language; Plan (archaeology); Relational database; Information retrieval; Query by Example; Web search query; Data mining; Search engine","score_opus":0.009645531516708428,"score_gpt":0.25325575695042896,"score_spread":0.24361022543372052,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2054681294","genre_codex":"methods","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":[0.039398916,0.0040915315,0.4838137,0.0016034056,0.000918162,0.0022427656,0.017552529,0.28637645,0.16400254],"genre_scores_gemma":[0.24951914,0.003969922,0.5451959,0.002680679,0.0005485195,0.0017930679,0.06471581,0.015247288,0.11632967],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99723333,0.00027670054,0.00013515951,0.00045974395,0.0016858188,0.00020922857],"domain_scores_gemma":[0.99620986,0.0006334701,0.00021619454,0.0012880709,0.001337702,0.00031477187],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018731644,0.0011047844,0.00088700134,0.0018462401,0.0011891774,0.003543005,0.0027812715,0.00070657226,0.021827843],"category_scores_gemma":[0.00502755,0.0007102371,0.0004418719,0.0016067359,0.0005489899,0.0040997756,0.0024200547,0.0014321526,0.008794304],"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":[0.0015652941,0.00046919208,0.011568765,0.0007533685,0.0000817265,0.00044837533,0.00064871565,0.003952073,0.022399442,0.029308299,0.33579585,0.593009],"study_design_scores_gemma":[0.00028412428,0.00065398304,0.0068165744,0.00020560295,0.00010207762,0.0012698757,0.00017711223,0.09646522,0.038847134,0.013048309,0.84195304,0.00017694815],"about_ca_topic_score_codex":0.0056378758,"about_ca_topic_score_gemma":0.006817178,"teacher_disagreement_score":0.021827843,"about_ca_system_score_codex":0.00081598037,"about_ca_system_score_gemma":0.0021277932,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W205518314","doi":"","title":"A formal temporal semantics for microsoft project based on Allen's interval algebra","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Acadia University","funders":"","keywords":"Rotation formalisms in three dimensions; Computer science; Process calculus; Programming language; Interval temporal logic; Semantics (computer science); Formalism (music); Temporal logic; Theoretical computer science; Mathematics","score_opus":0.020925389113116116,"score_gpt":0.28332073915552153,"score_spread":0.26239535004240544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W205518314","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":[0.008197462,0.0006434252,0.9737588,0.0011176188,0.00026656227,0.0001087239,0.00037675054,0.00070425984,0.014826347],"genre_scores_gemma":[0.24768604,0.0013920194,0.7408061,0.00063153525,0.00040405805,0.0005021051,0.0009053104,0.00027764187,0.007395164],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99782914,0.0005478758,0.00035413104,0.00030493087,0.0007941882,0.00016968301],"domain_scores_gemma":[0.99824995,0.00067066535,0.0003218342,0.00018582332,0.00043574613,0.0001360192],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034680942,0.00059849763,0.00059891527,0.0016970832,0.0012991114,0.004000704,0.0018521848,0.0011896272,0.003985053],"category_scores_gemma":[0.0034800838,0.00040342766,0.0014844771,0.0021274944,0.0027352623,0.0065887887,0.0015181995,0.0026257106,0.00082633516],"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":[0.00001035876,0.000010022357,0.000029510687,0.000028422997,0.0000032846078,0.000070414586,0.00025302047,0.001363116,0.0005125103,0.99166685,0.00079581235,0.005256599],"study_design_scores_gemma":[0.000040767063,0.00006379106,0.00013799107,0.00011554308,0.000028454622,0.00042179707,0.00040905862,0.034359116,0.0027796852,0.86490595,0.09668256,0.000055284436],"about_ca_topic_score_codex":0.00447825,"about_ca_topic_score_gemma":0.0024916467,"teacher_disagreement_score":0.00447825,"about_ca_system_score_codex":0.0017556754,"about_ca_system_score_gemma":0.0020575565,"threshold_uncertainty_score":0.018341243},"labels":[],"label_agreement":null},{"id":"W2056191114","doi":"10.14778/1920841.1921016","title":"MEET DB2","year":2010,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada)","funders":"","keywords":"Computer science; Database; XML; Data migration; Source code; Executable; Process (computing); Software engineering; Operating system","score_opus":0.004885213329562108,"score_gpt":0.20289898918943194,"score_spread":0.19801377585986984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2056191114","genre_codex":"software","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":"software","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00828917,0.0011412674,0.10596487,0.0009637795,0.0005765121,0.00071860314,0.08019769,0.6121009,0.1900473],"genre_scores_gemma":[0.058008175,0.0011801057,0.14346565,0.0022475605,0.00037690377,0.0012439683,0.44545949,0.17776458,0.17025347],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99579394,0.00047764718,0.00037329856,0.00097652647,0.0019777857,0.00040080003],"domain_scores_gemma":[0.99544275,0.0006785772,0.0002704242,0.0014902327,0.0015591356,0.0005588511],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030837771,0.0023778984,0.0011659003,0.0028721606,0.0010581032,0.0064809243,0.004207209,0.0014429512,0.13965134],"category_scores_gemma":[0.006819768,0.0016975778,0.001320484,0.0026215157,0.0005178995,0.005910335,0.0040322538,0.0021981178,0.15163316],"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":[0.0012566254,0.00020043169,0.0026382143,0.0007474605,0.00012766986,0.00023582642,0.00041901195,0.001283275,0.0066377027,0.015109074,0.8138116,0.15753318],"study_design_scores_gemma":[0.00017664174,0.000110456866,0.0017708173,0.0000618389,0.000031215957,0.00034788015,0.00015685588,0.006681029,0.008200773,0.0047957725,0.97759104,0.00007569741],"about_ca_topic_score_codex":0.0055341306,"about_ca_topic_score_gemma":0.004671375,"teacher_disagreement_score":0.13965134,"about_ca_system_score_codex":0.0011364082,"about_ca_system_score_gemma":0.0022633797,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W2057545667","doi":"10.1145/1508857.1508858","title":"The design of a query monitoring system","year":2009,"lang":"en","type":"article","venue":"ACM Transactions on Database Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":169,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Query optimization; Online aggregation; Joins; Query expansion; Sargable; Query plan; View; Data mining; Database; Query language; Cardinality (data modeling); Web query classification; Information retrieval; Web search query; Search engine; Database design","score_opus":0.034277973946782773,"score_gpt":0.26691792212526705,"score_spread":0.23263994817848427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2057545667","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":[0.010724148,0.00022156566,0.9742353,0.0004908641,0.00009500238,0.0007574908,0.00012286732,0.011996241,0.0013564616],"genre_scores_gemma":[0.21831886,0.00030868078,0.7740512,0.00064785377,0.00023564004,0.0011814734,0.0005507702,0.00077329774,0.003932154],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9951591,0.00079410285,0.0006581429,0.0013716399,0.001706362,0.0003105866],"domain_scores_gemma":[0.99472284,0.0015220954,0.0004387884,0.0010661832,0.0017347932,0.00051537046],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005352603,0.0007736016,0.0013875815,0.0011321045,0.0015894073,0.0043182536,0.0039578876,0.0020913412,0.0033822078],"category_scores_gemma":[0.009265824,0.001312127,0.0006248969,0.0010759275,0.0012107971,0.004988434,0.0026866384,0.0023400155,0.002229899],"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":[0.0034331058,0.0015054166,0.020414403,0.001449778,0.00043143556,0.0017917681,0.0029557608,0.07104931,0.23895007,0.10105241,0.03948348,0.5174831],"study_design_scores_gemma":[0.00028401287,0.0008010718,0.002684423,0.00010414427,0.00025679255,0.0011866451,0.00029632973,0.8149929,0.09537934,0.014746041,0.06909358,0.00017481264],"about_ca_topic_score_codex":0.0019670192,"about_ca_topic_score_gemma":0.00094351225,"teacher_disagreement_score":0.005352603,"about_ca_system_score_codex":0.0009907882,"about_ca_system_score_gemma":0.0025122664,"threshold_uncertainty_score":0.028307617},"labels":[],"label_agreement":null},{"id":"W2057731143","doi":"10.5539/cis.v3n2p38","title":"A Proposal for Constructing Relational Database from Class Diagram","year":2010,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Database design; Database schema; Relational database; Class diagram; Entity–relationship model; Database; Semi-structured model; Schema (genetic algorithms); View; Data mining; Data redundancy; Database model; Information schema; Information retrieval; Programming language; Unified Modeling Language; Software","score_opus":0.013669767991309903,"score_gpt":0.25499678153071137,"score_spread":0.24132701353940147,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2057731143","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":[0.00080798706,0.0011446874,0.9855472,0.0008979847,0.00058863027,0.00039436395,0.0006045089,0.0033314577,0.0066832807],"genre_scores_gemma":[0.0095005315,0.0014853765,0.97965986,0.00029346588,0.00020348019,0.00042452815,0.0014719336,0.00024810113,0.0067126886],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99730104,0.0006064823,0.00033748482,0.0006991975,0.00093057164,0.00012522777],"domain_scores_gemma":[0.9988135,0.00022271209,0.00008785341,0.00020519312,0.0005578818,0.000112866815],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022594656,0.0006885785,0.0007834369,0.0026279246,0.0012233881,0.0045293584,0.0024103434,0.0014956924,0.009035338],"category_scores_gemma":[0.0033134478,0.0007260698,0.0017196997,0.0029415356,0.0007635643,0.0055100685,0.0019449363,0.0023565567,0.00434478],"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":[0.00011858651,0.00013755291,0.0009607967,0.0010411184,0.00008712573,0.00085838756,0.0011495174,0.0029454401,0.013322477,0.45376056,0.05514119,0.47047722],"study_design_scores_gemma":[0.00009585769,0.00013637879,0.00048140026,0.00021726862,0.000098472316,0.001788046,0.0002553805,0.01606692,0.0046607503,0.09756739,0.87853986,0.00009222113],"about_ca_topic_score_codex":0.0024160324,"about_ca_topic_score_gemma":0.0014335185,"teacher_disagreement_score":0.009035338,"about_ca_system_score_codex":0.00079956726,"about_ca_system_score_gemma":0.002248951,"threshold_uncertainty_score":0.03022623},"labels":[],"label_agreement":null},{"id":"W2058942233","doi":"10.1145/1866480.1866492","title":"Ambiguous content and disambiguation of XML schemata","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; Laurentian University","funders":"","keywords":"Computer science; XML Schema (W3C); XML; Schema (genetic algorithms); Expression (computer science); XML Schema Editor; Regular expression; XML validation; RELAX NG; Natural language processing; Content (measure theory); Document Structure Description; Information retrieval; Programming language; Artificial intelligence; XML Encryption; Mathematics; World Wide Web","score_opus":0.024902068764099713,"score_gpt":0.23876260710645594,"score_spread":0.21386053834235624,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2058942233","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":[0.052624904,0.0013764247,0.9346577,0.0010378821,0.00015809429,0.00016034933,0.00021606352,0.0012197739,0.0085488735],"genre_scores_gemma":[0.32362178,0.0011256163,0.66768235,0.0006853592,0.0001903073,0.00020932863,0.00071833003,0.00080230937,0.004964567],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9850819,0.0065804245,0.0014852965,0.0023431438,0.003909001,0.0006001829],"domain_scores_gemma":[0.98384327,0.009588196,0.0013891207,0.0032877913,0.0016411793,0.0002504375],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007110375,0.0007576863,0.0010784823,0.0039560576,0.0022894093,0.004164217,0.0016875499,0.001499722,0.0018951198],"category_scores_gemma":[0.028558647,0.001299102,0.0012190308,0.0034480484,0.005944875,0.0126260305,0.005413944,0.0022340692,0.0007900015],"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":[0.00019831596,0.00004382434,0.0024397923,0.00036352364,0.00006784838,0.0008159443,0.004855511,0.01678163,0.005925069,0.83055574,0.002532049,0.1354207],"study_design_scores_gemma":[0.000033131193,0.000043961827,0.0007470735,0.00031056616,0.00010869425,0.0007336292,0.0011667348,0.059948523,0.021102231,0.86009586,0.055618905,0.000090712616],"about_ca_topic_score_codex":0.0015786302,"about_ca_topic_score_gemma":0.0013977168,"teacher_disagreement_score":0.007110375,"about_ca_system_score_codex":0.0017589972,"about_ca_system_score_gemma":0.0014265691,"threshold_uncertainty_score":0.037603676},"labels":[],"label_agreement":null},{"id":"W2060490725","doi":"10.4018/jdwm.2008070101","title":"RCUBE","year":2008,"lang":"en","type":"article","venue":"International Journal of Data Warehousing and Mining","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; Concordia University; Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Online analytical processing; Computer science; Scalability; Search engine indexing; Materialized view; Scheme (mathematics); Multidimensional data; Volume (thermodynamics); Database index; Index (typography); Distributed computing; Data mining; Database; Information retrieval; Data warehouse; View; Database design; World Wide Web","score_opus":0.09224246699132363,"score_gpt":0.32406961971131504,"score_spread":0.2318271527199914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2060490725","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":[0.014906794,0.0042193197,0.6339746,0.0023659868,0.0028855316,0.0010678377,0.01549952,0.08417237,0.2409081],"genre_scores_gemma":[0.12013897,0.005067561,0.6110688,0.0022252966,0.0010973483,0.0016037513,0.05571482,0.016868588,0.18621495],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99712026,0.0003200158,0.00024729798,0.0005127203,0.0014872178,0.000312583],"domain_scores_gemma":[0.9956073,0.0005254775,0.00016757242,0.0022249005,0.0012161836,0.00025853107],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010130275,0.0009886472,0.0013153728,0.0022119726,0.0019263295,0.004708216,0.00424791,0.0014300566,0.059196968],"category_scores_gemma":[0.005784268,0.00052341237,0.0009624464,0.004585113,0.0007222232,0.0053468407,0.005807356,0.001898882,0.05229347],"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":[0.00042845664,0.00014548747,0.0013283428,0.0008228854,0.00006443438,0.00038465657,0.0003219821,0.0070836404,0.008889474,0.082714066,0.32497278,0.57284385],"study_design_scores_gemma":[0.00005495992,0.00010695081,0.00054861547,0.000097867196,0.000022655038,0.0008348045,0.00015817402,0.033438213,0.010287071,0.02523286,0.9291553,0.00006248627],"about_ca_topic_score_codex":0.004512007,"about_ca_topic_score_gemma":0.0050189183,"teacher_disagreement_score":0.059196968,"about_ca_system_score_codex":0.0013897339,"about_ca_system_score_gemma":0.0025324759,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W2061236021","doi":"10.1145/1923947.1924023","title":"Hands-on","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada)","funders":"","keywords":"Computer science; XML; World Wide Web; Database; De facto; Data exchange; Efficient XML Interchange; XML database; XML Schema Editor; Political science","score_opus":0.006334748170838882,"score_gpt":0.23105516731139406,"score_spread":0.22472041914055518,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2061236021","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0038194978,0.0015076464,0.02549926,0.0129103605,0.009245839,0.00043746782,0.0016099983,0.004838657,0.9401312],"genre_scores_gemma":[0.02046153,0.0014317646,0.009480152,0.008915772,0.0019484685,0.00034127518,0.0020179085,0.0012950004,0.95410806],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9972595,0.00047083187,0.000108232685,0.00058688194,0.0009703137,0.00060422055],"domain_scores_gemma":[0.99356294,0.0007309634,0.00017954725,0.0011838846,0.0016772115,0.0026653667],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0027241157,0.0013993564,0.0008535165,0.0012827006,0.0024901784,0.004962926,0.0031357524,0.002892256,0.74921787],"category_scores_gemma":[0.009209231,0.00053403963,0.0012131528,0.0008521013,0.0011844509,0.0040039695,0.0083867125,0.0027144703,0.5897582],"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":[0.00034626882,0.0003437511,0.000827778,0.0002050063,0.000018066683,0.000628722,0.00034752037,0.00020271125,0.0018115647,0.012701756,0.6571928,0.32537404],"study_design_scores_gemma":[0.000036731624,0.00008741504,0.0004966779,0.00016144494,0.000010535225,0.0008323942,0.00032776655,0.00018403247,0.0006351916,0.005869914,0.9913325,0.00002526416],"about_ca_topic_score_codex":0.0018270733,"about_ca_topic_score_gemma":0.0036334705,"teacher_disagreement_score":0.25078213,"about_ca_system_score_codex":0.001599555,"about_ca_system_score_gemma":0.003222639,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W2062189134","doi":"10.1109/wi.2004.2","title":"A Fast Tree Pattern Matching Algorithm for XML Query","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":27,"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 Regina","funders":"","keywords":"Computer science; Pattern matching; XML; Matching (statistics); Tree (set theory); Query optimization; Tree decomposition; Algorithm; Theoretical computer science; Data mining; Mathematics; Artificial intelligence; Combinatorics","score_opus":0.012929554931064693,"score_gpt":0.24916345623125083,"score_spread":0.23623390130018612,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2062189134","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":[0.0030666476,0.00030210664,0.9914784,0.00011770637,0.00004491065,0.00016055077,0.00029963328,0.0032634207,0.0012667179],"genre_scores_gemma":[0.034951434,0.00030821827,0.9598858,0.00012335568,0.00003910902,0.00029149005,0.0016419742,0.00032567038,0.0024330532],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998514,0.00020038316,0.00018071009,0.00032955874,0.0006543338,0.00012101114],"domain_scores_gemma":[0.99910516,0.00023896758,0.000068880305,0.00020547277,0.00034670095,0.000034808643],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010698126,0.0008817658,0.00093633815,0.002024442,0.0011165704,0.0014070824,0.0016663445,0.0012041872,0.0058194078],"category_scores_gemma":[0.002834901,0.00051424146,0.00096462434,0.0034256345,0.00057044864,0.0042550154,0.0021275806,0.0012248894,0.003068051],"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":[0.00043690662,0.00013947737,0.0011073773,0.00038423846,0.00008993149,0.00022014116,0.00030821943,0.019499125,0.033751097,0.057182565,0.030116538,0.8567644],"study_design_scores_gemma":[0.0003022042,0.00039070178,0.0009696881,0.00007967371,0.00011469961,0.0014039619,0.0002646818,0.71206194,0.055012617,0.12553644,0.10372784,0.00013556237],"about_ca_topic_score_codex":0.002754798,"about_ca_topic_score_gemma":0.0026755317,"teacher_disagreement_score":0.0058194078,"about_ca_system_score_codex":0.0008712765,"about_ca_system_score_gemma":0.0016424865,"threshold_uncertainty_score":0.01946789},"labels":[],"label_agreement":null},{"id":"W2062851193","doi":"10.4108/icst.simutools2008.2936","title":"PDST: A Peer Database Simulation Tool for Data Sharing Systems","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Peer-to-peer; Data sharing; File sharing; Database; Distributed database; Distributed computing; Data modeling; File system; Operating system; The Internet","score_opus":0.14976473572264565,"score_gpt":0.3431743677517162,"score_spread":0.19340963202907058,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2062851193","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":[0.02084953,0.0006305031,0.90173244,0.00061208947,0.00039454317,0.000538697,0.006461834,0.053500697,0.015279647],"genre_scores_gemma":[0.3597528,0.001801668,0.5955905,0.0004863021,0.0001434265,0.0021685287,0.013620067,0.010096465,0.0163402],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990569,0.00033173925,0.00010785969,0.00008462405,0.0003313497,0.0000875339],"domain_scores_gemma":[0.9980003,0.001083226,0.00006803783,0.0002633905,0.00041415135,0.00017089547],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016475157,0.0010598919,0.0011793145,0.00083449844,0.0007649744,0.0013492826,0.003091987,0.0014847995,0.017471012],"category_scores_gemma":[0.004955892,0.000770903,0.0010558179,0.001049853,0.00049629016,0.0020723103,0.0018860922,0.0020198114,0.0031429108],"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":[0.00061514834,0.00026236617,0.003173319,0.00081456307,0.00022346503,0.00029424275,0.0004781186,0.8260697,0.0062345075,0.03039591,0.050664637,0.080774024],"study_design_scores_gemma":[0.00014726847,0.000057306843,0.00018454963,0.00003507637,0.000031738185,0.00006820722,0.000026413501,0.9521771,0.0035511488,0.0064167283,0.037275653,0.000028663711],"about_ca_topic_score_codex":0.0072576744,"about_ca_topic_score_gemma":0.00418715,"teacher_disagreement_score":0.017471012,"about_ca_system_score_codex":0.00084934925,"about_ca_system_score_gemma":0.0014211723,"threshold_uncertainty_score":0.058446348},"labels":[],"label_agreement":null},{"id":"W2063278540","doi":"10.1145/2390045.2390054","title":"Towards intensional answers to OLAP queries for analytical sessions","year":2012,"lang":"en","type":"preprint","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Online analytical processing; Computer science; Session (web analytics); Information retrieval; Extensional definition; Query language; Data cube; Cube (algebra); Database; Data mining; Data warehouse; World Wide Web","score_opus":0.056006562427515415,"score_gpt":0.34224368275728884,"score_spread":0.28623712032977344,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2063278540","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":[0.011405113,0.00015392019,0.98513734,0.00054284226,0.000023929932,0.00015223742,0.00023904647,0.0011901583,0.0011552864],"genre_scores_gemma":[0.12143365,0.0003306315,0.8742219,0.00042132806,0.00016324296,0.00031701688,0.001162193,0.00029359688,0.0016563003],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9861136,0.0046939054,0.0015544917,0.0017157407,0.0052317777,0.0006904936],"domain_scores_gemma":[0.9790759,0.009403458,0.0021551286,0.0046234024,0.0040854407,0.0006565469],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013920374,0.0016051464,0.0018201666,0.0033169154,0.0013527464,0.008424278,0.0029312633,0.0021619608,0.0029138706],"category_scores_gemma":[0.03874717,0.00114603,0.0023749683,0.0035642867,0.0026833608,0.01644071,0.0069628395,0.0044901576,0.0010512873],"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":[0.00064013764,0.0004298189,0.0037334447,0.0007856568,0.00028267372,0.00061055104,0.0063344836,0.074787095,0.022450496,0.6987521,0.0079888,0.18320473],"study_design_scores_gemma":[0.00005948985,0.00014472814,0.00041437976,0.00013033592,0.000114540286,0.00035128166,0.0010615084,0.44365677,0.013416452,0.5229973,0.017566146,0.00008709844],"about_ca_topic_score_codex":0.0015461295,"about_ca_topic_score_gemma":0.0018975547,"teacher_disagreement_score":0.013920374,"about_ca_system_score_codex":0.001297911,"about_ca_system_score_gemma":0.0020225123,"threshold_uncertainty_score":0.07361889},"labels":[],"label_agreement":null},{"id":"W2063388849","doi":"10.1007/978-3-031-01837-4","title":"Data Stream Management","year":2010,"lang":"en","type":"book","venue":"Synthesis lectures on data management","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":59,"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; Stream processing; Data warehouse; Data stream mining; Data stream; Database; Data management; Transaction log; Process (computing); Paging; Information retrieval; Database transaction; Data mining; Distributed computing; Computer network; Operating system","score_opus":0.04680600989006113,"score_gpt":0.2827983911401374,"score_spread":0.23599238125007627,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2063388849","genre_codex":"methods","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":[0.0030056762,0.015972566,0.6615009,0.0029180006,0.0060194475,0.00041326176,0.0025269787,0.01972231,0.28792083],"genre_scores_gemma":[0.021607606,0.014894012,0.15234637,0.0013955983,0.003255905,0.0002761109,0.0065506115,0.0027468058,0.79692703],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995552,0.000026009482,0.000023803654,0.000089686044,0.0002787305,0.000026576456],"domain_scores_gemma":[0.9994686,0.000092400194,0.000020101199,0.00013301085,0.00023022405,0.00005564349],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006113336,0.0012125203,0.0006938309,0.0014899877,0.000522672,0.002395288,0.0010785959,0.0006376836,0.056108274],"category_scores_gemma":[0.0013724784,0.0005126059,0.0005039844,0.0023094467,0.00037030326,0.0026473415,0.0012242869,0.0016204624,0.039110214],"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":[0.00007331933,0.000059961174,0.00014174744,0.00019314529,0.000017867373,0.000057450405,0.0000634342,0.0014593144,0.005504433,0.027660113,0.34783038,0.61693877],"study_design_scores_gemma":[0.000020161306,0.00003635513,0.00033525997,0.000093837465,0.000022042384,0.00024304652,0.00003169681,0.014899889,0.006560386,0.030505084,0.94723296,0.000019271345],"about_ca_topic_score_codex":0.0008741265,"about_ca_topic_score_gemma":0.0009704965,"teacher_disagreement_score":0.056108274,"about_ca_system_score_codex":0.0006130569,"about_ca_system_score_gemma":0.0007413116,"threshold_uncertainty_score":0.18770087},"labels":[],"label_agreement":null},{"id":"W2064580935","doi":"10.1007/s00778-004-0123-7","title":"Querying XML streams","year":2004,"lang":"en","type":"article","venue":"The VLDB Journal","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":126,"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; XQuery; XML; Streaming XML; Tuple; XML database; Path (computing); Query plan; Programming language; Database; Efficient XML Interchange; XML Encryption; Concurrency; Information retrieval; Operating system; Search engine; Web search query; Sargable","score_opus":0.010352431843665732,"score_gpt":0.22936693184287188,"score_spread":0.21901449999920614,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2064580935","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":[0.056309525,0.0019071333,0.867203,0.00254368,0.0007876902,0.0004269332,0.007390821,0.044232056,0.019199098],"genre_scores_gemma":[0.4196128,0.0028207062,0.5065785,0.0014087165,0.00073694385,0.0004413061,0.031239608,0.005327012,0.031834424],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99629384,0.0006468805,0.0004999244,0.0006088804,0.001751194,0.00019926566],"domain_scores_gemma":[0.99545175,0.0020027594,0.00018783392,0.0013873357,0.0007694774,0.00020085176],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036332824,0.0012061204,0.0015915827,0.0027979144,0.0011371651,0.0065316367,0.0022404578,0.001973054,0.0102072805],"category_scores_gemma":[0.013146792,0.00091859564,0.0012877604,0.0035167914,0.0011176803,0.009381784,0.0032969401,0.0018984699,0.0035972875],"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":[0.002492207,0.00057538936,0.012927976,0.0010704205,0.00038264805,0.0013228157,0.001637983,0.03220011,0.02944381,0.23246281,0.09486795,0.59061587],"study_design_scores_gemma":[0.0003122075,0.00023525824,0.001594074,0.00024204687,0.0002849004,0.0014593849,0.00098274,0.5070152,0.0790376,0.24127679,0.16742958,0.00013017569],"about_ca_topic_score_codex":0.0025575708,"about_ca_topic_score_gemma":0.002188037,"teacher_disagreement_score":0.0102072805,"about_ca_system_score_codex":0.0012041637,"about_ca_system_score_gemma":0.0010828401,"threshold_uncertainty_score":0.034146726},"labels":[],"label_agreement":null},{"id":"W2065614356","doi":"10.1016/j.jal.2009.09.003","title":"Selected papers from the Logic in Databases Workshop 2008","year":2009,"lang":"en","type":"article","venue":"Journal of Applied Logic","topic":"Advanced Database Systems and Queries","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 British Columbia","funders":"","keywords":"Database; Computer science; Programming language; Information retrieval; Artificial intelligence; Natural language processing","score_opus":0.02759794682926558,"score_gpt":0.2627217851141027,"score_spread":0.23512383828483713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2065614356","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":[0.0060460865,0.3989902,0.052866593,0.10970297,0.22488813,0.00072588853,0.014309973,0.0017019033,0.19076821],"genre_scores_gemma":[0.016676487,0.26882136,0.028787784,0.013776037,0.07426231,0.0004319201,0.02554843,0.0017504013,0.5699452],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9981294,0.00022234168,0.00016387553,0.00038323828,0.00096686336,0.00013425662],"domain_scores_gemma":[0.9934068,0.0014767579,0.00026732698,0.00030533457,0.0034691223,0.001074789],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030035304,0.0016252332,0.0020566452,0.007835593,0.0015313267,0.0066884942,0.0017353996,0.0014740869,0.07214886],"category_scores_gemma":[0.0055550826,0.0006898873,0.0013542429,0.010044148,0.00063071394,0.0047731036,0.00204409,0.002399931,0.024538085],"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":[0.0000785942,0.00005426148,0.00020362955,0.00073978887,0.00002609614,0.000076275704,0.00007657804,0.00028095572,0.0006586973,0.002908696,0.89107174,0.10382468],"study_design_scores_gemma":[0.00003705592,0.00003327032,0.0007087134,0.0005898718,0.00005313901,0.00015769618,0.000118430326,0.0004128117,0.00069355796,0.0045708623,0.99260193,0.00002263438],"about_ca_topic_score_codex":0.003857657,"about_ca_topic_score_gemma":0.008025049,"teacher_disagreement_score":0.07214886,"about_ca_system_score_codex":0.004594603,"about_ca_system_score_gemma":0.0035088046,"threshold_uncertainty_score":0.24136198},"labels":[],"label_agreement":null},{"id":"W2065657080","doi":"10.1016/j.accinf.2014.05.004","title":"An approach to correctness of security and operational business policies","year":2014,"lang":"en","type":"article","venue":"International Journal of Accounting Information Systems","topic":"Advanced Database Systems and Queries","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":"Correctness; Computer science; Construct (python library); Business rule; Security policy; Set (abstract data type); Computer security model; State (computer science); Artifact-centric business process model; Computer security; Business process; Business process modeling; Process management; Business; Programming language; Work in process","score_opus":0.008412294475648785,"score_gpt":0.25453566489693624,"score_spread":0.24612337042128746,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2065657080","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":[0.0061914874,0.0002385014,0.97753364,0.0054908628,0.00028580235,0.00014311318,0.00015497826,0.00074541534,0.0092162015],"genre_scores_gemma":[0.4177824,0.00067554764,0.56737804,0.0021602376,0.0015765497,0.00041699456,0.0006221915,0.0008277863,0.008560283],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.96662056,0.012236375,0.0033676277,0.0038202424,0.0109426,0.003012645],"domain_scores_gemma":[0.87161684,0.07269678,0.0043737954,0.02906886,0.020393869,0.0018498438],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.022570278,0.0015293042,0.0024566432,0.004794689,0.0047033806,0.010480449,0.0069010863,0.0063416464,0.008447948],"category_scores_gemma":[0.09553385,0.0032547892,0.0065811025,0.0035137483,0.015149904,0.02945989,0.010775623,0.015143921,0.0019221526],"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":[0.000048318,0.00003731526,0.00038689421,0.00006559583,0.000028761695,0.00008893942,0.0003857826,0.0047326297,0.00026219798,0.9825283,0.0016715527,0.009763642],"study_design_scores_gemma":[0.000029794974,0.000018292016,0.000078336416,0.00003213798,0.000047010166,0.000056761786,0.00009716406,0.023716072,0.0008673358,0.96966445,0.0053763636,0.000016382195],"about_ca_topic_score_codex":0.0065588164,"about_ca_topic_score_gemma":0.0032977515,"teacher_disagreement_score":0.022570278,"about_ca_system_score_codex":0.0052518914,"about_ca_system_score_gemma":0.008290238,"threshold_uncertainty_score":0.1193645},"labels":[],"label_agreement":null},{"id":"W2065871101","doi":"10.1016/j.mcm.2011.09.017","title":"Deadline-aware complex event processing models over distributed monitoring streams","year":2011,"lang":"en","type":"article","venue":"Mathematical and Computer Modelling","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":12,"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":"National Natural Science Foundation of China; University of Saskatchewan","keywords":"Complex event processing; Computer science; Correctness; Quality of service; Event (particle physics); Distributed computing; Real-time computing; Metric (unit); Process (computing); Discrete event simulation; Performance metric; Data mining; Algorithm; Computer network; Simulation","score_opus":0.09409060897207644,"score_gpt":0.2648648086717115,"score_spread":0.1707741996996351,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2065871101","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":[0.051340546,0.00040300668,0.9452766,0.00048213283,0.00008304759,0.000053602682,0.00014595182,0.00019083075,0.0020242285],"genre_scores_gemma":[0.94101757,0.000630645,0.053120784,0.00009862567,0.00014233743,0.00013192579,0.0001747511,0.0001007654,0.004582605],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99859256,0.00042485024,0.000099933925,0.00031377623,0.00039541523,0.00017348937],"domain_scores_gemma":[0.9930829,0.0047542374,0.00083293923,0.00036705623,0.00071278977,0.0002500646],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029571617,0.0010775303,0.0015356592,0.0006901316,0.00052314677,0.0030236074,0.002425819,0.0013978247,0.0018547226],"category_scores_gemma":[0.011522049,0.00087723,0.0008420263,0.0010644413,0.0010748877,0.003025678,0.0013103249,0.0016942694,0.0002476606],"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":[0.00008628514,0.000031979256,0.0003351511,0.000039955776,0.000016467713,0.00006255284,0.00005895538,0.96994877,0.0006019146,0.025597872,0.00023961806,0.002980472],"study_design_scores_gemma":[0.0000058304367,0.0000053676195,0.000030184932,0.0000011579566,0.000003822494,0.0000052895557,0.0000040725413,0.9960598,0.000073103045,0.0037482232,0.000061236424,0.0000019089],"about_ca_topic_score_codex":0.0044179107,"about_ca_topic_score_gemma":0.0029703828,"teacher_disagreement_score":0.0044179107,"about_ca_system_score_codex":0.001559936,"about_ca_system_score_gemma":0.0011962394,"threshold_uncertainty_score":0.015639186},"labels":[],"label_agreement":null},{"id":"W2066376202","doi":"10.1145/1923947.1923959","title":"LLS","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; XML; Prefix; Scheme (mathematics); Search engine indexing; Interval (graph theory); Tree (set theory); Set (abstract data type); Information retrieval; Data mining; Programming language; Mathematics; World Wide Web; Combinatorics","score_opus":0.004613509425564375,"score_gpt":0.2227759121071394,"score_spread":0.21816240268157502,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2066376202","genre_codex":"methods","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":[0.012649328,0.0013672484,0.74932474,0.0023800987,0.0013582777,0.0007920315,0.012182845,0.058982063,0.16096336],"genre_scores_gemma":[0.1845213,0.0017843035,0.595152,0.0026630284,0.0007154977,0.00087302935,0.038511984,0.006125716,0.16965303],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99794346,0.00048325933,0.00025865826,0.0003231431,0.00080336677,0.00018808548],"domain_scores_gemma":[0.99394506,0.0008877024,0.0003309985,0.0030234384,0.0016038758,0.00020895315],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001978822,0.00057331024,0.00047831118,0.00201469,0.0010030235,0.0028573137,0.0015564575,0.0011578851,0.056993004],"category_scores_gemma":[0.00792005,0.00041784224,0.0005499382,0.0020580061,0.00062467175,0.005375349,0.002604497,0.0011620949,0.04509487],"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":[0.0004930785,0.00013798974,0.0017644287,0.00054801995,0.000036379057,0.0002997208,0.00057519943,0.0026053695,0.017181797,0.14355837,0.19859338,0.63420624],"study_design_scores_gemma":[0.00005288924,0.00013720283,0.0007040946,0.00014338118,0.000024449802,0.00048630568,0.00023365131,0.011830896,0.013010295,0.040983398,0.9323448,0.000048633236],"about_ca_topic_score_codex":0.0019205393,"about_ca_topic_score_gemma":0.0020864676,"teacher_disagreement_score":0.943007,"about_ca_system_score_codex":0.001197481,"about_ca_system_score_gemma":0.0014799195,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W2068157134","doi":"10.1007/s00778-002-0076-7","title":"Tree pattern query minimization","year":2002,"lang":"en","type":"article","venue":"The VLDB Journal","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":109,"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 British Columbia","funders":"","keywords":"Minification; Computer science; Tree (set theory); XML; Reduction (mathematics); Pattern matching; Algorithm; Query optimization; Data mining; Theoretical computer science; Mathematics; Artificial intelligence","score_opus":0.02434631267444179,"score_gpt":0.2217052823758772,"score_spread":0.1973589697014354,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2068157134","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":[0.045243844,0.0008133336,0.91946256,0.0023595088,0.0001743238,0.0004324718,0.0020999196,0.004549313,0.024864826],"genre_scores_gemma":[0.32503852,0.0006863857,0.6233127,0.0010965841,0.00031596454,0.000467711,0.0069009652,0.001764973,0.04041621],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9969784,0.0005933564,0.00019628736,0.0006492062,0.0011958856,0.0003868044],"domain_scores_gemma":[0.9970939,0.0010511606,0.0001341071,0.0010675918,0.0005310765,0.000122149],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013569826,0.0009073167,0.0015924954,0.0014081454,0.00088059914,0.002378471,0.0023335025,0.0011972619,0.017205302],"category_scores_gemma":[0.0058462843,0.00050491554,0.001429913,0.0026742457,0.000725089,0.003728926,0.0024318532,0.002081223,0.004724224],"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":[0.0009952836,0.00062505505,0.0026708478,0.00058710674,0.00021702048,0.00022419705,0.00023088626,0.038999163,0.018517213,0.14419985,0.0741691,0.7185643],"study_design_scores_gemma":[0.00021113799,0.00038426032,0.0014667166,0.00005030237,0.0002626363,0.0011197644,0.0002900104,0.64634645,0.037333544,0.28347582,0.02901756,0.00004182628],"about_ca_topic_score_codex":0.0015441948,"about_ca_topic_score_gemma":0.0027780132,"teacher_disagreement_score":0.017205302,"about_ca_system_score_codex":0.00098216,"about_ca_system_score_gemma":0.0019259216,"threshold_uncertainty_score":0.057557464},"labels":[],"label_agreement":null},{"id":"W2068346480","doi":"10.1109/icde.2012.39","title":"Multi-query Stream Processing on FPGAs","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Stream processing; Complex event processing; Event (particle physics); Analytics; Field-programmable gate array; Query optimization; Query language; Online aggregation; Sargable; Parallel computing; Computer architecture; Web search query; Database; Embedded system; Process (computing); Search engine; Operating system; Information retrieval","score_opus":0.03514703579065826,"score_gpt":0.2900362544331165,"score_spread":0.2548892186424582,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2068346480","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":[0.2340246,0.0016500424,0.7310577,0.0004396929,0.0003408679,0.00026437448,0.0006522983,0.010813341,0.020757068],"genre_scores_gemma":[0.8333395,0.0004456641,0.16009301,0.00017863867,0.00007480071,0.000079342666,0.00054825406,0.00010591534,0.0051348726],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996973,0.000036819336,0.000028907874,0.0000650987,0.00011497789,0.000056800567],"domain_scores_gemma":[0.9997495,0.00009200868,0.000023450682,0.000049462677,0.000064801236,0.00002069697],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022726537,0.00041028924,0.0002802326,0.00043349696,0.00024245975,0.0007886599,0.00068749953,0.00024547853,0.0038096951],"category_scores_gemma":[0.0005110211,0.00017690515,0.00018960367,0.0004328687,0.00016542421,0.0007191556,0.0002862244,0.00028859294,0.0007353843],"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":[0.00286291,0.00034887876,0.005268855,0.0005408505,0.00016966372,0.0012291536,0.00022643615,0.11965899,0.27121192,0.021398162,0.021505404,0.5555788],"study_design_scores_gemma":[0.00029390003,0.0007085693,0.0022305239,0.000034869387,0.000072064766,0.000638502,0.00010038453,0.78228265,0.17978,0.005592601,0.028212072,0.000053787793],"about_ca_topic_score_codex":0.0017188755,"about_ca_topic_score_gemma":0.0023196186,"teacher_disagreement_score":0.0038096951,"about_ca_system_score_codex":0.00041522333,"about_ca_system_score_gemma":0.00033575337,"threshold_uncertainty_score":0.012744665},"labels":[],"label_agreement":null},{"id":"W2069082489","doi":"10.1016/j.tcs.2011.04.037","title":"Evolving schemas for streaming XML","year":2011,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Advanced Database Systems and Queries","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":"University of Victoria","funders":"","keywords":"Computer science; Streaming XML; Programming language; XML; Theoretical computer science; World Wide Web","score_opus":0.02430770528093338,"score_gpt":0.25787714938655976,"score_spread":0.23356944410562638,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2069082489","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":[0.037142675,0.0007949173,0.9443012,0.001123718,0.00023408701,0.0002843702,0.0020943373,0.007832844,0.006191879],"genre_scores_gemma":[0.19703002,0.00090935157,0.78379023,0.00033880016,0.000104306644,0.00025442895,0.006877835,0.0019298729,0.008765175],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9972473,0.00064654835,0.00042656445,0.00047049575,0.0010577072,0.00015147006],"domain_scores_gemma":[0.9902956,0.0037268042,0.0004246448,0.003459734,0.0016999308,0.00039324473],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0051269266,0.0005214693,0.0007795447,0.001677268,0.0010462542,0.0037515836,0.0033378873,0.0016927063,0.006830936],"category_scores_gemma":[0.021332158,0.0009788987,0.0011888162,0.0024708374,0.0012301116,0.009099382,0.0035434715,0.0024049995,0.0016914246],"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":[0.0007362875,0.00027445203,0.004815293,0.0004596393,0.000120537814,0.00074750226,0.0021621631,0.053271335,0.012926713,0.5491608,0.025858795,0.3494666],"study_design_scores_gemma":[0.00014154361,0.00013523328,0.00077537645,0.0001722653,0.00012722383,0.0007058745,0.00065160525,0.4905305,0.022242647,0.39050516,0.093917094,0.00009556089],"about_ca_topic_score_codex":0.004122083,"about_ca_topic_score_gemma":0.0047286227,"teacher_disagreement_score":0.006830936,"about_ca_system_score_codex":0.001718928,"about_ca_system_score_gemma":0.0013113499,"threshold_uncertainty_score":0.027114093},"labels":[],"label_agreement":null},{"id":"W2070571200","doi":"10.1145/1062745.1062786","title":"X-warehouse","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Data warehouse; XML; Information retrieval; Cluster analysis; Database; XML database; Data mining; World Wide Web; Artificial intelligence","score_opus":0.00953728755594049,"score_gpt":0.2292020128781794,"score_spread":0.2196647253222389,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2070571200","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":[0.02138437,0.0037865902,0.7492972,0.0018502609,0.0010443341,0.0013895537,0.016919376,0.1009897,0.10333851],"genre_scores_gemma":[0.15190679,0.0058122273,0.6344683,0.0025494378,0.00046379544,0.0010467712,0.084020644,0.0065390775,0.11319288],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985469,0.00017455884,0.00024374633,0.00037768838,0.0005109067,0.00014619458],"domain_scores_gemma":[0.99806327,0.00019472034,0.000115778996,0.0011003867,0.00038558527,0.0001402328],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019205139,0.0010979291,0.00088072877,0.0015392159,0.00111585,0.0062062135,0.0041112974,0.0010218006,0.027079428],"category_scores_gemma":[0.0025515726,0.0007856704,0.0013429482,0.0029939106,0.00041178527,0.007626705,0.0036793426,0.0012476435,0.019667668],"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":[0.0016230007,0.0005529006,0.009571898,0.001682606,0.00043987055,0.0015357487,0.001006267,0.011710588,0.02219911,0.16361284,0.20579046,0.5802747],"study_design_scores_gemma":[0.00021147003,0.00035375613,0.002114163,0.0002303527,0.0001362858,0.0012168715,0.00052424555,0.037441093,0.026205232,0.051276732,0.8801792,0.00011065215],"about_ca_topic_score_codex":0.0021517917,"about_ca_topic_score_gemma":0.0016006542,"teacher_disagreement_score":0.027079428,"about_ca_system_score_codex":0.0005735412,"about_ca_system_score_gemma":0.0012021781,"threshold_uncertainty_score":0.0905897},"labels":[],"label_agreement":null},{"id":"W2070598375","doi":"10.1007/s10844-006-0368-2","title":"Holes in joins","year":2006,"lang":"en","type":"article","venue":"Journal of Intelligent Information Systems","topic":"Advanced Database Systems and Queries","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":"York University","funders":"","keywords":"Joins; Computer science; Join (topology); Sketch; Tuple; Query optimization; Cartesian product; Product (mathematics); Materialized view; Data warehouse; Data mining; Information retrieval; Theoretical computer science; Database; Algorithm; View; Programming language; Database design; Mathematics","score_opus":0.011954212229282675,"score_gpt":0.23464857003499115,"score_spread":0.22269435780570848,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2070598375","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":[0.2500614,0.007894242,0.45777237,0.014023477,0.0021680756,0.00021465785,0.0019395446,0.0021226618,0.26380354],"genre_scores_gemma":[0.8623587,0.0025728971,0.071468174,0.0014317714,0.0013263788,0.00015427955,0.0013728361,0.0008784882,0.05843647],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9977404,0.00047973078,0.00016822462,0.0006056179,0.00070185325,0.0003041867],"domain_scores_gemma":[0.9943515,0.0032808855,0.00043992873,0.0008892375,0.0005830597,0.00045544523],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020930464,0.0007840983,0.0019659942,0.0030666294,0.0042000017,0.0068270164,0.0014234532,0.0017903851,0.019005274],"category_scores_gemma":[0.010823165,0.0012543895,0.0011688737,0.003917478,0.0045210733,0.018782256,0.0052420185,0.003951509,0.0020864161],"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":[0.000068902904,0.000013341193,0.00024281247,0.000030491005,0.000007716939,0.000047281315,0.00029920065,0.00023271682,0.00020954873,0.9896193,0.0028449828,0.006383727],"study_design_scores_gemma":[0.000017121924,0.000009405153,0.000097759366,0.000012889828,0.000011971418,0.00008492687,0.00013879481,0.0011086407,0.00021711836,0.98941934,0.008874883,0.000007150547],"about_ca_topic_score_codex":0.0012343199,"about_ca_topic_score_gemma":0.0010190994,"teacher_disagreement_score":0.019005274,"about_ca_system_score_codex":0.0015018007,"about_ca_system_score_gemma":0.00083281,"threshold_uncertainty_score":0.06357896},"labels":[],"label_agreement":null},{"id":"W2071206012","doi":"10.1109/icsssm.2005.1500163","title":"Managing hot XML data in memory for high performance","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Computer science; The Internet; XML; World Wide Web; Database","score_opus":0.030990105359809655,"score_gpt":0.27137560735178057,"score_spread":0.24038550199197092,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2071206012","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":[0.3122254,0.010208655,0.64522564,0.0011412,0.0004696258,0.0003023683,0.00053274835,0.016003838,0.013890577],"genre_scores_gemma":[0.6522577,0.0028228764,0.3277288,0.00058328424,0.0003966552,0.00027949194,0.00135615,0.0011094359,0.013465636],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991357,0.00015310517,0.00011712333,0.00011831039,0.00034363254,0.0001322379],"domain_scores_gemma":[0.9967301,0.00089936034,0.00033929414,0.0012763157,0.0006280517,0.00012675727],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008676647,0.00051039265,0.00078090944,0.0016209933,0.0010554006,0.0022204956,0.0022798965,0.00055177347,0.002353505],"category_scores_gemma":[0.0030930308,0.00046079958,0.00037361894,0.0026763615,0.00052229577,0.004103211,0.0020932935,0.0006843882,0.001122817],"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":[0.0023929523,0.00043718662,0.011383674,0.0009031717,0.00024854045,0.0015875378,0.0027659412,0.011618353,0.30467793,0.020613363,0.023176882,0.6201945],"study_design_scores_gemma":[0.0003241183,0.0011041581,0.0053990823,0.00018958698,0.0005702902,0.003232942,0.0013893537,0.1677319,0.6990372,0.021860607,0.09900146,0.00015928995],"about_ca_topic_score_codex":0.0008190949,"about_ca_topic_score_gemma":0.0016075867,"teacher_disagreement_score":0.002353505,"about_ca_system_score_codex":0.0005822506,"about_ca_system_score_gemma":0.0008528453,"threshold_uncertainty_score":0.007873297},"labels":[],"label_agreement":null},{"id":"W2071661326","doi":"10.1108/17440080810919495","title":"DTD schema: a simple but powerful XML schema language","year":2008,"lang":"en","type":"article","venue":"International Journal of Web Information Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"RELAX NG; Document Structure Description; XML Schema Editor; Computer science; XML validation; Programming language; Efficient XML Interchange; Information retrieval; XML Schema (W3C); Streaming XML; Document type definition; XML Encryption; Semi-structured model; XML; World Wide Web","score_opus":0.012081299878634738,"score_gpt":0.2603187900425474,"score_spread":0.24823749016391264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2071661326","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":[0.0013732731,0.0027140433,0.9168953,0.0028874343,0.0015965868,0.0015240383,0.024047568,0.017901018,0.031060766],"genre_scores_gemma":[0.016234322,0.0063963667,0.8673905,0.0035549097,0.00070027367,0.0026004754,0.07292103,0.0054836026,0.024718575],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9925426,0.0022406261,0.0022649483,0.0008306122,0.0018737735,0.00024739426],"domain_scores_gemma":[0.9928981,0.0021540648,0.00060892885,0.0014730928,0.0024431648,0.00042267895],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0075334096,0.0011547821,0.0013670577,0.0032481162,0.0012677973,0.007537697,0.0031966784,0.0026258766,0.017640281],"category_scores_gemma":[0.012621074,0.0010665364,0.001849858,0.0062495335,0.0011439366,0.008361352,0.0028004078,0.004000715,0.016620029],"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":[0.00031479416,0.00013920007,0.0015089292,0.0028687427,0.00019598352,0.001088161,0.0018586898,0.0049805106,0.01075876,0.36170778,0.34663048,0.26794803],"study_design_scores_gemma":[0.000058010606,0.000026820213,0.00015897733,0.00032510125,0.00003546205,0.0007332361,0.00015066277,0.0058338493,0.0026981786,0.019025646,0.9709004,0.000053538133],"about_ca_topic_score_codex":0.004306712,"about_ca_topic_score_gemma":0.0023718635,"teacher_disagreement_score":0.017640281,"about_ca_system_score_codex":0.0019633921,"about_ca_system_score_gemma":0.0048980815,"threshold_uncertainty_score":0.05901265},"labels":[],"label_agreement":null},{"id":"W2071678891","doi":"10.1504/ijbdi.2015.067567","title":"Terms analytics service for CouchDB: a document-based NoSQL","year":2015,"lang":"en","type":"article","venue":"International Journal of Big Data Intelligence","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"NoSQL; Analytics; Computer science; Database; Service (business); World Wide Web; Data science; Big data; Data mining; Business","score_opus":0.23671493802496896,"score_gpt":0.3786380129374237,"score_spread":0.14192307491245476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2071678891","genre_codex":"software","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":[0.019858018,0.00095999223,0.44750848,0.0026200663,0.0005096735,0.0016406421,0.050763372,0.44793525,0.02820451],"genre_scores_gemma":[0.3541285,0.0013819762,0.4407857,0.0031086802,0.00047605438,0.002371934,0.14247215,0.019582912,0.035692062],"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99704057,0.00031088342,0.00049319176,0.0004984019,0.0014257646,0.00023116248],"domain_scores_gemma":[0.9958039,0.0009985553,0.0003062194,0.0016139452,0.0009265443,0.00035079845],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030337782,0.000977593,0.0010856579,0.0025767402,0.0011447297,0.00467681,0.004155902,0.0015030624,0.01991238],"category_scores_gemma":[0.012230411,0.0005981133,0.00090158154,0.0032775528,0.0007654538,0.0054797945,0.004128634,0.002060641,0.009126763],"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":[0.0035805032,0.0010473207,0.011526134,0.0020060088,0.0003371081,0.0011643973,0.0018408118,0.018970866,0.034110386,0.10557592,0.423928,0.3959126],"study_design_scores_gemma":[0.0006366798,0.00035774734,0.004025633,0.00027162852,0.00013496308,0.000868821,0.0008452546,0.35076386,0.045104306,0.09982589,0.4968255,0.00033978836],"about_ca_topic_score_codex":0.009684245,"about_ca_topic_score_gemma":0.0055167223,"teacher_disagreement_score":0.01991238,"about_ca_system_score_codex":0.0017941174,"about_ca_system_score_gemma":0.0029585161,"threshold_uncertainty_score":0.066613615},"labels":[],"label_agreement":null},{"id":"W2072801150","doi":"10.4018/jdwm.2013070101","title":"Efficient Top-k Keyword Search Over Multidimensional Databases","year":2013,"lang":"en","type":"article","venue":"International Journal of Data Warehousing and Mining","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Computer science; Keyword search; Online analytical processing; Perspective (graphical); Database; Search algorithm; Search engine; Search engine indexing; Information retrieval; Data mining; Algorithm; Artificial intelligence; Data warehouse","score_opus":0.061530596177754776,"score_gpt":0.33968236031463683,"score_spread":0.27815176413688203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2072801150","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":[0.09653792,0.0052697985,0.8894861,0.00030584843,0.000086199514,0.00022443243,0.0010591398,0.0043730913,0.002657384],"genre_scores_gemma":[0.31879362,0.00153779,0.6753004,0.000097723416,0.000056276793,0.00009472139,0.001715573,0.00021527043,0.002188623],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984376,0.00027285726,0.00024732642,0.0003215265,0.000539139,0.00018155717],"domain_scores_gemma":[0.99737394,0.0011905622,0.00027128728,0.00045839525,0.00055879477,0.0001470172],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007093286,0.0009855396,0.0023283793,0.0027001037,0.0011230203,0.0017870348,0.0019190364,0.0013946216,0.0020245798],"category_scores_gemma":[0.004170898,0.00059178367,0.0010714526,0.0067504225,0.00043190195,0.004207465,0.0020140575,0.0006074101,0.0015351753],"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":[0.0009959495,0.00037258028,0.0045006676,0.0015961762,0.00034703105,0.000904004,0.0005888494,0.110216476,0.069150515,0.008340673,0.010708257,0.79227895],"study_design_scores_gemma":[0.00012132797,0.0003289997,0.0012975339,0.00004507565,0.00015943745,0.0018829524,0.00056571024,0.9332895,0.032681268,0.022339607,0.007222642,0.000065871456],"about_ca_topic_score_codex":0.0037791186,"about_ca_topic_score_gemma":0.0058948733,"teacher_disagreement_score":0.0037791186,"about_ca_system_score_codex":0.00058487145,"about_ca_system_score_gemma":0.0016469494,"threshold_uncertainty_score":0.0075142384},"labels":[],"label_agreement":null},{"id":"W2073669932","doi":"10.1145/1401890.1551568","title":"Mining Uncertain and Probabilistic Data: problems, Challenges, Methods, and Applications","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Probabilistic logic; Data mining; Data science; Artificial intelligence","score_opus":0.13922133478825938,"score_gpt":0.3494704518118307,"score_spread":0.2102491170235713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2073669932","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":[0.0076150396,0.09808051,0.8539521,0.02735211,0.0013996224,0.0002549072,0.0014725594,0.00065022294,0.009222984],"genre_scores_gemma":[0.14847238,0.176102,0.6470989,0.0027153648,0.010227528,0.00055695185,0.0044500246,0.00028996944,0.010086933],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9959329,0.0015937294,0.0002973958,0.0006013046,0.0014196893,0.00015494632],"domain_scores_gemma":[0.96626353,0.02886276,0.00079932704,0.0017829539,0.0017065551,0.0005849968],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008756975,0.0010118387,0.003032041,0.0022817021,0.0010443779,0.0058053606,0.0035976921,0.0024779167,0.009561662],"category_scores_gemma":[0.02621251,0.0009943561,0.0012875488,0.0067766863,0.0025354018,0.009103458,0.0027825322,0.0032897806,0.0037566805],"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":[0.00027939607,0.00017241204,0.005278322,0.003344305,0.00033853095,0.00060145266,0.00030347702,0.026005056,0.0020488822,0.06518976,0.066488884,0.82994944],"study_design_scores_gemma":[0.00006378461,0.00020952357,0.0036916542,0.001425573,0.00027632012,0.0026484227,0.0013420914,0.24275324,0.0029955432,0.5936723,0.15075798,0.0001635958],"about_ca_topic_score_codex":0.0014461764,"about_ca_topic_score_gemma":0.0020403613,"teacher_disagreement_score":0.009561662,"about_ca_system_score_codex":0.0007627266,"about_ca_system_score_gemma":0.0014840036,"threshold_uncertainty_score":0.046311915},"labels":[],"label_agreement":null},{"id":"W2075429730","doi":"10.1145/1151454.1151483","title":"An extensible text extraction tool for learning objects","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; XML; Interoperability; Document Structure Description; World Wide Web; Information retrieval; Context (archaeology); Information extraction; XML Base; Efficient XML Interchange; XML validation; XML framework; Document type definition","score_opus":0.010491187112095623,"score_gpt":0.2735226169605028,"score_spread":0.26303142984840716,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2075429730","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":[0.006391115,0.00043273554,0.9053619,0.00020234061,0.00013619167,0.00059032603,0.005771191,0.07703573,0.0040784236],"genre_scores_gemma":[0.035938434,0.00064403174,0.9155935,0.00023818089,0.000070111324,0.0005619526,0.02757488,0.006355868,0.013023137],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99878055,0.00014179078,0.0002919266,0.0002429937,0.00048195876,0.000060752016],"domain_scores_gemma":[0.99811625,0.00078067114,0.00018193875,0.0003349351,0.00050106103,0.000085203144],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001574631,0.0011316302,0.0008454625,0.0039766794,0.0007170226,0.0021382307,0.0017146245,0.0009543074,0.008024794],"category_scores_gemma":[0.004829873,0.0006687221,0.001069326,0.0026201634,0.00035382377,0.0032255228,0.0018897715,0.0011909452,0.006882676],"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":[0.00043159077,0.00023760571,0.002582512,0.0016524562,0.00009644452,0.0015302235,0.00089906435,0.0029841557,0.06353666,0.0146662565,0.045189388,0.86619365],"study_design_scores_gemma":[0.00026838615,0.00027096467,0.0074480046,0.00073365524,0.00023098964,0.003959738,0.0004888624,0.070712514,0.15070295,0.018425561,0.74651223,0.00024616125],"about_ca_topic_score_codex":0.0017320127,"about_ca_topic_score_gemma":0.0021272586,"teacher_disagreement_score":0.008024794,"about_ca_system_score_codex":0.00048254055,"about_ca_system_score_gemma":0.0012153683,"threshold_uncertainty_score":0.026845574},"labels":[],"label_agreement":null},{"id":"W2075872531","doi":"10.48550/arxiv.0903.4100","title":"Decentralized Management of Bi-modal Network Resources in a Distributed Stream Processing Platform","year":2009,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Modal; Computer science; Stream processing; Distributed computing; Network management; Computer network","score_opus":0.032150128383642736,"score_gpt":0.27544384714033765,"score_spread":0.24329371875669492,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2075872531","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":[0.09781383,0.00013767064,0.89928466,0.00021216841,0.000023864417,0.00010520852,0.000023641156,0.00036279653,0.0020361096],"genre_scores_gemma":[0.8038129,0.00013639519,0.19368185,0.000050916293,0.00003446089,0.00015573448,0.00004639918,0.00004161703,0.0020396402],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994293,0.00016806193,0.000029534222,0.000120395256,0.0001667221,0.000086023494],"domain_scores_gemma":[0.99927706,0.00032928106,0.00008866926,0.00013311149,0.000104723316,0.000067176494],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009650242,0.00032826426,0.00050518656,0.0003535065,0.0008365534,0.0010873496,0.0010556746,0.0004776487,0.0009313316],"category_scores_gemma":[0.00159401,0.00026025763,0.0002965056,0.00039227938,0.00073541654,0.0015808753,0.0013319656,0.00064359326,0.00017045993],"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":[0.00031392786,0.00020139074,0.0016366604,0.00010738196,0.000053244992,0.00029356623,0.0003024209,0.8162571,0.03808178,0.04586026,0.0014198576,0.095472395],"study_design_scores_gemma":[0.000015694133,0.00004157455,0.00016053513,0.0000028226561,0.000007191193,0.00003317594,0.000041581923,0.9896757,0.002687048,0.006334346,0.0009932388,0.000007089785],"about_ca_topic_score_codex":0.0013319834,"about_ca_topic_score_gemma":0.0021582074,"teacher_disagreement_score":0.0013319834,"about_ca_system_score_codex":0.00070762745,"about_ca_system_score_gemma":0.0010531624,"threshold_uncertainty_score":0.005134225},"labels":[],"label_agreement":null},{"id":"W2077439276","doi":"10.1145/1806916.1806920","title":"Exploring XML web collections with DescribeX","year":2010,"lang":"en","type":"article","venue":"ACM Transactions on the Web","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa; Carleton University; University of Toronto","funders":"","keywords":"Computer science; XPath; Document Structure Description; Information retrieval; Schema (genetic algorithms); World Wide Web; XML; XML Schema Editor; RSS; XML validation","score_opus":0.06726977821672953,"score_gpt":0.2344276321629866,"score_spread":0.16715785394625707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2077439276","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":[0.008143252,0.0015968432,0.930631,0.00081999926,0.00011022422,0.00032761408,0.003540566,0.033617083,0.021213505],"genre_scores_gemma":[0.047948018,0.0025465898,0.914193,0.00037301285,0.000079185935,0.00048775828,0.014497797,0.0074246163,0.01245006],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9986619,0.00032908647,0.0001269516,0.0002340638,0.00054247666,0.00010553],"domain_scores_gemma":[0.99865544,0.00058130926,0.00013343185,0.0003678919,0.00015510843,0.00010676268],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026952212,0.0011275096,0.0007550461,0.0035054851,0.0015726538,0.0052965307,0.0020012828,0.0010278642,0.010794095],"category_scores_gemma":[0.004557909,0.0014475342,0.0021653313,0.0035560927,0.0012902042,0.007778185,0.0070011923,0.0020687399,0.0037451643],"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":[0.00028568835,0.00022969401,0.0036463721,0.0015606357,0.00018083856,0.0024259954,0.008243144,0.022207983,0.009109743,0.61310744,0.057673167,0.28132927],"study_design_scores_gemma":[0.000054904074,0.000052289313,0.00080005155,0.00039961498,0.000050392995,0.00124298,0.0010900814,0.052256208,0.006871432,0.118960164,0.8181247,0.00009721975],"about_ca_topic_score_codex":0.0065279705,"about_ca_topic_score_gemma":0.010425012,"teacher_disagreement_score":0.010794095,"about_ca_system_score_codex":0.0011941202,"about_ca_system_score_gemma":0.0014178987,"threshold_uncertainty_score":0.036109865},"labels":[],"label_agreement":null},{"id":"W207807543","doi":"","title":"Teaching data bases with a learning tool","year":2006,"lang":"en","type":"article","venue":"Annual Conference on Computers","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Usability; Learning Management; Component (thermodynamics); Open source; Human–computer interaction; Base (topology); Multimedia; Management system; Software engineering; Operating system; Software; Engineering","score_opus":0.029293252799317576,"score_gpt":0.26606346914172657,"score_spread":0.236770216342409,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W207807543","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":[0.07116255,0.00038992098,0.7850487,0.0007977691,0.00022788148,0.00067044876,0.00092026324,0.109151684,0.031630874],"genre_scores_gemma":[0.17317596,0.0005811825,0.7487479,0.00072158943,0.00020985615,0.00073526567,0.0024018667,0.0034767943,0.069949605],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99938333,0.00009138221,0.000044795885,0.00013697309,0.00027543164,0.00006804355],"domain_scores_gemma":[0.99726886,0.0012624577,0.00013564133,0.00044040265,0.00028128194,0.0006113534],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00080560066,0.00080983964,0.0005335873,0.0008453405,0.00066457805,0.0017139006,0.0016950171,0.0010016408,0.03717967],"category_scores_gemma":[0.0036529603,0.0004477386,0.00048947905,0.00083634176,0.00023304761,0.002065589,0.0019899616,0.0012765032,0.013278005],"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":[0.00045231477,0.0012367857,0.0021594479,0.00039253477,0.000020083933,0.0005044862,0.0007669825,0.0022093595,0.04467786,0.0051528607,0.03756126,0.9048661],"study_design_scores_gemma":[0.0011819814,0.004052967,0.011258386,0.00047114183,0.00031751982,0.0053213825,0.00091992354,0.08703344,0.2087427,0.020211589,0.66008687,0.00040217923],"about_ca_topic_score_codex":0.00089974597,"about_ca_topic_score_gemma":0.0010622542,"teacher_disagreement_score":0.03717967,"about_ca_system_score_codex":0.00053172046,"about_ca_system_score_gemma":0.0010088264,"threshold_uncertainty_score":0.12437844},"labels":[],"label_agreement":null},{"id":"W2079634072","doi":"10.1016/j.jlap.2014.02.015","title":"Gunther Schmidt's life as a mathematician and computer scientist","year":2014,"lang":"en","type":"article","venue":"Journal of Logical and Algebraic Methods in Programming","topic":"Advanced Database Systems and Queries","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":"Brock University","funders":"","keywords":"Period (music); Art history; Philosophy; Epistemology; History; Aesthetics","score_opus":0.028879207341779133,"score_gpt":0.34946862807609186,"score_spread":0.32058942073431274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2079634072","genre_codex":"commentary","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":[0.005532676,0.041790675,0.03006675,0.76077646,0.050216675,0.00002856998,0.00029177405,0.0003562959,0.110940054],"genre_scores_gemma":[0.33951798,0.06750727,0.042718753,0.18076782,0.037293278,0.00015144664,0.00031193942,0.0009160215,0.33081555],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9971641,0.0008450461,0.00012804827,0.00041576003,0.0011848308,0.00026226908],"domain_scores_gemma":[0.9954657,0.0017573667,0.00021940494,0.00035081647,0.0012354512,0.00097122806],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025318014,0.00080442126,0.0007457635,0.0015707009,0.0030372473,0.0036912095,0.0007013214,0.0023260012,0.005552381],"category_scores_gemma":[0.012820152,0.0003776543,0.0003493252,0.0010859728,0.011140446,0.006389632,0.0039988,0.009005917,0.0029787645],"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":[0.00004737052,0.000019009663,0.000122060046,0.000081704005,0.000016911092,0.00010294114,0.0007466988,0.00031960756,0.00030966822,0.67765385,0.2947306,0.02584961],"study_design_scores_gemma":[0.000016393487,0.00002236625,0.00014152253,0.00013273073,0.000010397226,0.00028618507,0.0002749134,0.0005035906,0.0005774843,0.46020967,0.53777826,0.00004644314],"about_ca_topic_score_codex":0.0023027326,"about_ca_topic_score_gemma":0.0020727017,"teacher_disagreement_score":0.005552381,"about_ca_system_score_codex":0.0028047878,"about_ca_system_score_gemma":0.00366049,"threshold_uncertainty_score":0.020350218},"labels":[],"label_agreement":null},{"id":"W2079690139","doi":"10.1016/j.datak.2006.11.002","title":"Load balancing and data placement for multi-tiered database systems","year":2006,"lang":"en","type":"article","venue":"Data & Knowledge Engineering","topic":"Advanced Database Systems and Queries","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":"IBM (Canada)","funders":"","keywords":"Computer science; Database; Materialized view; View; Database server; Workload; Online analytical processing; Database tuning; Server; Table (database); IBM; Database administrator; Distributed database; Database testing; Operating system; Application server; Load balancing (electrical power); Data warehouse; Database design","score_opus":0.057066989033939385,"score_gpt":0.3019583151155923,"score_spread":0.2448913260816529,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2079690139","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":[0.22471386,0.0031204126,0.75596535,0.0015914012,0.0005190193,0.00025754134,0.0007640208,0.0060121026,0.00705633],"genre_scores_gemma":[0.8202351,0.0003839562,0.17345151,0.00018902942,0.00017669237,0.00009128208,0.0005671654,0.00031101122,0.004594261],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973677,0.00065082253,0.00033592785,0.00040128033,0.0007551654,0.00048910483],"domain_scores_gemma":[0.99510324,0.0013307884,0.0003896233,0.0016500568,0.001040132,0.00048623624],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002174549,0.0008293857,0.0011339383,0.0012545185,0.002088974,0.0033514285,0.003729957,0.0010892267,0.0050645326],"category_scores_gemma":[0.007683186,0.0009684344,0.00044479952,0.003204073,0.0007915994,0.004922389,0.0024643089,0.0009357112,0.00088389695],"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":[0.0033954685,0.00081460166,0.011480995,0.00050842855,0.00022672398,0.00045984675,0.00089061534,0.364609,0.052430127,0.027949829,0.03248292,0.5047514],"study_design_scores_gemma":[0.000103906095,0.00017617753,0.0021178958,0.000014929002,0.000069481255,0.00022324472,0.0003038031,0.962184,0.010323278,0.02082719,0.003613489,0.000042582542],"about_ca_topic_score_codex":0.0070429193,"about_ca_topic_score_gemma":0.014078478,"teacher_disagreement_score":0.0070429193,"about_ca_system_score_codex":0.0015766773,"about_ca_system_score_gemma":0.002043777,"threshold_uncertainty_score":0.01694262},"labels":[],"label_agreement":null},{"id":"W2080139625","doi":"10.1007/s10619-011-7085-8","title":"Scaling XML query processing: distribution, localization and pruning","year":2011,"lang":"en","type":"article","venue":"Distributed and Parallel Databases","topic":"Advanced Database Systems and Queries","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":"University of Waterloo","funders":"","keywords":"Computer science; Query optimization; XML database; Query plan; Sargable; Scalability; Query expansion; Query language; Information retrieval; Database; Data mining; XML; Web search query; Search engine; World Wide Web","score_opus":0.04172179025022446,"score_gpt":0.25388811319574134,"score_spread":0.21216632294551688,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2080139625","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":[0.24064867,0.0061815097,0.7250597,0.002591463,0.00039495522,0.0003173503,0.000617764,0.015361886,0.008826747],"genre_scores_gemma":[0.6888909,0.0010031975,0.30320737,0.00031528904,0.00032680423,0.0002179364,0.0010192282,0.0013685183,0.0036508585],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9933683,0.0015643644,0.00055700185,0.000995848,0.0028389315,0.0006754935],"domain_scores_gemma":[0.97683245,0.011428139,0.0010471989,0.006909888,0.0031536908,0.000628538],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0048868386,0.0014331978,0.0026056627,0.0032511172,0.001650663,0.0038636515,0.004108101,0.0014872306,0.0035795271],"category_scores_gemma":[0.028652439,0.0012025412,0.0009095823,0.0053054444,0.0014051488,0.0063958494,0.00313172,0.0021088507,0.0011180115],"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":[0.0016578225,0.0010616846,0.011299197,0.00038373965,0.00015329347,0.00023399266,0.0006536415,0.16132991,0.028289348,0.02445721,0.0194799,0.75100034],"study_design_scores_gemma":[0.00014443322,0.00013946845,0.0019725938,0.000022455099,0.00009167016,0.0002495499,0.00025965102,0.96259177,0.013676189,0.017900411,0.0029218164,0.000029962743],"about_ca_topic_score_codex":0.009337986,"about_ca_topic_score_gemma":0.012078158,"teacher_disagreement_score":0.009337986,"about_ca_system_score_codex":0.0024123508,"about_ca_system_score_gemma":0.0031101466,"threshold_uncertainty_score":0.025844395},"labels":[],"label_agreement":null},{"id":"W2080359851","doi":"10.1145/1723028.1723075","title":"The 'X' side of Cobra","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada)","funders":"","keywords":"XML; Computer science; Database; Representation (politics); Relational database; XML database; Document Structure Description; Data exchange; World Wide Web","score_opus":0.008232499006083627,"score_gpt":0.23861171159554306,"score_spread":0.23037921258945943,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2080359851","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":[0.0035923047,0.005339647,0.2362594,0.038100865,0.010578795,0.00008390099,0.00062793447,0.008788524,0.69662863],"genre_scores_gemma":[0.18557107,0.006724282,0.1823152,0.027505836,0.00537263,0.00054583134,0.0012023171,0.0095827775,0.58118004],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9954751,0.0018921744,0.00021586519,0.0009994659,0.0010067094,0.00041064853],"domain_scores_gemma":[0.9937448,0.001629514,0.00034872588,0.0025450524,0.0012904946,0.00044140383],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003064936,0.001105754,0.000796336,0.0018687148,0.0048602927,0.009795205,0.0020226634,0.00383761,0.073028564],"category_scores_gemma":[0.012124269,0.0006677687,0.00073879457,0.002330853,0.009438148,0.012502881,0.0056051095,0.0058048433,0.036465492],"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":[0.0001354803,0.000010733724,0.00019957681,0.00012290341,0.000015301872,0.00010692861,0.0008671562,0.00033473896,0.0009773051,0.867903,0.08401669,0.045310024],"study_design_scores_gemma":[0.000010184497,0.000021561364,0.00013148053,0.00012040766,0.000009770592,0.00017704976,0.00020605543,0.00046380537,0.00087960414,0.0670066,0.930948,0.000025393867],"about_ca_topic_score_codex":0.006792901,"about_ca_topic_score_gemma":0.00597749,"teacher_disagreement_score":0.073028564,"about_ca_system_score_codex":0.0015417426,"about_ca_system_score_gemma":0.0019176506,"threshold_uncertainty_score":0.2443049},"labels":[],"label_agreement":null},{"id":"W2082076097","doi":"10.1504/ijitcc.2011.042125","title":"Unordered tree matching and ordered tree matching: the evaluation of tree pattern queries","year":2011,"lang":"en","type":"article","venue":"International Journal of Information Technology Communications and Convergence","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Computer science; Tree (set theory); Descendant; Matching (statistics); Ancestor; K-ary tree; Theoretical computer science; Search tree; Set (abstract data type); Tree traversal; Tree structure; Algorithm; Mathematics; Binary tree; Combinatorics; Search algorithm","score_opus":0.037282766949322275,"score_gpt":0.2923406455522601,"score_spread":0.2550578786029378,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2082076097","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":[0.07631083,0.0019526834,0.91430634,0.00046077772,0.00010668281,0.0002321979,0.00039685718,0.0016514008,0.004582236],"genre_scores_gemma":[0.37482703,0.0007558173,0.61974806,0.00016546292,0.00011059714,0.00016379682,0.0009983813,0.0004847085,0.0027461092],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99183285,0.002969559,0.0006184688,0.0010226218,0.0030220728,0.0005343246],"domain_scores_gemma":[0.99020535,0.006442485,0.00065260375,0.0014015182,0.0010318641,0.00026600694],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004457454,0.0007736639,0.0014215696,0.002417842,0.00067795557,0.002995444,0.0027090388,0.0014648199,0.003904278],"category_scores_gemma":[0.022159355,0.00037733561,0.00075566984,0.0043980493,0.0011558281,0.011034241,0.002032863,0.0008993937,0.0007572994],"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":[0.001900583,0.0004174147,0.006863754,0.0008632494,0.0001525552,0.0005255659,0.00056387676,0.0859401,0.012856194,0.13524653,0.0062874053,0.74838275],"study_design_scores_gemma":[0.000095434836,0.00042703436,0.0014194819,0.00005731469,0.00006772269,0.0006588,0.0002938818,0.8431475,0.020501139,0.12501098,0.008278423,0.000042279626],"about_ca_topic_score_codex":0.0027773727,"about_ca_topic_score_gemma":0.0020864021,"teacher_disagreement_score":0.004457454,"about_ca_system_score_codex":0.0013557845,"about_ca_system_score_gemma":0.0015704151,"threshold_uncertainty_score":0.023573577},"labels":[],"label_agreement":null},{"id":"W2084007999","doi":"10.1109/icde.2008.4497496","title":"Multiple Materialized View Selection for XPath Query Rewriting","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":60,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Materialized view; Computer science; Rewriting; XPath; Selection (genetic algorithm); Query optimization; Heuristic; Query language; Information retrieval; Set (abstract data type); Theoretical computer science; Scheme (mathematics); View; XML; Programming language; Artificial intelligence; Mathematics; World Wide Web","score_opus":0.03289630735022392,"score_gpt":0.2594823799693533,"score_spread":0.2265860726191294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2084007999","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":[0.016038958,0.00025910506,0.9821222,0.00012080492,0.000017905224,0.000071052906,0.00003832099,0.000529116,0.00080262223],"genre_scores_gemma":[0.24214299,0.00031218628,0.7551575,0.000127571,0.0000906073,0.00013594932,0.00032943755,0.0002918306,0.0014118735],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9941723,0.0020497255,0.00045268485,0.0010008087,0.0020082905,0.00031613949],"domain_scores_gemma":[0.99234444,0.004837255,0.0004501588,0.0015728037,0.000623412,0.00017198149],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038023135,0.0008067318,0.0010923247,0.001155012,0.00073875516,0.0020083417,0.0016751632,0.0012273279,0.0015799821],"category_scores_gemma":[0.009595811,0.00049829285,0.001771151,0.0012444503,0.0015324507,0.0035733366,0.0017059775,0.001626745,0.00038377917],"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":[0.0005707044,0.0004173297,0.0039500375,0.0007971062,0.00029511206,0.0015751075,0.0025298197,0.14966445,0.095418334,0.23677704,0.004989581,0.50301546],"study_design_scores_gemma":[0.00006526848,0.00033508363,0.00062534143,0.00007172785,0.00014681167,0.00096609665,0.0003217576,0.8047341,0.059692767,0.12102303,0.011934794,0.00008317387],"about_ca_topic_score_codex":0.0018761863,"about_ca_topic_score_gemma":0.0014915095,"teacher_disagreement_score":0.0038023135,"about_ca_system_score_codex":0.0010229027,"about_ca_system_score_gemma":0.0007757047,"threshold_uncertainty_score":0.020108819},"labels":[],"label_agreement":null},{"id":"W2084932584","doi":"10.3166/isi.16.1.113-138","title":"Recommandation de requêtes dans les bases de données multidimensionnelles annotées","year":2011,"lang":"fr","type":"article","venue":"Ingénierie des systèmes d information","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Philosophy","score_opus":0.054755020784681564,"score_gpt":0.24624628908663285,"score_spread":0.1914912683019513,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2084932584","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":[0.06018582,0.0053179623,0.8696318,0.014630815,0.002132358,0.0008127087,0.009279482,0.018414494,0.019594537],"genre_scores_gemma":[0.19896708,0.0059753787,0.73563606,0.00216783,0.0009990198,0.001145525,0.033191293,0.0058795675,0.016038276],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.95947134,0.013721756,0.006064354,0.0032967234,0.016230099,0.0012157543],"domain_scores_gemma":[0.8632788,0.07920637,0.0029603748,0.023597868,0.029121691,0.001834916],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.038390804,0.0014508112,0.0015626432,0.004834551,0.002495442,0.010562149,0.0030396136,0.004877667,0.009159165],"category_scores_gemma":[0.13620482,0.0015241397,0.002283079,0.0030263024,0.0021796229,0.009660795,0.003012697,0.005419922,0.0056293043],"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":[0.0045869215,0.0010794146,0.029077385,0.004199997,0.00061136554,0.005200499,0.0065290546,0.026131228,0.07937034,0.09082605,0.0921198,0.660268],"study_design_scores_gemma":[0.0005697117,0.0005870786,0.014146213,0.002508714,0.0006018675,0.004554628,0.002745484,0.25634137,0.11414917,0.04558366,0.55768406,0.00052812416],"about_ca_topic_score_codex":0.013547365,"about_ca_topic_score_gemma":0.0115487175,"teacher_disagreement_score":0.038390804,"about_ca_system_score_codex":0.0020988889,"about_ca_system_score_gemma":0.0037961483,"threshold_uncertainty_score":0.20303237},"labels":[],"label_agreement":null},{"id":"W2085108405","doi":"10.3166/isi.13.6.85-114","title":"Impact de l'évolution de nomenclature sur le versionnement des entrepôts de données","year":2008,"lang":"fr","type":"article","venue":"Ingénierie des systèmes d information","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Nomenclature; Humanities; Philosophy; Biology; Taxonomy (biology); Zoology","score_opus":0.02926180225571575,"score_gpt":0.23848527378311704,"score_spread":0.20922347152740128,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2085108405","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":[0.76382816,0.001975654,0.22426814,0.00146783,0.00021580838,0.00011380743,0.0002446507,0.0011835054,0.0067024864],"genre_scores_gemma":[0.9362032,0.0006021374,0.06069588,0.0001485363,0.00009526425,0.000037553316,0.00022296408,0.00032868376,0.0016656987],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9805238,0.00916737,0.0018584538,0.0026459384,0.004964109,0.00084022904],"domain_scores_gemma":[0.89518124,0.07257588,0.010689737,0.013024814,0.0069136904,0.0016146632],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.020027483,0.00070836494,0.0005917721,0.0018044423,0.0014752011,0.0063603935,0.0014990496,0.0017308706,0.00087843195],"category_scores_gemma":[0.10259933,0.00071581925,0.0009180111,0.0027910953,0.0026245483,0.008123471,0.0023306534,0.0020359599,0.000196311],"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":[0.0016551204,0.0004101339,0.14116192,0.000610294,0.00041447167,0.0029157093,0.005975953,0.23232226,0.059652478,0.07948596,0.0026377134,0.47275802],"study_design_scores_gemma":[0.00010668977,0.001048431,0.059119508,0.00018317661,0.00044909932,0.00517244,0.0020545025,0.8301865,0.0557823,0.028831884,0.016821243,0.00024430477],"about_ca_topic_score_codex":0.0052060336,"about_ca_topic_score_gemma":0.0024718011,"teacher_disagreement_score":0.020027483,"about_ca_system_score_codex":0.0022742914,"about_ca_system_score_gemma":0.0013271613,"threshold_uncertainty_score":0.10591674},"labels":[],"label_agreement":null},{"id":"W2085746308","doi":"10.1108/09699980610669679","title":"Internet‐based database management system for project control","year":2006,"lang":"en","type":"article","venue":"Engineering Construction & Architectural Management","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Earned value management; Work breakdown structure; Project planning; Computer science; Schedule; Project management triangle; Project management; Integrated project delivery; Database; Procurement; Engineering management; Systems engineering; Project charter; Engineering","score_opus":0.007249666930738565,"score_gpt":0.2032218018514673,"score_spread":0.19597213492072874,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2085746308","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":[0.015776357,0.0024238352,0.8541833,0.0010224121,0.000489967,0.0011714536,0.004186306,0.08763986,0.03310658],"genre_scores_gemma":[0.38344043,0.003811105,0.51497763,0.0015684763,0.000990593,0.003124176,0.033655137,0.0029284696,0.055503946],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9971311,0.0006626623,0.00042462672,0.0005299565,0.0011033356,0.00014831456],"domain_scores_gemma":[0.9967843,0.00052467507,0.00020856911,0.0008970552,0.0012953642,0.0002900626],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003288516,0.0005658042,0.0009151402,0.0027549749,0.00086072844,0.0038762395,0.0026590822,0.0008044242,0.01365121],"category_scores_gemma":[0.0042615826,0.0004293732,0.00041794378,0.0026886887,0.00033696872,0.0030051442,0.0012593672,0.0011090307,0.009974224],"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":[0.0009887383,0.00066382706,0.0050790785,0.000553472,0.00018369354,0.0006178786,0.0004373317,0.008934601,0.024894811,0.032576233,0.18707363,0.7379967],"study_design_scores_gemma":[0.00067276694,0.00051940145,0.0070269527,0.00028391398,0.00030286887,0.0018094986,0.00029956282,0.24069385,0.055413593,0.020168036,0.67255056,0.0002590462],"about_ca_topic_score_codex":0.0020050062,"about_ca_topic_score_gemma":0.0008082318,"teacher_disagreement_score":0.01365121,"about_ca_system_score_codex":0.00095585216,"about_ca_system_score_gemma":0.0014874118,"threshold_uncertainty_score":0.045667887},"labels":[],"label_agreement":null},{"id":"W2086395677","doi":"10.1007/s00778-011-0217-y","title":"Interaction-aware scheduling of report-generation workloads","year":2011,"lang":"en","type":"article","venue":"The VLDB Journal","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":40,"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; Online aggregation; Query optimization; View; Sargable; Scheduling (production processes); Web query classification; Leverage (statistics); Query language; IBM; Database; Workload; Query plan; Query expansion; Web search query; Data mining; Database design; Information retrieval; Search engine; Artificial intelligence; Operating system","score_opus":0.08655948616922705,"score_gpt":0.28821611297236155,"score_spread":0.2016566268031345,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2086395677","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":[0.72043467,0.0017528486,0.24368863,0.00094274775,0.0006094374,0.0002993814,0.00066831324,0.018971585,0.01263237],"genre_scores_gemma":[0.95880103,0.00012195652,0.038339566,0.00009190742,0.0001373195,0.000053666725,0.0005850564,0.00047354688,0.001395902],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974306,0.0007958046,0.0001865725,0.00032359487,0.00078173535,0.00048164625],"domain_scores_gemma":[0.99339503,0.0023788286,0.0005509715,0.0017061596,0.0011620172,0.00080691214],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019992096,0.0010376243,0.000960589,0.001026904,0.001039119,0.0018448435,0.0028677206,0.0005770706,0.002662172],"category_scores_gemma":[0.0080983825,0.0006900636,0.00041305143,0.0014221133,0.00036072533,0.0014760372,0.0013627842,0.00094069866,0.0008115894],"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":[0.011424339,0.0023598988,0.023058187,0.0005415319,0.00038449978,0.00100653,0.0017039904,0.26339033,0.2231225,0.010653922,0.04473553,0.4176187],"study_design_scores_gemma":[0.00014260312,0.00048778526,0.004331651,0.000011437146,0.00009833279,0.00018002777,0.00021982494,0.9587099,0.027297089,0.0026872733,0.005780621,0.00005346302],"about_ca_topic_score_codex":0.0030076755,"about_ca_topic_score_gemma":0.0064385813,"teacher_disagreement_score":0.0030076755,"about_ca_system_score_codex":0.000745464,"about_ca_system_score_gemma":0.0022791256,"threshold_uncertainty_score":0.01057297},"labels":[],"label_agreement":null},{"id":"W2087413773","doi":"10.1002/spe.724","title":"Declarative generation of synthetic XML data","year":2006,"lang":"en","type":"article","venue":"Software Practice and Experience","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University of Calgary","funders":"","keywords":"Computer science; XML; Benchmarking; XML Schema (W3C); Programming language; Schema (genetic algorithms); Synthetic data; Generator (circuit theory); Software engineering; XML validation; Information retrieval; Artificial intelligence; World Wide Web; Document type definition","score_opus":0.05494910959855257,"score_gpt":0.31884425796099464,"score_spread":0.26389514836244204,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2087413773","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":[0.06975999,0.000072485826,0.9070699,0.00041268877,0.00011429142,0.00064061047,0.0047410466,0.011978324,0.0052107116],"genre_scores_gemma":[0.36403987,0.00016222261,0.60951954,0.00029458487,0.00003243001,0.0012354876,0.019368608,0.002141758,0.0032055676],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99695253,0.0011887032,0.00031304525,0.00032088635,0.0011062089,0.000118575874],"domain_scores_gemma":[0.9845674,0.009473197,0.00067439384,0.0029408091,0.00209332,0.00025093323],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005199251,0.0004927017,0.0003774639,0.00079952495,0.00041900313,0.0018435812,0.0019217164,0.00096470705,0.0028794473],"category_scores_gemma":[0.018570714,0.00047695462,0.0005718387,0.0009604544,0.00095720316,0.0013001665,0.0014731459,0.0009778161,0.0007478401],"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":[0.00079202,0.000695057,0.012469981,0.0010454959,0.00015361105,0.0024830478,0.0023558466,0.5390909,0.03880213,0.18155588,0.04096158,0.1795944],"study_design_scores_gemma":[0.000121593,0.00017061445,0.00076230883,0.000072636,0.00002272188,0.00045051047,0.0002967685,0.8721011,0.050308403,0.031319402,0.044321954,0.000051999796],"about_ca_topic_score_codex":0.0014685113,"about_ca_topic_score_gemma":0.0011530004,"teacher_disagreement_score":0.005199251,"about_ca_system_score_codex":0.00067097176,"about_ca_system_score_gemma":0.0011648546,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W2089118216","doi":"10.1145/1099554.1099603","title":"Typed functional query languages with equational specifications","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Query language; Equivalence (formal languages); Query optimization; RDF query language; Programming language; Query expansion; Sargable; Pattern matching; Type (biology); Theoretical computer science; Web search query; Web query classification; Database; Information retrieval; Mathematics; Discrete mathematics; Search engine","score_opus":0.04185926145607038,"score_gpt":0.24844462013143964,"score_spread":0.20658535867536926,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2089118216","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":[0.0013722472,0.00021953568,0.99338657,0.00065695884,0.00007076147,0.000075862845,0.00014539955,0.0004710977,0.0036015953],"genre_scores_gemma":[0.090278566,0.0010515127,0.8955016,0.0011456473,0.00036665486,0.0007179554,0.0011407766,0.00051933975,0.009277996],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9883818,0.004176887,0.0020256874,0.0012225042,0.0035039282,0.0006891621],"domain_scores_gemma":[0.98814595,0.0057216054,0.0011553955,0.0022050447,0.0024601961,0.0003118427],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009892668,0.0016149537,0.0010663855,0.0025272258,0.0016475728,0.0060048504,0.0043615643,0.0027716323,0.0066576703],"category_scores_gemma":[0.016923726,0.0017415483,0.0039656362,0.0037906815,0.005791597,0.015790155,0.0045547322,0.0051785335,0.002276802],"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":[0.000012002195,0.000016619977,0.000092326554,0.00005980017,0.000010914428,0.00008133109,0.0003893348,0.003374765,0.0003954869,0.98847467,0.0010180571,0.0060747797],"study_design_scores_gemma":[0.000035025347,0.00003226083,0.000053736956,0.00006857709,0.000049265454,0.00020569327,0.00016238735,0.050829373,0.0014637893,0.9026935,0.04436301,0.000043413762],"about_ca_topic_score_codex":0.006731414,"about_ca_topic_score_gemma":0.004306203,"teacher_disagreement_score":0.009892668,"about_ca_system_score_codex":0.0033556311,"about_ca_system_score_gemma":0.0032760766,"threshold_uncertainty_score":0.052318096},"labels":[],"label_agreement":null},{"id":"W2089247150","doi":"10.1145/2602622.2602624","title":"Automated schema design for NoSQL databases","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"NoSQL; Computer science; Schema (genetic algorithms); Schema evolution; Schema migration; Database schema; Database; Materialized view; Conceptual schema; Star schema; Workload; Relational database; View; Information retrieval; Data mining; Semi-structured model; Database design; Scalability; Operating system; Gender schema theory","score_opus":0.052117208545980745,"score_gpt":0.30193147865512404,"score_spread":0.2498142701091433,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2089247150","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":[0.01138988,0.0002912327,0.9816595,0.0004648888,0.000038405793,0.00032708154,0.00032402095,0.0041101114,0.0013948082],"genre_scores_gemma":[0.13162875,0.00039284548,0.8645381,0.00020706694,0.00003371396,0.00032338113,0.0010979172,0.0006517242,0.0011265001],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9952663,0.0016225905,0.0007126198,0.00042899064,0.0017639428,0.00020561102],"domain_scores_gemma":[0.99223435,0.0022805058,0.0006205303,0.0026260968,0.0020505849,0.00018801501],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0054668295,0.00046599156,0.00055829843,0.0008253094,0.0006390334,0.0031248648,0.0019413502,0.00083855813,0.0021125467],"category_scores_gemma":[0.012668623,0.0007934818,0.00092013826,0.0012842561,0.00072487304,0.003391356,0.0019081687,0.0012939168,0.0006680698],"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":[0.00054651534,0.00035881824,0.008152635,0.0011103059,0.0002458811,0.0006678164,0.0013838249,0.16163178,0.07907246,0.2300207,0.021233914,0.4955753],"study_design_scores_gemma":[0.00013134787,0.00010487076,0.00079036294,0.00012281688,0.000088536966,0.00038964365,0.00033176626,0.7577044,0.05705085,0.1178087,0.06541438,0.00006235677],"about_ca_topic_score_codex":0.0012106362,"about_ca_topic_score_gemma":0.001789487,"teacher_disagreement_score":0.0054668295,"about_ca_system_score_codex":0.0009895581,"about_ca_system_score_gemma":0.001600209,"threshold_uncertainty_score":0.02891171},"labels":[],"label_agreement":null},{"id":"W2089760975","doi":"10.1007/s00778-004-0122-8","title":"Views as first-class citizens in object-oriented databases","year":2004,"lang":"en","type":"article","venue":"The VLDB Journal","topic":"Advanced Database Systems and Queries","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":"University of Calgary","funders":"","keywords":"Class hierarchy; Hierarchy; Computer science; Class (philosophy); Schema (genetic algorithms); Object (grammar); Set (abstract data type); Schema evolution; Theoretical computer science; Human–computer interaction; Object-oriented programming; Programming language; Artificial intelligence; Database; Information retrieval; Database schema","score_opus":0.02986945958720896,"score_gpt":0.28454405881404765,"score_spread":0.2546745992268387,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2089760975","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":[0.19061737,0.0020822543,0.77086574,0.0025834015,0.00065592723,0.00017824875,0.00066506595,0.006080424,0.026271597],"genre_scores_gemma":[0.7595986,0.0017670416,0.21117009,0.0008205549,0.00056480634,0.00024882628,0.0014980092,0.0024654085,0.021866696],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99549156,0.0011289204,0.0004489597,0.000871233,0.0013526118,0.0007067946],"domain_scores_gemma":[0.9896192,0.004869935,0.0007428275,0.0029544325,0.0010494305,0.00076411647],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006009543,0.00044762317,0.0015850156,0.0017610824,0.0028758144,0.0150961755,0.0019995635,0.0030050871,0.0031068265],"category_scores_gemma":[0.015039048,0.001656742,0.0013991859,0.0025807042,0.0050395885,0.022679867,0.0041513424,0.0038666867,0.0011311345],"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":[0.0001874251,0.00007430781,0.0034237432,0.000085483895,0.000025843125,0.00030144156,0.0029117512,0.0013022927,0.0015734632,0.94864213,0.00336044,0.038111676],"study_design_scores_gemma":[0.00008211709,0.00008163509,0.0008343121,0.00010101962,0.00016145289,0.0005127035,0.0012203876,0.016339907,0.006954972,0.91777897,0.055866003,0.00006647584],"about_ca_topic_score_codex":0.003113034,"about_ca_topic_score_gemma":0.0029866688,"teacher_disagreement_score":0.0150961755,"about_ca_system_score_codex":0.0018259387,"about_ca_system_score_gemma":0.002179459,"threshold_uncertainty_score":0.03178191},"labels":[],"label_agreement":null},{"id":"W2090057889","doi":"10.1145/2513190.2513203","title":"Lazy data structure maintenance for main-memory analytics over sliding windows","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Overhead (engineering); Sliding window protocol; Data structure; Address space; Parallel computing; Operating system; Window (computing)","score_opus":0.031241954301242422,"score_gpt":0.2713907305566817,"score_spread":0.2401487762554393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2090057889","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":[0.0781772,0.0010488098,0.9116205,0.00025332303,0.000060407703,0.00012775254,0.00015018528,0.007936343,0.0006254505],"genre_scores_gemma":[0.5337548,0.00045776993,0.46307692,0.00010649739,0.00008207786,0.00012509317,0.00035666238,0.0005786884,0.0014614792],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983535,0.00026404843,0.00019651552,0.00034969594,0.00065326074,0.00018303048],"domain_scores_gemma":[0.99134773,0.0022240884,0.0010741926,0.0042441,0.0008245448,0.0002852793],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022042622,0.00058954867,0.0009495658,0.0012132949,0.0010070187,0.001999668,0.0035087662,0.00071644026,0.0010194018],"category_scores_gemma":[0.00890889,0.0005806612,0.0005584251,0.0020086418,0.0011963522,0.006400509,0.0022691004,0.0014433216,0.00045814714],"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":[0.0012175352,0.0005046588,0.014753207,0.0005664835,0.0001945312,0.0004942573,0.0017514355,0.09161965,0.10502831,0.057285342,0.011551234,0.71503335],"study_design_scores_gemma":[0.00014540566,0.0004953252,0.0024449704,0.000059554684,0.00017371603,0.0006280976,0.0003045994,0.84667706,0.10559868,0.030946877,0.012441488,0.00008424805],"about_ca_topic_score_codex":0.0033966156,"about_ca_topic_score_gemma":0.0034237877,"teacher_disagreement_score":0.0035087662,"about_ca_system_score_codex":0.00085243507,"about_ca_system_score_gemma":0.001969371,"threshold_uncertainty_score":0.011657417},"labels":[],"label_agreement":null},{"id":"W2090154982","doi":"10.1145/357775.357778","title":"Emancipating instances from the tyranny of classes in information modeling","year":2000,"lang":"en","type":"article","venue":"ACM Transactions on Database Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":165,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Schema (genetic algorithms); Interoperability; Relational database; Class (philosophy); Semi-structured model; Theoretical computer science; Information schema; Data mining; Information retrieval; Artificial intelligence; Database model; World Wide Web","score_opus":0.0253603979568016,"score_gpt":0.2532512764296321,"score_spread":0.2278908784728305,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2090154982","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":[0.01777291,0.008733952,0.78210175,0.106151566,0.0013580264,0.00006673618,0.00011881284,0.0003500306,0.083346196],"genre_scores_gemma":[0.5990382,0.010864572,0.35529315,0.015359718,0.0028624907,0.0005916795,0.00023724408,0.00063256756,0.015120401],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9847799,0.008661253,0.0008816159,0.0019234713,0.003014071,0.00073969853],"domain_scores_gemma":[0.9756977,0.014712992,0.0011553179,0.006333902,0.0013865614,0.0007134534],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01802305,0.00082204404,0.0010823683,0.0025143584,0.0036317965,0.0139512755,0.0026584577,0.0056157904,0.0016046552],"category_scores_gemma":[0.02406001,0.0008786718,0.0014480575,0.0031510482,0.039993867,0.02947354,0.01135887,0.01372405,0.0007311671],"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":[0.000006006442,0.000003904168,0.00014207815,0.000015737502,0.0000037507361,0.000020069823,0.0013238929,0.00035402476,0.0000392839,0.9928981,0.000811284,0.0043818406],"study_design_scores_gemma":[0.000005915294,0.000006610186,0.00006721102,0.00006644332,0.000006217553,0.00004872068,0.00033425668,0.0030968385,0.00018000379,0.9585594,0.037616678,0.000011797189],"about_ca_topic_score_codex":0.006898737,"about_ca_topic_score_gemma":0.0038499339,"teacher_disagreement_score":0.01802305,"about_ca_system_score_codex":0.0052975686,"about_ca_system_score_gemma":0.0039129388,"threshold_uncertainty_score":0.09531611},"labels":[],"label_agreement":null},{"id":"W2091298248","doi":"10.1145/1321440.1321572","title":"Ix-cubes","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Online analytical processing; Computer science; XML database; XML Schema Editor; Streaming XML; XML; Data cube; Database; Information retrieval; Cube (algebra); Relational database; XML Schema (W3C); Efficient XML Interchange; Data warehouse; Data mining; XML Encryption; World Wide Web; Mathematics","score_opus":0.011768887893049319,"score_gpt":0.258167998344998,"score_spread":0.24639911045194868,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091298248","genre_codex":"methods","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":[0.014439257,0.0017112661,0.93449485,0.0010625138,0.00041272712,0.00043659614,0.006020785,0.0029245308,0.038497485],"genre_scores_gemma":[0.19249994,0.0038296962,0.75941765,0.00090442965,0.00033123462,0.00092076504,0.01907334,0.00057991646,0.02244301],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99672735,0.00048039705,0.00037507765,0.0004558606,0.0016431584,0.0003181097],"domain_scores_gemma":[0.99750704,0.0004988643,0.00021611176,0.00068155257,0.00091805944,0.00017850685],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015290471,0.0011173477,0.0011634617,0.0014054753,0.0011381436,0.004883711,0.0024730111,0.0008925476,0.013075227],"category_scores_gemma":[0.005704636,0.0005037251,0.0016941138,0.0039656875,0.0009952423,0.005295338,0.004824057,0.0019460318,0.004656482],"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":[0.0005612701,0.00012440806,0.0027251989,0.0006660371,0.00018389356,0.00055282225,0.00046585762,0.09130791,0.0056692734,0.57157445,0.05050494,0.2756639],"study_design_scores_gemma":[0.00007870955,0.00014566783,0.0006003806,0.0001584074,0.00006193758,0.0007389126,0.0005153903,0.22621085,0.007484688,0.54545176,0.21849169,0.00006169652],"about_ca_topic_score_codex":0.0033272917,"about_ca_topic_score_gemma":0.0027635137,"teacher_disagreement_score":0.013075227,"about_ca_system_score_codex":0.001237027,"about_ca_system_score_gemma":0.00184476,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W2091367497","doi":"10.1002/bult.2007.1720330604","title":"Functional requirements for bibliographic records: Introducing the <i>Functional Requirements for Bibliographic Records</i> and related IFLA developments","year":2007,"lang":"en","type":"article","venue":"Bulletin of the American Society for Information Science and Technology","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bibliothèque et Archives nationales du Québec","funders":"","keywords":"Context (archaeology); Computer science; Set (abstract data type); Function (biology); Functional requirement; Information retrieval; Cataloging; Work (physics); World Wide Web; Data science; Software engineering; Engineering; Geography","score_opus":0.019361649279314178,"score_gpt":0.2611635095578213,"score_spread":0.24180186027850714,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091367497","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":[0.0070938175,0.019032605,0.7842166,0.062399484,0.0034948876,0.0012836898,0.0010524378,0.0012425822,0.12018388],"genre_scores_gemma":[0.07869185,0.015445902,0.8690017,0.008225596,0.0034242456,0.0018238607,0.0015936209,0.0006411237,0.021152096],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.94857883,0.022294566,0.0060009193,0.0030341523,0.017915105,0.002176469],"domain_scores_gemma":[0.9177645,0.04664685,0.0064877653,0.0059671164,0.021112414,0.002021385],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.03706334,0.0016261155,0.0011458036,0.010299941,0.004683865,0.017165693,0.0051730485,0.008634446,0.007615377],"category_scores_gemma":[0.054393873,0.0017914915,0.0034886254,0.009542011,0.013958014,0.025106536,0.009975416,0.010874488,0.004017669],"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":[0.00003914654,0.00015194317,0.0016503652,0.0010617641,0.00002809082,0.0005273093,0.005672966,0.002392349,0.0017828634,0.89649224,0.018279226,0.07192165],"study_design_scores_gemma":[0.000019362195,0.00017223829,0.0015522053,0.0026104324,0.000031322976,0.0013498588,0.0034234778,0.007805168,0.0013738195,0.21121822,0.77030766,0.00013627885],"about_ca_topic_score_codex":0.015966328,"about_ca_topic_score_gemma":0.008025326,"teacher_disagreement_score":0.9828343,"about_ca_system_score_codex":0.010333866,"about_ca_system_score_gemma":0.012307276,"threshold_uncertainty_score":0.19601202},"labels":[],"label_agreement":null},{"id":"W2092324613","doi":"10.1007/s007780200062","title":"Query processing techniques for arrays","year":2002,"lang":"en","type":"article","venue":"The VLDB Journal","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":64,"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; Variety (cybernetics); Class (philosophy); Rewriting; Query plan; Function (biology); Query optimization; Data structure; Space (punctuation); Theoretical computer science; Programming language; Database; Information retrieval; Sargable; Artificial intelligence; Search engine; Web search query","score_opus":0.03430227086175861,"score_gpt":0.26878400891824294,"score_spread":0.23448173805648434,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2092324613","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":[0.0033363132,0.0030606273,0.9804765,0.0006342405,0.00023079515,0.000092455375,0.00033775563,0.0047589205,0.0070723137],"genre_scores_gemma":[0.10462277,0.004929546,0.8683001,0.0007808017,0.00093359576,0.0003516893,0.0019071298,0.001864398,0.016309945],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99543875,0.0008560827,0.0005256697,0.00072048017,0.0020235314,0.00043549473],"domain_scores_gemma":[0.9947647,0.002037353,0.0002332329,0.0019192114,0.0009383738,0.00010709499],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024668844,0.0013682703,0.0018086237,0.0029300442,0.00203488,0.0053291684,0.0029009902,0.0011948927,0.011534825],"category_scores_gemma":[0.009459683,0.0012049025,0.0019936801,0.0069329003,0.0017547373,0.009747375,0.0033060263,0.0034541965,0.006127321],"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":[0.00048386081,0.00012737073,0.0008632146,0.00091000594,0.00019271807,0.00023084237,0.0010022096,0.010671038,0.0155230565,0.3672738,0.049470432,0.55325145],"study_design_scores_gemma":[0.00014167937,0.00019984301,0.00052650966,0.00019379794,0.0003040991,0.0008597743,0.00046223417,0.13355885,0.029189147,0.67695284,0.15750052,0.00011069983],"about_ca_topic_score_codex":0.0024982851,"about_ca_topic_score_gemma":0.0021155071,"teacher_disagreement_score":0.011534825,"about_ca_system_score_codex":0.0010956445,"about_ca_system_score_gemma":0.0011589554,"threshold_uncertainty_score":0.03858787},"labels":[],"label_agreement":null},{"id":"W2094817912","doi":"10.1145/1084805.1084825","title":"Exchange, integration, and consistency of data","year":2005,"lang":"en","type":"article","venue":"ACM SIGMOD Record","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"IBM (Canada); University of Victoria; York University; Carleton University","funders":"","keywords":"Computer science; IBM; Data exchange; Consistency (knowledge bases); Data consistency; Data integration; Database; Operating system; Programming language","score_opus":0.057434164822293146,"score_gpt":0.30152373536708393,"score_spread":0.2440895705447908,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2094817912","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":[0.022291671,0.003637989,0.95303833,0.0064801956,0.00054905465,0.0004606436,0.00069936836,0.002432297,0.010410481],"genre_scores_gemma":[0.29433817,0.003682106,0.68176824,0.0021059362,0.00090121146,0.00093247415,0.0047614407,0.0019388427,0.009571611],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9025375,0.03998942,0.012523609,0.011771278,0.028909812,0.00426837],"domain_scores_gemma":[0.80970275,0.043451875,0.010209693,0.11412131,0.020086598,0.0024277947],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.07596805,0.0010237952,0.0025939397,0.0056424704,0.00474472,0.025118962,0.0076039303,0.0045179715,0.0029262714],"category_scores_gemma":[0.20889042,0.0031258424,0.0021165975,0.009057824,0.009996237,0.035976518,0.019499104,0.006687119,0.0028412626],"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":[0.0005237047,0.00027824295,0.013101656,0.00057243224,0.0003010116,0.0005579981,0.0054144617,0.012786256,0.0041040266,0.7287231,0.018054422,0.2155827],"study_design_scores_gemma":[0.00017890455,0.0001910155,0.002651162,0.0005086768,0.00033320874,0.0010372677,0.0013897496,0.042735014,0.012291938,0.8173557,0.12114097,0.00018643712],"about_ca_topic_score_codex":0.005371878,"about_ca_topic_score_gemma":0.0023625395,"teacher_disagreement_score":0.07596805,"about_ca_system_score_codex":0.0027142975,"about_ca_system_score_gemma":0.00981249,"threshold_uncertainty_score":0.40176225},"labels":[],"label_agreement":null},{"id":"W2096077069","doi":"10.1109/hicss.1991.184165","title":"Semantic query optimization using inter-relational functional dependencies","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Functional dependency; Computer science; Dependency (UML); Query optimization; Relational database; Dependency theory (database theory); Relational model; Sargable; Extension (predicate logic); Codd's theorem; Process (computing); Relational calculus; Information retrieval; Theoretical computer science; Data mining; Artificial intelligence; Programming language; Web search query; Search engine","score_opus":0.06303274988772185,"score_gpt":0.23498745314933142,"score_spread":0.17195470326160955,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2096077069","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":[0.0036810413,0.00008337906,0.9903758,0.00049010466,0.000025474323,0.00008766346,0.00011550948,0.00052975176,0.004611294],"genre_scores_gemma":[0.17619805,0.00045984317,0.81484914,0.0004916577,0.000113958944,0.00024781685,0.0010605253,0.00037484552,0.0062042014],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99421835,0.001993907,0.0004469702,0.00071763544,0.0023124765,0.00031067643],"domain_scores_gemma":[0.9944371,0.0032199328,0.00033673964,0.0010668084,0.00087577157,0.0000635076],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003849976,0.0008171728,0.00076399744,0.0014776714,0.0011187978,0.0021163004,0.0019987025,0.0010241697,0.003960182],"category_scores_gemma":[0.0094357105,0.0005639134,0.0015595885,0.0017462149,0.0025936535,0.005392935,0.0025992475,0.0023941374,0.0011422836],"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":[0.0001284677,0.00011363572,0.0007459262,0.0003460078,0.00008658918,0.0006792708,0.0006317525,0.07082769,0.015453564,0.70545113,0.010501465,0.19503458],"study_design_scores_gemma":[0.00004065615,0.00007478159,0.0005044637,0.00006840233,0.000093355826,0.0006631404,0.00020910456,0.5440021,0.029821008,0.36878622,0.055658333,0.000078400866],"about_ca_topic_score_codex":0.0028969902,"about_ca_topic_score_gemma":0.0051313206,"teacher_disagreement_score":0.003960182,"about_ca_system_score_codex":0.001483808,"about_ca_system_score_gemma":0.0017446679,"threshold_uncertainty_score":0.020360887},"labels":[],"label_agreement":null},{"id":"W2096195970","doi":"10.1109/cyberc.2010.17","title":"Unordered Tree Matching and Strict Unordered Tree Matching: The Evaluation of Tree Pattern Queries","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Computer science; Tree (set theory); Search tree; K-ary tree; Matching (statistics); Search engine indexing; Interval tree; XML; Segment tree; Pattern matching; Fractal tree index; Node (physics); B-tree; Theoretical computer science; Tree structure; Algorithm; Combinatorics; Mathematics; Binary tree; Search algorithm; Artificial intelligence","score_opus":0.027696717646224587,"score_gpt":0.2851073827450467,"score_spread":0.2574106650988221,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2096195970","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":[0.066186845,0.0009390891,0.92432684,0.00088961463,0.00015442226,0.00055547385,0.00047280974,0.0012635005,0.0052113635],"genre_scores_gemma":[0.30066252,0.00050584006,0.6927476,0.00040640487,0.00012958936,0.0002935663,0.0011569323,0.00044282633,0.0036546784],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9930964,0.0018612567,0.00075804535,0.0009486177,0.002672343,0.00066336605],"domain_scores_gemma":[0.99132943,0.0049531874,0.00064646726,0.0016203191,0.0010703084,0.0003803587],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003538811,0.0007086759,0.00119409,0.0013388493,0.0010024756,0.0024410367,0.0026092662,0.0015759771,0.003946061],"category_scores_gemma":[0.016276307,0.00042106948,0.0010448362,0.0026932124,0.0013479642,0.010693646,0.0023716989,0.0012897354,0.0005302598],"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":[0.0018006802,0.0006937757,0.006375366,0.0013210317,0.00017443374,0.0011284505,0.0008491385,0.0808977,0.025023883,0.16925384,0.0124489125,0.70003283],"study_design_scores_gemma":[0.00016229745,0.000603056,0.0020018702,0.000114080256,0.00010814311,0.0013423077,0.00065381237,0.7212795,0.040005613,0.21368444,0.019942544,0.000102377686],"about_ca_topic_score_codex":0.0030850044,"about_ca_topic_score_gemma":0.0036663255,"teacher_disagreement_score":0.003946061,"about_ca_system_score_codex":0.0011933094,"about_ca_system_score_gemma":0.0018228559,"threshold_uncertainty_score":0.018715262},"labels":[],"label_agreement":null},{"id":"W2097000000","doi":"10.1109/icde.2005.110","title":"Predicate Derivation and Monotonicity Detection in DB2 UDB","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada)","funders":"","keywords":"Computer science; Predicate (mathematical logic); Rewriting; Schema (genetic algorithms); Search engine indexing; Database; Data mining; Programming language; Information retrieval","score_opus":0.00816891070638493,"score_gpt":0.2266155199875499,"score_spread":0.21844660928116497,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097000000","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":[0.030804262,0.00086725445,0.9352693,0.0009188503,0.00011654407,0.000363307,0.0011894372,0.02159428,0.00887674],"genre_scores_gemma":[0.24109079,0.00070701377,0.74077004,0.0011613909,0.00013212327,0.0005094382,0.0052953768,0.004163983,0.006169825],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9860663,0.0036413085,0.0015147694,0.0013313771,0.0066738934,0.0007723599],"domain_scores_gemma":[0.990213,0.0034728758,0.0005791168,0.003294148,0.0022138855,0.00022705745],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007903458,0.0007372863,0.0013440946,0.002379357,0.0018187005,0.004802103,0.0032794976,0.0011625268,0.0022456783],"category_scores_gemma":[0.017775178,0.0015495546,0.0013214881,0.0027477175,0.0018979143,0.0061792876,0.0049731843,0.0023905435,0.0018500807],"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":[0.00079584465,0.0005085477,0.011679699,0.000765568,0.00014247665,0.0014774324,0.0021606751,0.026574405,0.050730947,0.33338344,0.03494434,0.53683674],"study_design_scores_gemma":[0.00016321352,0.00012504209,0.0021080016,0.00013516741,0.000121800826,0.0012565133,0.00046476896,0.5392801,0.17493227,0.14660648,0.13459693,0.00020976187],"about_ca_topic_score_codex":0.008753213,"about_ca_topic_score_gemma":0.006883119,"teacher_disagreement_score":0.008753213,"about_ca_system_score_codex":0.0020288986,"about_ca_system_score_gemma":0.0030760816,"threshold_uncertainty_score":0.041797996},"labels":[],"label_agreement":null},{"id":"W2097363104","doi":"10.1109/coopis.1996.555013","title":"A generic integration architecture for cooperative information systems","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Reference architecture; Software engineering; Architecture; Applications architecture; Schema (genetic algorithms); Data architecture; Information integration; Data integration; Software architecture; Software; Database; Programming language; Information retrieval","score_opus":0.02097674779765135,"score_gpt":0.22905456650459927,"score_spread":0.20807781870694791,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097363104","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":[0.0068520275,0.00036588692,0.98056006,0.00050587876,0.000061069266,0.00019010896,0.000068671456,0.0025938863,0.008802436],"genre_scores_gemma":[0.12796752,0.00086367596,0.8633545,0.00036522484,0.000066988876,0.00032266995,0.0007652898,0.00022025887,0.006073779],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99801123,0.00041170453,0.00024231728,0.00038092493,0.00065875455,0.0002950246],"domain_scores_gemma":[0.99902153,0.00008073835,0.00008576514,0.00034816668,0.00033710574,0.00012665719],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027215756,0.00061186467,0.0005558395,0.0013438247,0.0013097379,0.003727914,0.0018279812,0.002450283,0.0020064865],"category_scores_gemma":[0.0024087615,0.00065368315,0.0012330326,0.0020215702,0.0019808344,0.0039834976,0.003147716,0.0018753044,0.0010454028],"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":[0.00007738602,0.00010264358,0.0016635937,0.0003740151,0.00009984781,0.00068457867,0.0015407208,0.03941085,0.01642452,0.8078462,0.010914871,0.12086071],"study_design_scores_gemma":[0.00007726014,0.00025717926,0.0018714544,0.00037791097,0.0002156451,0.0021919743,0.00053802156,0.28143144,0.010356675,0.35423926,0.348297,0.00014629203],"about_ca_topic_score_codex":0.004222363,"about_ca_topic_score_gemma":0.004158277,"teacher_disagreement_score":0.004222363,"about_ca_system_score_codex":0.0014386161,"about_ca_system_score_gemma":0.002332407,"threshold_uncertainty_score":0.01439327},"labels":[],"label_agreement":null},{"id":"W2097966074","doi":"10.1109/cmpsac.1989.65088","title":"On schema integration in a heterogeneous distributed database management system","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Schema (genetic algorithms); Distributed database; Database schema; Database; Schema evolution; Data integration; Data management; Database design; Semi-structured model; Information retrieval","score_opus":0.013913153354353617,"score_gpt":0.2413801723619476,"score_spread":0.22746701900759397,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097966074","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":[0.0063393107,0.0034592436,0.96565473,0.002972388,0.0002756695,0.00017616569,0.000042400497,0.00058473554,0.020495428],"genre_scores_gemma":[0.10971586,0.008252711,0.85965544,0.0021539067,0.00056540046,0.0004910387,0.00033789448,0.0003507283,0.018477025],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99471045,0.0020482014,0.00033058436,0.00044531337,0.0021545894,0.00031081628],"domain_scores_gemma":[0.9981559,0.0006883991,0.00010467437,0.00043024842,0.00044772497,0.00017301507],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004986181,0.00057825545,0.0008162996,0.0013690172,0.0019424775,0.0067198793,0.0021760697,0.0025334756,0.0028826308],"category_scores_gemma":[0.00550831,0.0009629714,0.0012652706,0.0027818414,0.0035237083,0.009069437,0.0044090855,0.0038866117,0.0012075366],"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":[0.00010283093,0.00015563253,0.0007886461,0.00028164755,0.000069235815,0.0010439476,0.0023148083,0.017256578,0.006005176,0.8594011,0.008862526,0.103717916],"study_design_scores_gemma":[0.00010618434,0.00022391118,0.0005267775,0.0005095133,0.00018428708,0.002204791,0.0010465556,0.15831701,0.009296473,0.51548815,0.31200132,0.00009496886],"about_ca_topic_score_codex":0.0027444751,"about_ca_topic_score_gemma":0.0026722497,"teacher_disagreement_score":0.0067198793,"about_ca_system_score_codex":0.0015326178,"about_ca_system_score_gemma":0.0017475802,"threshold_uncertainty_score":0.02636975},"labels":[],"label_agreement":null},{"id":"W2098375495","doi":"10.1109/icsssm.2007.4280189","title":"A High Performance Architecture for Web Service Systems in XML","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Computer science; Web service; XML; The Internet; World Wide Web; Efficient XML Interchange; SOAP; WS-Policy; Database; Web development; Web application security","score_opus":0.011671796838651691,"score_gpt":0.23672073104028124,"score_spread":0.22504893420162955,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2098375495","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":[0.016757015,0.0004684626,0.9636861,0.0005745726,0.00016633318,0.00046345833,0.00016932968,0.010452929,0.0072617894],"genre_scores_gemma":[0.17469132,0.0006651598,0.8037133,0.00044011822,0.00019447699,0.0007374953,0.0014614123,0.00086426927,0.017232534],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976144,0.0005527983,0.00039101703,0.00021201425,0.0010300992,0.0001996158],"domain_scores_gemma":[0.99830025,0.0003318492,0.00011691608,0.00046391028,0.0006382814,0.00014894031],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028954162,0.00067972206,0.00062857044,0.0013934406,0.0015541073,0.0038856429,0.0027259015,0.0016835892,0.0043367245],"category_scores_gemma":[0.004054785,0.00070433045,0.00091765,0.0018157501,0.0011859054,0.004316411,0.0019749103,0.0022713763,0.0030384953],"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":[0.0014310352,0.0007068913,0.0050315065,0.0010064348,0.00025903966,0.0014095304,0.0019211653,0.059255734,0.07536675,0.43643305,0.033483412,0.3836955],"study_design_scores_gemma":[0.00036711362,0.0013302292,0.0020654686,0.0002089114,0.00026373917,0.0013530419,0.00030458937,0.60991067,0.06969562,0.10489717,0.20936207,0.00024135383],"about_ca_topic_score_codex":0.0029160576,"about_ca_topic_score_gemma":0.0022154734,"teacher_disagreement_score":0.0043367245,"about_ca_system_score_codex":0.0015402994,"about_ca_system_score_gemma":0.0016839748,"threshold_uncertainty_score":0.015312612},"labels":[],"label_agreement":null},{"id":"W2098380006","doi":"10.1016/j.procs.2010.04.054","title":"Exploring utilisation of GPU for database applications","year":2010,"lang":"en","type":"article","venue":"Procedia Computer Science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Institut de Cardiologie de Montréal; Nvidia","keywords":"Computer science; Acceleration; Central processing unit; CUDA; Parallel computing; Base (topology); General-purpose computing on graphics processing units; Algorithm; Computational science; Computer graphics (images); Operating system; Graphics","score_opus":0.07559545320925348,"score_gpt":0.2876882253438074,"score_spread":0.2120927721345539,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2098380006","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":[0.6240356,0.017295796,0.28354943,0.002061105,0.0004322114,0.00023848604,0.0007026387,0.006979029,0.06470571],"genre_scores_gemma":[0.85453945,0.0032253745,0.13557869,0.0002589992,0.00006104787,0.00009813875,0.0006885462,0.00037799627,0.0051717972],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993513,0.00020292221,0.000037166657,0.000097050164,0.00017206237,0.0001394858],"domain_scores_gemma":[0.998965,0.0005062406,0.000028925018,0.00020695874,0.00024212248,0.00005071118],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053914654,0.00093425595,0.00074927893,0.00074935757,0.0005236926,0.0021845035,0.0017062236,0.00072644354,0.0052399673],"category_scores_gemma":[0.002608795,0.00040551773,0.00042922483,0.002366348,0.00028558844,0.0020265607,0.00091056124,0.00064339244,0.0010694151],"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":[0.0029023772,0.0004637136,0.015907738,0.001262529,0.0003862099,0.0015202583,0.0007228133,0.13488124,0.14716803,0.047262456,0.027340963,0.62018174],"study_design_scores_gemma":[0.00021379435,0.00071096234,0.0039858674,0.00014375392,0.00020402597,0.0008954868,0.00049407664,0.8335963,0.07288191,0.018885663,0.06792811,0.000060035323],"about_ca_topic_score_codex":0.00399003,"about_ca_topic_score_gemma":0.004323719,"teacher_disagreement_score":0.0052399673,"about_ca_system_score_codex":0.0007289224,"about_ca_system_score_gemma":0.0005239175,"threshold_uncertainty_score":0.017529428},"labels":[],"label_agreement":null},{"id":"W2099525917","doi":"10.1007/s00778-009-0157-y","title":"A framework for testing DBMS features","year":2009,"lang":"en","type":"article","venue":"The VLDB Journal","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":41,"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; Database; Generator (circuit theory); Set (abstract data type); Feature (linguistics); Test case; Test suite; Test (biology); Data mining; Programming language; Power (physics); Machine learning","score_opus":0.0426218733597992,"score_gpt":0.3124691026543456,"score_spread":0.26984722929454635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2099525917","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":[0.053926412,0.00019673392,0.9164899,0.0006941945,0.00010286814,0.0010846247,0.0013967745,0.021263305,0.0048451405],"genre_scores_gemma":[0.29708588,0.000114535236,0.6957729,0.00037606087,0.00004877413,0.0008969759,0.0020695208,0.001531177,0.002104207],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9720072,0.009471626,0.0033174262,0.003379909,0.009620407,0.002203445],"domain_scores_gemma":[0.94463074,0.02869226,0.0027124623,0.015394362,0.007135031,0.0014351928],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.017568536,0.002010628,0.0012444503,0.00456622,0.0017077324,0.006557925,0.007544273,0.004018087,0.0055464073],"category_scores_gemma":[0.055266224,0.001865669,0.003094841,0.0019095533,0.0039326493,0.015298515,0.0058092205,0.004642787,0.0013990159],"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":[0.0020552091,0.0054680067,0.050066832,0.0020616713,0.00085731404,0.0016455075,0.003530375,0.096004404,0.07654272,0.34258214,0.026281292,0.39290455],"study_design_scores_gemma":[0.0003871399,0.0017036223,0.0058425767,0.00040112287,0.00042822666,0.00096498034,0.0014244942,0.7316642,0.07261649,0.15375902,0.030484367,0.00032389784],"about_ca_topic_score_codex":0.009674661,"about_ca_topic_score_gemma":0.007729436,"teacher_disagreement_score":0.017568536,"about_ca_system_score_codex":0.0021761057,"about_ca_system_score_gemma":0.0039778696,"threshold_uncertainty_score":0.092912436},"labels":[],"label_agreement":null},{"id":"W2099552474","doi":"10.1109/icde.2007.367909","title":"XPlainer: Visual Explanations of XPath Queries","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"XPath; Computer science; Programming language; XML; Information retrieval; XSLT; XML database; Streaming XML; XML Schema (W3C); Path expression; Database; World Wide Web; XML Encryption","score_opus":0.007938188705698868,"score_gpt":0.2733380035259547,"score_spread":0.2653998148202559,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2099552474","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":[0.005034922,0.00023570246,0.91629994,0.0007483205,0.00007643277,0.00018392994,0.0024125357,0.06797591,0.007032385],"genre_scores_gemma":[0.112148575,0.0010963727,0.8462056,0.0008034226,0.00010406203,0.0005920023,0.008269067,0.012522145,0.018258737],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990701,0.0003316184,0.000084621046,0.00013538185,0.0003179874,0.000060260616],"domain_scores_gemma":[0.99595994,0.0029301597,0.00020721665,0.00036495685,0.00043608504,0.0001017385],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016894669,0.0015769476,0.0004711719,0.0014376884,0.00036913028,0.0022856994,0.0019692238,0.001733683,0.027926032],"category_scores_gemma":[0.008281598,0.0006575794,0.00075567304,0.0008246986,0.0005795623,0.0035841458,0.0020920169,0.0018539723,0.004700736],"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":[0.0011445655,0.00029918985,0.0029088939,0.0021222527,0.00009003641,0.002804976,0.0071613025,0.024119643,0.033248045,0.1167988,0.23714925,0.572153],"study_design_scores_gemma":[0.00039434244,0.0001899566,0.0019868354,0.0006329137,0.0000673915,0.0018060487,0.0012093381,0.23272187,0.043902487,0.10272478,0.6141781,0.00018599974],"about_ca_topic_score_codex":0.0018945344,"about_ca_topic_score_gemma":0.0022067493,"teacher_disagreement_score":0.027926032,"about_ca_system_score_codex":0.00054658327,"about_ca_system_score_gemma":0.00069589034,"threshold_uncertainty_score":0.09342188},"labels":[],"label_agreement":null},{"id":"W2099782014","doi":"10.1109/icsm.2002.1167821","title":"Re-engineering of E-commerce legacy applications for Enterprise Java/spl trade/ environment","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor; IBM (Canada)","funders":"","keywords":"Computer science; JavaBeans; Java; Software engineering; IBM; Database; Suite; Legacy system; World Wide Web; Software; Operating system","score_opus":0.012443514520343304,"score_gpt":0.22992370960943265,"score_spread":0.21748019508908933,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2099782014","genre_codex":"methods","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":[0.23435226,0.0022813387,0.55692035,0.0030507457,0.001141742,0.0009271538,0.0007451858,0.038654953,0.16192639],"genre_scores_gemma":[0.39280826,0.0023092714,0.44574273,0.001420766,0.00030951737,0.00024658997,0.0035404759,0.0067950985,0.14682718],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99915826,0.00020449821,0.00007872756,0.000079552476,0.00039862687,0.00008024878],"domain_scores_gemma":[0.9964535,0.00091659586,0.00014479243,0.001000081,0.0013050633,0.00017990173],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017364399,0.00029983182,0.00024251983,0.0005113422,0.00043708392,0.0021151146,0.0011524041,0.0005338773,0.0062033585],"category_scores_gemma":[0.0044205077,0.00028903875,0.00035725476,0.00051992346,0.00020175724,0.0015506484,0.0007464429,0.0008249761,0.0031250787],"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":[0.00036130496,0.00057093496,0.0047432575,0.00028744602,0.000035931866,0.0010733107,0.0008087604,0.0053236657,0.036780782,0.014044911,0.04725941,0.88871026],"study_design_scores_gemma":[0.00013282779,0.000658926,0.018432118,0.00032495937,0.00014688821,0.0031394195,0.000976628,0.11756442,0.09615694,0.010349628,0.7519975,0.00011973653],"about_ca_topic_score_codex":0.0013787695,"about_ca_topic_score_gemma":0.0024966258,"teacher_disagreement_score":0.0062033585,"about_ca_system_score_codex":0.00038588516,"about_ca_system_score_gemma":0.0005313858,"threshold_uncertainty_score":0.02075231},"labels":[],"label_agreement":null},{"id":"W2100142798","doi":"10.1093/comjnl/bxu039","title":"Functional Dependencies with null Markers","year":2014,"lang":"en","type":"article","venue":"The Computer Journal","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Null (SQL); Axiom; Extension (predicate logic); Computer science; Dependency theory (database theory); Functional dependency; Set (abstract data type); Theoretical computer science; Mathematics; Data mining; Programming language; Relational database","score_opus":0.010246035185894176,"score_gpt":0.18872358441520898,"score_spread":0.1784775492293148,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2100142798","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":[0.022669878,0.0011167355,0.9590444,0.002538383,0.00034479576,0.0001797649,0.0009409194,0.00157248,0.011592628],"genre_scores_gemma":[0.38806093,0.001449835,0.5910495,0.002342427,0.00052979984,0.0008057228,0.0021751332,0.0010615978,0.012525088],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9819697,0.006039541,0.00331039,0.003529022,0.0042739,0.00087755005],"domain_scores_gemma":[0.9396643,0.027252277,0.0038059284,0.021084333,0.007295917,0.0008973142],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.018652072,0.0013438424,0.001192902,0.0021087884,0.0022176881,0.005376677,0.003994888,0.0026406466,0.005899897],"category_scores_gemma":[0.05279629,0.0016830948,0.0017540058,0.0025356275,0.0060774186,0.024686435,0.0063575613,0.0037421267,0.0014680437],"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":[0.0001555682,0.000059618975,0.0036839307,0.0004143643,0.00005918718,0.00035708194,0.0016128287,0.0033539387,0.0024982945,0.9190306,0.0051991697,0.0635755],"study_design_scores_gemma":[0.000056038803,0.00012819875,0.00087095133,0.00044713836,0.00019546467,0.0008797047,0.00044938998,0.01687071,0.00955751,0.8191275,0.15128729,0.00012999575],"about_ca_topic_score_codex":0.0028473565,"about_ca_topic_score_gemma":0.0028374,"teacher_disagreement_score":0.018652072,"about_ca_system_score_codex":0.0020556443,"about_ca_system_score_gemma":0.0036904977,"threshold_uncertainty_score":0.09864271},"labels":[],"label_agreement":null},{"id":"W2100622378","doi":"10.1109/icde.2005.249","title":"Novel Approach for Reengineering Relational Databases into XML","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Relational database; XML Schema Editor; XML database; Document Structure Description; XML; XML Schema (W3C); Database; XML validation; Database model; Schema (genetic algorithms); Semi-structured model; Entity–relationship model; Efficient XML Interchange; Business process reengineering; Database schema; Streaming XML; Information retrieval; Database design; World Wide Web; XML Encryption; Engineering","score_opus":0.04473729049941801,"score_gpt":0.26825821232732555,"score_spread":0.22352092182790753,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2100622378","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":[0.0021783516,0.000362503,0.9901676,0.00032394493,0.00012947687,0.00012024925,0.000088050096,0.003351796,0.0032781041],"genre_scores_gemma":[0.02434844,0.00053706876,0.9675509,0.00037653578,0.00008306056,0.00010545056,0.00047064124,0.00028040347,0.006247647],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99764997,0.00039758373,0.00023475995,0.00038890875,0.001254514,0.000074283984],"domain_scores_gemma":[0.99809486,0.00035247454,0.00011400186,0.0008554609,0.00052247714,0.000060797393],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016911791,0.00044723594,0.0004634247,0.0011101527,0.00046213594,0.0019932257,0.0019158408,0.00084378896,0.0041518863],"category_scores_gemma":[0.0031575658,0.00041942872,0.0007177643,0.0011696401,0.000578638,0.0031964416,0.001865037,0.0017038551,0.0016544838],"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":[0.00014108303,0.00019998735,0.0010316054,0.0004996202,0.00011639756,0.00093702384,0.00076372415,0.0039887573,0.055458065,0.18718478,0.020144152,0.7295348],"study_design_scores_gemma":[0.00012277618,0.0002879651,0.0011506017,0.00019354241,0.00019758924,0.0049606357,0.0004369614,0.115892835,0.09543989,0.046121057,0.73505414,0.0001420745],"about_ca_topic_score_codex":0.0014800895,"about_ca_topic_score_gemma":0.0020610325,"teacher_disagreement_score":0.0041518863,"about_ca_system_score_codex":0.00051939,"about_ca_system_score_gemma":0.0008329751,"threshold_uncertainty_score":0.013889432},"labels":[],"label_agreement":null},{"id":"W2101631389","doi":"10.1109/ideas.2004.16","title":"Building large ROLAP data cubes in parallel","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Dalhousie University","funders":"","keywords":"Speedup; Computer science; Online analytical processing; Parallel computing; Scalability; Data cube; Row; Materialized view; Data warehouse; Cube (algebra); Bottleneck; Database; Data mining; View; Mathematics","score_opus":0.03382534961749922,"score_gpt":0.3058648990970239,"score_spread":0.2720395494795247,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2101631389","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":[0.046436507,0.00016191721,0.9441983,0.0002712912,0.00007030148,0.00021737182,0.00048637256,0.0039494834,0.0042083836],"genre_scores_gemma":[0.15792304,0.00017693419,0.83633626,0.00011401256,0.000029322231,0.0003291261,0.0024140072,0.00039469646,0.0022826402],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990565,0.00019427684,0.000061783554,0.00016464398,0.00041009716,0.000112757305],"domain_scores_gemma":[0.998626,0.00040869415,0.00007788417,0.00047610886,0.00034415003,0.00006722601],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007365061,0.00065725326,0.0008058939,0.0005873929,0.0007356787,0.0015283732,0.0016425233,0.00047869727,0.0024067173],"category_scores_gemma":[0.00242672,0.00048582847,0.0010647075,0.0012816797,0.0006452737,0.0017848408,0.0025704291,0.00095755793,0.0010978078],"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":[0.0008978392,0.00032815526,0.0036640624,0.0005719305,0.0002447438,0.0014608225,0.001133625,0.39975786,0.071855254,0.044181082,0.026048543,0.4498561],"study_design_scores_gemma":[0.00010515479,0.00014188906,0.00061172416,0.000021122292,0.00003994302,0.00032091985,0.00041227066,0.89580375,0.04369265,0.032972634,0.025835836,0.000042095482],"about_ca_topic_score_codex":0.0016913813,"about_ca_topic_score_gemma":0.0022257438,"teacher_disagreement_score":0.0024067173,"about_ca_system_score_codex":0.00035373168,"about_ca_system_score_gemma":0.0007241136,"threshold_uncertainty_score":0.008051276},"labels":[],"label_agreement":null},{"id":"W2102247866","doi":"10.1109/dexa.2006.62","title":"Finding Syntactic Similarities Between XML Documents","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":32,"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 Alberta","funders":"","keywords":"Computer science; XML; Document Structure Description; Edit distance; XML validation; Information retrieval; Tree (set theory); Efficient XML Interchange; Simple API for XML; Tree structure; XML Schema (W3C); XML database; Document type definition; Theoretical computer science; Data mining; XML Signature; Algorithm; Programming language; Data structure; World Wide Web; Mathematics","score_opus":0.017814360969210116,"score_gpt":0.2641840172389015,"score_spread":0.24636965626969137,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2102247866","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":[0.30889127,0.0032326935,0.66342664,0.0008596503,0.00026709685,0.0009052391,0.008296332,0.0057131196,0.008407887],"genre_scores_gemma":[0.4698904,0.00130883,0.51280856,0.00017981452,0.00019185567,0.00032140044,0.012387154,0.00044300247,0.0024689287],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973239,0.00053662993,0.00043431553,0.00058132864,0.0009951399,0.00012878171],"domain_scores_gemma":[0.99150556,0.0039427625,0.001541454,0.0010986908,0.0016984445,0.00021315145],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017160313,0.0006028794,0.0009629435,0.008699205,0.00090233533,0.0021652419,0.0012825857,0.0011569776,0.0029550353],"category_scores_gemma":[0.015019854,0.00052147027,0.0011118541,0.0057035247,0.0004721066,0.0043115774,0.0016761713,0.0008222046,0.0011311845],"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":[0.0009921003,0.00046357035,0.03198187,0.0025175896,0.00046670568,0.0020599186,0.0024977701,0.014321851,0.06203843,0.047684263,0.009939002,0.825037],"study_design_scores_gemma":[0.0003875901,0.00224416,0.0905733,0.0010877539,0.0015231144,0.009150766,0.0060605532,0.39352134,0.16125093,0.18614557,0.14767677,0.0003780359],"about_ca_topic_score_codex":0.001031652,"about_ca_topic_score_gemma":0.0016503251,"teacher_disagreement_score":0.008699205,"about_ca_system_score_codex":0.0007712436,"about_ca_system_score_gemma":0.0013777451,"threshold_uncertainty_score":0.009885609},"labels":[],"label_agreement":null},{"id":"W2102696193","doi":"10.1109/icde.2008.4497609","title":"AxPRE Summaries: Exploring the (Semi-)Structure of XML Web Collections","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Center for Advanced Study, University of Illinois at Urbana-Champaign","keywords":"Computer science; XML; Document Structure Description; World Wide Web; XML Schema Editor; Efficient XML Interchange; Information retrieval; Streaming XML; Formalism (music); XML validation; Database","score_opus":0.03419905116325708,"score_gpt":0.22457766507023394,"score_spread":0.19037861390697686,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2102696193","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":[0.013183746,0.00036574044,0.97357166,0.00021068989,0.00002183281,0.00011615821,0.0013738995,0.008855087,0.0023011735],"genre_scores_gemma":[0.11824824,0.00077635964,0.8708788,0.000117147516,0.00003284147,0.0002561645,0.0033613667,0.0023479597,0.0039810957],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990252,0.00034014645,0.000104513856,0.00016556372,0.00031053944,0.000053865508],"domain_scores_gemma":[0.99704677,0.001635802,0.00027333057,0.0006427068,0.00025750007,0.00014390286],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017689385,0.00065430766,0.0005276748,0.0020487264,0.0010300296,0.0036788848,0.0013205543,0.0006877293,0.0054011643],"category_scores_gemma":[0.0063475324,0.0007388818,0.00094041193,0.0021234278,0.00086612254,0.0072422097,0.0031814747,0.0012079686,0.0010124351],"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":[0.0006234691,0.00012771174,0.00527428,0.0015397582,0.00012412468,0.0013592595,0.013406452,0.04972574,0.03182424,0.3671234,0.026953744,0.5019178],"study_design_scores_gemma":[0.00012810797,0.000195634,0.002527302,0.00047683346,0.00009564813,0.0014299677,0.0030644655,0.2620075,0.041489232,0.3449983,0.3433761,0.00021086453],"about_ca_topic_score_codex":0.0027678602,"about_ca_topic_score_gemma":0.005344721,"teacher_disagreement_score":0.0054011643,"about_ca_system_score_codex":0.00053542113,"about_ca_system_score_gemma":0.00093750795,"threshold_uncertainty_score":0.018068671},"labels":[],"label_agreement":null},{"id":"W2102729564","doi":"10.1016/j.tcs.2004.10.033","title":"Data exchange: semantics and query answering","year":2004,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1203,"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; Data exchange; Schema (genetic algorithms); Theoretical computer science; Semantics (computer science); Information retrieval; Database; Programming language","score_opus":0.022598624166246625,"score_gpt":0.2786496916886596,"score_spread":0.25605106752241297,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2102729564","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":[0.011483171,0.009430942,0.9594916,0.008982442,0.0005868182,0.00013505264,0.00052122807,0.0008704953,0.008498204],"genre_scores_gemma":[0.4480446,0.013946088,0.5140966,0.002632444,0.0034675582,0.0006963182,0.0033463668,0.00076205673,0.013007939],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98861814,0.0045568915,0.0016646781,0.0016976785,0.002859619,0.0006029936],"domain_scores_gemma":[0.98338795,0.0093707945,0.0011285617,0.0036264414,0.0019777664,0.00050849246],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010682277,0.0013519529,0.002815471,0.0038938608,0.0028785588,0.015152608,0.0034102385,0.0044612563,0.0045990865],"category_scores_gemma":[0.03031478,0.0014552257,0.002298429,0.008585234,0.00794145,0.04401869,0.0051269215,0.0050905026,0.0014994942],"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":[0.000102184036,0.000039465398,0.00033246278,0.00025024914,0.000030642088,0.000083347,0.00050675834,0.0025309396,0.00039100103,0.96038646,0.004545911,0.03080057],"study_design_scores_gemma":[0.000024400217,0.000014206131,0.00008998936,0.000061968516,0.00003859767,0.00020853193,0.00018179564,0.014964259,0.00062904146,0.9704724,0.01329495,0.000019719384],"about_ca_topic_score_codex":0.0025926768,"about_ca_topic_score_gemma":0.0012047074,"teacher_disagreement_score":0.015152608,"about_ca_system_score_codex":0.0028851717,"about_ca_system_score_gemma":0.0026601446,"threshold_uncertainty_score":0.056493938},"labels":[],"label_agreement":null},{"id":"W2102732129","doi":"10.1145/1183614.1183759","title":"Multi-query optimization of sliding window aggregates by schedule synchronization","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Sliding window protocol; Computer science; Synchronization (alternating current); Schedule; Query optimization; Window (computing); Data synchronization; Real-time computing; Distributed computing; Information retrieval; Computer network; Operating system","score_opus":0.0073586816761182965,"score_gpt":0.2176659231287611,"score_spread":0.2103072414526428,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2102732129","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":[0.11963914,0.001287423,0.8607654,0.0003667654,0.00023122386,0.00019024129,0.0004720711,0.0070077097,0.010039956],"genre_scores_gemma":[0.8532685,0.0004045357,0.13967732,0.00004439169,0.00015292139,0.00015529845,0.0005719514,0.0005210431,0.0052040378],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989328,0.00024514552,0.00006335115,0.00016682834,0.00039537836,0.0001965197],"domain_scores_gemma":[0.99843186,0.00060723023,0.0001392699,0.00041604135,0.00025891987,0.00014671279],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001284264,0.0008892429,0.0011775431,0.00064142223,0.00059120863,0.0011274676,0.0013114804,0.00034801883,0.005621865],"category_scores_gemma":[0.0031317244,0.0003136981,0.00041110616,0.0014533437,0.00031855487,0.0013557457,0.0012058107,0.000573239,0.0009445353],"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":[0.0035915815,0.000444831,0.0022811505,0.00026623686,0.00016471953,0.00025447342,0.00021415942,0.4370436,0.08445727,0.02520469,0.020903338,0.4251739],"study_design_scores_gemma":[0.00015783636,0.00025680696,0.000687687,0.0000070109995,0.000054679334,0.000043232358,0.00005780154,0.9708562,0.017217297,0.0066519687,0.003993616,0.000015885847],"about_ca_topic_score_codex":0.004586064,"about_ca_topic_score_gemma":0.00521768,"teacher_disagreement_score":0.005621865,"about_ca_system_score_codex":0.00064197264,"about_ca_system_score_gemma":0.0012140579,"threshold_uncertainty_score":0.018806934},"labels":[],"label_agreement":null},{"id":"W2102820708","doi":"10.1109/apsec.2003.1254379","title":"Implementing the PostgreSQL query optimizer within the OPT++ framework","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Query optimization; Sargable; Reuse; Simple (philosophy); Code (set theory); Relational database; Query by Example; Query language; Database; Web search query; Information retrieval; Programming language; Search engine","score_opus":0.013981260655586051,"score_gpt":0.26873288548990826,"score_spread":0.25475162483432223,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2102820708","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":[0.090577155,0.0009345189,0.8209103,0.0011003717,0.00017438835,0.00032691733,0.00083265,0.074633576,0.010510154],"genre_scores_gemma":[0.33066556,0.0004387913,0.6554479,0.0007449556,0.000081199236,0.00011141198,0.0016165524,0.006156549,0.0047370372],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9956274,0.0010116756,0.00030861172,0.00067617535,0.0018396117,0.0005364911],"domain_scores_gemma":[0.99530256,0.0014078665,0.00028992989,0.0018567274,0.0009310196,0.00021179259],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005812479,0.00070809736,0.0007011199,0.00045112844,0.00079602306,0.0026447515,0.003501002,0.0008896251,0.0025946358],"category_scores_gemma":[0.0071457247,0.0007471652,0.0010444004,0.0009297853,0.0012044911,0.003239675,0.0020035887,0.0019627644,0.0011306265],"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":[0.0031487397,0.00090439373,0.016003221,0.0011325516,0.00026725556,0.0007401752,0.0019550754,0.079195365,0.0929122,0.07659014,0.06258448,0.66456634],"study_design_scores_gemma":[0.000568052,0.0008668539,0.007811964,0.00013120285,0.00018603013,0.0010013203,0.000671609,0.67141795,0.15652125,0.024676338,0.13585798,0.000289408],"about_ca_topic_score_codex":0.012039915,"about_ca_topic_score_gemma":0.0095513705,"teacher_disagreement_score":0.012039915,"about_ca_system_score_codex":0.0014721812,"about_ca_system_score_gemma":0.0029189305,"threshold_uncertainty_score":0.030739725},"labels":[],"label_agreement":null},{"id":"W2104103390","doi":"10.1007/11408079_77","title":"Finding and Analyzing Database User Sessions","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":41,"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; Database; World Wide Web; Information retrieval","score_opus":0.02282801602035875,"score_gpt":0.2754174075454001,"score_spread":0.25258939152504134,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2104103390","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":[0.751363,0.0021930353,0.2171776,0.00046435435,0.00006974272,0.0004014626,0.010458176,0.008454142,0.009418505],"genre_scores_gemma":[0.8833127,0.0007777262,0.09869848,0.00007677983,0.000103903025,0.0001360089,0.008252001,0.00042790713,0.008214469],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99770916,0.0004532725,0.0001648622,0.0005257028,0.0009198898,0.00022712872],"domain_scores_gemma":[0.99386346,0.0032848248,0.00053627,0.0007933088,0.0010398275,0.00048233976],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013231491,0.00054109923,0.0006447425,0.0065502245,0.0007960822,0.0020303666,0.00096367445,0.00056758587,0.0020349931],"category_scores_gemma":[0.007386214,0.00040193577,0.00067823764,0.0038156922,0.00030776716,0.0029901622,0.0011064601,0.0007378261,0.0013982675],"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":[0.0006825148,0.000880051,0.24654472,0.00046253283,0.00022173864,0.0003484887,0.00278802,0.0051847924,0.03864632,0.0050497237,0.014016349,0.68517476],"study_design_scores_gemma":[0.00007336603,0.00091590115,0.2952566,0.0002203765,0.00054367294,0.0029631492,0.007896586,0.5296265,0.0875267,0.022166343,0.052585978,0.00022487417],"about_ca_topic_score_codex":0.004717644,"about_ca_topic_score_gemma":0.008661418,"teacher_disagreement_score":0.0065502245,"about_ca_system_score_codex":0.00051515223,"about_ca_system_score_gemma":0.0010683256,"threshold_uncertainty_score":0.0093804},"labels":[],"label_agreement":null},{"id":"W2104241878","doi":"10.1109/icde.1992.213204","title":"The design and implementation of a parallel join algorithm for nested relations on shared-memory multiprocessors","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Parallel computing; Join (topology); Nesting (process); Parallelism (grammar); Shared memory; Nested loop join; Hash join; Speedup; Parallel algorithm; Hash function; Theoretical computer science; Algorithm; Programming language; Mathematics; Combinatorics","score_opus":0.02583467103076926,"score_gpt":0.2969546913942387,"score_spread":0.27112002036346944,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2104241878","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":[0.018595314,0.0001712476,0.97753906,0.000093908275,0.00004440891,0.0001539061,0.000039619124,0.0018663028,0.0014961088],"genre_scores_gemma":[0.10394194,0.0001319388,0.8935093,0.000054182598,0.000030003452,0.00018915084,0.00019629879,0.00021463583,0.0017325125],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992512,0.00011768665,0.00008123946,0.00014243237,0.00030898882,0.000098431454],"domain_scores_gemma":[0.99909794,0.00020044032,0.000053171858,0.00021944931,0.00035888285,0.00007015854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009906141,0.00036151646,0.000624985,0.00040094156,0.0008959963,0.0013146219,0.002341042,0.0007683109,0.0019646278],"category_scores_gemma":[0.0018065941,0.00062114355,0.0005933622,0.00063923653,0.0005164465,0.0015074593,0.0009202084,0.00073680305,0.0008247485],"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":[0.0010232524,0.00045189343,0.003234703,0.00065686903,0.00027304862,0.00043754492,0.0009482844,0.20468107,0.14116038,0.059655674,0.010793903,0.57668346],"study_design_scores_gemma":[0.0002344975,0.00037045206,0.0004879007,0.000025573236,0.00009276179,0.00024617984,0.00011620319,0.8936483,0.06054651,0.015082292,0.029107848,0.00004139008],"about_ca_topic_score_codex":0.0022876172,"about_ca_topic_score_gemma":0.0019398911,"teacher_disagreement_score":0.002341042,"about_ca_system_score_codex":0.0005943771,"about_ca_system_score_gemma":0.00142806,"threshold_uncertainty_score":0.0065723658},"labels":[],"label_agreement":null},{"id":"W2104367954","doi":"10.1109/ccgrid.2012.19","title":"Parallel Real-Time OLAP on Multi-core Processors","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Online analytical processing; Computer science; Data warehouse; Data cube; Benchmark (surveying); Speedup; Database; Decision support system; Data mining; Parallel computing","score_opus":0.041708321251881605,"score_gpt":0.29259678294094466,"score_spread":0.25088846168906304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2104367954","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":[0.28786892,0.0019109871,0.6641388,0.00064909464,0.00044857865,0.0007808324,0.00075777865,0.027850952,0.015594146],"genre_scores_gemma":[0.5644249,0.0005313644,0.42701837,0.0002721939,0.00008378036,0.0004369532,0.0013102341,0.00068815495,0.0052341586],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979956,0.0003430562,0.00018029739,0.00047096063,0.0007159144,0.0002941415],"domain_scores_gemma":[0.99771667,0.000543963,0.00016154215,0.0006114255,0.0007902721,0.00017622243],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012617734,0.0014811053,0.0009172086,0.0008557583,0.0009405289,0.0018145345,0.0023385554,0.00048563955,0.003709198],"category_scores_gemma":[0.0030952133,0.00058018375,0.00060944696,0.0016124998,0.0006658803,0.0020518582,0.0014276855,0.0011772964,0.0012585578],"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":[0.004175348,0.0010010825,0.006973679,0.00090302207,0.00041465336,0.0010095617,0.0007318121,0.36329582,0.10134356,0.0109966,0.037269585,0.47188532],"study_design_scores_gemma":[0.0002587006,0.0004889795,0.0011844421,0.00002638366,0.00007220052,0.00019726566,0.00014873773,0.9431537,0.040285565,0.0044032885,0.009721194,0.000059589554],"about_ca_topic_score_codex":0.006334895,"about_ca_topic_score_gemma":0.005134045,"teacher_disagreement_score":0.006334895,"about_ca_system_score_codex":0.0009855673,"about_ca_system_score_gemma":0.002362416,"threshold_uncertainty_score":0.012596071},"labels":[],"label_agreement":null},{"id":"W2104476081","doi":"10.1109/icde.2002.994698","title":"From XML schema to relations: a cost-based approach to XML storage","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":294,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bell (Canada)","funders":"","keywords":"XML Schema Editor; Computer science; XML validation; Document Structure Description; Streaming XML; Efficient XML Interchange; XML database; RELAX NG; XML Schema (W3C); Information retrieval; XML Encryption; Database; Programming language; XML; World Wide Web","score_opus":0.02478139544480722,"score_gpt":0.25875490465932277,"score_spread":0.23397350921451554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2104476081","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":[0.010032024,0.0015181855,0.9750543,0.0011986613,0.00010296051,0.00024563968,0.00074568024,0.0028834548,0.008219021],"genre_scores_gemma":[0.11025389,0.0015348848,0.8790104,0.00036760885,0.00011223642,0.00031958154,0.0014072636,0.0009831438,0.0060110358],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9957718,0.0010986218,0.00031320273,0.00044021566,0.0021631094,0.00021300538],"domain_scores_gemma":[0.99618965,0.0011564416,0.00024273254,0.0015565335,0.00074686005,0.00010782661],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002611743,0.0011537628,0.0013812963,0.0034202521,0.0011110393,0.005245451,0.0050235847,0.0014214531,0.0062515177],"category_scores_gemma":[0.00982075,0.0009684828,0.0015529054,0.007392635,0.0013591988,0.009081071,0.0038732893,0.0017293592,0.0016071061],"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":[0.00041954246,0.00025982969,0.0020718216,0.0005392835,0.00021347828,0.00031810752,0.0006870375,0.16379629,0.010109742,0.3549637,0.028634803,0.43798625],"study_design_scores_gemma":[0.00008457174,0.00014470154,0.0005774928,0.00010658679,0.00013255847,0.00060835376,0.0003160111,0.74020106,0.01452201,0.1865424,0.05667975,0.000084581974],"about_ca_topic_score_codex":0.0073920265,"about_ca_topic_score_gemma":0.011090591,"teacher_disagreement_score":0.0073920265,"about_ca_system_score_codex":0.0022145493,"about_ca_system_score_gemma":0.0019556445,"threshold_uncertainty_score":0.020913422},"labels":[],"label_agreement":null},{"id":"W2104541214","doi":"10.1002/spe.500","title":"DrawCAD: using deductive object‐relational databases in CAD","year":2003,"lang":"en","type":"article","venue":"Software Practice and Experience","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Relational database; Database; Reuse; Database design; Object (grammar); CAD; Data model (GIS); View; Relational database management system; Object-relational mapping; Database model; Engineering drawing; Artificial intelligence; Engineering","score_opus":0.04430888468270976,"score_gpt":0.33100777486243793,"score_spread":0.28669889017972816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2104541214","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":[0.006980439,0.001920412,0.93984646,0.0008227011,0.00018575888,0.00034604056,0.001281663,0.03774299,0.0108735785],"genre_scores_gemma":[0.08977704,0.0026428024,0.89430624,0.00050783873,0.00015489949,0.0003157999,0.0055913194,0.0014581614,0.005245835],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99543566,0.0012831652,0.0005937719,0.00053298566,0.0020245227,0.00012987718],"domain_scores_gemma":[0.9945298,0.0025051746,0.00037916415,0.0016161485,0.00077153806,0.0001981825],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004781526,0.0007553765,0.0008055519,0.0027128172,0.00071773253,0.007728887,0.0032238201,0.0013960646,0.007577019],"category_scores_gemma":[0.014386812,0.0009944257,0.0009918464,0.0036747712,0.001104838,0.0065466044,0.0029736324,0.0013862592,0.0036692112],"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":[0.0006025888,0.00028266414,0.003361942,0.0012351379,0.000240555,0.0022394913,0.0018107636,0.027671367,0.011522694,0.19475359,0.06930397,0.68697524],"study_design_scores_gemma":[0.0005413956,0.00018469892,0.0015388862,0.0004844267,0.0003080922,0.0024106298,0.0005972569,0.32407105,0.034497634,0.15173756,0.4833919,0.00023650988],"about_ca_topic_score_codex":0.0038027235,"about_ca_topic_score_gemma":0.0029606167,"teacher_disagreement_score":0.007728887,"about_ca_system_score_codex":0.0008393744,"about_ca_system_score_gemma":0.0012613353,"threshold_uncertainty_score":0.02534771},"labels":[],"label_agreement":null},{"id":"W2104674547","doi":"10.1111/1467-9884.00296","title":"Simulation of hidden Markov models with EXCEL","year":2002,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series D (The Statistician)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Hidden Markov model; Computer science; Markov model; Markov chain; Maximum-entropy Markov model; Variable-order Markov model; Machine learning; Markov process; Artificial intelligence; Data mining; Statistics; Mathematics","score_opus":0.016982797524428387,"score_gpt":0.2316784564581534,"score_spread":0.21469565893372503,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2104674547","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":[0.06281476,0.00040461216,0.90304404,0.00055622373,0.0001935004,0.00017955746,0.0057067354,0.012640358,0.014460261],"genre_scores_gemma":[0.40105677,0.00066946866,0.5826408,0.00021170352,0.000060610186,0.00071625755,0.0068719257,0.00089568837,0.006876692],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987716,0.00057421083,0.00018221106,0.00011354287,0.0002803473,0.000078115954],"domain_scores_gemma":[0.9868002,0.01128556,0.00041672474,0.0005561727,0.0007592959,0.00018187768],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028157278,0.0006988139,0.00061548856,0.0010075005,0.00044044375,0.001437268,0.0011050387,0.0007267545,0.010136343],"category_scores_gemma":[0.011682628,0.00039805443,0.0007851016,0.0012004903,0.00030537715,0.0010263856,0.0008452462,0.00096465694,0.0017632458],"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":[0.00044590473,0.00016610045,0.004900445,0.00039914306,0.00012649641,0.00060602225,0.00038422568,0.8347407,0.0014390139,0.082569875,0.012472008,0.061749972],"study_design_scores_gemma":[0.00004927919,0.000038466576,0.00024731175,0.00003052304,0.000015405314,0.00008170469,0.000028599623,0.96852475,0.0021039005,0.023392646,0.005470424,0.0000168897],"about_ca_topic_score_codex":0.002349622,"about_ca_topic_score_gemma":0.0014827492,"teacher_disagreement_score":0.010136343,"about_ca_system_score_codex":0.00046768322,"about_ca_system_score_gemma":0.0008404808,"threshold_uncertainty_score":0.03390944},"labels":[],"label_agreement":null},{"id":"W2104761699","doi":"10.1109/ideas.2004.64","title":"Using reflection to introduce self-tuning technology into DBMSs","year":2004,"lang":"en","type":"article","venue":"International Database Engineering and Applications Symposium","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Acadia University; Queen's University","funders":"","keywords":"Computer science; Reflection (computer programming); Task (project management); Autonomic computing; Distributed computing; Programming language; Operating system; Cloud computing","score_opus":0.009777746665744632,"score_gpt":0.27072555879706545,"score_spread":0.2609478121313208,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2104761699","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":[0.0043558665,0.00011746115,0.9886253,0.00036708065,0.00011041423,0.000109508284,0.00001664705,0.004076327,0.0022214514],"genre_scores_gemma":[0.08142695,0.00027636118,0.9138832,0.0006334102,0.00012914982,0.0002490378,0.000060288134,0.0010538686,0.0022877646],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.993624,0.0020866154,0.00058114226,0.0012457208,0.0019306471,0.0005319203],"domain_scores_gemma":[0.9872399,0.0054242085,0.0009890222,0.0046855686,0.0012973773,0.00036384337],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0059414017,0.0010048676,0.0008386168,0.0009428221,0.000870173,0.004556518,0.0033670045,0.0020492598,0.0027817318],"category_scores_gemma":[0.017981872,0.0014813987,0.0012980562,0.0006329842,0.004119895,0.010084573,0.004263503,0.005914682,0.0012010552],"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":[0.0004190923,0.00047926154,0.0034510763,0.0007858951,0.0001723816,0.00088402285,0.0053870003,0.021331122,0.11710818,0.52786094,0.009620352,0.3125006],"study_design_scores_gemma":[0.0002933,0.0010273383,0.00087228406,0.00044140918,0.00023851354,0.0024483441,0.0007027379,0.26007244,0.27507427,0.26891527,0.18961181,0.0003023597],"about_ca_topic_score_codex":0.0005918285,"about_ca_topic_score_gemma":0.00047656972,"teacher_disagreement_score":0.0059414017,"about_ca_system_score_codex":0.0007716641,"about_ca_system_score_gemma":0.0013368496,"threshold_uncertainty_score":0.031421542},"labels":[],"label_agreement":null},{"id":"W2104999292","doi":"","title":"Configuring buffer pools in DB2 UDB","year":2002,"lang":"en","type":"article","venue":"Conference of the Centre for Advanced Studies on Collaborative Research","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Database; Partition (number theory); Database transaction; Transaction processing; Database index; Online transaction processing; Database tuning; Database design; Workload; Distributed database; View; Set (abstract data type); Database testing; Database theory; Operating system; Information retrieval; Search engine indexing","score_opus":0.17734453243430087,"score_gpt":0.39948172426546075,"score_spread":0.22213719183115987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2104999292","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":[0.43051067,0.004675655,0.51710933,0.0013140948,0.00034924102,0.0010423613,0.00092866685,0.030141495,0.013928462],"genre_scores_gemma":[0.7811583,0.00052535156,0.21244907,0.00041235497,0.00006628503,0.00040440535,0.0009390424,0.0009400088,0.0031051056],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.995805,0.001368904,0.0005402778,0.00078629825,0.00083196105,0.00066761096],"domain_scores_gemma":[0.99308807,0.0018605657,0.00060613424,0.0026463675,0.0009496724,0.0008491225],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0050978954,0.0010686513,0.0010624491,0.0016334412,0.0020435008,0.0062751514,0.004477115,0.0013327409,0.0019321892],"category_scores_gemma":[0.01146169,0.0014491493,0.0003183344,0.0024980807,0.0009608196,0.006432806,0.00400124,0.0010028663,0.0010681968],"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":[0.005741704,0.0012244213,0.056503374,0.00089588994,0.00022278549,0.0021294488,0.0057724887,0.15232243,0.11237544,0.069086984,0.044930533,0.5487945],"study_design_scores_gemma":[0.0003759323,0.0004912384,0.005770755,0.00017848558,0.00015865908,0.0011046152,0.0020621817,0.771904,0.11372636,0.031616904,0.07234691,0.00026401514],"about_ca_topic_score_codex":0.0060026394,"about_ca_topic_score_gemma":0.004315108,"teacher_disagreement_score":0.0062751514,"about_ca_system_score_codex":0.002055175,"about_ca_system_score_gemma":0.0017010666,"threshold_uncertainty_score":0.026960552},"labels":[],"label_agreement":null},{"id":"W2105007848","doi":"10.1109/cmpsac.1979.762564","title":"Security is partitioned dynamic stastical databases","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Database; Data mining","score_opus":0.01668051275942333,"score_gpt":0.28881292079041826,"score_spread":0.2721324080309949,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105007848","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":[0.082131855,0.00074383366,0.9064975,0.0017090922,0.000083765204,0.00012040674,0.0003756431,0.0005004585,0.007837558],"genre_scores_gemma":[0.9348254,0.0007862264,0.059079196,0.00019778099,0.0000998152,0.00012639769,0.000402966,0.000056704936,0.004425473],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99621296,0.0012290417,0.0002414232,0.0007047286,0.001093344,0.0005186268],"domain_scores_gemma":[0.99199945,0.0032305752,0.0007106598,0.0027650078,0.0009790587,0.0003152988],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026770947,0.00074242475,0.0007012529,0.0008878565,0.0008977468,0.00499298,0.0016830139,0.0017385506,0.0024115213],"category_scores_gemma":[0.010072232,0.00057034264,0.0007250105,0.0013679797,0.0023664436,0.007917746,0.0024019,0.0017601973,0.00071783067],"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":[0.0006206476,0.0000648869,0.00088399695,0.00011900159,0.00005235454,0.00036030597,0.00043460677,0.27054924,0.0054539954,0.6858825,0.0030989056,0.032479543],"study_design_scores_gemma":[0.00004737311,0.00010311774,0.00020438802,0.000036003144,0.000024914854,0.00040608938,0.00015613035,0.65132016,0.0026957374,0.33865386,0.0063234027,0.0000289118],"about_ca_topic_score_codex":0.001846843,"about_ca_topic_score_gemma":0.00082856184,"teacher_disagreement_score":0.00499298,"about_ca_system_score_codex":0.0019395096,"about_ca_system_score_gemma":0.001323076,"threshold_uncertainty_score":0.0141580105},"labels":[],"label_agreement":null},{"id":"W2105285787","doi":"","title":"Optimizing Correlated Path Queries in XML Languages","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"XPath; Computer science; Path expression; XQuery; XSLT; XML; Rewriting; Theoretical computer science; Path (computing); Pattern matching; Programming language; XML database","score_opus":0.014340049280962656,"score_gpt":0.23257807018761814,"score_spread":0.21823802090665548,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105285787","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":[0.11078485,0.00028473008,0.88231784,0.00025424917,0.000021271684,0.00018659791,0.00016367475,0.0031906646,0.0027960544],"genre_scores_gemma":[0.5096736,0.0003096804,0.4851403,0.00018398157,0.00002570941,0.00018670954,0.000557442,0.0012579671,0.002664567],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99504036,0.0019387499,0.0003145334,0.0006176616,0.0017669732,0.00032178144],"domain_scores_gemma":[0.9969584,0.0017871979,0.00029502605,0.00056258,0.00032857902,0.00006827004],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032972204,0.00087170285,0.00096423755,0.00064954313,0.00059673644,0.0017578873,0.0019458763,0.00088691333,0.0014713809],"category_scores_gemma":[0.0068322136,0.0007044419,0.001103682,0.0018363153,0.0014913888,0.0035437292,0.0020783166,0.0011530548,0.00033359634],"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":[0.00066449516,0.00036473668,0.0035989431,0.0003348573,0.00019664192,0.00059086015,0.00065201044,0.70152575,0.039865494,0.07828764,0.0050230487,0.1688955],"study_design_scores_gemma":[0.0000802803,0.000101306076,0.00045810852,0.000013984498,0.000060764953,0.00011066041,0.0001330464,0.9353766,0.026250236,0.035299197,0.002087512,0.000028260805],"about_ca_topic_score_codex":0.003842936,"about_ca_topic_score_gemma":0.0059588565,"teacher_disagreement_score":0.003842936,"about_ca_system_score_codex":0.001204786,"about_ca_system_score_gemma":0.0014052102,"threshold_uncertainty_score":0.017437577},"labels":[],"label_agreement":null},{"id":"W2105556948","doi":"10.1109/icde.2008.4497492","title":"XML Index Recommendation with Tight Optimizer Coupling","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada); University of Toronto; University of Waterloo","funders":"","keywords":"Computer science; XML; Index (typography); Search engine indexing; Set (abstract data type); Workload; Information retrieval; Relational database; Data mining; Database index; Database; Programming language; World Wide Web; Operating system","score_opus":0.018609243542780336,"score_gpt":0.2219442740110783,"score_spread":0.20333503046829796,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105556948","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":[0.11331047,0.0009298646,0.8460276,0.00053839764,0.00007892298,0.00033036398,0.00037734403,0.032182597,0.006224443],"genre_scores_gemma":[0.39171493,0.00024402275,0.5991807,0.00049924,0.000096164054,0.00020949339,0.0011995179,0.0012143711,0.0056416467],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99542516,0.001021534,0.0005244851,0.0010907252,0.0015503351,0.00038775068],"domain_scores_gemma":[0.9958474,0.0012754005,0.0003684152,0.0016530759,0.00064481195,0.00021086428],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029819896,0.0015009914,0.0018045066,0.0012808363,0.0007089015,0.002174336,0.0029084617,0.001456583,0.002380238],"category_scores_gemma":[0.011157184,0.0010389759,0.00089417427,0.0020132621,0.000666405,0.0036663623,0.0022790367,0.0017490924,0.0013228102],"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":[0.0010419535,0.00072661386,0.009810934,0.0001913395,0.0002926714,0.00024530175,0.0003321583,0.3036952,0.032300696,0.0053514848,0.013585278,0.6324263],"study_design_scores_gemma":[0.00006359387,0.00010084102,0.00071852305,0.000005497755,0.000035302746,0.00006839415,0.000040195537,0.98617953,0.0085565895,0.001989385,0.0022193396,0.00002272766],"about_ca_topic_score_codex":0.011542613,"about_ca_topic_score_gemma":0.01679022,"teacher_disagreement_score":0.011542613,"about_ca_system_score_codex":0.0012780834,"about_ca_system_score_gemma":0.0020767013,"threshold_uncertainty_score":0.022950888},"labels":[],"label_agreement":null},{"id":"W2105568982","doi":"10.1007/3-540-44503-x_3","title":"Scalar Aggregation in FD-Inconsistent Databases","year":2001,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":47,"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; Scalar (mathematics); Graph database; Graph; Set (abstract data type); Theoretical computer science; Database; Database query; Database theory; Characterization (materials science); Relational database; Mathematics; Programming language","score_opus":0.024882359239949733,"score_gpt":0.2599877209056143,"score_spread":0.23510536166566454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105568982","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":[0.0332853,0.001947098,0.95472175,0.00053623534,0.0001668932,0.00006269779,0.0002356576,0.0015891569,0.007455161],"genre_scores_gemma":[0.43987772,0.00180521,0.54572034,0.00021514982,0.00031259054,0.000093881215,0.0007864515,0.00033216874,0.010856628],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9977621,0.0005435102,0.000323804,0.00028563946,0.00090014294,0.00018483734],"domain_scores_gemma":[0.99605787,0.0017202358,0.00028737017,0.0013099307,0.00054098887,0.000083637475],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00396594,0.0004011,0.0010199988,0.0011991668,0.00108184,0.0029088503,0.0016466798,0.000731602,0.0032368076],"category_scores_gemma":[0.008653294,0.00078398286,0.00067830813,0.004043103,0.0012592509,0.005882092,0.0018264427,0.001389823,0.0004997165],"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":[0.00052400946,0.000102438615,0.0026675665,0.0005379047,0.00006298259,0.0005130797,0.0007934288,0.032118212,0.0047578723,0.6790121,0.0129864365,0.2659239],"study_design_scores_gemma":[0.00007357388,0.00008955098,0.0007478865,0.000079998994,0.00011263778,0.0007818008,0.0002631274,0.24789304,0.008639098,0.716328,0.024944128,0.0000471229],"about_ca_topic_score_codex":0.0014624365,"about_ca_topic_score_gemma":0.001442596,"teacher_disagreement_score":0.00396594,"about_ca_system_score_codex":0.0009681494,"about_ca_system_score_gemma":0.0008277549,"threshold_uncertainty_score":0.02097416},"labels":[],"label_agreement":null},{"id":"W2105879586","doi":"10.1109/dexa.2003.1232095","title":"Today's DBMSs: how autonomic are they","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Oracle; Database; Oracle database; Sql server; Order (exchange); SQL; Software engineering; Business","score_opus":0.013896228414296006,"score_gpt":0.22358992898149183,"score_spread":0.20969370056719583,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105879586","genre_codex":"empirical","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.47605824,0.04580322,0.14504465,0.11992742,0.0048503503,0.0003356018,0.00064508285,0.004488344,0.20284706],"genre_scores_gemma":[0.9232683,0.013052616,0.04731903,0.006188925,0.0018984665,0.00010620986,0.00041369483,0.0004660967,0.0072867004],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99372923,0.0015394458,0.00041907077,0.0006492038,0.0029743093,0.00068870006],"domain_scores_gemma":[0.98615927,0.002314274,0.0015245255,0.0028420999,0.004855761,0.0023040974],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010973045,0.00027741666,0.00046559903,0.0011956902,0.0021336095,0.011252128,0.001391352,0.0016022712,0.0016427853],"category_scores_gemma":[0.023384407,0.00044177228,0.00026880018,0.0019714274,0.0023597514,0.019175582,0.0022293685,0.0020118991,0.0011530394],"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":[0.00033779533,0.00035274334,0.100796014,0.0004837495,0.000232763,0.00034612726,0.007084317,0.0036361648,0.006166306,0.28440753,0.058232836,0.53792363],"study_design_scores_gemma":[0.00007785936,0.0002903368,0.08241179,0.0010489925,0.0001737043,0.0012588048,0.0111053595,0.012946069,0.002566553,0.26287618,0.6250518,0.00019252488],"about_ca_topic_score_codex":0.002513727,"about_ca_topic_score_gemma":0.0029421973,"teacher_disagreement_score":0.011252128,"about_ca_system_score_codex":0.0010690643,"about_ca_system_score_gemma":0.0018631374,"threshold_uncertainty_score":0.058031738},"labels":[],"label_agreement":null},{"id":"W2106170712","doi":"10.1109/icde.2004.1320036","title":"Efficient incremental validation of XML documents","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":61,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; XML; Information retrieval; Programming language; World Wide Web","score_opus":0.011116564244163936,"score_gpt":0.2570269491096669,"score_spread":0.24591038486550296,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106170712","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":[0.036050428,0.0008093084,0.9530198,0.00047482143,0.00008786404,0.00022386748,0.00042026167,0.0062845335,0.0026290815],"genre_scores_gemma":[0.27469733,0.0006318394,0.7186245,0.00024498452,0.00009371395,0.00016678777,0.0017267689,0.0006952043,0.003118835],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99618906,0.0012745253,0.00032664833,0.0004820423,0.0013751542,0.00035252277],"domain_scores_gemma":[0.9832593,0.008228416,0.0009717793,0.005597683,0.0016987241,0.00024401526],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0039930763,0.0006581628,0.00081154535,0.0012445054,0.0009690915,0.0022395402,0.0037176248,0.0015149659,0.0019639174],"category_scores_gemma":[0.016447142,0.0007100594,0.0008903552,0.0020483113,0.0009526138,0.005283248,0.003051194,0.0012056264,0.0008203154],"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":[0.00061354524,0.0003201843,0.0049007754,0.00066495116,0.00014396646,0.00083315553,0.0012326494,0.12428653,0.06796705,0.05960849,0.017026657,0.7224021],"study_design_scores_gemma":[0.00016114536,0.00021847134,0.0015159277,0.00011489959,0.00012332604,0.0015109215,0.00042304402,0.7508436,0.1251951,0.07226147,0.04750065,0.0001314193],"about_ca_topic_score_codex":0.0022979118,"about_ca_topic_score_gemma":0.002383671,"teacher_disagreement_score":0.0039930763,"about_ca_system_score_codex":0.00085555983,"about_ca_system_score_gemma":0.001591992,"threshold_uncertainty_score":0.021117687},"labels":[],"label_agreement":null},{"id":"W2106325388","doi":"10.1109/ideas.1997.625671","title":"A uniform approach for selecting views and indexes in a data warehouse","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Data warehouse; Materialized view; Computer science; Dimensional modeling; Aggregate (composite); Database; Warehouse; Cube (algebra); Data cube; Constraint (computer-aided design); Online analytical processing; Time constraint; Order (exchange); Data mining; View; Mathematics; Database design","score_opus":0.1423262350985746,"score_gpt":0.2958641791096648,"score_spread":0.1535379440110902,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106325388","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":[0.003846791,0.00039607473,0.99236417,0.00013435958,0.00003825831,0.00031883887,0.000101464044,0.001379038,0.0014209794],"genre_scores_gemma":[0.02589957,0.00035103844,0.9723049,0.00008976574,0.000034579403,0.00017019444,0.00023309478,0.00021825093,0.00069869106],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99263495,0.0025670945,0.0010455746,0.0010081969,0.0023501602,0.000393991],"domain_scores_gemma":[0.99342865,0.0012748978,0.00037576092,0.00295696,0.001679576,0.00028410228],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0047645923,0.00096475065,0.0015998267,0.0023941624,0.0014795638,0.0055402224,0.0027728651,0.0011249095,0.0013245278],"category_scores_gemma":[0.013389478,0.001461128,0.000978778,0.004806572,0.0011649289,0.005076375,0.0036681287,0.0020989478,0.001411043],"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":[0.0005207736,0.00036887333,0.003455849,0.0004739306,0.00015239464,0.00064123044,0.0013906882,0.017971195,0.108280346,0.06041091,0.016506642,0.78982717],"study_design_scores_gemma":[0.00033850275,0.00088156725,0.0038781597,0.0004545215,0.00046226557,0.0035636746,0.0025391085,0.31694216,0.25939846,0.11876077,0.29227015,0.00051065075],"about_ca_topic_score_codex":0.00096913957,"about_ca_topic_score_gemma":0.0014087678,"teacher_disagreement_score":0.0055402224,"about_ca_system_score_codex":0.0006077772,"about_ca_system_score_gemma":0.0017114305,"threshold_uncertainty_score":0.025197864},"labels":[],"label_agreement":null},{"id":"W2106713193","doi":"10.1007/3-540-45675-9_8","title":"Calculating Aggregates with Range-Encoded Bit-Sliced Index","year":2002,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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 Windsor","funders":"","keywords":"Bitmap; Computer science; Range (aeronautics); Index (typography); Population; Aggregate (composite); Algorithm; Range query (database); Data mining; Information retrieval; Artificial intelligence; Search engine; Web search query; Sargable; Programming language","score_opus":0.01510223831996642,"score_gpt":0.23033694610440972,"score_spread":0.21523470778444329,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106713193","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":[0.08013963,0.0009330621,0.8998071,0.00017327434,0.00018846728,0.00009434375,0.00095456623,0.011279323,0.0064302566],"genre_scores_gemma":[0.2973832,0.00037691274,0.6964524,0.0000919246,0.0000746141,0.000103244056,0.0017917429,0.0009290016,0.0027969882],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986753,0.00012507832,0.00014355613,0.0001478063,0.0007817202,0.00012657467],"domain_scores_gemma":[0.9971916,0.0006393252,0.00018986256,0.0009419216,0.0009022239,0.00013501407],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010831733,0.0007598277,0.00111963,0.0020977745,0.00071445416,0.002863306,0.001527165,0.0007168507,0.0035090814],"category_scores_gemma":[0.0068303957,0.0005568842,0.0005879497,0.0036036237,0.0006098287,0.004162586,0.002138833,0.0006642409,0.0016980699],"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":[0.0019701077,0.00018352183,0.010736885,0.0006037488,0.00021677926,0.00060095463,0.0006918621,0.06137816,0.09005416,0.09423185,0.022755116,0.7165768],"study_design_scores_gemma":[0.000120478086,0.00029325034,0.0032211412,0.00010749914,0.00017110264,0.0006124021,0.00030871757,0.7424211,0.13105676,0.10480247,0.01675412,0.000130898],"about_ca_topic_score_codex":0.0025610414,"about_ca_topic_score_gemma":0.0044795386,"teacher_disagreement_score":0.0035090814,"about_ca_system_score_codex":0.0011312821,"about_ca_system_score_gemma":0.0012366034,"threshold_uncertainty_score":0.011739016},"labels":[],"label_agreement":null},{"id":"W2106897839","doi":"10.1109/iccbss.2006.4","title":"A Service-Sharing Methodology for Integrating COTS-Based Software Systems","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University; University of Manitoba","funders":"","keywords":"Interoperability; Computer science; Software engineering; Domain (mathematical analysis); Service (business); Ontology; Systems engineering; Software; Legacy system; Engineering; World Wide Web; Operating system","score_opus":0.07558113242278175,"score_gpt":0.3168445339360086,"score_spread":0.24126340151322684,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106897839","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":[0.0034170814,0.000060508675,0.9938251,0.00014505949,0.00002463878,0.00014292037,0.000009478328,0.00032356643,0.002051623],"genre_scores_gemma":[0.06438368,0.00016214461,0.9321757,0.00008275284,0.000033497276,0.00031895103,0.000055089804,0.000110493325,0.0026777245],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9956665,0.0013006474,0.00039693012,0.00047981483,0.0018775739,0.0002785008],"domain_scores_gemma":[0.9973029,0.0004993009,0.0002781778,0.0010567841,0.00066887285,0.00019396043],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005639815,0.00091980124,0.0007180442,0.002143893,0.0018579564,0.0026490956,0.0025586283,0.0014678185,0.0025142375],"category_scores_gemma":[0.0045415456,0.00085285434,0.0018934294,0.001962869,0.0022875748,0.005230734,0.0044628936,0.0019999899,0.0009735062],"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":[0.00006441185,0.00035893166,0.0022168513,0.00051885087,0.00014651899,0.0012666698,0.004515001,0.020154333,0.034616493,0.6294797,0.0038049666,0.30285725],"study_design_scores_gemma":[0.00010684516,0.0006276786,0.0018280038,0.00042635805,0.0003890822,0.0050937915,0.0021487046,0.30903986,0.070288695,0.37675288,0.233027,0.00027111615],"about_ca_topic_score_codex":0.0019290256,"about_ca_topic_score_gemma":0.0020321694,"teacher_disagreement_score":0.005639815,"about_ca_system_score_codex":0.0012106362,"about_ca_system_score_gemma":0.0030254968,"threshold_uncertainty_score":0.029826581},"labels":[],"label_agreement":null},{"id":"W2107343618","doi":"10.1016/b978-012722442-8/50051-3","title":"Processing Sliding Window Multi-Joins in Continuous Queries over Data Streams","year":2003,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":263,"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 Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Joins; Sliding window protocol; Computer science; Window (computing); STREAMS; Data stream mining; Data stream; Database; Data mining; World Wide Web; Computer network; Programming language; Telecommunications","score_opus":0.039176995035026904,"score_gpt":0.2780517687702607,"score_spread":0.2388747737352338,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2107343618","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":[0.08322421,0.0015485098,0.9052908,0.00030454955,0.00032048114,0.00017113726,0.0005685593,0.0063348943,0.0022369958],"genre_scores_gemma":[0.4068008,0.0010796281,0.5791604,0.00017313467,0.0005687006,0.0002488379,0.0026186586,0.00087467604,0.008475137],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998309,0.00021290248,0.00021759389,0.00028102592,0.00085031224,0.00012923277],"domain_scores_gemma":[0.99549294,0.0027803557,0.00023606891,0.000682108,0.00056930137,0.00023922593],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027476337,0.0010534168,0.0021367336,0.0011138752,0.00094564294,0.0036291385,0.0014521173,0.0010104086,0.004792253],"category_scores_gemma":[0.006387561,0.00096583273,0.00069003,0.002483239,0.0006825884,0.004219016,0.0017258552,0.0015617678,0.0013745832],"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":[0.0046871686,0.00069157075,0.0045147114,0.0008846906,0.00028929263,0.00092262164,0.0014603355,0.06272125,0.1354782,0.026324173,0.022586748,0.73943925],"study_design_scores_gemma":[0.00020473242,0.0004226333,0.0012679907,0.000053410953,0.00010145347,0.00042206197,0.00050054083,0.87827146,0.06093111,0.043651756,0.014120396,0.000052489006],"about_ca_topic_score_codex":0.0010734668,"about_ca_topic_score_gemma":0.0012255225,"teacher_disagreement_score":0.004792253,"about_ca_system_score_codex":0.00047392165,"about_ca_system_score_gemma":0.0006040176,"threshold_uncertainty_score":0.016031623},"labels":[],"label_agreement":null},{"id":"W2107629627","doi":"10.1109/time.2001.930704","title":"Optimizing temporal queries: efficient handling of duplicates","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; SQL; Query language; Query by Example; Query optimization; Relational database; Semantics (computer science); Temporal database; Context (archaeology); Expressive power; Sargable; Information retrieval; Programming language; Database; Web search query; Search engine","score_opus":0.022833133931300664,"score_gpt":0.23163786814090676,"score_spread":0.2088047342096061,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2107629627","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":[0.12776732,0.0014524688,0.85378724,0.00080834667,0.00014338362,0.00032456408,0.00062932045,0.007882968,0.0072044884],"genre_scores_gemma":[0.521726,0.001061886,0.4653815,0.00045574387,0.00024897818,0.00024106468,0.001563471,0.001975772,0.0073455647],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99322236,0.0017579305,0.0006687047,0.00063286215,0.0031915721,0.000526514],"domain_scores_gemma":[0.99014586,0.004772764,0.0008758675,0.0024317591,0.0015926526,0.00018114479],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004974583,0.00082153425,0.0014626655,0.0011980183,0.00097274175,0.0029705158,0.0029008207,0.0010116715,0.0018497461],"category_scores_gemma":[0.016078914,0.0005892549,0.0008560234,0.0032688067,0.0011260074,0.0055666957,0.00282507,0.000976083,0.00073902134],"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":[0.0023898478,0.00052488677,0.00717218,0.00093487784,0.00029929145,0.0018168974,0.002414829,0.14164685,0.084439814,0.08632936,0.03094491,0.6410862],"study_design_scores_gemma":[0.00028335638,0.00033018147,0.0017889797,0.00006692816,0.00024178074,0.0016398808,0.0010996093,0.76092035,0.10300106,0.09951628,0.030981496,0.00013012243],"about_ca_topic_score_codex":0.0029718578,"about_ca_topic_score_gemma":0.002491099,"teacher_disagreement_score":0.004974583,"about_ca_system_score_codex":0.00080147735,"about_ca_system_score_gemma":0.001870125,"threshold_uncertainty_score":0.026308477},"labels":[],"label_agreement":null},{"id":"W2107662595","doi":"10.1109/cmpsac.1992.217607","title":"Organizing software repositories modeling requirements and implementation experiences","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Universität Passau","keywords":"Computer science; Software engineering; Software; Semantics (computer science); Software requirements; Software development; Requirements elicitation; Requirements analysis; Programming language; Software design","score_opus":0.026991410753625655,"score_gpt":0.29819146090746407,"score_spread":0.2712000501538384,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2107662595","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":[0.35384375,0.002233707,0.4291171,0.019923575,0.00019618895,0.0009654696,0.00033872557,0.0027340823,0.19064741],"genre_scores_gemma":[0.74052215,0.0014174123,0.23803142,0.0005106572,0.0000670379,0.0006337226,0.00085769076,0.00060604175,0.017353954],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.97027594,0.018748347,0.001878307,0.0013634267,0.005591734,0.0021422645],"domain_scores_gemma":[0.97766155,0.0110352915,0.0012751624,0.004099873,0.0049631703,0.00096499344],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.024033312,0.000567868,0.0006201675,0.003198931,0.003204184,0.013650883,0.0054060845,0.0037131996,0.00474167],"category_scores_gemma":[0.032477766,0.0012132694,0.0011965801,0.0048242607,0.0028909224,0.0152319325,0.004939075,0.0018744976,0.0017259044],"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":[0.00019393362,0.0007831343,0.0066895843,0.0007767031,0.000047019883,0.002899553,0.06288177,0.034791533,0.004929423,0.65141535,0.012195399,0.2223966],"study_design_scores_gemma":[0.00028323042,0.000876767,0.0042962856,0.0018266458,0.00014885639,0.0051611946,0.123312406,0.16802727,0.012825972,0.20533687,0.47764224,0.00026228523],"about_ca_topic_score_codex":0.006131675,"about_ca_topic_score_gemma":0.006612523,"teacher_disagreement_score":0.024033312,"about_ca_system_score_codex":0.005341482,"about_ca_system_score_gemma":0.0056743966,"threshold_uncertainty_score":0.12710178},"labels":[],"label_agreement":null},{"id":"W2108869243","doi":"10.1109/icsmc.1995.537892","title":"Mediator: an intelligent information system supporting the virtual manufacturing enterprise","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":45,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Product lifecycle; Interface (matter); Process (computing); Function (biology); Mediator; User interface; Knowledge management; Process management; New product development; Engineering; Business","score_opus":0.01453915786691142,"score_gpt":0.228231128211924,"score_spread":0.21369197034501258,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2108869243","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":[0.03741779,0.0008805163,0.8767312,0.00069603714,0.00021724087,0.0006930294,0.0008529871,0.063038155,0.019473093],"genre_scores_gemma":[0.39335024,0.0014748905,0.56783235,0.0005463925,0.00021249344,0.0006700523,0.003759422,0.0019783527,0.03017593],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99919814,0.00021190778,0.000084194035,0.00014124274,0.00025613076,0.0001083917],"domain_scores_gemma":[0.99863356,0.0003862153,0.000097271026,0.0003533447,0.00020890085,0.00032069132],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021606365,0.0005370158,0.0010153189,0.0011325802,0.0010507411,0.003962959,0.0029218837,0.0021045913,0.009662803],"category_scores_gemma":[0.0033770024,0.0005654484,0.0004940821,0.0011370757,0.0007019075,0.004688591,0.0042202966,0.0011797785,0.0047928966],"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":[0.005539185,0.0014110043,0.0058144014,0.0013093705,0.00034835894,0.004797476,0.0045045856,0.021060647,0.15528364,0.13601376,0.100616924,0.56330055],"study_design_scores_gemma":[0.0010832569,0.0010174075,0.0029290202,0.0002486229,0.0005132216,0.0029566642,0.001082087,0.26831788,0.11026864,0.059544522,0.5517169,0.0003216741],"about_ca_topic_score_codex":0.0012023986,"about_ca_topic_score_gemma":0.0008244008,"teacher_disagreement_score":0.009662803,"about_ca_system_score_codex":0.00052666204,"about_ca_system_score_gemma":0.0018015337,"threshold_uncertainty_score":0.032325327},"labels":[],"label_agreement":null},{"id":"W2108912387","doi":"","title":"Reconfiguration of large-scale surveillance systems (abstract)","year":2013,"lang":"en","type":"article","venue":"Research Repository (Delft University of Technology)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Control reconfiguration; Metis; Scalability; Computer science; Decomposition; Argumentation theory; Software deployment; Computation; Argumentation framework; Scale (ratio); Distributed computing; Theoretical computer science; Software engineering; Embedded system; Database; Algorithm; Geography","score_opus":0.017751789172490724,"score_gpt":0.25855439827041116,"score_spread":0.24080260909792042,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2108912387","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":[0.022728637,0.00036712832,0.9705037,0.00040523525,0.000055351014,0.0001221219,0.00016635223,0.00045286416,0.005198542],"genre_scores_gemma":[0.6982187,0.00057645736,0.2947643,0.00013162833,0.00009630253,0.00029372447,0.0005728486,0.00011750441,0.0052285204],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9981115,0.00067543227,0.00018276811,0.00040764225,0.0004433333,0.0001793974],"domain_scores_gemma":[0.99797946,0.001132092,0.00029111112,0.00029645357,0.00018322033,0.00011771052],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001936327,0.0006957842,0.0005096214,0.0012381184,0.00097194506,0.0029460967,0.001338785,0.001556019,0.004076841],"category_scores_gemma":[0.0039702877,0.00050703983,0.001213682,0.0012797688,0.002528724,0.0035614802,0.0020537856,0.0014940433,0.000500998],"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":[0.00009794402,0.000045954497,0.0009898591,0.00030830872,0.000078069985,0.0008732103,0.0013402541,0.2827525,0.0074669984,0.67699206,0.0017547992,0.027300073],"study_design_scores_gemma":[0.000050804698,0.00008021503,0.0005237706,0.000078862286,0.00005183544,0.00030991773,0.00033048762,0.6797111,0.0024823227,0.29866984,0.017681746,0.000029176434],"about_ca_topic_score_codex":0.0027790375,"about_ca_topic_score_gemma":0.0016030563,"teacher_disagreement_score":0.004076841,"about_ca_system_score_codex":0.0016874229,"about_ca_system_score_gemma":0.0005865188,"threshold_uncertainty_score":0.013638377},"labels":[],"label_agreement":null},{"id":"W2108940246","doi":"10.1109/icde.2007.367866","title":"A Semantic Approach to Discovering Schema Mapping Expressions","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":70,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Schema (genetic algorithms); Information retrieval; Theoretical computer science; Semantics (computer science); Precision and recall; Recall; Natural language processing; Data mining; Programming language","score_opus":0.026667496300886932,"score_gpt":0.26420639511589655,"score_spread":0.2375388988150096,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2108940246","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":[0.0059818174,0.0001442194,0.98992187,0.00041525566,0.000021789287,0.00013162482,0.00045890303,0.0013562917,0.0015681923],"genre_scores_gemma":[0.05475351,0.00025249447,0.94152474,0.00015854028,0.00003301559,0.00017754179,0.0020104665,0.00018959376,0.0009001431],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99602735,0.0011905382,0.00040596054,0.0008446726,0.0013931902,0.00013825303],"domain_scores_gemma":[0.99368626,0.0028439125,0.0004519754,0.0015861525,0.0013344532,0.00009721329],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003900604,0.001060457,0.0007761957,0.00594208,0.001504521,0.003133988,0.0021281221,0.0013275197,0.0033368594],"category_scores_gemma":[0.01641376,0.00085096253,0.0022394154,0.005838964,0.002054249,0.009720463,0.0025518918,0.0017430735,0.0010380781],"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":[0.00019409729,0.00023685476,0.005657001,0.00085275114,0.00022421632,0.00067228696,0.0024861114,0.026782317,0.021369984,0.51213455,0.010038191,0.41935164],"study_design_scores_gemma":[0.000058968006,0.0001683388,0.0017424577,0.0002640241,0.00024410019,0.001813541,0.0020624348,0.3358452,0.034172617,0.5255043,0.09802279,0.00010129165],"about_ca_topic_score_codex":0.0025743393,"about_ca_topic_score_gemma":0.0032372356,"teacher_disagreement_score":0.00594208,"about_ca_system_score_codex":0.0014233069,"about_ca_system_score_gemma":0.0026513666,"threshold_uncertainty_score":0.020628631},"labels":[],"label_agreement":null},{"id":"W2108958132","doi":"10.1007/11788911_17","title":"Efficient Update of Data Warehouse Views with Generalised Referential Integrity Differential Files","year":2006,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","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 Manitoba","funders":"","keywords":"Computer science; Star schema; Joins; Schema (genetic algorithms); Tuple; Data warehouse; Information retrieval; Information schema; Data source; Database; Data mining; Theoretical computer science; Relational database; Database schema; Programming language; Semi-structured model; Database design; Database model","score_opus":0.043000614226424684,"score_gpt":0.2718704064846981,"score_spread":0.22886979225827345,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2108958132","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":[0.13161975,0.0014976024,0.8280634,0.00042532157,0.00018839902,0.00028318263,0.0018714595,0.031209426,0.004841402],"genre_scores_gemma":[0.6073511,0.0005197347,0.3819092,0.0001798139,0.00009395378,0.00013551762,0.0032747542,0.0018758635,0.0046599964],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99711764,0.0005529648,0.0003102419,0.00038205995,0.0013135374,0.0003235628],"domain_scores_gemma":[0.99065393,0.0018411595,0.00038014882,0.0062460895,0.000748278,0.00013045964],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002031133,0.000705571,0.0014121151,0.0016705355,0.0006423505,0.003114108,0.0034760695,0.0008855167,0.0031693608],"category_scores_gemma":[0.009369641,0.000829008,0.00089499506,0.00376633,0.00093458896,0.0056883395,0.0046665487,0.0011295273,0.0009664375],"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":[0.0022009143,0.0002509567,0.0056427824,0.0006149179,0.00025720857,0.0006673582,0.0011330508,0.039637435,0.05015675,0.02561981,0.022011379,0.8518074],"study_design_scores_gemma":[0.0006468223,0.000664945,0.0060304846,0.00014254158,0.0005578305,0.0017248102,0.0008530457,0.646123,0.22115733,0.0738148,0.048039652,0.00024478984],"about_ca_topic_score_codex":0.002364057,"about_ca_topic_score_gemma":0.0035889563,"teacher_disagreement_score":0.0034760695,"about_ca_system_score_codex":0.0009028638,"about_ca_system_score_gemma":0.0011865862,"threshold_uncertainty_score":0.01074177},"labels":[],"label_agreement":null},{"id":"W2110233945","doi":"10.1109/hpcs.2006.45","title":"The OLAP-Enabled Grid: Model and Query Processing Algorithms","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Online analytical processing; Computer science; Grid; Scalability; Database; Data warehouse; Grid computing; Query optimization; Distributed computing; Data mining","score_opus":0.00912608318194907,"score_gpt":0.2251133518439737,"score_spread":0.21598726866202464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2110233945","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":[0.0052667265,0.00062549586,0.9883796,0.0012690577,0.000051980624,0.00009513241,0.00025949298,0.00065654604,0.0033960564],"genre_scores_gemma":[0.21169697,0.0021100922,0.7803059,0.00034075984,0.00024870018,0.00058882404,0.00093661476,0.00020229962,0.00356975],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983203,0.00061532966,0.00010763821,0.00024468,0.00056446117,0.00014764912],"domain_scores_gemma":[0.99812907,0.0010723427,0.00014882647,0.0002803278,0.00028045295,0.00008893083],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022876814,0.0008202333,0.001228291,0.0008552122,0.0009932942,0.005306597,0.0035866823,0.0018356215,0.0019002869],"category_scores_gemma":[0.0063977283,0.00066395797,0.00077650277,0.0041867383,0.0017711053,0.0055548144,0.0018435048,0.002243837,0.0011114887],"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":[0.00012520123,0.00011369096,0.0008707089,0.00017954476,0.000043489923,0.00018806927,0.00018683472,0.71701133,0.0008017989,0.22978586,0.007895473,0.04279804],"study_design_scores_gemma":[0.000013724706,0.000008807315,0.000036885423,0.000007902736,0.00000434101,0.000022843915,0.000030551368,0.9356463,0.00017438311,0.06188155,0.0021672917,0.000005395446],"about_ca_topic_score_codex":0.014569688,"about_ca_topic_score_gemma":0.007026329,"teacher_disagreement_score":0.014569688,"about_ca_system_score_codex":0.0022452746,"about_ca_system_score_gemma":0.0025072251,"threshold_uncertainty_score":0.028969765},"labels":[],"label_agreement":null},{"id":"W2110993096","doi":"10.1145/1066157.1066176","title":"ConQuer","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":204,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Scalability; Set (abstract data type); Divide and conquer algorithms; Overhead (engineering); Rewriting; SQL; Consistency (knowledge bases); Query optimization; Spatial query; Key (lock); Query by Example; Query language; Data integrity; Workload; Theoretical computer science; Sargable; Programming language; Database; Information retrieval; Web search query; Artificial intelligence","score_opus":0.008281356346079124,"score_gpt":0.2321370144608133,"score_spread":0.22385565811473418,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2110993096","genre_codex":"methods","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02329735,0.003469569,0.79693925,0.005483246,0.0016022046,0.0016429387,0.0048696543,0.04252472,0.12017103],"genre_scores_gemma":[0.1997959,0.0025834364,0.63171583,0.005867752,0.00084452325,0.0014911187,0.020662466,0.009235484,0.12780358],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99266183,0.0013396217,0.000547221,0.0016934486,0.0028755234,0.00088232884],"domain_scores_gemma":[0.99334514,0.0015901994,0.00040587378,0.002741143,0.0016759709,0.00024159806],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036511405,0.0017719606,0.0014880338,0.0015143956,0.0019699438,0.0041501517,0.0039056763,0.0017323352,0.032633763],"category_scores_gemma":[0.0100644715,0.0006044651,0.001515595,0.0018682034,0.0016722232,0.00671518,0.0055305264,0.0027338124,0.010017745],"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":[0.0010763549,0.00040114069,0.00453495,0.0010912481,0.00024946828,0.0006934111,0.0008848274,0.008647052,0.013008689,0.16533345,0.18662898,0.61745036],"study_design_scores_gemma":[0.00043430104,0.0003259181,0.0015128339,0.00026192702,0.00020574972,0.0013259266,0.0010208975,0.09263298,0.028915448,0.17554154,0.69771224,0.00011030669],"about_ca_topic_score_codex":0.0042090155,"about_ca_topic_score_gemma":0.0071732546,"teacher_disagreement_score":0.032633763,"about_ca_system_score_codex":0.0013622462,"about_ca_system_score_gemma":0.002743956,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W2111068616","doi":"10.1145/2064676.2064690","title":"Data visualization on web-based OLAP","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Systems, Applications & Products in Data Processing (Canada); Simon Fraser University","funders":"","keywords":"Online analytical processing; Computer science; Middleware (distributed applications); Database; Visualization; Client-side; Data visualization; Server-side; Client–server model; World Wide Web; Data warehouse; Server; Data mining","score_opus":0.10706421225060392,"score_gpt":0.309830234231596,"score_spread":0.20276602198099208,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111068616","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":[0.060436677,0.0005623768,0.90115386,0.0005797277,0.000058672296,0.00015889909,0.0008385505,0.026092645,0.010118658],"genre_scores_gemma":[0.45820904,0.0008005393,0.5336184,0.0002504557,0.000071269744,0.000233897,0.0014082002,0.001651103,0.0037570149],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986884,0.0004961419,0.00007624519,0.00009583978,0.0005845473,0.00005886593],"domain_scores_gemma":[0.9975938,0.00094149983,0.00013613465,0.0005297045,0.00066619396,0.0001326233],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011550884,0.0006610256,0.0005532536,0.001434978,0.00063485204,0.0028010746,0.0009809256,0.000558531,0.004538617],"category_scores_gemma":[0.0034077244,0.00039342046,0.00038580626,0.0025316495,0.00043611982,0.0016343537,0.002225981,0.0008939267,0.0012082683],"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":[0.0021807924,0.0004933082,0.009907755,0.0011794413,0.000415177,0.0030863169,0.002769958,0.13875149,0.13870248,0.036486987,0.041115616,0.6249107],"study_design_scores_gemma":[0.000120610544,0.00017481447,0.005299432,0.00016678576,0.000094737574,0.0013839446,0.0009901974,0.8220519,0.07418294,0.04107641,0.054312177,0.00014602201],"about_ca_topic_score_codex":0.0031028516,"about_ca_topic_score_gemma":0.0025097833,"teacher_disagreement_score":0.004538617,"about_ca_system_score_codex":0.0005000484,"about_ca_system_score_gemma":0.00054353155,"threshold_uncertainty_score":0.01518321},"labels":[],"label_agreement":null},{"id":"W2111675636","doi":"10.1007/s10844-009-0087-6","title":"VIREX and VRXQuery: interactive approach for visual querying of relational databases to produce XML","year":2009,"lang":"en","type":"article","venue":"Journal of Intelligent Information Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":12,"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","funders":"","keywords":"Computer science; XML validation; XML Schema Editor; Document Structure Description; XML database; Information retrieval; XML Schema (W3C); Efficient XML Interchange; Streaming XML; Database; XML Encryption; XML; World Wide Web","score_opus":0.034521501535760064,"score_gpt":0.30764220292814476,"score_spread":0.2731207013923847,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111675636","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":[0.0043392223,0.00037579297,0.95046586,0.00026702878,0.0000698245,0.00019825867,0.0007798651,0.039937392,0.0035667748],"genre_scores_gemma":[0.08310638,0.00077870226,0.8840368,0.00061968627,0.00006824767,0.00044838068,0.005312611,0.011816423,0.013812836],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99574983,0.0013157221,0.00038387298,0.0005374349,0.001677492,0.00033555404],"domain_scores_gemma":[0.99606365,0.0023298322,0.00014744073,0.0008167832,0.0004196568,0.0002225796],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004868628,0.0013681438,0.0013942138,0.00211242,0.00084193406,0.0053818617,0.0049178367,0.0021174569,0.016746266],"category_scores_gemma":[0.008464496,0.0015084429,0.0023058127,0.0016895118,0.0020987531,0.005347992,0.0045678085,0.0026537334,0.0036732086],"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":[0.0031725548,0.000538758,0.0027145187,0.0022004258,0.0005369417,0.0016791972,0.0058111474,0.018106168,0.091162205,0.24999036,0.10445271,0.519635],"study_design_scores_gemma":[0.00089549297,0.00050754857,0.0016756597,0.00046497807,0.0004195766,0.0014808538,0.0014125656,0.33285028,0.17368013,0.096783526,0.38930547,0.00052399735],"about_ca_topic_score_codex":0.0055253226,"about_ca_topic_score_gemma":0.005616025,"teacher_disagreement_score":0.016746266,"about_ca_system_score_codex":0.0009925985,"about_ca_system_score_gemma":0.0012893466,"threshold_uncertainty_score":0.05602181},"labels":[],"label_agreement":null},{"id":"W2111984440","doi":"10.1109/icde.2009.131","title":"Query Rewrites with Views for XML in DB2","year":2009,"lang":"en","type":"article","venue":"Proceedings - International Conference on Data Engineering","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada); Microsoft (Canada); York University","funders":"","keywords":"Computer science; XML database; Streaming XML; XQuery; Efficient XML Interchange; XML validation; XML Schema Editor; XML Encryption; Information retrieval; Document Structure Description; Database; XML; World Wide Web","score_opus":0.08982055515052091,"score_gpt":0.3150799005651456,"score_spread":0.22525934541462472,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111984440","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":[0.008375889,0.0005841897,0.963706,0.00072251714,0.0002630015,0.0002606307,0.00080816395,0.015632715,0.009646866],"genre_scores_gemma":[0.10608414,0.00058450364,0.86929697,0.0015491025,0.0002131609,0.00036967229,0.0038895125,0.004418345,0.01359464],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99292386,0.0016327985,0.00085328816,0.000984857,0.0030107382,0.00059447694],"domain_scores_gemma":[0.9969273,0.00092725444,0.00013883847,0.0012248767,0.0006557256,0.00012595684],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004277022,0.00082227116,0.0008098365,0.0009738801,0.000980174,0.0041620187,0.0024086724,0.001026127,0.008040129],"category_scores_gemma":[0.006852242,0.0009003188,0.002206154,0.0012389076,0.0018177036,0.0056036613,0.0033043188,0.0035170205,0.0033285206],"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":[0.00085287367,0.00033904825,0.002275905,0.0005432996,0.00018992762,0.00087815616,0.0020923933,0.01969993,0.031529814,0.61704606,0.058034156,0.26651856],"study_design_scores_gemma":[0.00030490203,0.00034561494,0.00089670275,0.00019998214,0.00019626849,0.0010330415,0.00080173404,0.19676995,0.087138265,0.26294538,0.449128,0.0002401638],"about_ca_topic_score_codex":0.009012823,"about_ca_topic_score_gemma":0.00821289,"teacher_disagreement_score":0.009012823,"about_ca_system_score_codex":0.0014867393,"about_ca_system_score_gemma":0.0019187097,"threshold_uncertainty_score":0.026896894},"labels":[],"label_agreement":null},{"id":"W2112438535","doi":"10.1109/icpr.2002.1048208","title":"Interaction-centric modelling for interactive virtual worlds: the APIA approach","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Intelligent Systems Center","keywords":"Reusability; Interoperability; Computer science; Abstraction; Software engineering; Conceptual model; Human–computer interaction; Programming language; World Wide Web; Database; Software","score_opus":0.030988670040214723,"score_gpt":0.26516316563261283,"score_spread":0.2341744955923981,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2112438535","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":[0.0010956222,0.0007463433,0.9828728,0.0007004106,0.00008874688,0.00004678666,0.000068043235,0.00044467274,0.013936543],"genre_scores_gemma":[0.09906726,0.002846149,0.8849464,0.00037922783,0.00023776507,0.00078590016,0.00044376202,0.00062230654,0.010671182],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978898,0.0009071728,0.00013388714,0.000261198,0.00065590686,0.00015198626],"domain_scores_gemma":[0.9987356,0.00045836967,0.00011170211,0.00043464213,0.00015139535,0.00010827181],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021611731,0.001308893,0.0013175833,0.0025071036,0.0016893968,0.008039962,0.0037064464,0.0028531908,0.0049656555],"category_scores_gemma":[0.0035237216,0.0010780565,0.0030926366,0.002218717,0.003819607,0.009797578,0.0064640166,0.004251263,0.0020754],"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":[0.0000121767225,0.000016946075,0.000113362206,0.00011298617,0.00002621555,0.00008478866,0.0004527108,0.009074154,0.00047408298,0.96731657,0.0015962655,0.020719789],"study_design_scores_gemma":[0.00001995476,0.000029306684,0.00015899516,0.00019337247,0.00007851541,0.00034215002,0.00020537197,0.12636,0.0010514011,0.73551905,0.13598965,0.000052349453],"about_ca_topic_score_codex":0.0033981686,"about_ca_topic_score_gemma":0.0023733533,"teacher_disagreement_score":0.008039962,"about_ca_system_score_codex":0.0018567798,"about_ca_system_score_gemma":0.0021199086,"threshold_uncertainty_score":0.016611814},"labels":[],"label_agreement":null},{"id":"W2112485457","doi":"10.14778/1687553.1687567","title":"SQL/MapReduce","year":2009,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":127,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"ASTER","funders":"","keywords":"Computer science; SQL; User-defined function; Database; Schema (genetic algorithms); Scalability; NoSQL; Programming language; Query by Example; Information retrieval","score_opus":0.007158007447369725,"score_gpt":0.213177163393006,"score_spread":0.20601915594563627,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2112485457","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":[0.0036482683,0.0005181087,0.59676063,0.0009794378,0.0005347223,0.0011045805,0.022950936,0.3411616,0.03234172],"genre_scores_gemma":[0.0767946,0.0017239376,0.6958285,0.0028941398,0.0005114646,0.0023064383,0.120700896,0.05727695,0.04196307],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9954478,0.0005650685,0.0005322359,0.000902441,0.0021679734,0.0003844705],"domain_scores_gemma":[0.9966191,0.0005944523,0.00016143371,0.0013026114,0.00098631,0.0003359623],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036377318,0.0023197366,0.0012255972,0.0015026703,0.0010127096,0.0036888674,0.0058805165,0.0009482381,0.023550596],"category_scores_gemma":[0.0058445833,0.0012690241,0.0021854567,0.0016646279,0.000776081,0.0033394804,0.004268332,0.003546485,0.032044742],"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":[0.000781192,0.00046706086,0.0017487651,0.0014320412,0.00030281898,0.00046088503,0.00063486357,0.011269496,0.017582018,0.06268515,0.6631722,0.23946348],"study_design_scores_gemma":[0.00024250096,0.00016750727,0.0012068474,0.00010120548,0.00005396668,0.0006207684,0.00027812287,0.075684644,0.032069746,0.049487393,0.8398957,0.00019160386],"about_ca_topic_score_codex":0.0042955275,"about_ca_topic_score_gemma":0.0032506026,"teacher_disagreement_score":0.023550596,"about_ca_system_score_codex":0.0010752216,"about_ca_system_score_gemma":0.003485363,"threshold_uncertainty_score":0.078784585},"labels":[],"label_agreement":null},{"id":"W2113503643","doi":"10.51847/scwyd25","title":"10.51847/SCwYD25","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Ramaiah Institute Of Technology; Department of Biotechnology, Government of West Bengal","keywords":"Database; Glossary; Computer science; Online database; Biological database; The Internet; World Wide Web; Information retrieval; Bioinformatics; Biology","score_opus":0.00633342619197629,"score_gpt":0.18748658961265816,"score_spread":0.18115316342068186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2113503643","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010596038,0.0009794481,0.00502225,0.0011794266,0.0011494958,0.00027342892,0.017327704,0.009244099,0.9637646],"genre_scores_gemma":[0.0027704632,0.00071863947,0.0026892873,0.00086257415,0.00020595265,0.00016133483,0.019119842,0.0015558085,0.971916],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99925834,0.00006979859,0.00007193647,0.0002021192,0.00029827727,0.00009952428],"domain_scores_gemma":[0.9984333,0.00017775044,0.00006699296,0.00040446414,0.00048942683,0.000427992],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00092629215,0.001887111,0.0011805424,0.0038955996,0.0013979932,0.004431295,0.0021524592,0.0028390803,0.95253205],"category_scores_gemma":[0.0018817022,0.00076822995,0.0009082352,0.0039059361,0.000833517,0.0026869643,0.003534119,0.0013719192,0.97150594],"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":[0.00013671773,0.000121801575,0.0004772048,0.00038276726,0.00001785408,0.0001465903,0.00004931146,0.00015180628,0.0024496284,0.0051325853,0.6050301,0.38590366],"study_design_scores_gemma":[0.000029943838,0.00002578331,0.00048095273,0.00008560155,0.0000065297313,0.00016387033,0.000024577255,0.00013292549,0.000419032,0.0011162135,0.997502,0.000012434105],"about_ca_topic_score_codex":0.0036888518,"about_ca_topic_score_gemma":0.0040343874,"teacher_disagreement_score":0.047467947,"about_ca_system_score_codex":0.0012420198,"about_ca_system_score_gemma":0.0014515733,"threshold_uncertainty_score":0.06770718},"labels":[],"label_agreement":null},{"id":"W2113640782","doi":"10.1109/icde.2005.1","title":"\"One size fits all\": an idea whose time has come and gone","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":385,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Factoring; Computer science; Architecture; Phrase; Database; Parsing; Data warehouse; Data science; Artificial intelligence; Finance","score_opus":0.02638103870997723,"score_gpt":0.2544461153456867,"score_spread":0.22806507663570944,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2113640782","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006513976,0.046675306,0.20277467,0.6343631,0.025480054,0.00011274757,0.00022886308,0.0013677109,0.08248353],"genre_scores_gemma":[0.21303214,0.060023043,0.32878157,0.2746097,0.025963198,0.0008501768,0.00050544203,0.0035694377,0.092665195],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.991996,0.0034062024,0.00043349675,0.0011106554,0.002543648,0.0005099857],"domain_scores_gemma":[0.9852482,0.00574967,0.0008793538,0.002470076,0.0030925325,0.0025602176],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.017343268,0.0015877034,0.0010702483,0.0023123105,0.005318619,0.018116923,0.0035816806,0.010502041,0.010296733],"category_scores_gemma":[0.02571176,0.0009205316,0.0011546726,0.0032915196,0.026137078,0.07704827,0.0088247955,0.016904037,0.0046165395],"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":[0.000071716095,0.000032793716,0.00026637808,0.00024964672,0.000018233488,0.00008302093,0.0018702215,0.00023416894,0.00058848516,0.86079526,0.0764408,0.05934924],"study_design_scores_gemma":[0.000025195384,0.0001137766,0.00018553628,0.00033559135,0.000022681481,0.00033959787,0.0021788138,0.00082110387,0.0003571132,0.4824575,0.5130975,0.000065664906],"about_ca_topic_score_codex":0.001923636,"about_ca_topic_score_gemma":0.0017321694,"teacher_disagreement_score":0.018116923,"about_ca_system_score_codex":0.0037253771,"about_ca_system_score_gemma":0.005661436,"threshold_uncertainty_score":0.09172106},"labels":[],"label_agreement":null},{"id":"W2113885315","doi":"10.1109/lics.2005.51","title":"Temporal Logics over Unranked Trees","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Unary operation; Discrete mathematics; Monadic predicate calculus; Computer science; Mathematics; Tree (set theory); Boolean function; Combinatorics; Theoretical computer science; Description logic; Higher-order logic","score_opus":0.011032693944322138,"score_gpt":0.23232040716264446,"score_spread":0.22128771321832233,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2113885315","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":[0.054478243,0.0016127926,0.91676253,0.001244043,0.0002619745,0.00015734135,0.0009945617,0.0011568893,0.023331702],"genre_scores_gemma":[0.55974525,0.0017452795,0.41848275,0.00093186775,0.00047483778,0.0002360513,0.0014054148,0.00024196942,0.016736574],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99772686,0.0004909943,0.0002555279,0.00043889842,0.0008186154,0.00026907347],"domain_scores_gemma":[0.99673355,0.0016880266,0.00047175298,0.00028700868,0.00058501045,0.00023471413],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002085338,0.0006263601,0.00052468135,0.0014504574,0.0013100448,0.0032857554,0.0012433354,0.0006853492,0.0031842527],"category_scores_gemma":[0.00419921,0.00033799038,0.0010505375,0.0022267767,0.0020236347,0.007583343,0.001559183,0.0017208306,0.0005369352],"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":[0.000040397852,0.00002599989,0.00030547907,0.000085918495,0.000011778452,0.00024447884,0.0003696602,0.004973769,0.0015596364,0.9711676,0.0011214506,0.020093702],"study_design_scores_gemma":[0.000024901525,0.00003816153,0.00016270309,0.000037092617,0.000031333126,0.00023677877,0.00021884804,0.05035453,0.0032359704,0.9256736,0.019959701,0.000026302405],"about_ca_topic_score_codex":0.0050297044,"about_ca_topic_score_gemma":0.0052617234,"teacher_disagreement_score":0.0050297044,"about_ca_system_score_codex":0.0025729695,"about_ca_system_score_gemma":0.0013233816,"threshold_uncertainty_score":0.018668294},"labels":[],"label_agreement":null},{"id":"W2114059764","doi":"10.1109/ccece.2004.1349657","title":"An architectural framework for a distributed process control information system","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Process (computing); Information integration; Information system; Interface (matter); Distributed Computing Environment; Distributed database; Knowledge base; Distributed computing; Software engineering; Database; World Wide Web; Engineering","score_opus":0.007048151998068198,"score_gpt":0.2585817643372541,"score_spread":0.2515336123391859,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2114059764","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":[0.002037077,0.0005070599,0.9824483,0.0016201546,0.00009552183,0.00033245777,0.00008252239,0.002332502,0.010544357],"genre_scores_gemma":[0.056375228,0.00076439156,0.9326119,0.0004952116,0.00013079535,0.00077604287,0.00058428454,0.0003155964,0.007946623],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.995095,0.0011715274,0.00067466625,0.00072599895,0.0018385684,0.00049434963],"domain_scores_gemma":[0.9976738,0.00041377274,0.00017924742,0.00046260274,0.0008356116,0.00043498012],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006407305,0.001210186,0.0010147691,0.002594426,0.0028914171,0.010435987,0.0043853587,0.004076823,0.0046652667],"category_scores_gemma":[0.004261226,0.0013508538,0.0018644886,0.0025519961,0.004828431,0.006444493,0.004508331,0.0040887063,0.0029137696],"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":[0.00007285531,0.00011053995,0.00065817,0.0003198165,0.00008441537,0.000591711,0.0017358646,0.043647427,0.005959892,0.8896006,0.0066340836,0.05058466],"study_design_scores_gemma":[0.00015648529,0.00018104841,0.0005404272,0.00053409865,0.00020608047,0.00085228216,0.00084257626,0.2757406,0.0054268185,0.3631655,0.35218126,0.00017286965],"about_ca_topic_score_codex":0.014229775,"about_ca_topic_score_gemma":0.009903444,"teacher_disagreement_score":0.014229775,"about_ca_system_score_codex":0.0034012415,"about_ca_system_score_gemma":0.007164264,"threshold_uncertainty_score":0.03388548},"labels":[],"label_agreement":null},{"id":"W2114952411","doi":"10.5539/cis.v5n6p1","title":"A Materialized View for the Same Generation Query in Deductive Databases","year":2012,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Materialized view; Deductive database; Recursion (computer science); Relational database; Prolog; Database; Relational database management system; View; Logic programming; Database theory; Database design; Programming language","score_opus":0.049766639237263724,"score_gpt":0.30509586936628735,"score_spread":0.25532923012902364,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2114952411","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":[0.011030311,0.0002733956,0.98244816,0.00029911226,0.00009225882,0.00011853999,0.00021816275,0.0025353087,0.0029847922],"genre_scores_gemma":[0.16933917,0.00023435304,0.8272962,0.00029690447,0.000112246984,0.00013257613,0.0007807597,0.00043332434,0.0013744883],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9954204,0.001231351,0.0003260432,0.0006137576,0.0021148494,0.00029352435],"domain_scores_gemma":[0.99445844,0.0024955715,0.00023091634,0.001876736,0.0008102746,0.00012803996],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003436967,0.00064257707,0.00093447324,0.0015545009,0.0007534257,0.0052302056,0.002558088,0.001918578,0.006353788],"category_scores_gemma":[0.012247007,0.00068134675,0.001850138,0.0017011029,0.0023773285,0.007934946,0.0024734056,0.0021300216,0.0011651597],"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":[0.0012935714,0.00028437522,0.0030021875,0.000377195,0.00014023687,0.0007395713,0.00092073705,0.07468786,0.022336256,0.6312761,0.015783885,0.24915811],"study_design_scores_gemma":[0.00023584515,0.00041165616,0.00057870086,0.00011646662,0.00014202287,0.00069366524,0.00020758045,0.6918977,0.042169917,0.22136031,0.042028613,0.00015757362],"about_ca_topic_score_codex":0.0022390191,"about_ca_topic_score_gemma":0.0022762106,"teacher_disagreement_score":0.006353788,"about_ca_system_score_codex":0.0014538378,"about_ca_system_score_gemma":0.001501233,"threshold_uncertainty_score":0.021255553},"labels":[],"label_agreement":null},{"id":"W2115844906","doi":"10.1109/ideas.2007.6","title":"A Generalized Model for Mediator Based Information Integration","year":2007,"lang":"en","type":"article","venue":"International Database Engineering and Applications Symposium","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Schema (genetic algorithms); Information integration; Theoretical computer science; Data integration; Metadata; Semi-structured model; Dimension (graph theory); Relational database; Data mining; Information retrieval; Mathematics; Database model; Pure mathematics","score_opus":0.008660242678827585,"score_gpt":0.24393139441510744,"score_spread":0.23527115173627985,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2115844906","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":[0.004359629,0.0005835896,0.9651208,0.0025216085,0.00012628945,0.0002755925,0.00018144917,0.0008020509,0.026029062],"genre_scores_gemma":[0.26388624,0.0016850427,0.7070049,0.0018608583,0.0003041287,0.0018406924,0.0008249725,0.00027382324,0.022319337],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99604094,0.0014535625,0.0003536788,0.00067325216,0.0011302276,0.00034822014],"domain_scores_gemma":[0.9985153,0.00045462773,0.000109227665,0.0004779909,0.0003192513,0.00012350846],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004125255,0.0008413759,0.0009955904,0.0015701521,0.001956666,0.007927205,0.0035774421,0.0043281717,0.006618041],"category_scores_gemma":[0.004703046,0.0007428434,0.0021439889,0.0031014362,0.003132944,0.009237485,0.0057325587,0.0033419477,0.0025887364],"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":[0.00002653836,0.000021532594,0.00012463544,0.000050634833,0.000028044937,0.0003494887,0.00046204386,0.00818778,0.001086762,0.98072225,0.001895747,0.0070445687],"study_design_scores_gemma":[0.00006977028,0.000049323266,0.000085300606,0.00006768155,0.00005538809,0.00043547328,0.00023086647,0.0952618,0.0013178214,0.8479476,0.054440476,0.000038477967],"about_ca_topic_score_codex":0.003785019,"about_ca_topic_score_gemma":0.0021257934,"teacher_disagreement_score":0.007927205,"about_ca_system_score_codex":0.0024760033,"about_ca_system_score_gemma":0.0025664028,"threshold_uncertainty_score":0.022139609},"labels":[],"label_agreement":null},{"id":"W2117012917","doi":"10.1109/icde.2001.914869","title":"Discovery and application of check constraints in DB2","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada); York University","funders":"","keywords":"Computer science; Data integrity; Query optimization; Domain (mathematical analysis); Query language; Database; Data mining; Information retrieval","score_opus":0.011565229361440455,"score_gpt":0.2262328330816985,"score_spread":0.21466760372025806,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2117012917","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":[0.025253663,0.0005106264,0.95129085,0.0015897026,0.00015711317,0.00030004955,0.0015157812,0.01256311,0.0068191653],"genre_scores_gemma":[0.13166521,0.0005121405,0.8557708,0.0008484905,0.00012176242,0.00024998994,0.0032937727,0.002789043,0.0047488073],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9873505,0.0027293342,0.0013558852,0.0022334938,0.0054763523,0.0008542731],"domain_scores_gemma":[0.9833808,0.0067898477,0.0010275057,0.005278567,0.0028727388,0.00065054325],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010356416,0.001449787,0.0023357535,0.0038288424,0.003051255,0.0107353795,0.0041371984,0.0022099067,0.004728589],"category_scores_gemma":[0.028417083,0.0016210605,0.0024285032,0.0055053593,0.0028995601,0.010542413,0.0065440745,0.0038156104,0.0020278445],"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":[0.0012119683,0.00041527773,0.011443104,0.00080148166,0.00025675836,0.0013950454,0.0034916522,0.02426875,0.024851084,0.46692297,0.03433674,0.43060517],"study_design_scores_gemma":[0.00024264414,0.00016402967,0.001996451,0.00016889391,0.00021949218,0.0013541318,0.0013168908,0.42045337,0.10990371,0.27733582,0.18653175,0.00031289356],"about_ca_topic_score_codex":0.012592903,"about_ca_topic_score_gemma":0.009551299,"teacher_disagreement_score":0.012592903,"about_ca_system_score_codex":0.0026866372,"about_ca_system_score_gemma":0.0047188103,"threshold_uncertainty_score":0.05477059},"labels":[],"label_agreement":null},{"id":"W2117212502","doi":"10.1109/ideas.2007.10","title":"Adaptive Execution of Stream Window Joins in a Limited Memory Environment","year":2007,"lang":"en","type":"article","venue":"International Database Engineering and Applications Symposium","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Joins; Data stream mining; Sliding window protocol; Data stream; Window (computing); Distributed computing; Parallel computing; Volume (thermodynamics); Real-time computing; Algorithm; Data mining; Operating system; Programming language","score_opus":0.007330074884625044,"score_gpt":0.21490768763927773,"score_spread":0.2075776127546527,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2117212502","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":[0.37811399,0.00043722495,0.6162872,0.000094453775,0.000068445486,0.000115377414,0.000092416965,0.002982289,0.0018086317],"genre_scores_gemma":[0.7791939,0.00018088035,0.21855032,0.000035642188,0.00004793076,0.00010188959,0.0002752221,0.00017520093,0.001439056],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990872,0.00019993377,0.000090504094,0.00022554035,0.00030585096,0.00009089289],"domain_scores_gemma":[0.9980726,0.0008735544,0.00017105622,0.00046110892,0.00024852552,0.00017308745],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014689064,0.00043171505,0.0005664952,0.0004026552,0.00055328227,0.0009315379,0.0012419465,0.00039210884,0.0009010741],"category_scores_gemma":[0.0040295986,0.00032660575,0.00030980696,0.00052979775,0.0004148785,0.0012871897,0.0012298573,0.00046309418,0.0002330583],"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":[0.0063268077,0.00069266726,0.016704556,0.00033321255,0.00024158956,0.0011570632,0.0011911556,0.23937798,0.26135996,0.022564473,0.003910651,0.44614],"study_design_scores_gemma":[0.00012599996,0.00022901926,0.0010163855,0.000007271681,0.000030822564,0.0001467361,0.000065862565,0.94831085,0.043406963,0.0043458045,0.0022987332,0.00001558185],"about_ca_topic_score_codex":0.00070404354,"about_ca_topic_score_gemma":0.0008427889,"teacher_disagreement_score":0.0014689064,"about_ca_system_score_codex":0.00027284672,"about_ca_system_score_gemma":0.00049643684,"threshold_uncertainty_score":0.007768452},"labels":[],"label_agreement":null},{"id":"W2117538598","doi":"10.14778/1687627.1687659","title":"A scalable, predictable join operator for highly concurrent data warehouses","year":2009,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":87,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"ASTER","funders":"","keywords":"Computer science; Query plan; Scalability; Query optimization; Online aggregation; Data warehouse; Tuple; Throughput; Computation; Query language; Pipeline (software); Sargable; Database; Data mining; Distributed computing; Web search query; Search engine; Information retrieval; Algorithm; Programming language","score_opus":0.035230274181042985,"score_gpt":0.27187334763998267,"score_spread":0.23664307345893967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2117538598","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":[0.085927665,0.0002727742,0.89041823,0.0002680905,0.00008081797,0.00028006025,0.00018183955,0.020662552,0.0019080575],"genre_scores_gemma":[0.5524328,0.00018168066,0.4438276,0.00017512027,0.00010251691,0.00019874256,0.00044907877,0.0005956781,0.0020368616],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986507,0.00013202179,0.00009276383,0.00025768395,0.0007286532,0.00013809715],"domain_scores_gemma":[0.9984194,0.00045569698,0.00013219302,0.00052932755,0.0002719664,0.00019132764],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019360201,0.00050874706,0.0005529565,0.0004267008,0.000803351,0.0013282615,0.0027246808,0.0005036845,0.0012959958],"category_scores_gemma":[0.002925025,0.0006188284,0.0004519189,0.00058044674,0.0006813659,0.0019151407,0.0019171132,0.0012459446,0.00041278356],"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":[0.0031635913,0.0011259685,0.010841678,0.00033601394,0.00015406875,0.0006994168,0.0012291957,0.06636148,0.36759812,0.02747726,0.025750143,0.49526298],"study_design_scores_gemma":[0.00037691186,0.0006037064,0.0017137072,0.00001416711,0.00008142966,0.00034490426,0.00015747616,0.9210724,0.05316964,0.008804369,0.013592032,0.0000691705],"about_ca_topic_score_codex":0.004068205,"about_ca_topic_score_gemma":0.0039870827,"teacher_disagreement_score":0.004068205,"about_ca_system_score_codex":0.0005839977,"about_ca_system_score_gemma":0.0019721508,"threshold_uncertainty_score":0.010238767},"labels":[],"label_agreement":null},{"id":"W2117934745","doi":"10.1109/icde.1989.47212","title":"Experience in applying conceptual modelling to interface with a real-life business application","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Underwriting; Computer science; Interface (matter); Conceptual model; Software engineering; World Wide Web; Data science; Database; Operating system; Business","score_opus":0.03949641063972097,"score_gpt":0.2845556962358557,"score_spread":0.2450592855961347,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2117934745","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":[0.33558577,0.0010369406,0.59960127,0.004223566,0.00018534053,0.0004422394,0.00023344686,0.005196849,0.05349453],"genre_scores_gemma":[0.5400154,0.001582895,0.4316322,0.001262414,0.000056187575,0.00023225647,0.00057972956,0.0009084068,0.023730597],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99601424,0.002709256,0.00018891654,0.00028811058,0.0005571843,0.00024230382],"domain_scores_gemma":[0.9921003,0.005370677,0.00014615868,0.0010813909,0.00079013844,0.0005113192],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008545252,0.00093477237,0.00058226177,0.00064374326,0.0014812413,0.0041309716,0.0028069052,0.003531447,0.006534942],"category_scores_gemma":[0.017374597,0.0007481834,0.0007659369,0.0009788371,0.0015560531,0.005037225,0.0023382362,0.002861349,0.0020593207],"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":[0.0008507584,0.00727948,0.017498273,0.0018203596,0.00021903777,0.005783811,0.18517816,0.056245845,0.05752272,0.062487084,0.045161374,0.5599531],"study_design_scores_gemma":[0.0003672976,0.0039007862,0.008881129,0.00083605753,0.0004229828,0.008341935,0.03954927,0.33735788,0.044266347,0.036738068,0.51884806,0.00049005414],"about_ca_topic_score_codex":0.005806613,"about_ca_topic_score_gemma":0.0065925037,"teacher_disagreement_score":0.008545252,"about_ca_system_score_codex":0.001399569,"about_ca_system_score_gemma":0.0010994278,"threshold_uncertainty_score":0.045192122},"labels":[],"label_agreement":null},{"id":"W2118336583","doi":"10.1007/11823728_4","title":"Dynamic View Selection for OLAP","year":2006,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Online analytical processing; Computer science; Materialized view; Data warehouse; Selection (genetic algorithm); Aggregate (composite); Task (project management); Set (abstract data type); Data mining; Information retrieval; Artificial intelligence; View","score_opus":0.011363035304567927,"score_gpt":0.252280441725159,"score_spread":0.2409174064205911,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2118336583","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":[0.01604042,0.0026804917,0.9555698,0.0003052316,0.00024805524,0.00010145711,0.0010584372,0.01248994,0.011506145],"genre_scores_gemma":[0.27984023,0.0016984552,0.6980116,0.0002527032,0.0002393187,0.00015613802,0.0037886146,0.001887905,0.014125078],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991856,0.0001465755,0.000053009582,0.00013059778,0.00039308323,0.000091150374],"domain_scores_gemma":[0.9990589,0.00028133517,0.000040500425,0.00038818145,0.0001685591,0.00006261031],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006912704,0.0007284022,0.0008169631,0.0008359983,0.0007249643,0.001984586,0.0015679142,0.0005220952,0.009477097],"category_scores_gemma":[0.0017951876,0.000545055,0.0005510708,0.0018012347,0.00045575382,0.0027919873,0.001789022,0.0014017125,0.0023620753],"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":[0.00070008537,0.00016788866,0.0010766367,0.00032292175,0.00008090454,0.00027308828,0.00019635417,0.020827623,0.022183497,0.058059484,0.056329668,0.83978176],"study_design_scores_gemma":[0.00016135766,0.00023604883,0.0012445461,0.00013355655,0.00010884425,0.0009146277,0.00031663207,0.5869222,0.044262577,0.24491097,0.12065896,0.00012963807],"about_ca_topic_score_codex":0.0017672773,"about_ca_topic_score_gemma":0.002468503,"teacher_disagreement_score":0.009477097,"about_ca_system_score_codex":0.0004915602,"about_ca_system_score_gemma":0.0005509854,"threshold_uncertainty_score":0.03170407},"labels":[],"label_agreement":null},{"id":"W2118899311","doi":"10.1007/978-3-642-15105-7_14","title":"The NOX Framework: Native Language Queries for Business Intelligence Applications","year":2010,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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":"Concordia University","funders":"","keywords":"Computer science; SQL; Online analytical processing; Relational database management system; Programming language; Software engineering; Database; Object-oriented programming; Query language; Flexibility (engineering); Relational database; Query by Example; Domain (mathematical analysis); World Wide Web; Data warehouse; Web search query","score_opus":0.014164071897745682,"score_gpt":0.2832514141021563,"score_spread":0.26908734220441066,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2118899311","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":[0.006596081,0.0010767785,0.8959129,0.000611447,0.00030253944,0.0002489527,0.0018633057,0.079654455,0.0137337],"genre_scores_gemma":[0.1801056,0.0027363421,0.7288641,0.0019994283,0.0004243189,0.0005674284,0.016743077,0.02703029,0.041529436],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979292,0.00033952144,0.00021115341,0.00026924614,0.0010719297,0.00017889433],"domain_scores_gemma":[0.9986926,0.00042529576,0.000070966766,0.00043381797,0.00026684397,0.00011060665],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027878666,0.00096611155,0.0011850202,0.001032926,0.0007196681,0.004768422,0.003349048,0.0012928741,0.00910105],"category_scores_gemma":[0.005001819,0.0009819046,0.0011269823,0.0011505213,0.0011970613,0.0058408636,0.0033757044,0.0020552296,0.0051871114],"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":[0.0009926417,0.0002973522,0.002269098,0.0010062649,0.00012109215,0.00052644045,0.0012838255,0.009838026,0.02155495,0.31563938,0.2663288,0.38014203],"study_design_scores_gemma":[0.00024305502,0.00012945822,0.00075464475,0.00023551757,0.00017219868,0.0008004886,0.00033602357,0.16658224,0.028388087,0.18707842,0.6151258,0.00015408082],"about_ca_topic_score_codex":0.004426068,"about_ca_topic_score_gemma":0.004370807,"teacher_disagreement_score":0.00910105,"about_ca_system_score_codex":0.0011895405,"about_ca_system_score_gemma":0.0016532526,"threshold_uncertainty_score":0.030446112},"labels":[],"label_agreement":null},{"id":"W2121195856","doi":"10.1145/1925805.1925812","title":"Exploiting uniqueness in query optimization","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada)","funders":"","keywords":"Query optimization; Computer science; Exploit; SQL; sort; Sargable; Query by Example; Query language; Conjunctive query; Query expansion; Table (database); Relational database; Uniqueness; Theoretical computer science; Data mining; Web search query; Information retrieval; Database; Mathematics; Search engine","score_opus":0.007625288036715054,"score_gpt":0.2320384156873776,"score_spread":0.22441312765066254,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121195856","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":[0.0625788,0.0007043988,0.92743534,0.0010067453,0.000060588212,0.00020728492,0.00018965198,0.0016693752,0.0061477874],"genre_scores_gemma":[0.5735722,0.00049410784,0.42224702,0.00063624687,0.00010793615,0.0001836215,0.00032427645,0.0005227025,0.0019119371],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.98955685,0.0039332085,0.0008134443,0.0014495419,0.0028250953,0.0014218267],"domain_scores_gemma":[0.9793444,0.014922212,0.0009598127,0.0030415817,0.0014918634,0.0002400413],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00878676,0.0009731988,0.0015482361,0.0015232539,0.0019918715,0.0031920914,0.0022128809,0.001436525,0.0029650354],"category_scores_gemma":[0.031034697,0.0009970223,0.0018653434,0.0023738297,0.004391709,0.010879346,0.007371011,0.0022449947,0.00078516896],"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":[0.00141721,0.0003717308,0.018999843,0.00093201717,0.00037597603,0.001954522,0.0016409528,0.13983917,0.039661158,0.47659004,0.009105991,0.30911136],"study_design_scores_gemma":[0.0001459816,0.00046180817,0.001844556,0.00013932172,0.00025918262,0.0013285434,0.00072909956,0.4758396,0.07053713,0.43405598,0.014484603,0.00017419503],"about_ca_topic_score_codex":0.0025922982,"about_ca_topic_score_gemma":0.0020498978,"teacher_disagreement_score":0.00878676,"about_ca_system_score_codex":0.0010371795,"about_ca_system_score_gemma":0.0025218404,"threshold_uncertainty_score":0.04646933},"labels":[],"label_agreement":null},{"id":"W2121324617","doi":"10.1145/1594156.1594170","title":"Query interactions in database workloads","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Database; View; Database tuning; Query optimization; Database testing; Data mining; Database theory; Online aggregation; Database design; Sargable; Information retrieval; Web search query; Search engine","score_opus":0.02252401156989909,"score_gpt":0.2980112363743665,"score_spread":0.2754872248044674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121324617","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":[0.95406514,0.0005649713,0.040727712,0.0006963387,0.00007539577,0.0002689459,0.00041556198,0.0008489907,0.0023369077],"genre_scores_gemma":[0.991252,0.00007439967,0.0074382965,0.00017299547,0.00004041928,0.00014772215,0.00045942917,0.00009262474,0.00032195987],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.95925575,0.014590956,0.003214713,0.0046607335,0.015754169,0.0025236856],"domain_scores_gemma":[0.8785884,0.09219353,0.008980515,0.008959116,0.008255989,0.0030225],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009998214,0.0011618304,0.0014303813,0.001553943,0.0019517397,0.0042612343,0.002026065,0.0020824804,0.0013530125],"category_scores_gemma":[0.07844724,0.0011192429,0.00068863464,0.0023202898,0.0014943812,0.0050317426,0.0023520521,0.0026557066,0.00057358795],"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":[0.0068414668,0.004369599,0.3644418,0.00095044664,0.00087168236,0.003125159,0.0039082193,0.25301206,0.21768148,0.023019856,0.0067669405,0.11501134],"study_design_scores_gemma":[0.00020052807,0.0019599057,0.062648386,0.000055578585,0.00022479163,0.0024309945,0.0014567234,0.8595367,0.049524512,0.017674735,0.004089924,0.00019717513],"about_ca_topic_score_codex":0.0018629478,"about_ca_topic_score_gemma":0.0014011794,"teacher_disagreement_score":0.009998214,"about_ca_system_score_codex":0.0017049181,"about_ca_system_score_gemma":0.0015394071,"threshold_uncertainty_score":0.052876234},"labels":[],"label_agreement":null},{"id":"W2121601564","doi":"10.1145/2247596.2247644","title":"Repair-oriented relational schemas for multidimensional databases","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Relational database; Computer science; Schema (genetic algorithms); Relational model; Database; Dimension (graph theory); Relational calculus; Information schema; Theoretical computer science; Data mining; Database model; Semi-structured model; Information retrieval; Mathematics","score_opus":0.05126526650099991,"score_gpt":0.3000863310589025,"score_spread":0.24882106455790257,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121601564","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":[0.00086454203,0.0010841243,0.99250174,0.00052743644,0.00018031558,0.00019226535,0.0007232915,0.0012944426,0.0026317616],"genre_scores_gemma":[0.021702986,0.0022492523,0.96968186,0.0005606879,0.00017970431,0.00046331322,0.002238033,0.00045555268,0.0024686744],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9934767,0.0020025293,0.0015076665,0.0007533299,0.002065066,0.0001947148],"domain_scores_gemma":[0.9909032,0.002322079,0.001086525,0.0034098842,0.002037656,0.00024070965],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0072446098,0.00092327734,0.0007900026,0.0021123698,0.0011145906,0.005603627,0.003456822,0.0021672165,0.007099786],"category_scores_gemma":[0.014311172,0.0009139329,0.0017643605,0.0044955383,0.0019103233,0.008379495,0.003047968,0.003493704,0.0037784297],"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":[0.00003763019,0.000029217008,0.00034314996,0.0004996664,0.000036441244,0.00024210032,0.0008543985,0.00508129,0.0026587122,0.9280722,0.012510002,0.049635194],"study_design_scores_gemma":[0.00004726865,0.0000667292,0.00023974759,0.0003546962,0.00007113468,0.0011046198,0.0006718237,0.025298871,0.0084693255,0.3445725,0.6190353,0.00006787835],"about_ca_topic_score_codex":0.001499797,"about_ca_topic_score_gemma":0.0015840114,"teacher_disagreement_score":0.0072446098,"about_ca_system_score_codex":0.0014230189,"about_ca_system_score_gemma":0.0022599334,"threshold_uncertainty_score":0.038313627},"labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"not_applicable","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"low"},{"model":"gpt","categories":[],"domain":null,"study_design":"theoretical_or_conceptual","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"low"}],"label_agreement":"split"},{"id":"W2122115541","doi":"10.1109/tkde.2003.1232279","title":"Reasoning about uniqueness constraints in object relational databases","year":2003,"lang":"en","type":"article","venue":"IEEE Transactions on Knowledge and Data Engineering","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Relational database; Uniqueness; Generalization; Functional dependency; Theoretical computer science; Relational model; Object (grammar); Simple (philosophy); Relational calculus; Representation (politics); Core (optical fiber); Database; Artificial intelligence; Mathematics","score_opus":0.03363073257960945,"score_gpt":0.27978618866793326,"score_spread":0.24615545608832382,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2122115541","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":[0.027876124,0.0010536715,0.96525663,0.0020293514,0.00004653363,0.000111603265,0.00032247652,0.00035944366,0.0029442592],"genre_scores_gemma":[0.41891316,0.0020622108,0.5730703,0.0006975381,0.00029411147,0.00029285235,0.001155058,0.00020547419,0.0033093302],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98575807,0.006545165,0.0014793696,0.0020085606,0.003469297,0.000739519],"domain_scores_gemma":[0.9743896,0.020441175,0.001500312,0.002121264,0.001177469,0.00037012793],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013913274,0.0010020527,0.0015658097,0.0019442166,0.0031167236,0.0072989725,0.0034211266,0.002779393,0.0035368928],"category_scores_gemma":[0.03767237,0.0015144532,0.0027446772,0.0043119704,0.0042837695,0.025530655,0.006035931,0.003876223,0.00051071314],"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":[0.00013683704,0.00007420541,0.002009736,0.00036986123,0.00012005643,0.0008083706,0.00080035714,0.052067425,0.0017422898,0.8795572,0.0038540221,0.05845949],"study_design_scores_gemma":[0.000030989617,0.000025071493,0.00023591435,0.00005298188,0.00008361493,0.00030549738,0.00041694724,0.104734726,0.0034730001,0.8851229,0.0054798583,0.000038434613],"about_ca_topic_score_codex":0.0034074038,"about_ca_topic_score_gemma":0.004556721,"teacher_disagreement_score":0.013913274,"about_ca_system_score_codex":0.0019964448,"about_ca_system_score_gemma":0.002306853,"threshold_uncertainty_score":0.07358128},"labels":[],"label_agreement":null},{"id":"W2122306245","doi":"10.1109/wise.2001.996477","title":"Mapping DTDs to object-oriented schemas","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Computer science; Document Structure Description; Document type definition; XML; Information retrieval; Relational database; XML validation; SGML; XML Schema (W3C); Programming language; Database; World Wide Web","score_opus":0.014798592482927383,"score_gpt":0.25461230505137555,"score_spread":0.23981371256844816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2122306245","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":[0.0010801642,0.00056525465,0.98914564,0.00056979177,0.00031701138,0.00023325183,0.0010012873,0.0015094979,0.0055780015],"genre_scores_gemma":[0.016044619,0.002146176,0.97136873,0.00052031205,0.00015977844,0.00053472986,0.0034813075,0.00059878733,0.005145687],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99248123,0.0026679537,0.0016106423,0.00083464844,0.0021445933,0.00026101604],"domain_scores_gemma":[0.9926945,0.0027307284,0.00054835324,0.0021247156,0.0016377497,0.00026392593],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007067723,0.000881565,0.000830337,0.004134726,0.001093854,0.0075332746,0.0026908927,0.0018894874,0.0062225955],"category_scores_gemma":[0.01627766,0.0011628536,0.0018305366,0.0061936504,0.0019011826,0.008598097,0.00433565,0.0032244301,0.004072427],"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":[0.000056094646,0.00006463453,0.00060558564,0.00047713108,0.000082977655,0.00071167323,0.0016688538,0.006821096,0.0029643339,0.84450614,0.015976485,0.12606493],"study_design_scores_gemma":[0.0000465923,0.00003437782,0.0001955699,0.0003047839,0.00007853057,0.00075163826,0.0006050072,0.028933115,0.0062166215,0.3806121,0.582169,0.00005257482],"about_ca_topic_score_codex":0.0037439263,"about_ca_topic_score_gemma":0.002429869,"teacher_disagreement_score":0.0075332746,"about_ca_system_score_codex":0.0020619791,"about_ca_system_score_gemma":0.0022751887,"threshold_uncertainty_score":0.037378132},"labels":[],"label_agreement":null},{"id":"W2122660326","doi":"10.1109/infcom.1993.253294","title":"Modeling and formal specification of the personal communication service","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Executable; Computer science; Formal specification; Language Of Temporal Ordering Specification; Specification language; Programming language; Formalism (music); Programming language specification; Formal methods; Software engineering; System requirements specification; Refinement; Algebraic specification","score_opus":0.04170833148359831,"score_gpt":0.22733563947936175,"score_spread":0.18562730799576344,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2122660326","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":[0.010333142,0.00042943138,0.96790254,0.0008005797,0.00008827286,0.0002907247,0.00046737926,0.0010745331,0.018613327],"genre_scores_gemma":[0.24998282,0.0015447385,0.71776587,0.00031834582,0.000111938156,0.0013661024,0.0013627381,0.00022255469,0.027324943],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984586,0.0003502264,0.00015027351,0.0001565845,0.0007033063,0.00018091818],"domain_scores_gemma":[0.9991702,0.0003437093,0.00011550541,0.00012677225,0.00019411946,0.000049669114],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014216703,0.00068777415,0.00046646886,0.00097123696,0.00084849744,0.0039365194,0.0016165768,0.0017486837,0.004066322],"category_scores_gemma":[0.0024391436,0.00060950534,0.0012255306,0.00088823016,0.0018347882,0.0022257704,0.0011160515,0.0015359969,0.0011338892],"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":[0.000046515626,0.00007848124,0.0003642361,0.00020394064,0.000014911334,0.00061269023,0.0006452336,0.06136797,0.0063165487,0.9117174,0.0020477946,0.016584273],"study_design_scores_gemma":[0.00013878354,0.00014999883,0.000383044,0.00026925837,0.00006560586,0.0010184499,0.0003588518,0.5617447,0.01587872,0.23882663,0.18108837,0.000077616176],"about_ca_topic_score_codex":0.011241232,"about_ca_topic_score_gemma":0.006483172,"teacher_disagreement_score":0.011241232,"about_ca_system_score_codex":0.0018081744,"about_ca_system_score_gemma":0.004936664,"threshold_uncertainty_score":0.022351563},"labels":[],"label_agreement":null},{"id":"W2123041000","doi":"10.1109/iv.2003.1217981","title":"A new algorithm for transitive closures and computation of recursion in relational databases","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Transitive closure; Transitive reduction; Recursion (computer science); Transitive relation; Graph; Computation; Algorithm; Computer science; Directed graph; Relational database; Mathematics; Combinatorics; Computational complexity theory; Discrete mathematics; Theoretical computer science; Voltage graph; Line graph; Database","score_opus":0.030538407827767882,"score_gpt":0.2948107845568169,"score_spread":0.264272376729049,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2123041000","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":[0.0025105078,0.00026613844,0.99276334,0.00011045792,0.000064114414,0.000109703105,0.00019610312,0.0025408021,0.0014389218],"genre_scores_gemma":[0.023714961,0.00024148622,0.9731939,0.000088735454,0.0000638208,0.0001962425,0.000646631,0.00039909614,0.0014551412],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9967513,0.0005047299,0.00042576235,0.00086205243,0.0011970331,0.00025913192],"domain_scores_gemma":[0.9965204,0.0015383422,0.00019871388,0.00088884035,0.0007316451,0.00012207212],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018849586,0.0010850017,0.0013680983,0.002571341,0.0014397784,0.0038323558,0.002496678,0.0012720398,0.0050824475],"category_scores_gemma":[0.007821171,0.0011625583,0.0020582508,0.0032397814,0.0014214219,0.009464325,0.0033020189,0.002468907,0.0022818586],"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":[0.00024397088,0.00020746514,0.001177082,0.0004789979,0.00012897624,0.00025517406,0.00093242805,0.018317869,0.015434915,0.21852978,0.020705407,0.72358793],"study_design_scores_gemma":[0.00023997315,0.00032944398,0.0007517955,0.00021130733,0.00021470955,0.0010606486,0.00044703865,0.4312004,0.026367705,0.41557005,0.12342672,0.00018028643],"about_ca_topic_score_codex":0.0038616464,"about_ca_topic_score_gemma":0.0041827145,"teacher_disagreement_score":0.0050824475,"about_ca_system_score_codex":0.0015617603,"about_ca_system_score_gemma":0.0023078346,"threshold_uncertainty_score":0.017002523},"labels":[],"label_agreement":null},{"id":"W2123061300","doi":"10.1145/1007568.1007591","title":"Optimization of query streams using semantic prefetching","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Latency (audio); Context (archaeology); Server; Query optimization; Data mining; Information retrieval; Computer network; Database","score_opus":0.01914326586735384,"score_gpt":0.254980061574268,"score_spread":0.23583679570691415,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2123061300","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":[0.5330257,0.0009109362,0.44718713,0.00064804463,0.000080367725,0.00026692817,0.00066666404,0.012825945,0.004388339],"genre_scores_gemma":[0.89014435,0.0001778996,0.106857,0.000110474066,0.000047645164,0.00008377217,0.0007040777,0.00024983738,0.0016249798],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999062,0.00017593274,0.0000774004,0.00020868954,0.00034137114,0.00013467083],"domain_scores_gemma":[0.99809057,0.0009193752,0.00014787355,0.00039448895,0.00036708466,0.00008066026],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009656864,0.000856953,0.00081631093,0.0005779322,0.00038704177,0.0009123372,0.0011401023,0.0005119936,0.0013692068],"category_scores_gemma":[0.0058037923,0.00036224577,0.00032796958,0.0011427607,0.00045928225,0.0018812224,0.0008382134,0.0007523556,0.00027921784],"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":[0.0014979069,0.00053144136,0.011083227,0.00015844557,0.00009169392,0.00026792943,0.00020854289,0.501859,0.052368324,0.004630949,0.007929933,0.41937265],"study_design_scores_gemma":[0.00003708781,0.000057621095,0.0005909258,0.0000018372347,0.000010830318,0.00002937995,0.000027918748,0.98552763,0.011383025,0.0017696811,0.0005566544,0.0000074574664],"about_ca_topic_score_codex":0.0057800077,"about_ca_topic_score_gemma":0.009036966,"teacher_disagreement_score":0.0057800077,"about_ca_system_score_codex":0.0007910218,"about_ca_system_score_gemma":0.0013647362,"threshold_uncertainty_score":0.011492729},"labels":[],"label_agreement":null},{"id":"W2123080243","doi":"10.1007/s00778-009-0159-9","title":"Schema mapping and query translation in heterogeneous P2P XML databases","year":2009,"lang":"en","type":"article","venue":"The VLDB Journal","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":42,"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 British Columbia Hospital","funders":"","keywords":"Computer science; XQuery; Information retrieval; Scalability; Schema (genetic algorithms); Document Structure Description; Metadata; XML; Query language; XML Schema Editor; Database; World Wide Web","score_opus":0.04612929082107779,"score_gpt":0.2739027125305562,"score_spread":0.2277734217094784,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2123080243","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":[0.06355721,0.0008864255,0.91413784,0.0016228833,0.00022221544,0.00045911514,0.0009818865,0.010725826,0.0074065207],"genre_scores_gemma":[0.51872003,0.0012496229,0.46529642,0.00082439446,0.00014645247,0.0004916566,0.004052925,0.0017399135,0.0074785696],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.992761,0.0029679702,0.00097629486,0.0008142027,0.0020212217,0.00045932995],"domain_scores_gemma":[0.9916053,0.004748578,0.00029886764,0.0022181275,0.0009218721,0.0002072663],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008666717,0.0006861103,0.0011798358,0.0019819944,0.0015291993,0.0061955648,0.0028188266,0.0019948815,0.003615539],"category_scores_gemma":[0.015462165,0.0011479482,0.0014382552,0.003282381,0.0018555155,0.008977483,0.0043622265,0.0019556577,0.0014194092],"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":[0.0021957965,0.000952195,0.008024548,0.001313444,0.00034906328,0.004070913,0.005851466,0.07184397,0.039745275,0.27234504,0.034413014,0.55889535],"study_design_scores_gemma":[0.00034207586,0.0002913464,0.0022723665,0.0002167929,0.0003449768,0.0016597371,0.0034959419,0.60882986,0.11046946,0.22234957,0.049541797,0.00018611719],"about_ca_topic_score_codex":0.004554855,"about_ca_topic_score_gemma":0.002707478,"teacher_disagreement_score":0.008666717,"about_ca_system_score_codex":0.0010436667,"about_ca_system_score_gemma":0.0018066276,"threshold_uncertainty_score":0.04583454},"labels":[],"label_agreement":null},{"id":"W2123539568","doi":"10.1109/ssdbm.2007.33","title":"Efficient Indexing of Heterogeneous Data Streams with Automatic Performance Configurations","year":2007,"lang":"en","type":"article","venue":"International Conference on Scientific and Statistical Database Management","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Search engine indexing; Computer science; Data stream mining; Stream processing; Data mining; Data stream; Bitmap; Lossless compression; Sketch; Data structure; Cluster analysis; Index (typography); Data compression; Distributed computing; Information retrieval; Algorithm; Artificial intelligence","score_opus":0.05475050939834741,"score_gpt":0.31661498309759284,"score_spread":0.2618644736992454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2123539568","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":[0.15661009,0.00047470295,0.8373263,0.00028151085,0.00007405532,0.00015291576,0.00016081867,0.0031839001,0.0017357083],"genre_scores_gemma":[0.7462261,0.00027034644,0.25134104,0.00006500113,0.00009642451,0.0001541462,0.00046359925,0.00025851795,0.0011248151],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99823546,0.0002865399,0.00017918694,0.00028115077,0.00081203686,0.00020560429],"domain_scores_gemma":[0.99561006,0.0018869991,0.00045798928,0.00090739405,0.0008962455,0.00024138298],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002354143,0.00076889794,0.0015199163,0.0013116421,0.0009861815,0.0028287664,0.0023681237,0.00091547205,0.00082520285],"category_scores_gemma":[0.011500959,0.00048421428,0.00043406885,0.0025352212,0.0011030576,0.004153675,0.0019448736,0.000953982,0.0004016803],"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":[0.0010765245,0.00045573222,0.005293198,0.0002419816,0.00008858437,0.00039982636,0.00053572137,0.5520873,0.055205684,0.0217323,0.00461095,0.3582721],"study_design_scores_gemma":[0.00002674369,0.00005456612,0.00027037977,0.0000034887712,0.000009193011,0.000043720767,0.000047049438,0.98291475,0.010917676,0.0051274016,0.00057254464,0.000012559511],"about_ca_topic_score_codex":0.0019564582,"about_ca_topic_score_gemma":0.0014790721,"teacher_disagreement_score":0.0028287664,"about_ca_system_score_codex":0.0009713128,"about_ca_system_score_gemma":0.0010970895,"threshold_uncertainty_score":0.012450039},"labels":[],"label_agreement":null},{"id":"W2123613512","doi":"10.1109/icde.1993.344024","title":"Normalization of linear recursions in deductive databases","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Normalization (sociology); Recursion (computer science); Computer science; Graph; Deductive database; Linear map; Linear algebra; Matrix (chemical analysis); Algorithm; Theoretical computer science; Algebra over a field; Mathematics; Pure mathematics","score_opus":0.04767208002207829,"score_gpt":0.2751483217472044,"score_spread":0.2274762417251261,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2123613512","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":[0.016115041,0.00013848896,0.9734528,0.00014229275,0.00003715604,0.00007822149,0.00015818441,0.004979875,0.004897904],"genre_scores_gemma":[0.32035977,0.00037094794,0.6707527,0.0002468494,0.0000748991,0.00021119323,0.00074876787,0.0014277716,0.005807122],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99634296,0.0009312376,0.00030610478,0.0007406147,0.0014680746,0.00021102595],"domain_scores_gemma":[0.99608254,0.0017136477,0.00022658333,0.0010759906,0.00083659135,0.000064666776],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016991793,0.0004423473,0.000587216,0.00105882,0.00069954677,0.0026132914,0.0016185143,0.00052314624,0.0033022244],"category_scores_gemma":[0.008171878,0.0006023639,0.0010052357,0.0016094783,0.002009969,0.0053665405,0.0017067086,0.0013346666,0.0010762074],"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":[0.00011776685,0.000086260705,0.0010729798,0.00018261565,0.000032547232,0.00021368083,0.00066470826,0.04342843,0.012347878,0.70266443,0.0040238234,0.23516485],"study_design_scores_gemma":[0.000030835636,0.000060630806,0.00045368195,0.000057759997,0.00004876982,0.00030729745,0.00014298694,0.3030102,0.046878956,0.6155015,0.03343562,0.00007178654],"about_ca_topic_score_codex":0.0039456,"about_ca_topic_score_gemma":0.0038033794,"teacher_disagreement_score":0.0039456,"about_ca_system_score_codex":0.0015782779,"about_ca_system_score_gemma":0.0013360006,"threshold_uncertainty_score":0.011451185},"labels":[],"label_agreement":null},{"id":"W2123753601","doi":"10.5381/jot.2003.2.5.c1","title":"The Impedance Imperative Tuples + Objects + Infosets = Too Much Stuff!","year":2003,"lang":"en","type":"article","venue":"The Journal of Object Technology","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"XQuery; Computer science; Tuple; XML; Programming language; XML database; Database; Information retrieval; World Wide Web","score_opus":0.006572448303507189,"score_gpt":0.244226806990999,"score_spread":0.2376543586874918,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2123753601","genre_codex":"methods","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008571301,0.0027793695,0.74651754,0.03756139,0.006936212,0.00020037392,0.002277386,0.021024553,0.17413186],"genre_scores_gemma":[0.16019015,0.004726615,0.4724432,0.042197227,0.0021961408,0.0005763934,0.002295365,0.031575907,0.28379893],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99747795,0.00086697703,0.00018647568,0.0004128684,0.00087923027,0.00017649507],"domain_scores_gemma":[0.99541485,0.0021862676,0.00020732851,0.0011507168,0.00082739204,0.00021339026],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002225135,0.0009900923,0.0007491083,0.0007111131,0.0014574273,0.0053814887,0.0014048663,0.0020790545,0.03302864],"category_scores_gemma":[0.00972167,0.0009032518,0.0007663099,0.0010773712,0.0042528235,0.014656353,0.0037547427,0.006066316,0.023845514],"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":[0.0003009228,0.0000392173,0.0011316716,0.0006708392,0.000036065565,0.00025713653,0.0024135376,0.00076985074,0.008277797,0.6844017,0.18350478,0.11819646],"study_design_scores_gemma":[0.000026869206,0.000046117413,0.00026137513,0.00015183022,0.000023800234,0.00040770753,0.0003338817,0.0020089026,0.0048236405,0.19912702,0.79273856,0.00005027911],"about_ca_topic_score_codex":0.0021707253,"about_ca_topic_score_gemma":0.002706695,"teacher_disagreement_score":0.03302864,"about_ca_system_score_codex":0.0011097224,"about_ca_system_score_gemma":0.0015470248,"threshold_uncertainty_score":0.11049181},"labels":[],"label_agreement":null},{"id":"W2124188761","doi":"10.1109/compsac.2008.191","title":"Sequential Demand-Driven Evaluation of Eager TransLucid","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Dataflow; Context (archaeology); Variable (mathematics); Set (abstract data type); Semantics (computer science); Identifier; Dimension (graph theory); Programming language; Theoretical computer science; Function (biology); Value (mathematics); Key (lock); Mathematics","score_opus":0.0708401515403871,"score_gpt":0.30029870858017826,"score_spread":0.22945855703979118,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2124188761","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":[0.18093246,0.00031694976,0.77788764,0.00046287384,0.0001304718,0.00031042454,0.0008626453,0.02125021,0.017846255],"genre_scores_gemma":[0.657118,0.00014584333,0.32393515,0.00031291318,0.000039790626,0.00033888608,0.001511256,0.003754774,0.012843323],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99651414,0.0007864335,0.000191971,0.00049073645,0.0014947432,0.0005219149],"domain_scores_gemma":[0.9947259,0.002204817,0.00024335932,0.0015496449,0.0011320455,0.00014417476],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036900837,0.00093216955,0.0009776033,0.0009221854,0.00070429256,0.0031010837,0.002984124,0.0008963605,0.009028203],"category_scores_gemma":[0.010451081,0.00065599167,0.0011599697,0.0010715716,0.0019702625,0.0063372096,0.0045506866,0.000991539,0.0013238254],"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":[0.004970248,0.0004947663,0.0089238435,0.00085014687,0.00023631874,0.0020067506,0.0028036553,0.18344088,0.087501146,0.33888564,0.027020384,0.34286618],"study_design_scores_gemma":[0.00025476105,0.0003158122,0.0008699612,0.00007295957,0.000098427205,0.00027776507,0.00043630804,0.739882,0.0959845,0.12911884,0.03256009,0.0001285872],"about_ca_topic_score_codex":0.004200185,"about_ca_topic_score_gemma":0.003925081,"teacher_disagreement_score":0.009028203,"about_ca_system_score_codex":0.0020910008,"about_ca_system_score_gemma":0.0018857446,"threshold_uncertainty_score":0.03020233},"labels":[],"label_agreement":null},{"id":"W2124364769","doi":"10.1109/saint.2011.14","title":"An XPath Query Aggregation Algorithm Using a Region Encoding","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Ontario Centres of Excellence","keywords":"XPath; Computer science; XML database; XML; Encoding (memory); Algorithm; Simple API for XML; Node (physics); Data mining; Theoretical computer science; Information retrieval; Document Structure Description; XML Signature; Artificial intelligence","score_opus":0.0703250464098357,"score_gpt":0.27505292595513764,"score_spread":0.20472787954530194,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2124364769","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":[0.021329196,0.0003514326,0.9714237,0.00017015974,0.000055636774,0.00013436888,0.0002457993,0.004627102,0.0016625976],"genre_scores_gemma":[0.13311003,0.0003125176,0.86060715,0.000133918,0.00005115585,0.00013714399,0.0011771244,0.00018055661,0.0042904695],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990988,0.00010425516,0.00011739387,0.00024404435,0.00037619006,0.00005925179],"domain_scores_gemma":[0.9993344,0.00015575289,0.00006565992,0.0001421408,0.00027464045,0.000027429558],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00080162665,0.00054382306,0.0007440279,0.001427952,0.000602948,0.0011626707,0.0011436767,0.00064532046,0.0018620524],"category_scores_gemma":[0.001435299,0.00034546686,0.00060988974,0.001805113,0.0003065273,0.0019038916,0.00094587356,0.0007605148,0.0009814963],"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":[0.0005415461,0.0002041429,0.0020245258,0.00016459427,0.00010683065,0.00043825552,0.00050112366,0.03391405,0.106106155,0.014805131,0.014035669,0.8271579],"study_design_scores_gemma":[0.00010305146,0.00034211314,0.0012166975,0.000030245714,0.00009503618,0.001390517,0.00024975595,0.86183244,0.09793953,0.007891289,0.028838078,0.00007122825],"about_ca_topic_score_codex":0.0030778442,"about_ca_topic_score_gemma":0.0018255267,"teacher_disagreement_score":0.0030778442,"about_ca_system_score_codex":0.0006528753,"about_ca_system_score_gemma":0.0007768121,"threshold_uncertainty_score":0.006229162},"labels":[],"label_agreement":null},{"id":"W2125022400","doi":"10.1109/dexa.2005.144","title":"On OLAP Data Model Driven Approach to Process Statistical Tables","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Online analytical processing; Computer science; Table (database); Data mining; Dimension (graph theory); Information retrieval; Decision table; Process (computing); Data exploration; Data warehouse; Database; Visualization; Programming language","score_opus":0.037662893339461,"score_gpt":0.29465182386257055,"score_spread":0.25698893052310956,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2125022400","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":[0.0016988808,0.000077825694,0.99570316,0.00021326609,0.0000214903,0.00013346666,0.00027177285,0.0013121344,0.00056794076],"genre_scores_gemma":[0.03631053,0.00017649606,0.96077573,0.00018598833,0.000028012179,0.0003311887,0.001104324,0.0001885209,0.0008991231],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9932567,0.002170874,0.000619905,0.0007986778,0.0029342356,0.00021970237],"domain_scores_gemma":[0.9914055,0.003365125,0.00048765598,0.0020889495,0.0023887581,0.00026402375],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0059987595,0.001283553,0.0011249926,0.0037754832,0.0011127753,0.0068455962,0.0032445227,0.0013725746,0.0029656163],"category_scores_gemma":[0.014624188,0.0009755266,0.0023914203,0.0047990074,0.0011560605,0.0053527066,0.0027047521,0.0027774759,0.0014312718],"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":[0.0005264637,0.0005360101,0.0055806115,0.0010871765,0.0004453333,0.0015303363,0.0022775517,0.19800088,0.016430354,0.20597102,0.01835951,0.5492548],"study_design_scores_gemma":[0.000027274293,0.0000670261,0.00043400683,0.00007305261,0.000048558573,0.000352102,0.00033965625,0.8760799,0.0069893613,0.096459925,0.01906649,0.00006257758],"about_ca_topic_score_codex":0.007979679,"about_ca_topic_score_gemma":0.008726579,"teacher_disagreement_score":0.007979679,"about_ca_system_score_codex":0.0016661255,"about_ca_system_score_gemma":0.002222218,"threshold_uncertainty_score":0.03172487},"labels":[],"label_agreement":null},{"id":"W2125619608","doi":"10.1109/vis.2003.10005","title":"KMVQL: a Graphical User Interface for Boolean Query Specification and Query Result Visualization","year":2003,"lang":"en","type":"article","venue":"IEEE Visualization","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Construct (python library); Window (computing); Query language; Visualization; Information retrieval; Query by Example; And-inverter graph; Query optimization; Graphical user interface; Boolean conjunctive query; Interface (matter); Data mining; Data visualization; Theoretical computer science; Web search query; Boolean expression; Boolean function; Programming language; Algorithm; Search engine; World Wide Web","score_opus":0.024731097625225972,"score_gpt":0.3196929198591682,"score_spread":0.29496182223394224,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2125619608","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":[0.0026915665,0.00020562156,0.6581218,0.0004459438,0.0000840778,0.00024370762,0.011208081,0.3178819,0.009117264],"genre_scores_gemma":[0.15340754,0.0007710889,0.69610846,0.0018797409,0.00018368228,0.0018216833,0.061412964,0.05833425,0.026080636],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99798393,0.00065091543,0.00026905147,0.0002554714,0.00071089866,0.00012975633],"domain_scores_gemma":[0.9958763,0.0021728734,0.00017762285,0.0007485215,0.000788858,0.0002357658],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029673863,0.0012666906,0.0009807125,0.0015768928,0.0005685794,0.0034039144,0.0025934153,0.0012239948,0.04089973],"category_scores_gemma":[0.009799391,0.0008782867,0.0007579145,0.0013797318,0.00055040146,0.0045168027,0.0028711134,0.0016892747,0.014152493],"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":[0.0018685679,0.000277164,0.0040086885,0.001798786,0.00019313817,0.0006289902,0.001590997,0.007257855,0.028497176,0.046294216,0.68726456,0.22032002],"study_design_scores_gemma":[0.0007250897,0.00023298424,0.0027332574,0.00034542085,0.00011203883,0.0010634933,0.0004968932,0.20264757,0.04110662,0.06747261,0.6827109,0.00035321203],"about_ca_topic_score_codex":0.0047495435,"about_ca_topic_score_gemma":0.0037856535,"teacher_disagreement_score":0.04089973,"about_ca_system_score_codex":0.00081654434,"about_ca_system_score_gemma":0.001069243,"threshold_uncertainty_score":0.13682318},"labels":[],"label_agreement":null},{"id":"W2126490564","doi":"10.1145/1066157.1066192","title":"Multiple aggregations over data streams","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":95,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Heuristics; Data stream mining; Granularity; Computation; Distributed computing; Optimization problem; Greedy algorithm; Data stream; Data mining; Algorithm","score_opus":0.03606557529230214,"score_gpt":0.2872740752089457,"score_spread":0.25120849991664357,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2126490564","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":[0.5222404,0.00043790243,0.46999696,0.0007221195,0.00007281807,0.00023842049,0.00035035954,0.0036279974,0.0023129676],"genre_scores_gemma":[0.8298031,0.0000872234,0.1687533,0.00007727646,0.00005392323,0.000101893216,0.00033559938,0.000101986945,0.00068575225],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9970873,0.0006284506,0.00034633893,0.00060860335,0.0010205099,0.0003087732],"domain_scores_gemma":[0.9951133,0.0017280851,0.0004599097,0.001581883,0.00077274867,0.00034413958],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024879447,0.0007598461,0.001262838,0.0010997357,0.001425642,0.002320526,0.0015250695,0.0006975699,0.00093322265],"category_scores_gemma":[0.0089113545,0.0005623199,0.00068220636,0.0023243707,0.00085327576,0.0034030797,0.0023091491,0.0009892969,0.00021456712],"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":[0.0021740152,0.000488558,0.038085774,0.00022890068,0.00029370975,0.0007456963,0.001398234,0.46499968,0.07926024,0.025378048,0.0064581744,0.380489],"study_design_scores_gemma":[0.000054048698,0.00013473655,0.0024877863,0.0000067919314,0.000036018584,0.000136366,0.0003508704,0.9643957,0.01579969,0.014633592,0.0019420917,0.000022286287],"about_ca_topic_score_codex":0.0029324426,"about_ca_topic_score_gemma":0.0042617177,"teacher_disagreement_score":0.0029324426,"about_ca_system_score_codex":0.0011010362,"about_ca_system_score_gemma":0.001119302,"threshold_uncertainty_score":0.013157666},"labels":[],"label_agreement":null},{"id":"W2128114397","doi":"10.1145/1228268.1228284","title":"Normalization theory for XML","year":2006,"lang":"en","type":"article","venue":"ACM SIGMOD Record","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":50,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Toronto","keywords":"Computer science; Relational database; Normalization (sociology); XML; XML database; Database; Relational model; Information retrieval; Simple (philosophy); World Wide Web","score_opus":0.012011270581554807,"score_gpt":0.24309843180001883,"score_spread":0.23108716121846404,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128114397","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":[0.004196031,0.0068479124,0.8306817,0.010184603,0.0014848216,0.00014470676,0.0013463973,0.0015374551,0.14357647],"genre_scores_gemma":[0.29805434,0.017861504,0.5152355,0.012074397,0.007858055,0.0018739449,0.0069281673,0.0023703303,0.13774389],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9950105,0.0015706728,0.00043893288,0.0010328336,0.0016258053,0.00032126985],"domain_scores_gemma":[0.99513704,0.002109293,0.0003023488,0.001259502,0.001034198,0.00015761705],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0056144963,0.00093564036,0.0012092239,0.0044302344,0.0037166306,0.006433757,0.0025961476,0.002470553,0.01733558],"category_scores_gemma":[0.010211608,0.0009094419,0.002106896,0.005285158,0.0059106904,0.01862656,0.004168019,0.006128062,0.0069993134],"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":[0.0000033707793,0.0000046018204,0.0000413515,0.000022540322,0.000004103442,0.000028115359,0.00008019608,0.0002545024,0.00007751093,0.9917413,0.0029787724,0.004763614],"study_design_scores_gemma":[0.000003456095,0.000003403727,0.000051711148,0.000026484819,0.0000053600616,0.00006782719,0.000035818375,0.0018089339,0.00017360035,0.9624922,0.035322968,0.000008149869],"about_ca_topic_score_codex":0.0046069105,"about_ca_topic_score_gemma":0.0027302643,"teacher_disagreement_score":0.01733558,"about_ca_system_score_codex":0.0043192585,"about_ca_system_score_gemma":0.0022654997,"threshold_uncertainty_score":0.057993352},"labels":[],"label_agreement":null},{"id":"W2128237060","doi":"10.1109/dest.2011.5936622","title":"Managing large and small files in a distributed system","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institute for Theoretical Astrophysics","keywords":"Computer science; Ecosystem; Distributed database; Variation (astronomy); Database; Data science","score_opus":0.022903540253912582,"score_gpt":0.2102780437879458,"score_spread":0.1873745035340332,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128237060","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":[0.3724758,0.0032129076,0.6021555,0.0037034638,0.00027377746,0.00045883306,0.0002561833,0.0033633837,0.014100077],"genre_scores_gemma":[0.7369761,0.0012152806,0.25293943,0.0004518121,0.00034927807,0.0002425208,0.0004560961,0.00042362502,0.006945859],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99304366,0.0017215753,0.00079276215,0.0010565555,0.002788367,0.00059707975],"domain_scores_gemma":[0.9566251,0.026631113,0.0027476803,0.009101923,0.002558222,0.0023360595],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00860009,0.00052781665,0.0012428227,0.0012579148,0.0030747266,0.008959475,0.0034955286,0.0024440808,0.0015393618],"category_scores_gemma":[0.026276626,0.0009463992,0.00060634036,0.0023004944,0.0027186223,0.014795365,0.006614202,0.0024542978,0.00054543285],"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":[0.001880035,0.0008782327,0.029589506,0.00060841406,0.00027851667,0.0027239,0.0045274207,0.14109345,0.03437514,0.1134296,0.010244826,0.660371],"study_design_scores_gemma":[0.0005953276,0.0008555891,0.012734001,0.00024714042,0.0005392506,0.003184077,0.003364809,0.5802824,0.039287798,0.29259774,0.06598447,0.00032739504],"about_ca_topic_score_codex":0.0029174502,"about_ca_topic_score_gemma":0.003543522,"teacher_disagreement_score":0.008959475,"about_ca_system_score_codex":0.0013995437,"about_ca_system_score_gemma":0.002233679,"threshold_uncertainty_score":0.04548216},"labels":[],"label_agreement":null},{"id":"W2128263201","doi":"10.1109/icdcsw.2002.1030823","title":"Predicate matching and subscription matching in Publish/Subscribe systems","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":57,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Matching (statistics); Publication; Predicate (mathematical logic); Implementation; Theoretical computer science; Blossom algorithm; Scheme (mathematics); Programming language","score_opus":0.01494513207553792,"score_gpt":0.2256672900339471,"score_spread":0.21072215795840918,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128263201","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":[0.029170265,0.00086332666,0.9584025,0.00065695716,0.00017716651,0.0002330883,0.00024529552,0.0021319655,0.008119435],"genre_scores_gemma":[0.47381943,0.0014423854,0.51203865,0.00039197126,0.00043018983,0.00025460924,0.0008361288,0.00041996868,0.010366714],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99407804,0.0016498998,0.00064423523,0.0008969562,0.0021727332,0.0005581147],"domain_scores_gemma":[0.99130476,0.00396557,0.0006136187,0.0031704823,0.00067317614,0.0002723519],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006084134,0.00044741225,0.0013053425,0.0017191848,0.0017850694,0.0063109933,0.0020918646,0.002065088,0.006416309],"category_scores_gemma":[0.016335355,0.00080977945,0.0009799214,0.0043220646,0.0016556296,0.00861523,0.0024894315,0.0017130825,0.0015202906],"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":[0.0007217535,0.00033725763,0.0045421575,0.0006108321,0.00012873515,0.0005155351,0.00064676465,0.058493324,0.01288508,0.52834016,0.009834546,0.3829439],"study_design_scores_gemma":[0.00020463388,0.00030172273,0.0017774152,0.00005016457,0.00014045098,0.0014063295,0.00036702532,0.4260486,0.04403699,0.4611727,0.06440179,0.000092180926],"about_ca_topic_score_codex":0.0017408859,"about_ca_topic_score_gemma":0.00080590544,"teacher_disagreement_score":0.006416309,"about_ca_system_score_codex":0.0013715168,"about_ca_system_score_gemma":0.0018533038,"threshold_uncertainty_score":0.032176316},"labels":[],"label_agreement":null},{"id":"W2128846511","doi":"10.1007/1-4020-5392-4_2","title":"Concepts and Architecture of Database Systems","year":2007,"lang":"en","type":"book-chapter","venue":"˜The œGeojournal library","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Computer science; Architecture; Database; Computer architecture; History; Archaeology","score_opus":0.020810376983314022,"score_gpt":0.24626279143926064,"score_spread":0.2254524144559466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128846511","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":[0.0034207746,0.0780319,0.70544344,0.005184235,0.001256705,0.00024533534,0.00056359434,0.0020077617,0.2038463],"genre_scores_gemma":[0.104350455,0.10701647,0.63818914,0.002725278,0.0026423545,0.0009980756,0.0017698223,0.0007222129,0.1415863],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983524,0.00031147627,0.00016308263,0.00023601908,0.00080617314,0.00013087397],"domain_scores_gemma":[0.99907,0.000368879,0.000052197636,0.00022262443,0.00021622136,0.00007017786],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015114371,0.0014292703,0.0009864287,0.0024803458,0.0014202406,0.011546742,0.0027347654,0.0018482236,0.008478225],"category_scores_gemma":[0.0031132882,0.0016349879,0.0010399513,0.0055378582,0.0048594484,0.011969876,0.0024927089,0.0044463235,0.005079138],"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":[0.0000062053155,0.0000146265,0.00007838709,0.00021441441,0.000010032179,0.00003545402,0.00037604873,0.000912688,0.00042449904,0.9511644,0.012220473,0.03454272],"study_design_scores_gemma":[0.000009465892,0.000013668726,0.00011506824,0.00019961025,0.000016137967,0.00024100496,0.00012638449,0.0043003727,0.00041225622,0.68185055,0.31270233,0.000013135247],"about_ca_topic_score_codex":0.0027259393,"about_ca_topic_score_gemma":0.0019423297,"teacher_disagreement_score":0.011546742,"about_ca_system_score_codex":0.002769576,"about_ca_system_score_gemma":0.002450567,"threshold_uncertainty_score":0.028362513},"labels":[],"label_agreement":null},{"id":"W2128869116","doi":"10.1145/380752.380841","title":"Data-streams and histograms","year":2001,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":269,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Histogram; Computer science; Linear programming; Distribution (mathematics); Dynamic programming; Quadratic equation; Algorithm; Mathematical optimization; Mathematics; Artificial intelligence; Image (mathematics)","score_opus":0.045360695411272065,"score_gpt":0.2771039333433259,"score_spread":0.2317432379320538,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128869116","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":[0.0039132647,0.0023213965,0.98511666,0.0007207888,0.00023740571,0.00013192376,0.0008899103,0.002879624,0.0037890177],"genre_scores_gemma":[0.1724151,0.006001609,0.8064589,0.0007538965,0.0007281959,0.00042599477,0.003771538,0.0010715306,0.008373226],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99593985,0.0010031197,0.00036796057,0.0006389329,0.001812534,0.00023758522],"domain_scores_gemma":[0.9908042,0.004328257,0.0006072102,0.0024222552,0.0014009837,0.0004371722],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024951443,0.001058022,0.0014963747,0.0025954612,0.0009806728,0.0048255776,0.0021561105,0.0013991672,0.007861633],"category_scores_gemma":[0.021409987,0.00092488556,0.00080475473,0.0072768014,0.0020566462,0.011965945,0.003982807,0.003488725,0.0032589408],"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":[0.0005801644,0.00010806817,0.0018358111,0.0005990236,0.00006011774,0.00014975389,0.00023904943,0.043654945,0.0038761166,0.63985986,0.025955155,0.28308195],"study_design_scores_gemma":[0.000071303664,0.000078362034,0.0006046523,0.00014280746,0.000024367415,0.00039964123,0.00017808763,0.18927684,0.009844886,0.71793807,0.081382886,0.00005802262],"about_ca_topic_score_codex":0.0016828441,"about_ca_topic_score_gemma":0.001087401,"teacher_disagreement_score":0.007861633,"about_ca_system_score_codex":0.001344336,"about_ca_system_score_gemma":0.001313931,"threshold_uncertainty_score":0.026299834},"labels":[],"label_agreement":null},{"id":"W2129081249","doi":"10.1007/3-540-44864-0_25","title":"An Adaptive Load Balancing Algorithm for Large Data Parallel Processing with Communication Delay","year":2003,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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":"Carleton University","funders":"","keywords":"Computer science; Load balancing (electrical power); Transfer (computing); Novelty; Data processing; Algorithm; Distributed computing; Parallel computing; Parallel processing; Load distribution; Database","score_opus":0.027744034000897734,"score_gpt":0.2807065179659685,"score_spread":0.25296248396507076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2129081249","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":[0.020566534,0.00040143772,0.9745696,0.00015680982,0.00023772357,0.000086267326,0.00004982263,0.002077772,0.0018539896],"genre_scores_gemma":[0.22652285,0.00023663236,0.7654861,0.00016431895,0.0001984238,0.0002492362,0.00023834391,0.00035789353,0.006546216],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996675,0.000056991383,0.000026295073,0.000061703184,0.00014506397,0.000042415373],"domain_scores_gemma":[0.99942625,0.00019640276,0.000042890475,0.00010131191,0.00019069006,0.000042467622],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006463151,0.00075641304,0.0007704874,0.00072389696,0.001065328,0.00085914665,0.0022194267,0.00067675003,0.0038162428],"category_scores_gemma":[0.0017838496,0.00042990723,0.00033752059,0.0013066174,0.0005032351,0.0012569412,0.0011346693,0.0008834389,0.0008313987],"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":[0.001025872,0.00025827702,0.00068324734,0.00015397399,0.00008660262,0.00007757939,0.00014863278,0.23821498,0.030592142,0.015489879,0.011567394,0.70170146],"study_design_scores_gemma":[0.000114868104,0.000065984976,0.0001742599,0.0000049199466,0.000024015813,0.0000320189,0.0000139596905,0.9858202,0.0043095187,0.0064081517,0.0030189187,0.0000131206325],"about_ca_topic_score_codex":0.0032954453,"about_ca_topic_score_gemma":0.005183417,"teacher_disagreement_score":0.0038162428,"about_ca_system_score_codex":0.00069646694,"about_ca_system_score_gemma":0.000993883,"threshold_uncertainty_score":0.0127666},"labels":[],"label_agreement":null},{"id":"W2129088288","doi":"10.1007/s00778-012-0297-3","title":"Modeling the execution semantics of stream processing engines with SECRET","year":2012,"lang":"en","type":"article","venue":"The VLDB Journal","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":54,"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; Semantics (computer science); Tuple; Key (lock); Range (aeronautics); Variation (astronomy); Window (computing); Programming language; Theoretical computer science; World Wide Web; Operating system; Engineering","score_opus":0.019849684280367718,"score_gpt":0.24530657120357555,"score_spread":0.22545688692320784,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2129088288","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":[0.089366876,0.00021591096,0.9022364,0.000544658,0.00007740187,0.00010239991,0.00048168458,0.0021888867,0.0047857673],"genre_scores_gemma":[0.8408599,0.00041978242,0.15283118,0.00014525816,0.000079847014,0.00012741945,0.00065936014,0.0005459359,0.004331274],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99820614,0.00043523358,0.00018695169,0.00028300536,0.0006142219,0.00027441152],"domain_scores_gemma":[0.9961868,0.0017594147,0.00042659306,0.0008833627,0.0006065163,0.00013744163],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026274533,0.0007554023,0.00062664854,0.0010265382,0.0006783857,0.0047507156,0.002361227,0.0013053344,0.002184543],"category_scores_gemma":[0.008479436,0.0008807061,0.0012167013,0.0010806384,0.0019065102,0.006652239,0.0014875067,0.0016320149,0.0005171864],"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":[0.00032072776,0.000109794586,0.0026968273,0.00008796752,0.00005130572,0.0003138934,0.0003753256,0.69861484,0.0032545582,0.27998903,0.0012229562,0.012962742],"study_design_scores_gemma":[0.00001740435,0.00001108843,0.000050246985,0.000007523701,0.000020966085,0.000022831447,0.000023017936,0.9400804,0.0022491438,0.05631048,0.0011992564,0.000007768394],"about_ca_topic_score_codex":0.009280956,"about_ca_topic_score_gemma":0.0068055107,"teacher_disagreement_score":0.009280956,"about_ca_system_score_codex":0.0017882771,"about_ca_system_score_gemma":0.0024968062,"threshold_uncertainty_score":0.018453836},"labels":[],"label_agreement":null},{"id":"W2129940802","doi":"","title":"Efficient bulk deletes for multi dimensional clustered tables in DB2","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada)","funders":"","keywords":"Computer science; Table (database); Cluster analysis; Commit; Data mining; Dimension (graph theory); Data warehouse; Asynchronous communication; Database; Scheme (mathematics); Online analytical processing; Machine learning; Computer network","score_opus":0.03061526244596681,"score_gpt":0.2913420918073013,"score_spread":0.2607268293613345,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2129940802","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":[0.27642897,0.0051777265,0.605359,0.0020008325,0.00080571097,0.00097386015,0.0035937494,0.09388521,0.011774908],"genre_scores_gemma":[0.4203689,0.0009900684,0.55305815,0.00065806456,0.00024175999,0.00029126494,0.007298839,0.0030842805,0.014008726],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99500126,0.0010055981,0.00047558203,0.00072861224,0.0023431974,0.000445683],"domain_scores_gemma":[0.9881654,0.002977214,0.00069402123,0.0062321876,0.0014853099,0.00044583337],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003410101,0.0014990759,0.0017712412,0.0017346621,0.0020483052,0.0037367512,0.0045264224,0.0015528225,0.0054547274],"category_scores_gemma":[0.009266131,0.0014167676,0.0009775311,0.0039447173,0.00111698,0.006628655,0.0032618293,0.0020078858,0.003323014],"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":[0.0066172,0.0011577216,0.018686453,0.0010028107,0.00025603833,0.0011921682,0.0025368535,0.051412404,0.105461985,0.016712109,0.07384126,0.72112304],"study_design_scores_gemma":[0.0015679954,0.0021917722,0.014747032,0.00019312256,0.00024946174,0.0030720949,0.0019933532,0.5339751,0.3027665,0.020978654,0.11770687,0.0005580941],"about_ca_topic_score_codex":0.0067798547,"about_ca_topic_score_gemma":0.008418457,"teacher_disagreement_score":0.0067798547,"about_ca_system_score_codex":0.0012892012,"about_ca_system_score_gemma":0.0019108987,"threshold_uncertainty_score":0.018247843},"labels":[],"label_agreement":null},{"id":"W2129948651","doi":"","title":"IDUX: INTERNATIONALIZATION OF DATA USING XML","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Acadia University","funders":"","keywords":"Computer science; Streaming XML; Efficient XML Interchange; XML validation; XML Schema Editor; XML; XML database; Database; World Wide Web; XML Signature; Interfacing; XML Schema (W3C); Programming language; XML framework; Information retrieval","score_opus":0.0943479949385023,"score_gpt":0.3426530083743851,"score_spread":0.24830501343588282,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2129948651","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":[0.004286647,0.0009076545,0.938324,0.00091207074,0.0003297587,0.0005011144,0.0026556624,0.03666619,0.0154167935],"genre_scores_gemma":[0.0701468,0.0041796477,0.8769373,0.001211466,0.00040603182,0.000809763,0.018101577,0.0072043585,0.021003015],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9962353,0.0009919533,0.00072667113,0.0004523453,0.0013764175,0.00021730513],"domain_scores_gemma":[0.99567837,0.0015171272,0.0003378505,0.0017955072,0.0004427218,0.00022848317],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005651512,0.0009460637,0.0007808238,0.0037570463,0.0012403481,0.0066484716,0.0022436492,0.0010207099,0.0085965],"category_scores_gemma":[0.009594801,0.00079068757,0.0011027677,0.0039310413,0.0015890101,0.008460443,0.0053348616,0.0025348112,0.0045770155],"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":[0.00039129736,0.00013355109,0.003919401,0.00095842674,0.00013121928,0.0012068403,0.003130825,0.0038412218,0.015924161,0.26829344,0.088704765,0.6133648],"study_design_scores_gemma":[0.000082637416,0.00010987633,0.0011071557,0.00034726135,0.00006249983,0.0009819119,0.0005526587,0.01872376,0.032187976,0.056984663,0.88876957,0.00009011165],"about_ca_topic_score_codex":0.0015823315,"about_ca_topic_score_gemma":0.0011783638,"teacher_disagreement_score":0.0085965,"about_ca_system_score_codex":0.0008927253,"about_ca_system_score_gemma":0.0014051957,"threshold_uncertainty_score":0.029888451},"labels":[],"label_agreement":null},{"id":"W2132145609","doi":"10.1145/1458082.1458109","title":"Modeling and exploiting query interactions in database systems","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":56,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Query optimization; View; Database; Sargable; Query language; Query by Example; Query expansion; Information retrieval; Web search query; Database design; Search engine","score_opus":0.06583125418043552,"score_gpt":0.2832805075986165,"score_spread":0.217449253418181,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2132145609","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":[0.29267275,0.0006105761,0.70191866,0.0006614087,0.000038124414,0.00026976762,0.00025997724,0.001880558,0.0016882023],"genre_scores_gemma":[0.9023759,0.00020669714,0.09643791,0.000075128875,0.000043067528,0.00017361197,0.00020230375,0.00011050487,0.00037498845],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9917293,0.004144906,0.00048917043,0.0010770005,0.0020970702,0.00046245675],"domain_scores_gemma":[0.98296297,0.012143806,0.0015140093,0.0018773364,0.0010769928,0.00042483656],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0062383465,0.0012896955,0.0010518654,0.0008237515,0.00088039105,0.0023711077,0.0023155722,0.0009838364,0.00053877383],"category_scores_gemma":[0.022515198,0.0010738192,0.0006120512,0.0014204673,0.0010829004,0.0033569678,0.0010480583,0.0016044986,0.000176185],"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":[0.0003041731,0.0002000581,0.009321484,0.000088540444,0.000076209464,0.00012544294,0.00039224987,0.94296414,0.009122131,0.009615307,0.0006169832,0.0271734],"study_design_scores_gemma":[0.000007400578,0.000029991555,0.00037205222,0.0000012120255,0.000009399628,0.000012251757,0.000021007203,0.9956655,0.0008027324,0.0028793076,0.00019403758,0.0000051914176],"about_ca_topic_score_codex":0.0126858475,"about_ca_topic_score_gemma":0.009341865,"teacher_disagreement_score":0.0126858475,"about_ca_system_score_codex":0.0019110788,"about_ca_system_score_gemma":0.0033851068,"threshold_uncertainty_score":0.032991886},"labels":[],"label_agreement":null},{"id":"W2132480966","doi":"10.1109/deec.2005.21","title":"Representing UML snowflake diagram from integrating XML data using XML schema","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Computer science; XML Schema Editor; XML validation; Streaming XML; Efficient XML Interchange; XML Schema (W3C); RELAX NG; Document Structure Description; Class diagram; XML database; Applications of UML; cXML; Database; XML Encryption; Programming language; Information retrieval; XML; Unified Modeling Language; World Wide Web","score_opus":0.08746908109078504,"score_gpt":0.33364563762105076,"score_spread":0.2461765565302657,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2132480966","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":[0.0025373206,0.00011897479,0.99236685,0.00022383512,0.000061422434,0.00012469936,0.00043503757,0.0019403378,0.0021916043],"genre_scores_gemma":[0.02469132,0.00037579774,0.97040594,0.00010720003,0.000024431374,0.00022122283,0.0021296088,0.00033068022,0.0017138607],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99744356,0.0007623441,0.00040451394,0.0003188837,0.00096036465,0.00011027516],"domain_scores_gemma":[0.99753666,0.0009890309,0.0002842679,0.0005211601,0.0005533855,0.00011533922],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032867424,0.0009040087,0.00050569535,0.0030673628,0.0007757628,0.004127236,0.0015802875,0.0013546409,0.005706854],"category_scores_gemma":[0.0063650263,0.00067944743,0.0016624517,0.002710348,0.0010333769,0.0054176114,0.0026744849,0.0014879062,0.0014745909],"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":[0.00020806491,0.00014678814,0.0032046516,0.0007838577,0.000119344404,0.0021230413,0.004023756,0.033882197,0.018906133,0.66390216,0.018642524,0.25405753],"study_design_scores_gemma":[0.00012890893,0.00012190079,0.00096912106,0.00048617157,0.00012495866,0.0014997491,0.0007887879,0.24095885,0.031650618,0.18651226,0.53661555,0.00014304997],"about_ca_topic_score_codex":0.0063792407,"about_ca_topic_score_gemma":0.0062843845,"teacher_disagreement_score":0.0063792407,"about_ca_system_score_codex":0.00088424823,"about_ca_system_score_gemma":0.0022674256,"threshold_uncertainty_score":0.019091308},"labels":[],"label_agreement":null},{"id":"W2132570338","doi":"10.1109/case.1995.465320","title":"Modeling N-ary data relationships in CASE environments","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; Cardinality (data modeling); Notation; Set (abstract data type); Data mining; Data modeling; Theoretical computer science; Programming language; Information retrieval; Software engineering; Mathematics","score_opus":0.17126779921584728,"score_gpt":0.27501017402623074,"score_spread":0.10374237481038345,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2132570338","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":[0.006781235,0.00008569398,0.9877891,0.00029730433,0.0000144632595,0.0001589311,0.0001504081,0.0006396109,0.004083333],"genre_scores_gemma":[0.08481756,0.00023666659,0.9107725,0.00012412635,0.000024866145,0.00034037215,0.00052362564,0.00014718401,0.0030130998],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9917984,0.0034283868,0.0011110315,0.00099874,0.002187874,0.00047561567],"domain_scores_gemma":[0.9908695,0.0040655443,0.0013128226,0.0025184494,0.00094291114,0.0002907393],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008743619,0.0008719611,0.0008041924,0.0029637725,0.0019147915,0.008242944,0.0039709737,0.002168253,0.0037675789],"category_scores_gemma":[0.016280439,0.0010278755,0.002481965,0.003263698,0.0029554528,0.013346367,0.004572399,0.0018465673,0.0010843157],"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":[0.00007134265,0.00017899314,0.005946264,0.00024204103,0.00007906813,0.0021204848,0.0045695384,0.08418518,0.002924064,0.82361794,0.002625503,0.073439606],"study_design_scores_gemma":[0.000044319524,0.00009972398,0.0010544584,0.00035457834,0.00015682695,0.0016054531,0.0015923913,0.4833793,0.0053284434,0.3872629,0.11903155,0.00009005995],"about_ca_topic_score_codex":0.0058686035,"about_ca_topic_score_gemma":0.009586363,"teacher_disagreement_score":0.008743619,"about_ca_system_score_codex":0.0016788786,"about_ca_system_score_gemma":0.0027136623,"threshold_uncertainty_score":0.046241224},"labels":[],"label_agreement":null},{"id":"W2132851185","doi":"10.1145/776985.776986","title":"Issues in data stream management","year":2003,"lang":"en","type":"article","venue":"ACM SIGMOD Record","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":916,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Timestamp; Data stream mining; Database; Query language; Streaming data; Data stream; Data management; Data science; Data mining; Computer security","score_opus":0.04335612978330646,"score_gpt":0.30557491160712486,"score_spread":0.2622187818238184,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2132851185","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":[0.00808037,0.061158802,0.6739842,0.21418989,0.008426955,0.00035920372,0.00052719977,0.0015942327,0.03167909],"genre_scores_gemma":[0.31275308,0.11741233,0.45961818,0.035003345,0.045564663,0.0012661286,0.0012540765,0.001033601,0.026094599],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9835491,0.005442186,0.0017780894,0.0016845855,0.00700507,0.00054094393],"domain_scores_gemma":[0.9556658,0.028759127,0.0017510623,0.0044588367,0.008038112,0.0013270503],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.030363197,0.0007013565,0.00130674,0.0018749357,0.002013788,0.014773264,0.0049120625,0.0051175444,0.0038195888],"category_scores_gemma":[0.074914835,0.0008204041,0.0012784171,0.0054957964,0.0064228084,0.029337067,0.0044361716,0.007979317,0.0020194289],"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":[0.00009991324,0.00007210702,0.0012182039,0.0005896482,0.000048880444,0.0001879617,0.000920778,0.0060246177,0.0005887382,0.78515166,0.042378217,0.16271941],"study_design_scores_gemma":[0.00005056511,0.0001106434,0.00040772994,0.00048958865,0.000038000024,0.000786826,0.0010877388,0.040999442,0.0010118416,0.736633,0.2183205,0.00006414104],"about_ca_topic_score_codex":0.0022975334,"about_ca_topic_score_gemma":0.0012642677,"teacher_disagreement_score":0.030363197,"about_ca_system_score_codex":0.002601151,"about_ca_system_score_gemma":0.0033452064,"threshold_uncertainty_score":0.1605779},"labels":[],"label_agreement":null},{"id":"W2132929844","doi":"10.2481/dsj.008-011","title":"Structured Query Translation in Peer to Peer Database Sharing Systems","year":2009,"lang":"en","type":"article","venue":"Data Science Journal","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Scope (computer science); Usability; Transparency (behavior); Data sharing; World Wide Web; Metadata; Implementation; Open data; Reuse; Data science; Database; Software engineering","score_opus":0.07014835883326626,"score_gpt":0.3407390784558296,"score_spread":0.27059071962256337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2132929844","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":[0.040846523,0.0012815011,0.93204755,0.0025579683,0.0004146836,0.0018677783,0.0008395397,0.007727283,0.012417199],"genre_scores_gemma":[0.4809901,0.00107666,0.49483663,0.0011944426,0.0004633707,0.0016082728,0.003073304,0.0015056219,0.0152516],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9578718,0.020955551,0.0044270502,0.00302987,0.011724606,0.001991146],"domain_scores_gemma":[0.92454505,0.04162369,0.002044756,0.021114772,0.009082134,0.0015895489],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.032106943,0.00093287276,0.0025487733,0.0024391378,0.0041135517,0.008625732,0.0056417696,0.004660389,0.009147139],"category_scores_gemma":[0.076873995,0.0015701498,0.0015965216,0.0057975305,0.005284288,0.014838799,0.013361566,0.0022773934,0.0055611],"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":[0.0022756031,0.0009550753,0.0040587853,0.0017005326,0.0003815055,0.0024923421,0.010883783,0.10572647,0.012498215,0.47438464,0.04516045,0.33948255],"study_design_scores_gemma":[0.0005292504,0.00039862556,0.00052611297,0.00018855004,0.00010117942,0.0006262182,0.0024781043,0.3987891,0.011949966,0.53894687,0.045278605,0.00018745867],"about_ca_topic_score_codex":0.0043505225,"about_ca_topic_score_gemma":0.0025076342,"teacher_disagreement_score":0.032106943,"about_ca_system_score_codex":0.0020434454,"about_ca_system_score_gemma":0.0050867633,"threshold_uncertainty_score":0.1697998},"labels":[],"label_agreement":null},{"id":"W2133307643","doi":"10.1109/wcre.2002.1173084","title":"Semantic grep: regular expressions + relational abstraction","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Relational database; Abstraction; Regular expression; Semantic matching; Programming language; Pattern matching; Matching (statistics); Expression (computer science); Semantic data model; Extension (predicate logic); Information retrieval","score_opus":0.021279896778063818,"score_gpt":0.2446688062483565,"score_spread":0.22338890947029266,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2133307643","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":[0.0026721044,0.0001050153,0.96457213,0.00036423904,0.000052374944,0.00021225573,0.000584985,0.028043075,0.0033939225],"genre_scores_gemma":[0.08111224,0.00044787145,0.89996445,0.00070206524,0.00016082953,0.00040703922,0.0026894668,0.006496768,0.0080193365],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99394315,0.0015219572,0.00079755153,0.0011419051,0.0022512318,0.00034413836],"domain_scores_gemma":[0.9935923,0.0028894092,0.0005123806,0.0022097046,0.0006381157,0.00015813786],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0075683254,0.0014214877,0.0012126346,0.0014397139,0.0008493614,0.0044865934,0.0034951367,0.001548565,0.009965178],"category_scores_gemma":[0.0119964825,0.0011700322,0.0021366074,0.0019312982,0.003212121,0.010527031,0.00469114,0.0027452216,0.0062303846],"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":[0.0005576847,0.00017804651,0.001968211,0.0010102079,0.00009720509,0.0010124223,0.0021864192,0.009218193,0.018247569,0.5826589,0.053347617,0.32951742],"study_design_scores_gemma":[0.00022964181,0.00025577264,0.0007014024,0.00022955202,0.00012723164,0.0017413739,0.0005794966,0.1396392,0.041687377,0.46265334,0.35196373,0.00019190219],"about_ca_topic_score_codex":0.0021899815,"about_ca_topic_score_gemma":0.0022485447,"teacher_disagreement_score":0.009965178,"about_ca_system_score_codex":0.0009683246,"about_ca_system_score_gemma":0.0015233359,"threshold_uncertainty_score":0.04002565},"labels":[],"label_agreement":null},{"id":"W2133491514","doi":"10.1145/872757.872832","title":"A comprehensive XQuery to SQL translation using dynamic interval encoding","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":162,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"XQuery; Computer science; SQL; Query language; XML; Information retrieval; Relational database; Programming language; Database; Theoretical computer science; XML database; World Wide Web","score_opus":0.05424338726814418,"score_gpt":0.30973911347114114,"score_spread":0.255495726202997,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2133491514","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":[0.0063964073,0.00019393384,0.96804285,0.00029088967,0.00007708729,0.00023977846,0.0007604448,0.016642688,0.0073558963],"genre_scores_gemma":[0.1014842,0.0008950664,0.8726176,0.00050781574,0.00011019689,0.00045621055,0.004893811,0.0051708147,0.013864275],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998221,0.00028663606,0.00022216706,0.00026937417,0.00085259683,0.00014826017],"domain_scores_gemma":[0.99908817,0.00021245667,0.00006178645,0.0002636414,0.00032027817,0.000053677104],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016597228,0.00065730995,0.00046604307,0.00066149945,0.000506429,0.0019008216,0.0012101555,0.0006155983,0.005636486],"category_scores_gemma":[0.0028556895,0.00059552345,0.0006571869,0.0009876536,0.0007493832,0.0021668496,0.0018622642,0.0015592893,0.003206815],"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":[0.00095223467,0.00046676927,0.001525507,0.00076754723,0.000098856755,0.0011238958,0.0020398786,0.015028325,0.10464841,0.25889102,0.08382721,0.5306304],"study_design_scores_gemma":[0.00051376416,0.00065622514,0.0017397383,0.0004028353,0.00014030389,0.0023258878,0.0010390345,0.21202883,0.19120386,0.11748923,0.47217137,0.00028892045],"about_ca_topic_score_codex":0.0019003049,"about_ca_topic_score_gemma":0.0010880874,"teacher_disagreement_score":0.005636486,"about_ca_system_score_codex":0.00043893902,"about_ca_system_score_gemma":0.001128266,"threshold_uncertainty_score":0.01885593},"labels":[],"label_agreement":null},{"id":"W2134227416","doi":"10.1016/s0169-023x(00)00044-6","title":"Selecting and materializing horizontally partitioned warehouse views","year":2001,"lang":"en","type":"article","venue":"Data & Knowledge Engineering","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":22,"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 Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Data warehouse; Cube (algebra); Aggregate (composite); Computer science; Table (database); Warehouse; Dimension (graph theory); Data cube; Materialized view; Dimensional modeling; Database; Constraint (computer-aided design); Online analytical processing; Data mining; Information retrieval; Mathematics; View; Geography; Database design; Combinatorics","score_opus":0.057702484360440495,"score_gpt":0.2827958738468403,"score_spread":0.2250933894863998,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2134227416","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":[0.312275,0.0020895377,0.6432935,0.0011905372,0.000335059,0.0011892748,0.0033481247,0.02242979,0.013849152],"genre_scores_gemma":[0.26880255,0.00087417866,0.7168713,0.00019622434,0.0000997905,0.00020177834,0.0065871687,0.0020818207,0.004285245],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99796176,0.00026248064,0.00018182422,0.00031964388,0.0009266374,0.0003477612],"domain_scores_gemma":[0.99611974,0.0016367408,0.0002374127,0.00084203837,0.00086793024,0.0002962083],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017548007,0.0012782387,0.0017967777,0.00345595,0.0012724354,0.006027469,0.002075428,0.0012466861,0.0076176473],"category_scores_gemma":[0.0091049345,0.0016518995,0.0021176564,0.0050217384,0.0008252127,0.005474849,0.0037061505,0.001475121,0.001513354],"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":[0.0022181154,0.0005762768,0.013838572,0.0009454864,0.00040971139,0.0017341713,0.0025088869,0.021190401,0.12503438,0.015042483,0.038500264,0.77800125],"study_design_scores_gemma":[0.00061411643,0.0015476609,0.017663332,0.0005439307,0.0013750866,0.002125824,0.011528413,0.5587093,0.27050745,0.060375642,0.07462111,0.00038824405],"about_ca_topic_score_codex":0.0038177967,"about_ca_topic_score_gemma":0.007632033,"teacher_disagreement_score":0.0076176473,"about_ca_system_score_codex":0.0009373035,"about_ca_system_score_gemma":0.0018467578,"threshold_uncertainty_score":0.025483608},"labels":[],"label_agreement":null},{"id":"W2134498478","doi":"10.1109/ipdps.2002.1015486","title":"An adaptive hash join algorithm on a network of workstations","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Hash join; Hash function; Join (topology); Workstation; Sort-merge join; Algorithm; Parallel computing; Pentium; MD5; Distributed computing; Query optimization; Database; Operating system; Programming language","score_opus":0.030826756101126358,"score_gpt":0.25083417904229754,"score_spread":0.22000742294117118,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2134498478","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":[0.10858865,0.00030004472,0.8847406,0.00014538877,0.00009641768,0.00018906401,0.00010555281,0.0031188978,0.0027152423],"genre_scores_gemma":[0.40304768,0.00019501589,0.59059143,0.0000779852,0.0001265337,0.0001652908,0.00048404775,0.0001940745,0.00511799],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991334,0.000093408125,0.00006740439,0.00019024988,0.0004179576,0.00009758645],"domain_scores_gemma":[0.9988336,0.0002700242,0.00009542231,0.00041214083,0.0002674085,0.00012144973],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009627715,0.000415657,0.0007106033,0.0007641984,0.00097056344,0.00071176665,0.0018708255,0.0004887485,0.0025635932],"category_scores_gemma":[0.0019872908,0.00032695528,0.00037506942,0.00093052565,0.00056790974,0.0022357788,0.0017702079,0.00059195544,0.0008628306],"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":[0.0026147072,0.0002117922,0.005463266,0.00015503724,0.00014540697,0.00025409274,0.0006052075,0.112524405,0.1319882,0.02022255,0.007383865,0.71843153],"study_design_scores_gemma":[0.00024893048,0.00064655335,0.002275819,0.000009738458,0.000062825595,0.00033805985,0.00017064971,0.93474823,0.03764539,0.012468324,0.01133197,0.00005357077],"about_ca_topic_score_codex":0.0023144016,"about_ca_topic_score_gemma":0.0026989703,"teacher_disagreement_score":0.0025635932,"about_ca_system_score_codex":0.00059010886,"about_ca_system_score_gemma":0.0010534228,"threshold_uncertainty_score":0.008576095},"labels":[],"label_agreement":null},{"id":"W2134884014","doi":"10.1109/pacrim.1995.519429","title":"Estimating the cost of GraphLog queries","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Transitive closure; Recursion (computer science); Computer science; Probabilistic logic; Closure (psychology); Order (exchange); Theoretical computer science; Transitive relation; Programming language; Mathematics; Artificial intelligence; Discrete mathematics","score_opus":0.027428141255244835,"score_gpt":0.24713541784142623,"score_spread":0.2197072765861814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2134884014","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":[0.65742946,0.00081944943,0.33407664,0.0012315209,0.000048827027,0.00018925234,0.0010545853,0.0019327909,0.0032175616],"genre_scores_gemma":[0.8539097,0.0003619215,0.14313625,0.000109783934,0.000051959545,0.00017728565,0.00092423323,0.00026701335,0.0010619189],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9938431,0.0022222928,0.00038385895,0.0007922046,0.0021646242,0.0005939045],"domain_scores_gemma":[0.9423523,0.04862062,0.0028142817,0.0039270604,0.001721204,0.0005644967],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004002963,0.00088826317,0.0010988483,0.0021502317,0.00073911605,0.0023275155,0.0023581143,0.0022737235,0.0018172209],"category_scores_gemma":[0.05557948,0.0009675872,0.0011103849,0.0032814806,0.0011505713,0.006364632,0.0012708397,0.0011562719,0.0003160784],"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":[0.0009535972,0.00023227348,0.016766196,0.00023610928,0.00014108911,0.00016892566,0.00013678451,0.87171376,0.0070208143,0.01943234,0.0018499851,0.081348054],"study_design_scores_gemma":[0.000019841902,0.000059471942,0.001181326,0.0000053360327,0.000026266802,0.00008915629,0.00002866538,0.9867198,0.0024196452,0.009159211,0.00027820969,0.000012981983],"about_ca_topic_score_codex":0.008377034,"about_ca_topic_score_gemma":0.008332637,"teacher_disagreement_score":0.008377034,"about_ca_system_score_codex":0.0032914148,"about_ca_system_score_gemma":0.0018493483,"threshold_uncertainty_score":0.023880959},"labels":[],"label_agreement":null},{"id":"W2135023474","doi":"10.1002/spe.378","title":"The Relationlog system prototype","year":2001,"lang":"en","type":"article","venue":"Software Practice and Experience","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Datalog; Computer science; Tuple; Programming language; SQL; Relational database; Data definition language; Data model (GIS); Object (grammar); Relational database management system; Relational model; Extension (predicate logic); Database model; Database design; Query language; Data manipulation language; Database; Artificial intelligence; Mathematics","score_opus":0.013209794887491856,"score_gpt":0.2793283712477387,"score_spread":0.26611857636024683,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2135023474","genre_codex":"methods","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0644968,0.002404332,0.6149466,0.003140456,0.0008167539,0.0015752383,0.007168694,0.2081755,0.09727573],"genre_scores_gemma":[0.3415909,0.0024863393,0.5519817,0.0021416768,0.00043428846,0.0009593937,0.020508897,0.009152177,0.07074468],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99867415,0.0004101019,0.00011554411,0.00027546176,0.0004225884,0.00010212167],"domain_scores_gemma":[0.9977937,0.0008444417,0.0000846043,0.00062862894,0.0004313904,0.00021721977],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002729462,0.00036935578,0.00037741568,0.000848082,0.0007690562,0.0028501237,0.0021371087,0.00097659,0.02440167],"category_scores_gemma":[0.005265059,0.0005516909,0.0004992394,0.0007503075,0.000916157,0.00650967,0.0020002534,0.0011777803,0.009116479],"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":[0.002017231,0.0013894032,0.0043377015,0.0015669421,0.00010636017,0.0021330083,0.0030315365,0.009806501,0.03599456,0.15146036,0.1772105,0.6109459],"study_design_scores_gemma":[0.0007827287,0.0006358259,0.0014539722,0.0002638844,0.00012170832,0.002034602,0.00056398753,0.06693664,0.024783092,0.06007966,0.8421924,0.00015149893],"about_ca_topic_score_codex":0.003409127,"about_ca_topic_score_gemma":0.0026577283,"teacher_disagreement_score":0.02440167,"about_ca_system_score_codex":0.00081840256,"about_ca_system_score_gemma":0.0021562427,"threshold_uncertainty_score":0.08163172},"labels":[],"label_agreement":null},{"id":"W2135133299","doi":"10.1023/b:dapd.0000018572.20283.e0","title":"Parallel ROLAP Data Cube Construction on Shared-Nothing Multiprocessors","year":2004,"lang":"en","type":"article","venue":"Distributed and Parallel Databases","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":58,"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; Dalhousie University","funders":"","keywords":"Computer science; Online analytical processing; Row; Parallel computing; Data cube; Speedup; Data warehouse; Data structure; Cube (algebra); Database; Data mining; Programming language; Mathematics","score_opus":0.05168987859294967,"score_gpt":0.2929623151742056,"score_spread":0.24127243658125597,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2135133299","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":[0.099168725,0.00068716245,0.87551373,0.0006726076,0.0001985528,0.00024746422,0.0012450911,0.011774555,0.010492015],"genre_scores_gemma":[0.40411124,0.00030217945,0.5849125,0.0001875427,0.00005345553,0.00030325894,0.0033342212,0.00080845517,0.005987238],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985838,0.00026181547,0.00009482989,0.00019022211,0.00058945065,0.00027986718],"domain_scores_gemma":[0.99746215,0.00046386046,0.00009571444,0.0012301704,0.0005924018,0.00015564133],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00097553956,0.00054132316,0.001256119,0.0010833394,0.0014250489,0.0021226832,0.0031038148,0.00066572736,0.0048035914],"category_scores_gemma":[0.0029629134,0.0005584235,0.0011035869,0.0024617293,0.00091903773,0.0031119108,0.0043629827,0.0011623324,0.0013178656],"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":[0.001936885,0.00043478582,0.004097954,0.00092013483,0.0002735665,0.00088057306,0.0008853112,0.20394652,0.037065312,0.078645684,0.05212998,0.6187833],"study_design_scores_gemma":[0.00022898523,0.00025277675,0.0010542274,0.00006448712,0.00011729076,0.0004597613,0.0008296918,0.78787965,0.07214467,0.10830128,0.028574953,0.00009231224],"about_ca_topic_score_codex":0.004628518,"about_ca_topic_score_gemma":0.0056627323,"teacher_disagreement_score":0.0048035914,"about_ca_system_score_codex":0.0007098239,"about_ca_system_score_gemma":0.0018945914,"threshold_uncertainty_score":0.01606965},"labels":[],"label_agreement":null},{"id":"W2135257313","doi":"10.1109/icsmc.1988.754387","title":"Intelligent Database Query Translation","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; View; Query optimization; Query language; Sargable; Graph database; Query expansion; Online aggregation; Database; Information retrieval; Joins; Web query classification; Query by Example; Web search query; RDF query language; Database design; Graph; Theoretical computer science; Programming language; Search engine","score_opus":0.03505594232909687,"score_gpt":0.2787471341784097,"score_spread":0.24369119184931282,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2135257313","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":[0.0073578847,0.0006835468,0.97487724,0.0011998999,0.00018348543,0.0003913751,0.00042544145,0.008105333,0.00677578],"genre_scores_gemma":[0.17381017,0.0016488193,0.80550516,0.0021238753,0.00027724603,0.00049939065,0.0032544353,0.0019139192,0.010966993],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9907774,0.00384062,0.000925852,0.001258802,0.0027485667,0.00044878235],"domain_scores_gemma":[0.98758113,0.0049153036,0.00058774283,0.0041323737,0.0026161056,0.00016745589],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0077407924,0.0010337953,0.0015200293,0.0020323899,0.001044796,0.0053702756,0.0027550638,0.0013885517,0.0074851243],"category_scores_gemma":[0.019044165,0.0007339679,0.0015666613,0.0028048295,0.0016731467,0.0059801964,0.0047236993,0.0026395482,0.004235467],"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":[0.0010391015,0.0003767296,0.0014707268,0.0014898863,0.00024344724,0.001386733,0.0047475453,0.01917376,0.04890718,0.289092,0.04908904,0.58298385],"study_design_scores_gemma":[0.00026389238,0.00041063895,0.00081141444,0.0003981769,0.000257724,0.0022485133,0.003069228,0.31375545,0.099931754,0.23745736,0.3411768,0.00021916309],"about_ca_topic_score_codex":0.0011622349,"about_ca_topic_score_gemma":0.0007143956,"teacher_disagreement_score":0.0077407924,"about_ca_system_score_codex":0.0012492418,"about_ca_system_score_gemma":0.0015356359,"threshold_uncertainty_score":0.04093772},"labels":[],"label_agreement":null},{"id":"W2136168913","doi":"10.1109/cmpsac.1978.810401","title":"An effective \"on-line\" deadlock detection technique for distributed data base management systems","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Deadlock prevention algorithms; Deadlock; Computer science; Distributed computing; Concurrency control; Wait-for graph; Resource allocation; Graph; Process (computing); Theoretical computer science; Computer network; Database; Graph rewriting; Programming language","score_opus":0.028301261090745967,"score_gpt":0.3023681533039255,"score_spread":0.27406689221317954,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2136168913","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":[0.0018824927,0.00007884473,0.99692106,0.00005350462,0.000013761384,0.000033197008,0.000014055853,0.00071730267,0.00028579333],"genre_scores_gemma":[0.083167724,0.00015624556,0.9154318,0.00007722997,0.000028227774,0.00010271687,0.000112579815,0.00011598213,0.0008073415],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981317,0.00078430696,0.00014223943,0.00022209146,0.0005891675,0.00013057081],"domain_scores_gemma":[0.9976031,0.001125682,0.00016675744,0.0006214891,0.00038727812,0.000095615],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023898543,0.0007301408,0.0009360642,0.0014365681,0.0007819281,0.0018313088,0.0020786498,0.0009994359,0.0016829481],"category_scores_gemma":[0.0043609426,0.00063507014,0.0007048421,0.0009359158,0.0011284595,0.0033092191,0.002095469,0.0013945983,0.00040941348],"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":[0.00043358802,0.00026020044,0.0017023751,0.0005652401,0.00013663119,0.0003302468,0.00068356725,0.120830595,0.052369554,0.20366822,0.008725375,0.6102944],"study_design_scores_gemma":[0.00008983633,0.00018629117,0.00033065726,0.000055027616,0.000069229856,0.0004779458,0.00009577685,0.8641471,0.02662323,0.088979065,0.018885616,0.000060104707],"about_ca_topic_score_codex":0.0010056989,"about_ca_topic_score_gemma":0.00078425364,"teacher_disagreement_score":0.0023898543,"about_ca_system_score_codex":0.0009432799,"about_ca_system_score_gemma":0.001158201,"threshold_uncertainty_score":0.012638867},"labels":[],"label_agreement":null},{"id":"W2136380520","doi":"10.1109/icalt.2008.258","title":"A Semantic-Rich Framework for Learning Software Patterns","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Athabasca University","funders":"","keywords":"Computer science; Domain (mathematical analysis); Context (archaeology); Software; Semantic Web; Software engineering; World Wide Web; Human–computer interaction; Data science; Programming language","score_opus":0.027052996371955542,"score_gpt":0.26873674106373496,"score_spread":0.24168374469177942,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2136380520","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":[0.0016030184,0.00024981773,0.99153113,0.0007394285,0.000050166847,0.00009786764,0.00023215284,0.0013707879,0.0041256794],"genre_scores_gemma":[0.037350655,0.000578453,0.9569254,0.00023446046,0.00007522461,0.00027301838,0.0009039471,0.00021027804,0.0034485268],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99736184,0.0006749333,0.00041364908,0.00041254458,0.0009825879,0.00015453644],"domain_scores_gemma":[0.9980405,0.00064130727,0.00016200844,0.00062978186,0.00030572698,0.00022064791],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032869815,0.0011196426,0.00080247805,0.0036531445,0.0018928222,0.005546118,0.0028604171,0.002166599,0.0050805937],"category_scores_gemma":[0.0046336753,0.0009606603,0.0024283563,0.0032808697,0.004051549,0.013318405,0.0043767206,0.003302099,0.0014056606],"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":[0.00003325009,0.00007030256,0.00032213866,0.00017528328,0.000025103991,0.00021148563,0.00094162504,0.005317884,0.0014666298,0.9288032,0.004637191,0.057995953],"study_design_scores_gemma":[0.000029269417,0.000041911473,0.00019999195,0.00015111422,0.00003384572,0.00037181878,0.0003261236,0.053767707,0.0017569617,0.81457084,0.12871304,0.00003728953],"about_ca_topic_score_codex":0.0041758027,"about_ca_topic_score_gemma":0.008053553,"teacher_disagreement_score":0.005546118,"about_ca_system_score_codex":0.0016546801,"about_ca_system_score_gemma":0.0023198482,"threshold_uncertainty_score":0.017383456},"labels":[],"label_agreement":null},{"id":"W2136629949","doi":"10.1109/sitis.2008.32","title":"Evaluation of Twig Pattern Queries Based on Ordered Tree Matching","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Twig; Computer science; Search engine indexing; Tree (set theory); Matching (statistics); Pattern matching; Scalability; Data mining; Search tree; Order (exchange); Theoretical computer science; Algorithm; Artificial intelligence; Mathematics; Database; Search algorithm; Combinatorics; Statistics","score_opus":0.05260850468837382,"score_gpt":0.2857172416372253,"score_spread":0.23310873694885148,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2136629949","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":[0.40667772,0.0031526498,0.56769466,0.00062468916,0.00022037848,0.0008891533,0.0016571484,0.010777139,0.00830645],"genre_scores_gemma":[0.6513141,0.0005752632,0.34181806,0.00015309302,0.00009353053,0.00022934453,0.0034290508,0.0005924394,0.0017950807],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.982624,0.004398318,0.0016047916,0.0014766799,0.00921194,0.00068426883],"domain_scores_gemma":[0.9818075,0.010040182,0.0010914849,0.0018320031,0.0045931214,0.0006356959],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0052457345,0.0014026212,0.0027191136,0.003361022,0.00092255237,0.002673615,0.0031126062,0.0014405437,0.002779562],"category_scores_gemma":[0.025982765,0.0003875016,0.0006300398,0.0043984815,0.000653638,0.0072907894,0.0016141189,0.00083926955,0.00077121024],"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":[0.0053209746,0.0010576103,0.019385867,0.0013821209,0.0004979378,0.00085993856,0.0006809236,0.09205449,0.06609428,0.012162089,0.017901042,0.7826027],"study_design_scores_gemma":[0.0001494665,0.0005768223,0.0030419715,0.000023996174,0.00006196381,0.0004670307,0.0003472818,0.95962113,0.026501227,0.00548316,0.0036783908,0.00004764315],"about_ca_topic_score_codex":0.00658969,"about_ca_topic_score_gemma":0.0050010527,"teacher_disagreement_score":0.00658969,"about_ca_system_score_codex":0.0015661796,"about_ca_system_score_gemma":0.001697446,"threshold_uncertainty_score":0.027742386},"labels":[],"label_agreement":null},{"id":"W2137162229","doi":"10.1007/978-3-642-00672-2_1","title":"Distributed XML Processing","year":2009,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Computer science; Efficient XML Interchange; Streaming XML; XML Schema Editor; XML database; XML; XML validation; XML Schema (W3C); XML framework; Database; Data exchange; XML Signature; XML Encryption; Focus (optics); External Data Representation; Information retrieval; World Wide Web; Operating system","score_opus":0.014627140083384936,"score_gpt":0.2493476856381141,"score_spread":0.23472054555472915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2137162229","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":[0.004268185,0.0017175007,0.8339847,0.00078756374,0.0006521774,0.00018917759,0.0009386501,0.02096762,0.13649449],"genre_scores_gemma":[0.082636625,0.0030161317,0.52481264,0.000674321,0.00049793493,0.00027009432,0.008366948,0.0038706772,0.3758547],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.999446,0.00007101773,0.000040921055,0.0001430521,0.00026079948,0.000038324564],"domain_scores_gemma":[0.9995054,0.000084592306,0.000011324425,0.00027789464,0.00009896749,0.000021773054],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063858676,0.00087822066,0.0006763573,0.0010041627,0.00083424756,0.0021625534,0.0017279119,0.0007435633,0.04353909],"category_scores_gemma":[0.0010748042,0.00065319426,0.00061811134,0.0015611686,0.00053906895,0.00261733,0.001394099,0.0012208719,0.023238136],"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":[0.00017333053,0.00014269531,0.00028242308,0.00023735662,0.00004054687,0.00014749872,0.00022520187,0.004234185,0.017161204,0.12560594,0.12557502,0.7261746],"study_design_scores_gemma":[0.00007217739,0.00009180584,0.0007658893,0.00011072747,0.00007223062,0.0008688486,0.000118149466,0.07393517,0.047575362,0.170186,0.70615715,0.000046511675],"about_ca_topic_score_codex":0.0010051146,"about_ca_topic_score_gemma":0.0011830949,"teacher_disagreement_score":0.04353909,"about_ca_system_score_codex":0.00055117265,"about_ca_system_score_gemma":0.0006123847,"threshold_uncertainty_score":0.14565271},"labels":[],"label_agreement":null},{"id":"W2137420824","doi":"10.1109/tkde.2002.1047768","title":"Efficient queries over Web views","year":2002,"lang":"en","type":"article","venue":"IEEE Transactions on Knowledge and Data Engineering","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Relational database; Information retrieval; Redundancy (engineering); Materialized view; Data redundancy; Set (abstract data type); SQL; Data mining; World Wide Web; Theoretical computer science; Database; View; Database design; Programming language","score_opus":0.036669561203935296,"score_gpt":0.2640088886651401,"score_spread":0.2273393274612048,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2137420824","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":[0.053177577,0.00081894774,0.9218262,0.0008228606,0.00009543469,0.0003086972,0.002525731,0.010092668,0.0103319455],"genre_scores_gemma":[0.4096172,0.0015342046,0.5648744,0.00046838727,0.00027877087,0.00035151266,0.010027363,0.0025390768,0.010309016],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9933571,0.0016109966,0.00080143294,0.0007193549,0.0029600537,0.00055097335],"domain_scores_gemma":[0.99237025,0.0035477437,0.0004196839,0.0022209547,0.0012728353,0.00016848327],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029094063,0.00092352333,0.0016581868,0.0018768348,0.0010171167,0.0061451322,0.0023471129,0.001650615,0.0042400346],"category_scores_gemma":[0.015400399,0.00092611474,0.0015460978,0.0032296341,0.001215734,0.010139185,0.004440961,0.0017223613,0.0018054998],"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":[0.0008259831,0.00040291267,0.0043621687,0.0009234331,0.00031997488,0.0014682114,0.003119778,0.09747008,0.048458718,0.42588264,0.05188553,0.36488056],"study_design_scores_gemma":[0.00024209924,0.00017465482,0.0010684228,0.00014400925,0.00019267057,0.0008272591,0.0016111338,0.51012915,0.0410604,0.36655942,0.07785262,0.00013808087],"about_ca_topic_score_codex":0.004563574,"about_ca_topic_score_gemma":0.00543475,"teacher_disagreement_score":0.0061451322,"about_ca_system_score_codex":0.0011680229,"about_ca_system_score_gemma":0.0013692641,"threshold_uncertainty_score":0.015386581},"labels":[],"label_agreement":null},{"id":"W2137580272","doi":"10.1007/s11280-005-1544-y","title":"Studying the XML Web: Gathering Statistics from an XML Sample","year":2005,"lang":"en","type":"article","venue":"World Wide Web","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":76,"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":"Institut national de recherche en informatique et en automatique (INRIA)","keywords":"Computer science; XML validation; Efficient XML Interchange; XML Schema Editor; XML Base; Streaming XML; Document Structure Description; XML Signature; XML Encryption; Information retrieval; World Wide Web; XML database; cXML; XML; Database","score_opus":0.02279868175895083,"score_gpt":0.2698407601171572,"score_spread":0.24704207835820635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2137580272","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":[0.81082547,0.00061827776,0.12013325,0.000585046,0.000043741744,0.00095767627,0.058041677,0.0026330927,0.0061617317],"genre_scores_gemma":[0.7689009,0.0007268259,0.10813208,0.00029899308,0.00016525656,0.0019143149,0.1163044,0.00058102224,0.0029762087],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9937411,0.0021312828,0.0009984407,0.0007623306,0.002065803,0.0003010466],"domain_scores_gemma":[0.91525584,0.054054577,0.006135259,0.010964789,0.011561567,0.0020280026],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00637815,0.000619735,0.0008321802,0.015441905,0.0009221823,0.0018372926,0.0008439264,0.00090354274,0.0024905647],"category_scores_gemma":[0.059661925,0.00044007128,0.00056726567,0.012505459,0.0005470302,0.0024274786,0.0013594183,0.0008229456,0.0022248165],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005443902,0.0011164123,0.75106627,0.0005131999,0.00033516527,0.0005404495,0.0033141486,0.0055731097,0.012445831,0.004953764,0.028374827,0.19122243],"study_design_scores_gemma":[0.00017120467,0.0015443448,0.7506283,0.00023205049,0.0006429473,0.0023225062,0.012385849,0.09675982,0.03256545,0.021920132,0.0806281,0.00019937477],"about_ca_topic_score_codex":0.004158435,"about_ca_topic_score_gemma":0.0045721126,"teacher_disagreement_score":0.015441905,"about_ca_system_score_codex":0.00050918874,"about_ca_system_score_gemma":0.0016020652,"threshold_uncertainty_score":0.03373128},"labels":[],"label_agreement":null},{"id":"W2137679685","doi":"10.1007/3-540-47887-6_26","title":"WebFrame: In Pursuit of Computationally and Cognitively Efficient Web Mining","year":2002,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":13,"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; Software deployment; Web mining; Data science; Data mining; Human–computer interaction; World Wide Web; Web service; Software engineering","score_opus":0.016972485408829216,"score_gpt":0.2414058275206697,"score_spread":0.22443334211184046,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2137679685","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":[0.0060805203,0.00078988855,0.972452,0.0012896347,0.00022410256,0.00011106511,0.0007454042,0.014307836,0.003999633],"genre_scores_gemma":[0.051831976,0.0009915745,0.93650985,0.00048348386,0.00028395947,0.00015182044,0.0023552922,0.001442843,0.005949231],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984224,0.00031952493,0.00007589651,0.0003267805,0.0007502262,0.00010520127],"domain_scores_gemma":[0.9960771,0.0016981143,0.0001306487,0.0011003965,0.0007678958,0.00022589338],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026905139,0.0009605249,0.0015679746,0.002802707,0.0012588107,0.003931775,0.0037888628,0.0014596323,0.0067346185],"category_scores_gemma":[0.008732608,0.00086349057,0.0012821602,0.0047165086,0.0013390464,0.007421362,0.0030328324,0.0020503385,0.0036870346],"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":[0.00066118385,0.00038430924,0.0015208636,0.00050627615,0.00013347999,0.0001343725,0.00034201585,0.010575982,0.0074824165,0.0890753,0.10150522,0.78767854],"study_design_scores_gemma":[0.00017720305,0.0001543754,0.001166868,0.00011964081,0.00011905476,0.0004572527,0.0002557249,0.57093483,0.021365806,0.29194993,0.11323782,0.00006153714],"about_ca_topic_score_codex":0.010818306,"about_ca_topic_score_gemma":0.013484429,"teacher_disagreement_score":0.010818306,"about_ca_system_score_codex":0.00095124054,"about_ca_system_score_gemma":0.0025533657,"threshold_uncertainty_score":0.022529542},"labels":[],"label_agreement":null},{"id":"W2138217670","doi":"10.1109/iti.2004.241404","title":"A direct method of data exchange between XML and relational database","year":2004,"lang":"en","type":"article","venue":"Information Technology Interfaces","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Novelis (Canada)","funders":"","keywords":"XML database; Computer science; XSLT; Streaming XML; Relational database; Database; XML validation; Efficient XML Interchange; Data exchange; XML; Information retrieval; XML Schema (W3C); XML Schema Editor; XML framework; Process (computing); XML Encryption; World Wide Web; Programming language","score_opus":0.04088600755220562,"score_gpt":0.31373727983073874,"score_spread":0.2728512722785331,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2138217670","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":[0.0016939183,0.0006400204,0.983373,0.0004989747,0.00040801847,0.0003398337,0.00024356543,0.004095062,0.008707574],"genre_scores_gemma":[0.036175903,0.001015814,0.9372003,0.0006776629,0.00050895213,0.0007911492,0.0010036812,0.0010567486,0.021569721],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9892653,0.0030883832,0.0014591266,0.0024489625,0.003354364,0.00038380915],"domain_scores_gemma":[0.99154526,0.0023304333,0.00046082443,0.0038816691,0.0016038355,0.00017781569],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0072816047,0.00097599137,0.001205639,0.0026729882,0.00143811,0.005449988,0.0027601623,0.0019992096,0.01049322],"category_scores_gemma":[0.011744368,0.0008338113,0.0014299355,0.002604041,0.0016893399,0.0075148726,0.0050456775,0.0031459164,0.007118928],"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":[0.00033762876,0.00026801048,0.0016983851,0.0008396637,0.00020365823,0.000837721,0.0020370535,0.0010991741,0.039010335,0.2774301,0.030092001,0.6461463],"study_design_scores_gemma":[0.00030355147,0.000422012,0.0014823624,0.00042006257,0.0003335702,0.0046856897,0.0006676512,0.025165884,0.09574384,0.11644462,0.75403166,0.00029909165],"about_ca_topic_score_codex":0.0009523786,"about_ca_topic_score_gemma":0.0007723914,"teacher_disagreement_score":0.01049322,"about_ca_system_score_codex":0.0005393727,"about_ca_system_score_gemma":0.0018084869,"threshold_uncertainty_score":0.03850925},"labels":[],"label_agreement":null},{"id":"W2138277932","doi":"10.1145/543613.543625","title":"A normal form for XML documents","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":107,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; XML validation; Document Structure Description; Functional dependency; XML Schema Editor; XML database; Information retrieval; XML; XML Schema (W3C); XML Encryption; Programming language; Relational database; Theoretical computer science; World Wide Web","score_opus":0.021205348079384144,"score_gpt":0.24944127376469227,"score_spread":0.22823592568530812,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2138277932","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":[0.0033170797,0.00031417955,0.9851757,0.0009183849,0.00033476597,0.00019402374,0.0008119053,0.0017713958,0.0071625523],"genre_scores_gemma":[0.06718381,0.00084899215,0.91572404,0.0005434868,0.00030823605,0.0005993949,0.002426693,0.0007680109,0.01159736],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9945157,0.001107091,0.0011184535,0.0011777104,0.0018439002,0.00023711655],"domain_scores_gemma":[0.9949051,0.0016529686,0.00041302762,0.001189089,0.0016921838,0.00014766077],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004093618,0.0008655788,0.0006466845,0.0021048689,0.0010105382,0.0038614206,0.0011523827,0.0013028625,0.004841856],"category_scores_gemma":[0.010708791,0.0006018454,0.00087048433,0.0021399183,0.0028749462,0.008568776,0.0019390696,0.0030245576,0.0027522983],"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":[0.00005362886,0.000027152499,0.00030770025,0.0001494295,0.000010682265,0.0001291245,0.0005238732,0.0026602116,0.002926194,0.89778745,0.009543563,0.085881025],"study_design_scores_gemma":[0.000033725075,0.000069607864,0.00015781945,0.0001271125,0.00001961273,0.0007786298,0.00020250527,0.0275851,0.0065082433,0.66777253,0.29669556,0.00004952624],"about_ca_topic_score_codex":0.002133047,"about_ca_topic_score_gemma":0.0015719464,"teacher_disagreement_score":0.004841856,"about_ca_system_score_codex":0.0018367664,"about_ca_system_score_gemma":0.0018657517,"threshold_uncertainty_score":0.02164936},"labels":[],"label_agreement":null},{"id":"W2138466075","doi":"10.1109/dbkda.2009.30","title":"Visualization and Integration of Databases Using Self-Organizing Map","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Computer science; Cluster analysis; Visualization; Data mining; Relational database; Information retrieval; Data integration; Semi-structured data; Schema (genetic algorithms); Data visualization; Database; Artificial intelligence","score_opus":0.0332067473715672,"score_gpt":0.3056416748080313,"score_spread":0.2724349274364641,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2138466075","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":[0.021644475,0.0006148562,0.9652281,0.00058203423,0.0000894065,0.00011681018,0.00059387274,0.007270697,0.0038598238],"genre_scores_gemma":[0.19156413,0.0007808523,0.8044206,0.00009267745,0.000053972246,0.00021444542,0.0008345212,0.00045722496,0.001581496],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993498,0.00021228543,0.000045600656,0.00007875061,0.00027124805,0.000042237796],"domain_scores_gemma":[0.99902546,0.00037809578,0.000081043756,0.00012349876,0.00033587238,0.000056001772],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001029162,0.0007397608,0.0004631975,0.004270738,0.00062313647,0.0026972163,0.0007096332,0.0006765762,0.0035966942],"category_scores_gemma":[0.002625566,0.00041666167,0.00058137556,0.0029875096,0.00033896588,0.0019078518,0.0018147773,0.000648224,0.00074791716],"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":[0.0005826552,0.0002353038,0.0057020825,0.000935952,0.00035379315,0.0009718643,0.0044642575,0.1084644,0.047000077,0.056710627,0.037551306,0.73702776],"study_design_scores_gemma":[0.00007212455,0.000064512715,0.004282044,0.000118084026,0.000058994254,0.00038644686,0.0010601219,0.873895,0.020501612,0.05489567,0.04454913,0.00011635801],"about_ca_topic_score_codex":0.0034270608,"about_ca_topic_score_gemma":0.0029831636,"teacher_disagreement_score":0.004270738,"about_ca_system_score_codex":0.00049860287,"about_ca_system_score_gemma":0.00066574325,"threshold_uncertainty_score":0.012032151},"labels":[],"label_agreement":null},{"id":"W2138757450","doi":"","title":"Structure and content scoring for XML","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":141,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; University of Toronto","funders":"","keywords":"Computer science; XML; Information retrieval; Path (computing); Document Structure Description; Data mining; World Wide Web","score_opus":0.03575117782653841,"score_gpt":0.2541037418922822,"score_spread":0.21835256406574377,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2138757450","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":[0.026603254,0.00061141426,0.9624734,0.0002956537,0.0000728286,0.00022277072,0.0011378151,0.0045519806,0.0040308726],"genre_scores_gemma":[0.23580122,0.00050249987,0.7524949,0.00010575496,0.00014661884,0.00031032285,0.004091637,0.00051353057,0.006033586],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99734133,0.0006631713,0.00025695987,0.00032199477,0.001276733,0.00013977675],"domain_scores_gemma":[0.99469596,0.002068621,0.0005097742,0.0010191106,0.0015571788,0.00014944431],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018277221,0.00078634155,0.00077865785,0.0038783504,0.00070334383,0.0017990909,0.0013358932,0.0009551534,0.005243284],"category_scores_gemma":[0.016588269,0.00031263308,0.0006826518,0.003980415,0.0006739586,0.002972547,0.0013783842,0.0007096981,0.0026015628],"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":[0.00037710048,0.00011211005,0.008672372,0.00050600746,0.00007807301,0.00028311508,0.0004531524,0.047827095,0.022520166,0.08922878,0.01905646,0.81088555],"study_design_scores_gemma":[0.00008512305,0.00029414837,0.0048448215,0.000092965885,0.0000668841,0.0009027658,0.00029982938,0.7899024,0.034646608,0.13336243,0.035420448,0.00008147518],"about_ca_topic_score_codex":0.002780962,"about_ca_topic_score_gemma":0.002926135,"teacher_disagreement_score":0.005243284,"about_ca_system_score_codex":0.0009779301,"about_ca_system_score_gemma":0.0010724155,"threshold_uncertainty_score":0.017540514},"labels":[],"label_agreement":null},{"id":"W2138779000","doi":"10.1142/s0129626413500023","title":"PARALLEL CONSTRUCTION OF DATA CUBES ON MULTI-CORE MULTI-DISK PLATFORMS","year":2013,"lang":"en","type":"article","venue":"Parallel Processing Letters","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Online analytical processing; Computer science; Data cube; Cube (algebra); Sorting; Very large database; Parallel computing; Speedup; Data warehouse; Aggregate (composite); sort; Core (optical fiber); Database; Data mining; Algorithm; Mathematics","score_opus":0.08356213875085854,"score_gpt":0.3058545924301158,"score_spread":0.22229245367925726,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2138779000","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":[0.13054189,0.00048798698,0.85594344,0.00047503522,0.00014589663,0.0002991547,0.00042646172,0.00528867,0.0063913767],"genre_scores_gemma":[0.23319902,0.00025642064,0.7620602,0.000114221286,0.000028732033,0.0003115273,0.0012394615,0.00025586796,0.002534445],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99884975,0.00022286337,0.00008288591,0.00014684197,0.0005485239,0.00014907561],"domain_scores_gemma":[0.9979505,0.0005925734,0.00010010653,0.00057276787,0.0006625987,0.00012148454],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00086859113,0.00059208804,0.00073220045,0.0007708292,0.00095309573,0.0011583319,0.0014953791,0.00045807418,0.002235664],"category_scores_gemma":[0.0029912842,0.00046080703,0.00092040084,0.0020415287,0.0006620583,0.0017475113,0.001730415,0.00095586444,0.00076021336],"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":[0.00086290797,0.00030824557,0.0043103453,0.00048820887,0.0001635577,0.00054906425,0.0006418364,0.42189878,0.04511684,0.036262415,0.018707277,0.47069064],"study_design_scores_gemma":[0.000110311026,0.00014862228,0.0007804611,0.0000152483535,0.000020146226,0.00013397382,0.0001940653,0.9384754,0.028932516,0.019584823,0.011574088,0.00003044198],"about_ca_topic_score_codex":0.004665238,"about_ca_topic_score_gemma":0.0058182217,"teacher_disagreement_score":0.004665238,"about_ca_system_score_codex":0.0007911952,"about_ca_system_score_gemma":0.0017363945,"threshold_uncertainty_score":0.009276152},"labels":[],"label_agreement":null},{"id":"W2138794734","doi":"10.1109/icde.2006.88","title":"Making Designer Schemas with Colors","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Schema (genetic algorithms); XML; Intuition; Data redundancy; Redundancy (engineering); Information retrieval; Theoretical computer science; Data mining; XML Schema (W3C); Document Structure Description; Programming language; Database; Document type definition; World Wide Web","score_opus":0.02104230506838537,"score_gpt":0.24599905588293333,"score_spread":0.22495675081454797,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2138794734","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":[0.00852487,0.00008517215,0.9839213,0.0006039786,0.00006713477,0.00012468973,0.00014423406,0.0024005242,0.0041280184],"genre_scores_gemma":[0.10501828,0.00031070568,0.88564014,0.000593836,0.000038854996,0.00024993502,0.00040315778,0.0009852586,0.006759837],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99213,0.00335004,0.0008408533,0.0012457317,0.002051979,0.0003813722],"domain_scores_gemma":[0.9830201,0.004622495,0.0009934059,0.008107901,0.00295969,0.0002963335],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008870814,0.0007231171,0.00053428987,0.00093169766,0.00063808454,0.0046010953,0.0022536134,0.0015921397,0.0036480818],"category_scores_gemma":[0.02208765,0.0012038895,0.0014491162,0.0011085543,0.002890591,0.009828626,0.0035410663,0.0026205834,0.0015818909],"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":[0.00018906152,0.000086368025,0.0025203107,0.0003732684,0.00007213855,0.000345583,0.0031883616,0.018664936,0.01950424,0.84281766,0.0067485073,0.10548955],"study_design_scores_gemma":[0.00016462393,0.0001918431,0.00043902767,0.0002184043,0.00019053486,0.00096060144,0.0013079075,0.07890585,0.087262236,0.3246095,0.50564253,0.00010696409],"about_ca_topic_score_codex":0.0020845633,"about_ca_topic_score_gemma":0.0023579428,"teacher_disagreement_score":0.008870814,"about_ca_system_score_codex":0.0012105221,"about_ca_system_score_gemma":0.0021481938,"threshold_uncertainty_score":0.046913862},"labels":[],"label_agreement":null},{"id":"W2139000699","doi":"10.1145/2338626.2338633","title":"Reordering rows for better compression","year":2012,"lang":"en","type":"article","venue":"ACM Transactions on Database Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Speedup; Lexicographical order; Row; Sorting; Compression (physics); Algorithm; Data compression; Heuristic; Heuristics; Huffman coding; Compression ratio; Encoding (memory); Parallel computing; Mathematics; Combinatorics; Artificial intelligence; Database","score_opus":0.040661275768922964,"score_gpt":0.289049769394661,"score_spread":0.248388493625738,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2139000699","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":[0.17265767,0.0040815184,0.774421,0.0033137163,0.0018193946,0.0005603269,0.0027996476,0.019016147,0.021330627],"genre_scores_gemma":[0.25103354,0.0012680349,0.72864544,0.0014535153,0.00038938542,0.00020062919,0.003628042,0.0025716906,0.010809714],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986203,0.00022235324,0.00021742894,0.00023039417,0.0005053591,0.00020429963],"domain_scores_gemma":[0.9934715,0.0017409571,0.0004224986,0.0030348732,0.0011987454,0.00013142767],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008232598,0.0012797078,0.0010414048,0.0014783329,0.00066859025,0.0023784053,0.0013174145,0.00090730935,0.014385993],"category_scores_gemma":[0.0078937765,0.0005491061,0.00067622174,0.0029803088,0.0007031323,0.004133627,0.0012465388,0.001414162,0.0070073716],"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":[0.0010022202,0.00035039833,0.003524898,0.00072837947,0.00011090166,0.00056430185,0.0004085753,0.02535396,0.19345893,0.025155531,0.04149568,0.7078462],"study_design_scores_gemma":[0.00032111246,0.0009703787,0.0035968137,0.0003803832,0.00023958011,0.002404997,0.00080682826,0.2302873,0.56036377,0.05274783,0.14765249,0.00022857735],"about_ca_topic_score_codex":0.0010832476,"about_ca_topic_score_gemma":0.002479769,"teacher_disagreement_score":0.014385993,"about_ca_system_score_codex":0.0005860187,"about_ca_system_score_gemma":0.0014985465,"threshold_uncertainty_score":0.048125982},"labels":[],"label_agreement":null},{"id":"W2139359621","doi":"10.1109/ideas.2007.41","title":"Stream Processing in a Relational Database: a Case Study","year":2007,"lang":"en","type":"article","venue":"International Database Engineering and Applications Symposium","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Computer science; Database; Stream processing; Relational database; Relational database management system; Point (geometry); Distributed computing","score_opus":0.01245179102156089,"score_gpt":0.27204981805998957,"score_spread":0.25959802703842866,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2139359621","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":[0.76967657,0.008597297,0.15616196,0.013110567,0.00035228324,0.0007094728,0.0017338222,0.0024242376,0.047233842],"genre_scores_gemma":[0.8723917,0.005061733,0.11278945,0.0008287352,0.0002861684,0.0001476471,0.00088538084,0.00041701517,0.007192143],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99461114,0.0020880492,0.0004421895,0.00044851005,0.0021012756,0.00030895782],"domain_scores_gemma":[0.9877819,0.008405862,0.00045139767,0.0012170768,0.0014206344,0.0007231481],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005385671,0.00033882275,0.0005240838,0.00097344175,0.0017995448,0.0040248497,0.002017387,0.002588724,0.0025398012],"category_scores_gemma":[0.015324146,0.00037043446,0.0007757428,0.0033828106,0.0014479967,0.004009286,0.0015491932,0.0017294219,0.00088989554],"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":[0.0029568744,0.0039064446,0.07699161,0.0030958476,0.0004095826,0.093180664,0.03220567,0.07583021,0.025919205,0.1865507,0.06834823,0.4306049],"study_design_scores_gemma":[0.000883917,0.0031851842,0.035462536,0.0008391694,0.00042127652,0.057085883,0.029428627,0.31659427,0.05637221,0.07150652,0.42785466,0.00036582124],"about_ca_topic_score_codex":0.007889674,"about_ca_topic_score_gemma":0.0062469016,"teacher_disagreement_score":0.007889674,"about_ca_system_score_codex":0.001404718,"about_ca_system_score_gemma":0.0010610552,"threshold_uncertainty_score":0.028482497},"labels":[],"label_agreement":null},{"id":"W2140192228","doi":"10.1109/kbse.1992.252906","title":"Reusing database queries in analogical domains","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Domain (mathematical analysis); Planner; SQL; Simple (philosophy); Documentation; Base (topology); Programming language; Reuse; Natural language; Information retrieval; Database; Theoretical computer science; Artificial intelligence; Mathematics","score_opus":0.02102617478679533,"score_gpt":0.2641187258968174,"score_spread":0.24309255111002206,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140192228","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":[0.036041275,0.00023491179,0.94817245,0.0006772677,0.000041047188,0.00019685521,0.00013140838,0.0033947309,0.011110001],"genre_scores_gemma":[0.4064143,0.0003065005,0.5828311,0.00067584787,0.000057640238,0.0001981885,0.0006372986,0.0010331074,0.007845983],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99160427,0.0035552504,0.0008741854,0.0013507019,0.0021727795,0.00044290008],"domain_scores_gemma":[0.9811364,0.008206476,0.0006879696,0.008494363,0.0012271672,0.00024763905],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006149202,0.00090947445,0.0010840782,0.0020494284,0.0012525623,0.0046035047,0.0048564933,0.0027422716,0.0034311395],"category_scores_gemma":[0.024558552,0.0012623431,0.0018030951,0.0021677373,0.004323454,0.013161244,0.008904636,0.0031789215,0.00101424],"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":[0.00023639064,0.00054808165,0.003710763,0.00037853877,0.00012758182,0.0012877199,0.0066267275,0.061031744,0.009271067,0.72173995,0.0035497542,0.19149168],"study_design_scores_gemma":[0.00011798784,0.00021846475,0.0006318889,0.000105371175,0.000110643305,0.0012710694,0.001539391,0.27878886,0.026255557,0.61060524,0.080207,0.00014856388],"about_ca_topic_score_codex":0.0041379984,"about_ca_topic_score_gemma":0.0041185436,"teacher_disagreement_score":0.006149202,"about_ca_system_score_codex":0.0017889922,"about_ca_system_score_gemma":0.0013750015,"threshold_uncertainty_score":0.032520473},"labels":[],"label_agreement":null},{"id":"W2140313478","doi":"10.1109/soac.1991.143894","title":"Query processing issues in object-oriented database system-preliminary ideas","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Query optimization; Query language; View; Sargable; Query expansion; Database design; Database; Relational database; Object (grammar); Database theory; Query by Example; Information retrieval; Set (abstract data type); Web search query; Web query classification; RDF query language; Data model (GIS); Programming language; Artificial intelligence; Search engine","score_opus":0.017100422294578355,"score_gpt":0.258737633478893,"score_spread":0.24163721118431464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140313478","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":[0.008013576,0.071068615,0.8460708,0.018639073,0.0015696227,0.00056032604,0.0002181507,0.0006537868,0.053206023],"genre_scores_gemma":[0.25103727,0.082732454,0.6145784,0.0071076658,0.007914145,0.0013108522,0.0008023635,0.0003665677,0.034150243],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99329376,0.0025267245,0.00056873326,0.0006954722,0.0025714762,0.00034382267],"domain_scores_gemma":[0.9870092,0.008523169,0.00034959018,0.0012780078,0.002555505,0.00028462685],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0134117715,0.0010798548,0.0010509393,0.0019364043,0.0020671072,0.012461295,0.004095965,0.0041658524,0.005106713],"category_scores_gemma":[0.018677007,0.0016894122,0.0015051838,0.004030489,0.006537967,0.021945864,0.002080523,0.00494027,0.002352297],"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":[0.00006711054,0.000080500715,0.00029947687,0.0006238331,0.000028672579,0.00035921703,0.001052466,0.0045848265,0.0007646914,0.9506821,0.009279246,0.03217779],"study_design_scores_gemma":[0.00005195843,0.00012332543,0.00033583486,0.0005146721,0.000057580954,0.0008799268,0.0006190046,0.037763935,0.0015494319,0.81511986,0.14291334,0.00007115895],"about_ca_topic_score_codex":0.0041836263,"about_ca_topic_score_gemma":0.0015605704,"teacher_disagreement_score":0.0134117715,"about_ca_system_score_codex":0.0033253299,"about_ca_system_score_gemma":0.0017833478,"threshold_uncertainty_score":0.07092911},"labels":[],"label_agreement":null},{"id":"W2140346433","doi":"10.1109/icde.2006.115","title":"Predicate-based Filtering of XPath Expressions","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"XPath; Computer science; Predicate (mathematical logic); XML; Scalability; Tuple; Path expression; Regular expression; Theoretical computer science; Algorithm; Programming language; XML database; Database; Mathematics","score_opus":0.0063204793357576235,"score_gpt":0.20594216933266551,"score_spread":0.19962168999690788,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140346433","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":[0.020750852,0.00039432143,0.9713657,0.00033100904,0.00007421144,0.00011121116,0.00040220187,0.0045432323,0.002027359],"genre_scores_gemma":[0.13881613,0.000764591,0.8508227,0.00044830877,0.00014037997,0.00013878221,0.0029018372,0.00090850604,0.005058783],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9963419,0.0006691263,0.00040534197,0.00081115996,0.0015445084,0.00022786617],"domain_scores_gemma":[0.992588,0.0040242826,0.00052739,0.001497502,0.001245851,0.00011705294],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037569962,0.0007755037,0.0011240906,0.002291558,0.00112171,0.0030256882,0.0016413446,0.0013098177,0.002844604],"category_scores_gemma":[0.0076342584,0.0005036103,0.0012714633,0.0031528717,0.0009292079,0.0051781675,0.0014355185,0.0015021046,0.0015086455],"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":[0.0007664956,0.00034061074,0.0073040645,0.00062475476,0.00020816295,0.00070101395,0.0010062628,0.036821205,0.071322575,0.07782099,0.019099673,0.7839841],"study_design_scores_gemma":[0.00010580742,0.00027422368,0.0031340031,0.00014403278,0.00015939005,0.001514628,0.0005701555,0.60344785,0.2047332,0.09276436,0.09303585,0.00011649721],"about_ca_topic_score_codex":0.0034952844,"about_ca_topic_score_gemma":0.0027585288,"teacher_disagreement_score":0.0037569962,"about_ca_system_score_codex":0.001050644,"about_ca_system_score_gemma":0.0013694469,"threshold_uncertainty_score":0.019869149},"labels":[],"label_agreement":null},{"id":"W2140710313","doi":"","title":"Towards the conceptual specification of statistical functions with OCL","year":2009,"lang":"en","type":"article","venue":"Repositorio Institucional de la Universidad de Alicante (Universidad de Alicante)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Ministerio de Economía y Competitividad","keywords":"Computer science; Set (abstract data type); Object Constraint Language; Constraint (computer-aided design); Programming language; Object (grammar); Conceptual model; Object-oriented programming; Theoretical computer science; Conceptual framework; Software engineering; Unified Modeling Language; Artificial intelligence; Mathematics; Database; Software","score_opus":0.011041634095108933,"score_gpt":0.24640869985299602,"score_spread":0.23536706575788707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140710313","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":[0.0024130843,0.00016889944,0.9925007,0.0006652618,0.000052723623,0.00011608144,0.00016692899,0.001738183,0.0021780473],"genre_scores_gemma":[0.059694197,0.00037717994,0.93581635,0.00074245397,0.0001136455,0.00041386732,0.00059495866,0.0010107605,0.0012366092],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.97747177,0.009757672,0.0034221157,0.0020100262,0.0061331755,0.0012052134],"domain_scores_gemma":[0.9595173,0.019844122,0.00318132,0.009246072,0.0073000113,0.0009110376],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.024068987,0.0017972003,0.0013182347,0.003064215,0.0018148955,0.012077237,0.0050677652,0.0029384857,0.0025373574],"category_scores_gemma":[0.032723613,0.0020146566,0.0026579949,0.004535557,0.007928136,0.013480117,0.006855277,0.0066435733,0.0011403679],"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":[0.000078299694,0.0000762284,0.0007140411,0.00049303414,0.000051397037,0.00028840985,0.0017251351,0.013514674,0.0038350837,0.9203939,0.004102969,0.054726727],"study_design_scores_gemma":[0.00012651931,0.00011740449,0.00048274535,0.0007945012,0.00014421222,0.00055707333,0.0008064446,0.26342666,0.022958105,0.49548244,0.21488774,0.00021613635],"about_ca_topic_score_codex":0.011072504,"about_ca_topic_score_gemma":0.006179203,"teacher_disagreement_score":0.024068987,"about_ca_system_score_codex":0.0034739494,"about_ca_system_score_gemma":0.0071010767,"threshold_uncertainty_score":0.12729049},"labels":[],"label_agreement":null},{"id":"W2140755262","doi":"10.1109/wcre.2000.891483","title":"Defining, transforming, and exchanging high-level schemas","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Abstraction; Reverse engineering; Software engineering; Programming language; Data exchange; Data science; Database","score_opus":0.025845179474903106,"score_gpt":0.226476895739955,"score_spread":0.20063171626505188,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140755262","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":[0.0074463137,0.00030364387,0.9843784,0.0009477174,0.0001288348,0.00047310235,0.00053057785,0.001534309,0.0042571966],"genre_scores_gemma":[0.038236078,0.0007179721,0.9550294,0.00045109526,0.0000695478,0.00040853748,0.001627942,0.00059986353,0.0028595356],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9799887,0.008187591,0.0035540625,0.0014818066,0.005800622,0.0009872213],"domain_scores_gemma":[0.9700224,0.008599405,0.0017060981,0.014388267,0.004501847,0.00078203925],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.034697633,0.0010027866,0.00133775,0.003186905,0.0021395627,0.014818424,0.0045291646,0.0029729782,0.0034416493],"category_scores_gemma":[0.032620292,0.0015454972,0.0023659293,0.0043467856,0.004478001,0.015347921,0.007342687,0.0058409544,0.0021304148],"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":[0.00008939993,0.00016674302,0.0028622933,0.00043380982,0.00008159682,0.0005201304,0.005732675,0.0071966485,0.008009495,0.8827915,0.0078061093,0.08430974],"study_design_scores_gemma":[0.00009725608,0.00017222365,0.0012628717,0.0007265221,0.00015984067,0.0016672928,0.0032862865,0.048105393,0.042653184,0.48290387,0.41877213,0.00019311575],"about_ca_topic_score_codex":0.0037665658,"about_ca_topic_score_gemma":0.0037511275,"teacher_disagreement_score":0.034697633,"about_ca_system_score_codex":0.0027668262,"about_ca_system_score_gemma":0.006434074,"threshold_uncertainty_score":0.18350083},"labels":[],"label_agreement":null},{"id":"W2140782543","doi":"10.1109/tsmcb.2003.810909","title":"Benchmarking attribute cardinality maps for database systems using the tpc-d specifications","year":2003,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Benchmarking; Computer science; Cardinality (data modeling); Query optimization; Benchmark (surveying); Data mining; Database; Histogram; Set (abstract data type); Software; Relational database; Online aggregation; Information retrieval; Sargable; Search engine; Artificial intelligence; Programming language; Image (mathematics)","score_opus":0.08332196498803661,"score_gpt":0.2780936541775184,"score_spread":0.1947716891894818,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140782543","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":[0.10936564,0.0008601053,0.869294,0.0007029006,0.00018557177,0.00074201386,0.0031016886,0.008476021,0.007272073],"genre_scores_gemma":[0.5042811,0.00060656224,0.4872221,0.00024375148,0.000042360967,0.0006914437,0.0049843146,0.0006700306,0.0012582799],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.97716796,0.0049662055,0.0026806004,0.0012031205,0.013284147,0.00069801806],"domain_scores_gemma":[0.95134866,0.022191705,0.002269168,0.012298386,0.011213138,0.0006789648],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010617024,0.0009621424,0.00095701066,0.0024629862,0.00082598015,0.0038506966,0.0030954545,0.0013015103,0.0019581888],"category_scores_gemma":[0.06714927,0.00060900097,0.0010954823,0.0043833414,0.0011217267,0.0044887727,0.0024160957,0.0019307496,0.00063018274],"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":[0.0011958719,0.0004782397,0.02289551,0.0014850128,0.0001673063,0.0004715636,0.0007802523,0.51000446,0.024528984,0.11171377,0.014582045,0.31169695],"study_design_scores_gemma":[0.000055895125,0.0002982818,0.0027716924,0.000066638044,0.000028365062,0.00031244406,0.00028413648,0.94162846,0.026075019,0.013342896,0.015063035,0.00007326669],"about_ca_topic_score_codex":0.0105632795,"about_ca_topic_score_gemma":0.007830346,"teacher_disagreement_score":0.010617024,"about_ca_system_score_codex":0.0025279834,"about_ca_system_score_gemma":0.004057412,"threshold_uncertainty_score":0.056148827},"labels":[],"label_agreement":null},{"id":"W2140884424","doi":"10.1016/j.ic.2011.08.001","title":"Modelling concurrency with comtraces and generalized comtraces","year":2011,"lang":"en","type":"article","venue":"Information and Computation","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":17,"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; McMaster University","funders":"","keywords":"Concurrency; Algebraic number; Mathematics; Computer science; Algebra over a field; Order (exchange); Pure mathematics; Programming language; Mathematical analysis","score_opus":0.033065042588781735,"score_gpt":0.2357557416152679,"score_spread":0.20269069902648618,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140884424","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":[0.019777842,0.00058372784,0.9699423,0.0005409085,0.00017243347,0.00009379902,0.00009714787,0.00045428524,0.00833757],"genre_scores_gemma":[0.62774354,0.0010826292,0.34848168,0.00039471997,0.00042874264,0.0004715715,0.0003227689,0.0007220795,0.020352243],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99215525,0.0030075097,0.0007583883,0.000989655,0.0020636593,0.0010255642],"domain_scores_gemma":[0.9810488,0.010333962,0.0011567225,0.00520949,0.0014853858,0.0007656319],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00593775,0.0014975778,0.0016187053,0.001980664,0.001924177,0.0073703346,0.004178258,0.0029941353,0.009448541],"category_scores_gemma":[0.022151794,0.0017287049,0.0026970739,0.003343795,0.006154208,0.017712306,0.007698135,0.005363039,0.0010434536],"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":[0.000045915058,0.000017721899,0.00033398424,0.00005577323,0.000024701427,0.00017783637,0.00032207716,0.027177392,0.00056399574,0.9651257,0.00043006247,0.005724803],"study_design_scores_gemma":[0.000044174427,0.000028973118,0.000070846414,0.00003272019,0.00004611647,0.00017807321,0.00012920295,0.1518203,0.0015269121,0.8358615,0.010230089,0.00003106717],"about_ca_topic_score_codex":0.005368592,"about_ca_topic_score_gemma":0.0044606677,"teacher_disagreement_score":0.009448541,"about_ca_system_score_codex":0.0018465724,"about_ca_system_score_gemma":0.0026278682,"threshold_uncertainty_score":0.031608462},"labels":[],"label_agreement":null},{"id":"W2141449497","doi":"10.1145/1242572.1242718","title":"XML design for relational storage","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Engineering and Physical Sciences Research Council","keywords":"Computer science; XML database; Streaming XML; Efficient XML Interchange; XML validation; XML Schema Editor; Relational database; XML; Database; XML Schema (W3C); XML Signature; XML Encryption; Document Structure Description; Information retrieval; Programming language; World Wide Web","score_opus":0.051325670370409214,"score_gpt":0.2831053443575294,"score_spread":0.23177967398712016,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2141449497","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":[0.0029736746,0.0017337144,0.9759035,0.0014041708,0.00051563233,0.00020260854,0.00033910084,0.0026644827,0.014263153],"genre_scores_gemma":[0.09554106,0.0034323968,0.86226004,0.0019177902,0.0006967823,0.0007996827,0.0011351175,0.0013830547,0.032834087],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9954566,0.0012841591,0.000774958,0.00059064705,0.001629599,0.00026422276],"domain_scores_gemma":[0.9962399,0.0008437369,0.00032727182,0.0014281578,0.0010369726,0.00012386608],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00451425,0.0006903148,0.00054026826,0.0009895392,0.00090675923,0.0042706872,0.0018743353,0.0017177755,0.01019092],"category_scores_gemma":[0.008277722,0.00079898577,0.0009452799,0.0015248539,0.0019888452,0.0066887694,0.0022709344,0.0020795125,0.004816918],"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":[0.00006830606,0.000031189695,0.00023830771,0.00040447793,0.00002727292,0.0001938729,0.0004951072,0.0029025548,0.0054831053,0.8940146,0.013776594,0.08236456],"study_design_scores_gemma":[0.00008334898,0.00014199507,0.00016397458,0.00024788623,0.00008351297,0.0010022355,0.00020416667,0.024673227,0.01909423,0.41552696,0.5387234,0.000055071036],"about_ca_topic_score_codex":0.00082839327,"about_ca_topic_score_gemma":0.0009029679,"teacher_disagreement_score":0.01019092,"about_ca_system_score_codex":0.0011576738,"about_ca_system_score_gemma":0.0015643955,"threshold_uncertainty_score":0.03409207},"labels":[],"label_agreement":null},{"id":"W2141593784","doi":"10.1145/1559845.1559983","title":"Extreme visualisation of query optimizer search space","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Query optimization; Query by Example; SQL; Database; User-defined function; Heuristics; Sargable; Web search query; Data Transformation Services; Stored procedure; Materialized view; Data mining; Information retrieval; View; Search engine; Operating system; Database design","score_opus":0.04591244616557154,"score_gpt":0.2951833316837544,"score_spread":0.24927088551818283,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2141593784","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":[0.13356608,0.0008585889,0.7060009,0.0016766384,0.00021257476,0.0003830197,0.0073373765,0.12204159,0.02792318],"genre_scores_gemma":[0.5860554,0.00062164065,0.38755837,0.00046764634,0.00006840216,0.0004360573,0.005449045,0.009305134,0.010038341],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991093,0.00027175882,0.00006207918,0.00011242138,0.00035082147,0.00009355163],"domain_scores_gemma":[0.99681693,0.0020099385,0.00014632693,0.00047829273,0.0003761215,0.00017247743],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012083489,0.0009490733,0.0005035086,0.0011442417,0.000433284,0.0022432809,0.0008863494,0.0007486562,0.010831867],"category_scores_gemma":[0.004962306,0.00033164266,0.00060480763,0.00075588445,0.00057526655,0.0019050773,0.0022079044,0.0014801092,0.0020498997],"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":[0.0068279696,0.0009812847,0.021619415,0.0018327611,0.00025293525,0.0024135655,0.015510183,0.07907102,0.17951748,0.08105617,0.15688266,0.45403457],"study_design_scores_gemma":[0.00041299796,0.0008331326,0.016574007,0.00047143677,0.00009276618,0.0012820114,0.00228252,0.6366656,0.117697254,0.034095008,0.18925501,0.00033828642],"about_ca_topic_score_codex":0.0029056724,"about_ca_topic_score_gemma":0.0021871545,"teacher_disagreement_score":0.010831867,"about_ca_system_score_codex":0.00048940553,"about_ca_system_score_gemma":0.00065357133,"threshold_uncertainty_score":0.036236167},"labels":[],"label_agreement":null},{"id":"W2141686985","doi":"10.1109/wcre.2001.957840","title":"Reengineering relational databases to object-oriented: constructing the class hierarchy and migrating the data","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Database; Database design; Database model; View; Class hierarchy; Relational database; Database schema; Semi-structured model; Database theory; Database testing; Graph database; Database tuning; Intelligent database; Data modeling; Physical data model; Database application; Graph; Object-oriented programming; Theoretical computer science; Programming language","score_opus":0.06439534131519042,"score_gpt":0.26176176165861054,"score_spread":0.1973664203434201,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2141686985","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":[0.013824711,0.00095275574,0.9783921,0.0008921882,0.00015588103,0.00013084017,0.00006560987,0.0030252598,0.0025606076],"genre_scores_gemma":[0.054345623,0.0013929971,0.94007415,0.00064522994,0.00009060662,0.00008414225,0.00025438314,0.0006206462,0.002492225],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983669,0.000411607,0.00014628831,0.000302846,0.0006592947,0.00011309655],"domain_scores_gemma":[0.9965857,0.0010390058,0.0003692686,0.0012371715,0.0006138612,0.00015502895],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0043590986,0.00070201885,0.00062315725,0.0012733295,0.0011047943,0.004285188,0.0025093835,0.0013494394,0.0012946923],"category_scores_gemma":[0.0084334565,0.0011820636,0.0013733128,0.0020320273,0.002749061,0.009300078,0.0017507592,0.002718086,0.0009088225],"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":[0.00015540187,0.00022148632,0.0034166088,0.00086332357,0.0001144373,0.00067624566,0.009411472,0.013615063,0.023615474,0.34112835,0.010778015,0.5960042],"study_design_scores_gemma":[0.00015121565,0.00028428287,0.0036084275,0.00050843786,0.00027213368,0.0015794828,0.001798043,0.096982464,0.032443516,0.44767147,0.41448075,0.00021981762],"about_ca_topic_score_codex":0.00880474,"about_ca_topic_score_gemma":0.007756527,"teacher_disagreement_score":0.00880474,"about_ca_system_score_codex":0.0014217225,"about_ca_system_score_gemma":0.0021168997,"threshold_uncertainty_score":0.023053408},"labels":[],"label_agreement":null},{"id":"W2141724398","doi":"10.1007/s00778-005-0172-6","title":"Query optimization in XML structured-document databases","year":2006,"lang":"en","type":"article","venue":"The VLDB Journal","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":68,"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; XPath; Query optimization; XML validation; Streaming XML; XML database; Information retrieval; Efficient XML Interchange; Query language; XML Schema Editor; XML; Document Structure Description; Query expansion; XML Schema (W3C); XML Encryption; Database; World Wide Web","score_opus":0.010908030588630723,"score_gpt":0.2453907915984678,"score_spread":0.2344827610098371,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2141724398","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":[0.07426152,0.0032004528,0.91365445,0.0013961497,0.000089896275,0.0001939711,0.00054549065,0.0028661848,0.0037918577],"genre_scores_gemma":[0.5193705,0.0016108444,0.4709459,0.0004394113,0.00020996903,0.0002340623,0.0017308096,0.0006280487,0.0048304326],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9920763,0.002825018,0.00085380627,0.0008178975,0.002856656,0.00057040784],"domain_scores_gemma":[0.9919504,0.005921576,0.00039994888,0.0007658566,0.00076725293,0.00019508522],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0057584196,0.00077326,0.0022906784,0.0014092516,0.00082716235,0.0037445151,0.002465655,0.0011750584,0.0025671904],"category_scores_gemma":[0.011878716,0.0009052192,0.0010910622,0.0037075875,0.0011757397,0.004623153,0.0018600782,0.0014502599,0.00059947046],"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":[0.002366523,0.0007564998,0.004721431,0.0012276646,0.0003110024,0.0006014063,0.00068351725,0.47872564,0.016563386,0.09702289,0.01998481,0.37703517],"study_design_scores_gemma":[0.0001190887,0.0001382344,0.0004603981,0.00002353141,0.000070889284,0.00018959238,0.00018894006,0.94159514,0.007931672,0.046109997,0.003148252,0.000024287943],"about_ca_topic_score_codex":0.0039854944,"about_ca_topic_score_gemma":0.0037701086,"teacher_disagreement_score":0.0057584196,"about_ca_system_score_codex":0.0015027511,"about_ca_system_score_gemma":0.0015439366,"threshold_uncertainty_score":0.030453801},"labels":[],"label_agreement":null},{"id":"W2141938776","doi":"10.1109/icde.2008.4497498","title":"An Efficient Algorithm for Answering Graph Reachability Queries","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":114,"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 Winnipeg","funders":"","keywords":"Reachability; Transitive reduction; Computer science; Directed acyclic graph; Directed graph; Transitive closure; Disjoint sets; Graph; Path (computing); Recursion (computer science); Node (physics); Combinatorics; Algorithm; Theoretical computer science; Discrete mathematics; Mathematics; Line graph; Programming language; Voltage graph","score_opus":0.019582247826646162,"score_gpt":0.2629155023223645,"score_spread":0.24333325449571833,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2141938776","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":[0.008445848,0.00051582116,0.95381504,0.0008324115,0.00011195627,0.0007125743,0.0029438955,0.025774501,0.00684788],"genre_scores_gemma":[0.07144063,0.00030817158,0.91424346,0.0004022663,0.00007452185,0.00067110587,0.007651062,0.0007903214,0.0044185114],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974993,0.0004685113,0.00024911866,0.0008416748,0.00062288606,0.0003184894],"domain_scores_gemma":[0.99666256,0.0019390653,0.00019187001,0.00062761613,0.00047903752,0.00009983328],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014771115,0.002419302,0.0013562539,0.003156043,0.0017065826,0.0034741675,0.0036307632,0.002853001,0.017881619],"category_scores_gemma":[0.0063893744,0.0011613226,0.002206046,0.0038182593,0.0009835196,0.0073282365,0.0028908344,0.0019939572,0.007805464],"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":[0.0008975562,0.0008056268,0.002072705,0.0011937089,0.00020008837,0.0003361877,0.00049124827,0.045001563,0.023532454,0.055520646,0.07131969,0.7986286],"study_design_scores_gemma":[0.0005707405,0.00029769287,0.0009107048,0.0001165293,0.0001541291,0.0006084993,0.0004901491,0.7687427,0.018299043,0.16384001,0.045848448,0.000121403216],"about_ca_topic_score_codex":0.0066406913,"about_ca_topic_score_gemma":0.011408337,"teacher_disagreement_score":0.017881619,"about_ca_system_score_codex":0.0024141795,"about_ca_system_score_gemma":0.0038916902,"threshold_uncertainty_score":0.059819996},"labels":[],"label_agreement":null},{"id":"W2142180115","doi":"10.1504/ijica.2008.019686","title":"A bottom-up algorithm for query decomposition","year":2008,"lang":"en","type":"article","venue":"International Journal of Innovative Computing and Applications","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; XPath; Schema (genetic algorithms); Path expression; Path (computing); XML; Algorithm; Query language; Tree (set theory); Materialized view; Query optimization; Decomposition; Set (abstract data type); Theoretical computer science; Data mining; Information retrieval; View; Programming language; XML database; Mathematics","score_opus":0.02080659436761335,"score_gpt":0.3354928541037452,"score_spread":0.31468625973613185,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2142180115","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":[0.0017600108,0.00016875289,0.9905177,0.00011761093,0.000049990984,0.00025217567,0.00016353486,0.0055137044,0.0014565609],"genre_scores_gemma":[0.021759814,0.000112374546,0.9738564,0.00014056869,0.00002727508,0.00021829274,0.00086926215,0.00060688535,0.0024090349],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99716777,0.00040068864,0.00029256273,0.0007695721,0.0009914889,0.00037788216],"domain_scores_gemma":[0.9980825,0.00046640748,0.000070622395,0.0005764369,0.0007274202,0.00007651774],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014224064,0.002104257,0.0014404771,0.0024627282,0.0015222621,0.0026083244,0.002268767,0.0015155937,0.014656037],"category_scores_gemma":[0.0037589872,0.00090028846,0.0019335587,0.0026321546,0.0009157778,0.0030744795,0.003560756,0.0027129257,0.007579533],"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":[0.0003644737,0.00025762766,0.0007761703,0.00037706463,0.00010149525,0.00018167558,0.00033834978,0.016409937,0.02900087,0.018213656,0.030830523,0.9031482],"study_design_scores_gemma":[0.00024326611,0.00026939486,0.0008627552,0.00011469016,0.00022342478,0.0009487438,0.00047253832,0.7893246,0.055580672,0.06593281,0.08589439,0.00013266156],"about_ca_topic_score_codex":0.0044349483,"about_ca_topic_score_gemma":0.004947359,"teacher_disagreement_score":0.014656037,"about_ca_system_score_codex":0.0011483195,"about_ca_system_score_gemma":0.002551655,"threshold_uncertainty_score":0.04902935},"labels":[],"label_agreement":null},{"id":"W2142448367","doi":"10.1109/ccece.1999.804972","title":"On data and probabilistic dependencies","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":14,"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 Regina","funders":"","keywords":"Functional dependency; Dependency (UML); Probabilistic logic; Conditional independence; Dependency theory (database theory); Normalization (sociology); Independence (probability theory); Computer science; Theoretical computer science; Relational database; Relational model; Artificial intelligence; Data mining; Mathematics; Statistics","score_opus":0.036654859151637985,"score_gpt":0.26636363187960876,"score_spread":0.22970877272797077,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2142448367","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":[0.014150932,0.008497234,0.91190684,0.012739211,0.0006124573,0.00008136697,0.0011171087,0.00032213438,0.050572857],"genre_scores_gemma":[0.6909549,0.022343807,0.2352394,0.0072864173,0.007834466,0.0006938464,0.0030198765,0.0007734114,0.031853832],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99159837,0.002720121,0.00062107097,0.0015334617,0.002959942,0.0005670328],"domain_scores_gemma":[0.95062846,0.036971625,0.002265606,0.0059718443,0.0033929558,0.000769527],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008465308,0.001131149,0.0013238639,0.0032145905,0.002472135,0.0050240164,0.0018146461,0.0028942863,0.008608277],"category_scores_gemma":[0.04104342,0.0012319947,0.0015921504,0.0051827827,0.007831887,0.02060283,0.005526117,0.004848296,0.0015759794],"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":[0.000020970454,0.000010640006,0.0004998424,0.00007778424,0.000018860103,0.00015978047,0.00017286064,0.004651367,0.0001871709,0.9803049,0.0025756785,0.011320284],"study_design_scores_gemma":[0.0000074016566,0.000009057333,0.00026332014,0.00004925972,0.000017534756,0.00027301357,0.00003502918,0.012725234,0.00026166392,0.9691019,0.017241443,0.000015223916],"about_ca_topic_score_codex":0.0036420636,"about_ca_topic_score_gemma":0.002271077,"teacher_disagreement_score":0.008608277,"about_ca_system_score_codex":0.0026823923,"about_ca_system_score_gemma":0.0018711016,"threshold_uncertainty_score":0.044769347},"labels":[],"label_agreement":null},{"id":"W2142712680","doi":"10.1109/icde.2009.124","title":"Join Reordering by Join Simulation","year":2009,"lang":"en","type":"article","venue":"Proceedings - International Conference on Data Engineering","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Join (topology); Computer science; Pipeline (software); Pipeline transport; Cardinality (data modeling); Parallel computing; Path (computing); Distributed computing; Data mining; Programming language","score_opus":0.05346340745751707,"score_gpt":0.3007754703162046,"score_spread":0.24731206285868754,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2142712680","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":[0.012422465,0.00009873167,0.9832145,0.00009404748,0.000027646849,0.0001190586,0.00012842489,0.002958275,0.0009368641],"genre_scores_gemma":[0.27579206,0.00018445497,0.7207123,0.00010361621,0.000052433672,0.00035435308,0.0005678731,0.0008067626,0.0014261483],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99577445,0.0013872681,0.00027814723,0.00062359526,0.0015892158,0.00034729298],"domain_scores_gemma":[0.98915905,0.0057743145,0.0007799355,0.0027923987,0.001149935,0.00034439797],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00515966,0.000958153,0.0012618707,0.0012543866,0.0009943779,0.002208371,0.0034046713,0.0012649941,0.0029572784],"category_scores_gemma":[0.016445676,0.0010311853,0.0016155167,0.0011253646,0.0010469566,0.003030917,0.00219982,0.0023981598,0.0006160041],"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":[0.00022835928,0.00010826555,0.0028965739,0.000085385436,0.00007885708,0.00009723232,0.00022692361,0.9101412,0.0059387633,0.03723746,0.0017097995,0.04125111],"study_design_scores_gemma":[0.000014178364,0.000028374243,0.00008370506,0.0000046104874,0.000009129489,0.000020758862,0.0000096687945,0.98944104,0.0019144628,0.006699363,0.0017633704,0.00001135295],"about_ca_topic_score_codex":0.0075051165,"about_ca_topic_score_gemma":0.0070400224,"teacher_disagreement_score":0.0075051165,"about_ca_system_score_codex":0.0013147164,"about_ca_system_score_gemma":0.0031291246,"threshold_uncertainty_score":0.027287245},"labels":[],"label_agreement":null},{"id":"W2143259408","doi":"10.1109/ideas.1999.787294","title":"An implementation architecture for orthogonally persistent deductive object-oriented database systems","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Common Object Request Broker Architecture; Computer science; Deductive database; Programming language; Object (grammar); Architecture; Class (philosophy); Component (thermodynamics); Database theory; Systems architecture; Database; Database design; Artificial intelligence","score_opus":0.01736245672579342,"score_gpt":0.2974764993681117,"score_spread":0.2801140426423183,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2143259408","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":[0.010505421,0.00012061456,0.9800679,0.00046062152,0.000058826245,0.00010814892,0.000034348468,0.005702625,0.002941405],"genre_scores_gemma":[0.14200357,0.0003320507,0.8497934,0.000324532,0.00006518312,0.00021178993,0.00023781681,0.00031167435,0.006719857],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99855906,0.00029922402,0.0002202629,0.00019436947,0.00058344577,0.00014377876],"domain_scores_gemma":[0.9980262,0.00026669566,0.00019384046,0.0007143339,0.00066341023,0.00013558015],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023344595,0.0002301852,0.00030932325,0.0007617863,0.00074135215,0.003485714,0.0021065832,0.000945547,0.0023805788],"category_scores_gemma":[0.0030442248,0.00056867214,0.0004897721,0.00058100384,0.0009772466,0.0035291337,0.0017392185,0.0012615421,0.0012770857],"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":[0.00030942756,0.00047077233,0.0037713614,0.000434765,0.00008590215,0.0007703969,0.0019837765,0.017239284,0.05850812,0.51352775,0.011437986,0.39146045],"study_design_scores_gemma":[0.0003989149,0.00078944745,0.0016565609,0.00022905374,0.00033491114,0.0022372778,0.00061992137,0.45432195,0.0846764,0.16535833,0.28917345,0.00020376386],"about_ca_topic_score_codex":0.001396732,"about_ca_topic_score_gemma":0.001443149,"teacher_disagreement_score":0.003485714,"about_ca_system_score_codex":0.00091195485,"about_ca_system_score_gemma":0.0016965088,"threshold_uncertainty_score":0.01234597},"labels":[],"label_agreement":null},{"id":"W2143706788","doi":"10.1145/2274576.2274599","title":"Representation systems for data exchange","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Homomorphic encryption; Equivalence (formal languages); Data exchange; Computer science; Representation (politics); Theoretical computer science; External Data Representation; Modulo; Context (archaeology); Monotone polygon; Algebra over a field; Mathematics; Discrete mathematics; Pure mathematics; Artificial intelligence; Database; Encryption","score_opus":0.15582514046075766,"score_gpt":0.3610786037345052,"score_spread":0.20525346327374752,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2143706788","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":[0.0038439678,0.007953917,0.88138884,0.007921019,0.0010536223,0.00021687442,0.00050489826,0.001059858,0.096057005],"genre_scores_gemma":[0.31686613,0.011859174,0.6075629,0.004280315,0.003237007,0.0011813544,0.0023938108,0.00073083135,0.05188859],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99262816,0.002762808,0.00079968025,0.001272527,0.0019531163,0.0005837154],"domain_scores_gemma":[0.99500567,0.0019775217,0.00032078518,0.0015972219,0.00085595675,0.00024292915],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006617957,0.0010744414,0.001134919,0.002707142,0.0028532872,0.010460637,0.002058914,0.003440276,0.012786522],"category_scores_gemma":[0.009654119,0.0007319305,0.0019119049,0.004013058,0.008599032,0.020406581,0.0079828305,0.006328979,0.0034208484],"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":[0.0000037366244,0.0000034967156,0.000017944336,0.000025595173,0.000003092472,0.00001846234,0.00011572543,0.00026568325,0.00008282577,0.9941246,0.0011466722,0.0041921535],"study_design_scores_gemma":[0.000010166912,0.0000084381,0.00002433075,0.00004229573,0.0000067312526,0.000098667995,0.00007054982,0.0026971502,0.00024275554,0.9374024,0.059385967,0.000010460724],"about_ca_topic_score_codex":0.0023718432,"about_ca_topic_score_gemma":0.0011080925,"teacher_disagreement_score":0.012786522,"about_ca_system_score_codex":0.0037640296,"about_ca_system_score_gemma":0.002523777,"threshold_uncertainty_score":0.042775154},"labels":[],"label_agreement":null},{"id":"W2144006311","doi":"","title":"MIX: a meta-data indexing system for XML","year":2005,"lang":"en","type":"article","venue":"Very Large Data Bases","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"XPath; Computer science; XML database; Information retrieval; Streaming XML; XML validation; Efficient XML Interchange; XML Encryption; Document Structure Description; XML Schema (W3C); Database; XML Schema Editor; Search engine indexing; Simple API for XML; XML Signature; XML; Data mining; World Wide Web","score_opus":0.1406926542850825,"score_gpt":0.32553850099715964,"score_spread":0.18484584671207713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2144006311","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":[0.0071364837,0.0010771449,0.83837867,0.00040318322,0.00017698982,0.00035672632,0.0048828973,0.13935123,0.008236703],"genre_scores_gemma":[0.11146884,0.0012670263,0.8288536,0.0011669444,0.00041755583,0.0012515475,0.023518326,0.013148443,0.018907692],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9974757,0.0003117606,0.00035413625,0.00038783601,0.0013289327,0.00014172807],"domain_scores_gemma":[0.9976005,0.0005757527,0.00022352955,0.0010214783,0.00036101014,0.00021764527],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027528284,0.00096826785,0.0011809561,0.0033249378,0.0010659483,0.005422274,0.0035735455,0.0013044184,0.011839228],"category_scores_gemma":[0.0055264076,0.0012455905,0.0010675524,0.0034969887,0.0009825493,0.009650578,0.005644654,0.0022196053,0.0073918975],"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":[0.0020765746,0.00030258863,0.0053681172,0.001578296,0.0003509223,0.00061815087,0.0015276207,0.007286623,0.0719251,0.12301332,0.14867045,0.63728225],"study_design_scores_gemma":[0.00047873362,0.00043897418,0.0020279125,0.0002882265,0.00030523227,0.0015711854,0.0003870929,0.14924979,0.13529475,0.08170447,0.62792546,0.00032829287],"about_ca_topic_score_codex":0.0013402937,"about_ca_topic_score_gemma":0.0012619777,"teacher_disagreement_score":0.011839228,"about_ca_system_score_codex":0.0012417039,"about_ca_system_score_gemma":0.0014229247,"threshold_uncertainty_score":0.039606214},"labels":[],"label_agreement":null},{"id":"W2144365146","doi":"10.1109/sew.2003.1270721","title":"Establishing a generic and multidimensional measurement repository in CMMI context","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"École de Technologie Supérieure","funders":"Division of Civil, Mechanical and Manufacturing Innovation","keywords":"Online analytical processing; Capability Maturity Model Integration; Data warehouse; Computer science; Context (archaeology); Database; LeanCMMI; Process (computing); Operating system","score_opus":0.023873379672974877,"score_gpt":0.2159877245942047,"score_spread":0.19211434492122983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2144365146","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":[0.013310549,0.00060566684,0.9730242,0.0016493135,0.00015769295,0.00076434336,0.0010376232,0.00692038,0.0025301646],"genre_scores_gemma":[0.066024736,0.0004852906,0.9272806,0.00030832124,0.00013178909,0.0007238336,0.0036039928,0.00044902143,0.0009924005],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9717638,0.0062953234,0.007342087,0.004187986,0.0087747285,0.001636113],"domain_scores_gemma":[0.9370118,0.0073102666,0.009363497,0.02828176,0.015245724,0.0027869018],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.031251367,0.001316554,0.0026796486,0.009644495,0.0024217993,0.01474586,0.006976328,0.0036412834,0.0016070396],"category_scores_gemma":[0.044382416,0.0016006144,0.0019517925,0.015029443,0.002196862,0.019639336,0.0104435235,0.0047348207,0.0015390489],"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":[0.0003962896,0.00091773126,0.048442654,0.0021750114,0.00050969026,0.0020420905,0.00639852,0.038916674,0.02721769,0.29971552,0.028458295,0.54481],"study_design_scores_gemma":[0.00027001163,0.00094739307,0.022735473,0.00253015,0.00077334954,0.004546767,0.0057779066,0.30336297,0.087382756,0.12898342,0.4414778,0.0012119793],"about_ca_topic_score_codex":0.0042117042,"about_ca_topic_score_gemma":0.0036438275,"teacher_disagreement_score":0.031251367,"about_ca_system_score_codex":0.003241551,"about_ca_system_score_gemma":0.00846996,"threshold_uncertainty_score":0.16527504},"labels":[],"label_agreement":null},{"id":"W2144447931","doi":"10.1109/tsmca.2005.843385","title":"Multiagent Immediate Incremental View Maintenance for Data Warehouses","year":2005,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Downtime; Data warehouse; Computer science; Consistency (knowledge bases); Delegate; Database; Process (computing); Materialized view; Operating system; Database design; Artificial intelligence","score_opus":0.054538002670355884,"score_gpt":0.28054976413761434,"score_spread":0.22601176146725846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2144447931","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":[0.08468279,0.000366755,0.90883666,0.00019426842,0.000057031422,0.00011475234,0.000055558863,0.0038872364,0.0018049085],"genre_scores_gemma":[0.70515513,0.00010048641,0.2925672,0.000057741647,0.000036405705,0.000088507004,0.00021024009,0.00014885057,0.0016353752],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998978,0.00024936974,0.00008144404,0.0002174776,0.00039575694,0.00007800999],"domain_scores_gemma":[0.9966185,0.0009611543,0.00048527707,0.0011552796,0.00057800714,0.00020165331],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013108156,0.0004156338,0.00041251545,0.00045268357,0.0006307055,0.0010821832,0.0018049859,0.0005232602,0.0008954966],"category_scores_gemma":[0.0047311797,0.00038585975,0.00036691767,0.00037159066,0.00043007798,0.0015408817,0.0013346488,0.00089645915,0.00029938135],"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":[0.0008770362,0.00062353275,0.00926239,0.0003424889,0.0002241864,0.0010996276,0.0010576005,0.27520204,0.115357995,0.024366515,0.008888253,0.56269836],"study_design_scores_gemma":[0.00006416622,0.00016923808,0.0013583737,0.000010132691,0.00004974494,0.00026358274,0.000064354484,0.9607043,0.025645727,0.005052959,0.006591366,0.000026089441],"about_ca_topic_score_codex":0.002316715,"about_ca_topic_score_gemma":0.0020074656,"teacher_disagreement_score":0.002316715,"about_ca_system_score_codex":0.00046829213,"about_ca_system_score_gemma":0.0005039741,"threshold_uncertainty_score":0.006932318},"labels":[],"label_agreement":null},{"id":"W2144581296","doi":"10.1109/hicss.2004.1265517","title":"Top-down computation of partial ROLAP data cubes","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; Carleton University","funders":"","keywords":"Online analytical processing; Data cube; Cube (algebra); Computation; Computer science; Precomputation; Algorithm; Theoretical computer science; Data warehouse; Data mining; Mathematics; Combinatorics","score_opus":0.036283537338202415,"score_gpt":0.2980136842146807,"score_spread":0.26173014687647833,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2144581296","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":[0.10082659,0.00034653654,0.88848794,0.00024085907,0.000064551816,0.00010645433,0.000701941,0.0055395635,0.0036856923],"genre_scores_gemma":[0.29889894,0.0002834794,0.695204,0.000120774275,0.000036053425,0.000164894,0.0023557502,0.0004108131,0.002525219],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99891615,0.0001671855,0.00008000073,0.00020033258,0.00048311215,0.00015316746],"domain_scores_gemma":[0.9976326,0.0008783173,0.00012944362,0.00063618325,0.00062357495,0.00009998984],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005904194,0.00084159157,0.0012161857,0.00068155164,0.00075419183,0.00162256,0.0014055321,0.00045080372,0.0027221888],"category_scores_gemma":[0.0033877222,0.0005022618,0.0009826523,0.0013399178,0.0007405854,0.002483153,0.0022596258,0.00073706004,0.0007759192],"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":[0.0011510884,0.00018756159,0.005112068,0.00065444456,0.00015953725,0.0006300662,0.00054031337,0.279727,0.08990584,0.021366112,0.019613562,0.5809524],"study_design_scores_gemma":[0.00004950667,0.00010635571,0.0006251718,0.000011489429,0.000031239368,0.00018508511,0.00015455918,0.9354682,0.04161565,0.015886722,0.0058418126,0.00002415903],"about_ca_topic_score_codex":0.005057982,"about_ca_topic_score_gemma":0.0073667914,"teacher_disagreement_score":0.005057982,"about_ca_system_score_codex":0.0005467536,"about_ca_system_score_gemma":0.0013359751,"threshold_uncertainty_score":0.010057092},"labels":[],"label_agreement":null},{"id":"W2144878221","doi":"","title":"Information preserving XML schema embedding","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bell (Canada)","funders":"","keywords":"Computer science; Document Structure Description; Embedding; XML Schema Editor; Information retrieval; RELAX NG; Schema (genetic algorithms); XML validation; XML; Document type definition; Star schema; Theoretical computer science; Artificial intelligence; World Wide Web","score_opus":0.00999603264537603,"score_gpt":0.2580510352798227,"score_spread":0.2480550026344467,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2144878221","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":[0.019383239,0.000500613,0.9740684,0.00031431013,0.000057025783,0.00014949142,0.00048895477,0.001561443,0.0034764593],"genre_scores_gemma":[0.21690644,0.0007762916,0.7767872,0.00021034986,0.00003916916,0.00013614925,0.0017253648,0.0002835725,0.003135518],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9974953,0.0008307732,0.000316912,0.0005286102,0.0006927205,0.00013570474],"domain_scores_gemma":[0.99444383,0.0016457757,0.00049606425,0.0026661223,0.0006478943,0.00010024954],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020550955,0.00065044046,0.0007741897,0.0013858863,0.00063770707,0.002001538,0.0015942977,0.0010133199,0.002111387],"category_scores_gemma":[0.009511841,0.00052023056,0.0011079225,0.0032886548,0.00087588903,0.0056916196,0.002952947,0.0014524956,0.0008824932],"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":[0.00029123013,0.0002675926,0.0022601327,0.0008272329,0.00015120993,0.0006470182,0.0010018084,0.06600201,0.026901672,0.22051375,0.009372664,0.6717636],"study_design_scores_gemma":[0.000098194345,0.00035476914,0.0010071228,0.00018058621,0.00023023147,0.0025769963,0.0009070824,0.3986055,0.1045687,0.397508,0.093885124,0.00007770427],"about_ca_topic_score_codex":0.0005051447,"about_ca_topic_score_gemma":0.00067005004,"teacher_disagreement_score":0.002111387,"about_ca_system_score_codex":0.0005012278,"about_ca_system_score_gemma":0.0009122707,"threshold_uncertainty_score":0.01086849},"labels":[],"label_agreement":null},{"id":"W2145067130","doi":"10.5555/1182635.1164147","title":"Using partial evaluation in distributed query evaluation","year":2006,"lang":"en","type":"article","venue":"Edinburgh Research Explorer (University of Edinburgh)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":57,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bell (Canada)","funders":"","keywords":"XPath; Computer science; Query optimization; XML; Computation; Tree (set theory); Data mining; Key (lock); Theoretical computer science; Sargable; Simple (philosophy); Range query (database); Query language; Distributed computing; Information retrieval; Algorithm; Web search query; XML database; Search engine; Mathematics","score_opus":0.1980289050009966,"score_gpt":0.3749218103564734,"score_spread":0.17689290535547678,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2145067130","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":[0.013611354,0.00054846535,0.98015916,0.00019962623,0.000037874142,0.00012034611,0.000052470732,0.0016004242,0.003670174],"genre_scores_gemma":[0.44456902,0.00072299986,0.5491182,0.0002325954,0.00011559759,0.00043402647,0.0002701179,0.0006915812,0.0038458265],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99376255,0.002573984,0.00039583666,0.0006870729,0.0021859063,0.00039467867],"domain_scores_gemma":[0.98965424,0.0056167506,0.00041536038,0.0027714763,0.0013573274,0.00018490547],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0056842547,0.00089889555,0.0014016931,0.00089694356,0.0009839353,0.003113167,0.0017136086,0.0007048347,0.00305343],"category_scores_gemma":[0.015156274,0.0007594812,0.0008204119,0.0017844874,0.0027735601,0.0062286993,0.0036670784,0.0013870748,0.0007212496],"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":[0.0011976265,0.0001643551,0.0035447737,0.0008956517,0.00017285183,0.00053036975,0.0015308092,0.20457263,0.016255468,0.23041458,0.0075051957,0.5332157],"study_design_scores_gemma":[0.0001989524,0.00042431647,0.0007837109,0.00012880245,0.00021354717,0.0005771061,0.00026855848,0.6991278,0.030135088,0.24139875,0.026659934,0.00008346899],"about_ca_topic_score_codex":0.00300902,"about_ca_topic_score_gemma":0.0028405585,"teacher_disagreement_score":0.0056842547,"about_ca_system_score_codex":0.0012814886,"about_ca_system_score_gemma":0.0014380731,"threshold_uncertainty_score":0.030061603},"labels":[],"label_agreement":null},{"id":"W2145186067","doi":"10.1109/icde.2004.1319984","title":"A succinct physical storage scheme for efficient evaluation of path queries in XML","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":89,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"University of Waterloo","keywords":"Computer science; XML; Path (computing); Scheme (mathematics); Node (physics); Matching (statistics); Pattern matching; XML Signature; Streaming XML; XML database; Efficient XML Interchange; Path expression; Theoretical computer science; Computer network; Programming language; World Wide Web; Mathematics","score_opus":0.02695081419634111,"score_gpt":0.3079136312393318,"score_spread":0.2809628170429907,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2145186067","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":[0.017568132,0.00037895283,0.97255516,0.00029965802,0.000101581405,0.00032955152,0.00065840856,0.006519426,0.0015891006],"genre_scores_gemma":[0.25572732,0.0004847427,0.7353608,0.00026844276,0.000129539,0.0005350947,0.002294761,0.0006401219,0.0045591593],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9972868,0.00049446186,0.00055481924,0.00033031282,0.0011791473,0.00015448044],"domain_scores_gemma":[0.99239606,0.0016124399,0.00066822267,0.004005476,0.0011096043,0.00020829072],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030363149,0.00076044665,0.0010460344,0.0013835008,0.0011554335,0.003270087,0.002980806,0.0009165098,0.0069447816],"category_scores_gemma":[0.010485677,0.00089579524,0.00044760166,0.0027396155,0.0013926724,0.009303127,0.0043222946,0.0011648334,0.0025833861],"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":[0.0020782736,0.00040448803,0.004335567,0.0009694136,0.000119550474,0.0005535581,0.001021486,0.040460967,0.09574604,0.14462793,0.031743627,0.6779391],"study_design_scores_gemma":[0.00053969445,0.0010704153,0.0023355891,0.00019967,0.00016714953,0.0024000858,0.00050562515,0.6764875,0.14351477,0.08481657,0.08758548,0.00037740506],"about_ca_topic_score_codex":0.0014221923,"about_ca_topic_score_gemma":0.001694017,"teacher_disagreement_score":0.0069447816,"about_ca_system_score_codex":0.0013243449,"about_ca_system_score_gemma":0.0020341072,"threshold_uncertainty_score":0.02323258},"labels":[],"label_agreement":null},{"id":"W2145409380","doi":"10.1109/icdt.2007.54","title":"Fast Archiving and Querying of Heterogeneous Sensor Data Streams","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Computer science; Bitmap; Data stream mining; Streaming data; Schema (genetic algorithms); Architecture; Throughput; Database; Distributed computing; Data mining; Operating system; Information retrieval; Computer graphics (images); Wireless","score_opus":0.030104291097979626,"score_gpt":0.2805378165977236,"score_spread":0.25043352549974396,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2145409380","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":[0.042923436,0.0005402153,0.9496296,0.0002186168,0.00009673678,0.00012254395,0.00036674656,0.0048190667,0.0012830154],"genre_scores_gemma":[0.35701534,0.000959556,0.6368648,0.00014609932,0.0001556577,0.00024060707,0.0020979696,0.00042120484,0.0020987464],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99904186,0.000118336975,0.0000920413,0.00014900703,0.000523797,0.00007493417],"domain_scores_gemma":[0.99709404,0.0008335287,0.00019607325,0.0010370997,0.00071071665,0.00012850303],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021158503,0.00072255335,0.0011844983,0.0019630054,0.00080906786,0.0029600621,0.0020361769,0.0007659653,0.0012200397],"category_scores_gemma":[0.006390279,0.0005255332,0.00046334811,0.0026231832,0.0005961663,0.0038553323,0.0018887087,0.001094202,0.0005895796],"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":[0.0016250382,0.000404444,0.008416421,0.0004904641,0.00029532018,0.0008292387,0.0014870621,0.07464799,0.24910031,0.036980376,0.016881613,0.60884166],"study_design_scores_gemma":[0.00012279871,0.0002850609,0.0025546604,0.00004377153,0.000112067835,0.00072383246,0.00040831434,0.771105,0.18151018,0.02465493,0.018378668,0.00010075784],"about_ca_topic_score_codex":0.0014304671,"about_ca_topic_score_gemma":0.0017531158,"teacher_disagreement_score":0.0029600621,"about_ca_system_score_codex":0.00045633267,"about_ca_system_score_gemma":0.0008176639,"threshold_uncertainty_score":0.011189818},"labels":[],"label_agreement":null},{"id":"W2145832235","doi":"10.1007/s10844-009-0091-x","title":"Queries with CASE expressions","year":2009,"lang":"en","type":"article","venue":"Journal of Intelligent Information Systems","topic":"Advanced Database Systems and Queries","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":"IBM (Canada); York University","funders":"","keywords":"Computer science; Query optimization; Expression (computer science); Information retrieval; Query language; Programming language","score_opus":0.013603735311779582,"score_gpt":0.25054809044073434,"score_spread":0.23694435512895476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2145832235","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":[0.02303825,0.0020979105,0.7850337,0.008074305,0.0010578586,0.0006833853,0.006843672,0.013721901,0.15944901],"genre_scores_gemma":[0.43203074,0.0029146473,0.4307539,0.0033593727,0.0015406202,0.00056744425,0.0199601,0.005545006,0.10332813],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9876057,0.003231396,0.0015133857,0.0017662048,0.0049406635,0.0009427056],"domain_scores_gemma":[0.9914185,0.0044212677,0.00038372562,0.0021180522,0.0013947538,0.00026373705],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00506111,0.001353608,0.0013624759,0.0031329542,0.0020057715,0.008830975,0.002350362,0.0024274637,0.038323008],"category_scores_gemma":[0.022671308,0.0014201378,0.001832301,0.0036506925,0.002595038,0.018270006,0.0056478716,0.003127883,0.011892426],"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":[0.0005578013,0.00017637621,0.00199807,0.00042285945,0.000090832094,0.0013917629,0.0016151593,0.0026379328,0.00563488,0.7731026,0.07760647,0.13476539],"study_design_scores_gemma":[0.00010555001,0.00005424003,0.00045248095,0.00016774733,0.00015999329,0.0019773047,0.0007826188,0.03248085,0.014242185,0.5918359,0.3576426,0.00009856393],"about_ca_topic_score_codex":0.0023663535,"about_ca_topic_score_gemma":0.0016635259,"teacher_disagreement_score":0.038323008,"about_ca_system_score_codex":0.0017115329,"about_ca_system_score_gemma":0.0014312555,"threshold_uncertainty_score":0.12820327},"labels":[],"label_agreement":null},{"id":"W2146021203","doi":"10.1109/ssdbm.2006.31","title":"InterJoin: Exploiting Indexes and Materialized Views in XPath Evaluation","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"XPath; Computer science; XML database; Information retrieval; Streaming XML; XML; Materialized view; Implementation; Query optimization; Simple API for XML; XML Schema (W3C); Path expression; XML validation; Exploit; Query language; Database; Data mining; Efficient XML Interchange; Programming language; XML Encryption; XML Signature; View; World Wide Web","score_opus":0.030211426833116888,"score_gpt":0.2796308239724061,"score_spread":0.24941939713928918,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2146021203","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":[0.018173803,0.00044338917,0.97299755,0.00011575298,0.000042309013,0.000119429424,0.00017682064,0.0055404836,0.0023904708],"genre_scores_gemma":[0.22145869,0.00047225857,0.7711767,0.00017551117,0.00007709236,0.00022241498,0.0012122091,0.0019783082,0.003226843],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99576867,0.00075258693,0.0003397783,0.00053491804,0.002335352,0.00026869038],"domain_scores_gemma":[0.9971208,0.0012104755,0.00021229731,0.0008167091,0.0005352114,0.00010444473],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030098842,0.00083673635,0.0006932492,0.0011547441,0.0005108224,0.003200575,0.0019579495,0.0007737804,0.0028148768],"category_scores_gemma":[0.0059874943,0.00066544826,0.0011305091,0.001294532,0.0011061587,0.0054114354,0.0026400818,0.001343463,0.0007237901],"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":[0.0013788412,0.00034691163,0.0062799407,0.0005887821,0.00024271608,0.00063836516,0.0013099553,0.099683866,0.10225544,0.15343441,0.015425885,0.6184149],"study_design_scores_gemma":[0.0002099536,0.0005035978,0.0013404905,0.000082193925,0.00011390794,0.0005843123,0.00028983835,0.7441725,0.14580631,0.06607837,0.040693063,0.00012547057],"about_ca_topic_score_codex":0.0025063965,"about_ca_topic_score_gemma":0.0026902528,"teacher_disagreement_score":0.003200575,"about_ca_system_score_codex":0.0008722628,"about_ca_system_score_gemma":0.0013010665,"threshold_uncertainty_score":0.015917957},"labels":[],"label_agreement":null},{"id":"W2146512991","doi":"10.1109/cmpsac.1979.762528","title":"Use of abstracted characteristics of data in relational databases","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Relational database; Database; Tuple; Information retrieval; Relational database management system; Database design; Relational model; Field (mathematics); Data retrieval; Interface (matter); Functional dependency; Data mining","score_opus":0.14087897639927394,"score_gpt":0.31579438479803124,"score_spread":0.1749154083987573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2146512991","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":[0.011054998,0.0022842493,0.9813737,0.00044622988,0.00015152889,0.00012081004,0.00055992376,0.0012825978,0.0027259195],"genre_scores_gemma":[0.2156339,0.0037097184,0.7754189,0.00045493816,0.00028922592,0.000337291,0.00158434,0.0005512335,0.0020204582],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99218494,0.0020646106,0.0011543925,0.0012701969,0.0030474085,0.00027845593],"domain_scores_gemma":[0.9833761,0.00713979,0.0018671796,0.0056448425,0.0015860428,0.00038601973],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004651175,0.0006661494,0.0011951359,0.0035202575,0.0009578787,0.0074256524,0.0020966658,0.0010744066,0.0016532046],"category_scores_gemma":[0.01950167,0.0009484129,0.0013691324,0.005351557,0.0033156434,0.014710882,0.0034936871,0.002353824,0.00074506307],"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":[0.0002563923,0.000039232884,0.002917653,0.0007897687,0.0001307608,0.0006604862,0.002794406,0.015151717,0.009854947,0.8031065,0.004183163,0.16011494],"study_design_scores_gemma":[0.0000762338,0.00022544892,0.0013739613,0.0005282443,0.0001932113,0.0013475966,0.0005773557,0.07704818,0.018576209,0.71525294,0.1845961,0.0002044887],"about_ca_topic_score_codex":0.0013432704,"about_ca_topic_score_gemma":0.00082111626,"teacher_disagreement_score":0.0074256524,"about_ca_system_score_codex":0.0014115247,"about_ca_system_score_gemma":0.0013620477,"threshold_uncertainty_score":0.024598062},"labels":[],"label_agreement":null},{"id":"W2146561295","doi":"10.1109/re.2005.8","title":"An algebraic framework for merging incomplete and inconsistent views","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":54,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Mitacs","keywords":"Computer science; Theoretical computer science; TRACE (psycholinguistics); Graph rewriting; Formalism (music); Traceability; Graph; Annotation; Data science; Artificial intelligence; Software engineering","score_opus":0.036248554037465366,"score_gpt":0.3148137874031153,"score_spread":0.2785652333656499,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2146561295","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":[0.0014633541,0.00005941068,0.99696213,0.00013935698,0.00001975202,0.000043518583,0.00004420061,0.00022368837,0.0010445132],"genre_scores_gemma":[0.040944446,0.00023778794,0.9570804,0.00009152577,0.00005741351,0.00014645622,0.00022453978,0.00009782437,0.0011196303],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99135125,0.0027421056,0.0011928318,0.0016666119,0.0026556116,0.00039167024],"domain_scores_gemma":[0.98815197,0.0048263706,0.0017956974,0.0024237602,0.0023791383,0.00042305974],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011705332,0.0011056093,0.001128854,0.004557524,0.003591503,0.006321388,0.0046787793,0.0018461207,0.0027650148],"category_scores_gemma":[0.020178512,0.0014639978,0.004342594,0.0053024604,0.005634768,0.0173279,0.00702303,0.0043914397,0.00067581545],"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":[0.000021002748,0.000016934671,0.00024634486,0.00010586201,0.00003125293,0.00019003169,0.00051311246,0.01524333,0.0009136578,0.955596,0.0008033302,0.0263191],"study_design_scores_gemma":[0.000034474495,0.00006558239,0.00013857534,0.00008813737,0.000134788,0.00043276863,0.00037133606,0.14717126,0.0043337024,0.8179066,0.02924442,0.000078289544],"about_ca_topic_score_codex":0.005046647,"about_ca_topic_score_gemma":0.0047145863,"teacher_disagreement_score":0.011705332,"about_ca_system_score_codex":0.0026705284,"about_ca_system_score_gemma":0.0035222536,"threshold_uncertainty_score":0.06190449},"labels":[],"label_agreement":null},{"id":"W2146624380","doi":"10.1007/s10115-006-0024-8","title":"Answering ad hoc aggregate queries from data streams using prefix aggregate trees","year":2006,"lang":"en","type":"article","venue":"Knowledge and Information Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":15,"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":"National University of Singapore","keywords":"Computer science; Aggregate (composite); Scalability; Trie; Prefix; Data stream mining; Data stream; Data warehouse; Data mining; Database; Data structure; Information retrieval","score_opus":0.02539816418324298,"score_gpt":0.257263077859474,"score_spread":0.23186491367623102,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2146624380","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":[0.1131701,0.0012277295,0.8752964,0.00091005076,0.0001874523,0.00030576315,0.0020676611,0.005271998,0.0015627947],"genre_scores_gemma":[0.5105448,0.0011902299,0.47687584,0.0003918043,0.00043619648,0.00029760913,0.0078266235,0.00041217514,0.002024767],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99531674,0.0006835784,0.0007602776,0.0007508041,0.0021715292,0.0003169777],"domain_scores_gemma":[0.9871508,0.008255642,0.0008368188,0.0019050223,0.0014803977,0.00037130387],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0041783457,0.0011667412,0.0028649333,0.0026944242,0.0014230304,0.00483431,0.0019344856,0.0022088469,0.0017865705],"category_scores_gemma":[0.014575249,0.0010208664,0.0013653113,0.0053178696,0.00095009926,0.010493503,0.003330774,0.002215965,0.00076951215],"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":[0.0036348489,0.0011094976,0.020980138,0.0014989657,0.0009109913,0.0016016675,0.0023826957,0.1981337,0.06432297,0.04017056,0.026028441,0.63922554],"study_design_scores_gemma":[0.00009372772,0.00016553041,0.0010137148,0.00003498153,0.00015587856,0.00031633832,0.0006740466,0.92352015,0.015106265,0.05393293,0.0049498104,0.00003652437],"about_ca_topic_score_codex":0.0025180145,"about_ca_topic_score_gemma":0.0038546934,"teacher_disagreement_score":0.00483431,"about_ca_system_score_codex":0.0008822839,"about_ca_system_score_gemma":0.0015764859,"threshold_uncertainty_score":0.022097468},"labels":[],"label_agreement":null},{"id":"W2147734897","doi":"10.1109/ride.1997.583698","title":"Mediator join indices","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Joins; Computer science; Join (topology); Query optimization; Overhead (engineering); Context (archaeology); Database; Data mining; Materialized view; View; Distributed computing; Programming language; Database design; Mathematics","score_opus":0.02059763017725208,"score_gpt":0.21744795069071518,"score_spread":0.1968503205134631,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147734897","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":[0.01133149,0.0012577055,0.9564987,0.000428214,0.00041593952,0.0010081835,0.0014010428,0.01559687,0.012061889],"genre_scores_gemma":[0.119988196,0.0011354134,0.85685205,0.00038437598,0.00038906382,0.00087903603,0.0062467097,0.0018525837,0.0122727025],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99615234,0.0004767656,0.00047106823,0.0005962401,0.0020399746,0.00026352354],"domain_scores_gemma":[0.9924064,0.0013977612,0.0004411824,0.0030713906,0.0019481165,0.0007351911],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0048208167,0.0010628965,0.0018351016,0.0024341804,0.0019744977,0.005993534,0.0039343177,0.0011642411,0.010356788],"category_scores_gemma":[0.0114563545,0.0009203605,0.0011219393,0.0031284525,0.00063965423,0.0065524774,0.005223725,0.0023850005,0.005831874],"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":[0.0021657385,0.00067210756,0.007821194,0.0007558986,0.0002943273,0.0005386073,0.00092075835,0.013309184,0.039293822,0.13854238,0.08106077,0.71462536],"study_design_scores_gemma":[0.000667378,0.0010120389,0.0027718057,0.00022408717,0.0003746982,0.001685847,0.00054549315,0.3865086,0.1272822,0.10686483,0.37176725,0.0002957959],"about_ca_topic_score_codex":0.0012118882,"about_ca_topic_score_gemma":0.0015887287,"teacher_disagreement_score":0.010356788,"about_ca_system_score_codex":0.0009930937,"about_ca_system_score_gemma":0.0030772958,"threshold_uncertainty_score":0.03464687},"labels":[],"label_agreement":null},{"id":"W2147756352","doi":"10.1111/1475-3995.00261","title":"A Web‐Based Query Interface for Health‐Care Data Warehouses","year":2001,"lang":"en","type":"article","venue":"International Transactions in Operational Research","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science; Interface (matter); The Internet; Data warehouse; World Wide Web; Application programming interface; User interface; Database; Information retrieval; Operating system","score_opus":0.18834726678992292,"score_gpt":0.4913165541899837,"score_spread":0.3029692874000608,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147756352","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":[0.006872782,0.00031343393,0.8764871,0.0006337562,0.00015055254,0.0005146852,0.0029294505,0.105223514,0.0068747755],"genre_scores_gemma":[0.0939543,0.0008685288,0.84552395,0.0027264121,0.00033961533,0.00150115,0.02028798,0.014573509,0.020224564],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981225,0.00050907856,0.00031681475,0.00021599304,0.00072803866,0.00010742985],"domain_scores_gemma":[0.99636036,0.002044371,0.00011101429,0.00044406945,0.00077056326,0.00026957813],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030386106,0.00087302655,0.00088141207,0.0018240841,0.0005174384,0.0026757964,0.0017061131,0.0013201149,0.015541343],"category_scores_gemma":[0.0061816666,0.0007025098,0.0008246637,0.0015477858,0.0004264383,0.0032025303,0.0021470515,0.001310966,0.008744082],"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":[0.0029068105,0.00080200424,0.0047905026,0.0012909336,0.00026789392,0.001932211,0.002606196,0.007859598,0.083199255,0.03880837,0.28823453,0.5673017],"study_design_scores_gemma":[0.00090990716,0.0004817916,0.00439028,0.00037479267,0.0001955342,0.0026571106,0.00038957893,0.21564345,0.054404803,0.026215393,0.6939822,0.00035524915],"about_ca_topic_score_codex":0.002077907,"about_ca_topic_score_gemma":0.0012243988,"teacher_disagreement_score":0.015541343,"about_ca_system_score_codex":0.00047366443,"about_ca_system_score_gemma":0.0006630964,"threshold_uncertainty_score":0.051990986},"labels":[],"label_agreement":null},{"id":"W2148682126","doi":"10.1109/ipdps.2012.85","title":"Query Optimization and Execution in a Parallel Analytics DBMS","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Online analytical processing; Computer science; Scalability; Query optimization; Sargable; Data warehouse; View; Database; Search engine indexing; NoSQL; Analytics; Big data; Query expansion; Parallel database; Relational database management system; Relational database; Web search query; Information retrieval; Data mining; Search engine; Database design","score_opus":0.01738522641094388,"score_gpt":0.24631535292834056,"score_spread":0.2289301265173967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2148682126","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":[0.1548314,0.00054961164,0.80804604,0.0017425285,0.00019378893,0.00033988027,0.0007327917,0.01676938,0.016794551],"genre_scores_gemma":[0.5688643,0.00041816925,0.41728702,0.00042225904,0.00023477859,0.00021136492,0.0017466417,0.0009607267,0.00985479],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9977489,0.00031381982,0.0002007788,0.0004490441,0.0010586471,0.00022876232],"domain_scores_gemma":[0.9989342,0.00028438045,0.000059076723,0.0003438376,0.0002896074,0.00008886533],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016551394,0.0007485164,0.0008958414,0.000634324,0.001366488,0.003051134,0.0018174128,0.0007757265,0.0025342966],"category_scores_gemma":[0.0027671484,0.00054580724,0.0007163419,0.0015523022,0.0009677745,0.0026217627,0.0018601444,0.0012112914,0.0012789876],"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":[0.002674828,0.0013765087,0.013485249,0.00040541496,0.00029737197,0.0016907627,0.00158366,0.35770777,0.14296551,0.11757465,0.042739365,0.31749898],"study_design_scores_gemma":[0.00016078871,0.00015796955,0.0007562884,0.0000110828405,0.000053422857,0.0002102952,0.0002482344,0.91942185,0.028392326,0.035114367,0.015439058,0.000034253157],"about_ca_topic_score_codex":0.0072518596,"about_ca_topic_score_gemma":0.0053527197,"teacher_disagreement_score":0.0072518596,"about_ca_system_score_codex":0.0011479269,"about_ca_system_score_gemma":0.0025652046,"threshold_uncertainty_score":0.014419317},"labels":[],"label_agreement":null},{"id":"W2148702471","doi":"10.1109/wcre.2008.30","title":"SQL2XMI: Reverse Engineering of UML-ER Diagrams from Relational Database Schemas","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Unified Modeling Language; Applications of UML; UML tool; Class diagram; Programming language; Metamodeling; Software engineering; Database; Data modeling; Model-driven architecture; Object Constraint Language; XML; XML Schema (W3C); Database schema; Database design; Software; XML database; World Wide Web","score_opus":0.02816733226416183,"score_gpt":0.2153139406939567,"score_spread":0.1871466084297949,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2148702471","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":[0.0033969574,0.00011951207,0.9785674,0.00018292261,0.000104044724,0.00026809046,0.000949205,0.013350164,0.003061612],"genre_scores_gemma":[0.027094476,0.00041626045,0.95884466,0.0001768228,0.000034349185,0.00032554558,0.004881696,0.00396591,0.0042603686],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9959027,0.0010415427,0.00051674014,0.00041014276,0.0019548174,0.00017394093],"domain_scores_gemma":[0.99354845,0.0029383407,0.00066876196,0.0015185394,0.0012222724,0.0001036917],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0057586385,0.0010163022,0.00059618586,0.0025229908,0.0005755907,0.0030815715,0.0018372088,0.001024939,0.0065427474],"category_scores_gemma":[0.013593322,0.0010459347,0.0014377472,0.0017226081,0.0008505742,0.0035359818,0.002305463,0.002409188,0.0034950401],"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":[0.00031397102,0.00029998148,0.003931926,0.0017234525,0.00013189239,0.0018144201,0.0034729983,0.018247355,0.03941662,0.25320104,0.04330563,0.63414073],"study_design_scores_gemma":[0.0001634148,0.00019929474,0.0017659162,0.0004657906,0.00012484743,0.0032357017,0.000733384,0.16347212,0.16984947,0.09184468,0.56797653,0.00016877557],"about_ca_topic_score_codex":0.001853092,"about_ca_topic_score_gemma":0.0023347815,"teacher_disagreement_score":0.0065427474,"about_ca_system_score_codex":0.00069160806,"about_ca_system_score_gemma":0.0018013779,"threshold_uncertainty_score":0.030454993},"labels":[],"label_agreement":null},{"id":"W2148832586","doi":"10.1145/564691.564713","title":"StatiX","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":130,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bell (Canada)","funders":"","keywords":"Document Structure Description; Computer science; XML Schema Editor; XML validation; XML database; XML Schema (W3C); Information retrieval; Efficient XML Interchange; Streaming XML; RELAX NG; XML; Data mining; Database; XML Encryption; World Wide Web","score_opus":0.02347652154432646,"score_gpt":0.21394513483080616,"score_spread":0.19046861328647968,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2148832586","genre_codex":"software","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":[0.0075162477,0.0014341194,0.24826024,0.0014755215,0.00067131093,0.0006190136,0.100849934,0.54529655,0.09387701],"genre_scores_gemma":[0.1109544,0.0028420105,0.25920376,0.002324197,0.00062798726,0.0014501248,0.41912046,0.08634019,0.11713676],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9971529,0.00040295682,0.00026517248,0.000567679,0.0013373604,0.0002738288],"domain_scores_gemma":[0.9950595,0.0018537504,0.00037458786,0.0014280882,0.0009882031,0.00029591308],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003110111,0.0012868384,0.001303402,0.0029450157,0.00097410555,0.0051829694,0.0034766279,0.0012552441,0.09474373],"category_scores_gemma":[0.011663901,0.0011845598,0.0012821723,0.0040600565,0.0008156594,0.0059272833,0.0034780935,0.002015278,0.056464776],"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":[0.0018601884,0.00013527655,0.004180639,0.0012821708,0.00015957725,0.00036432096,0.00037134805,0.005833554,0.007697296,0.055510573,0.68461275,0.23799226],"study_design_scores_gemma":[0.0003422181,0.00021725878,0.0025498786,0.00016673224,0.000076819844,0.00064826297,0.00013192778,0.037319016,0.014686593,0.038265847,0.90547174,0.00012369803],"about_ca_topic_score_codex":0.0040046233,"about_ca_topic_score_gemma":0.0038061533,"teacher_disagreement_score":0.09474373,"about_ca_system_score_codex":0.0015185897,"about_ca_system_score_gemma":0.0026938375,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W2149776851","doi":"10.1007/3-540-47961-9_26","title":"Reengineering of Database Applications to EJB Based Architecture","year":2002,"lang":"en","type":"book-chapter","venue":"Notes on numerical fluid mechanics and multidisciplinary design","topic":"Advanced Database Systems and Queries","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 Toronto","funders":"","keywords":"Computer science; Business process reengineering; Database; JavaBeans; SQL; Architecture; Software engineering; Set (abstract data type); Programming language; Engineering; Java","score_opus":0.03748256450213635,"score_gpt":0.26070810399614713,"score_spread":0.22322553949401078,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2149776851","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":[0.26895997,0.0028163802,0.66587895,0.0009369558,0.00028813118,0.00030188347,0.0003608869,0.020345144,0.040111713],"genre_scores_gemma":[0.49260968,0.002044348,0.42349738,0.0005548931,0.0000906402,0.0001241213,0.001276925,0.0054694586,0.07433254],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990553,0.00019076878,0.00006829272,0.00011227838,0.00046205224,0.00011128399],"domain_scores_gemma":[0.9984205,0.0003709355,0.000051868938,0.00077779556,0.00030465683,0.00007418993],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018388053,0.00035460282,0.0004481827,0.00073421525,0.00046155986,0.0024373806,0.0022444797,0.0009522588,0.005114782],"category_scores_gemma":[0.00466913,0.00085368566,0.0005814997,0.00093238015,0.00042957012,0.0024845942,0.0011329148,0.0017320861,0.0017057395],"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":[0.00040660586,0.00037766516,0.0033656324,0.0003830707,0.000072815645,0.0010560588,0.0033719176,0.023673948,0.07531267,0.09205263,0.021511044,0.77841586],"study_design_scores_gemma":[0.00016829248,0.0004059651,0.0073908796,0.00031690736,0.00024412126,0.002120783,0.0006171266,0.35662952,0.17886159,0.05919147,0.39394107,0.00011222217],"about_ca_topic_score_codex":0.0023062022,"about_ca_topic_score_gemma":0.0026279006,"teacher_disagreement_score":0.005114782,"about_ca_system_score_codex":0.000512894,"about_ca_system_score_gemma":0.0005958257,"threshold_uncertainty_score":0.017110705},"labels":[],"label_agreement":null},{"id":"W2149846355","doi":"10.1109/snpd.2007.572","title":"Xregion: A structure-based approach to Storing XML Data in Relational Databases","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; XML database; Relational database; Disjoint sets; Cardinality (data modeling); XML; Efficient XML Interchange; Streaming XML; Database; Document Structure Description; XML validation; Information retrieval; XML Encryption; XML Schema Editor; Data mining; World Wide Web; Mathematics","score_opus":0.0985764162699108,"score_gpt":0.3125179495817499,"score_spread":0.21394153331183907,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2149846355","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":[0.01021033,0.0024502487,0.9601607,0.0009115094,0.00021204355,0.00029117393,0.0014220619,0.021194652,0.003147325],"genre_scores_gemma":[0.07085912,0.0021462978,0.9154487,0.0011007274,0.0001424039,0.00029590266,0.005108305,0.0012161374,0.0036824944],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99612147,0.0007374149,0.0004947784,0.00060567865,0.0018060793,0.0002345577],"domain_scores_gemma":[0.9961062,0.0009927242,0.00042252566,0.0017705993,0.0005745236,0.00013345882],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029017061,0.0008211276,0.0013053362,0.0031651666,0.00074222806,0.0035930306,0.0048450804,0.0012799638,0.004119093],"category_scores_gemma":[0.0063703367,0.0009809934,0.001315141,0.0037382196,0.0013038632,0.009650691,0.0042825295,0.002080209,0.0019132757],"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":[0.001289374,0.00035169642,0.0067038154,0.0014763261,0.00067275605,0.0010373244,0.0017322944,0.023036523,0.049612083,0.11050362,0.0584066,0.74517757],"study_design_scores_gemma":[0.0008179795,0.001518156,0.0049360264,0.0007280195,0.00075311516,0.004028554,0.0010334423,0.2347406,0.17216031,0.09292468,0.48565826,0.00070096226],"about_ca_topic_score_codex":0.0034425883,"about_ca_topic_score_gemma":0.0032170147,"teacher_disagreement_score":0.0048450804,"about_ca_system_score_codex":0.0008912715,"about_ca_system_score_gemma":0.0013123638,"threshold_uncertainty_score":0.015345871},"labels":[],"label_agreement":null},{"id":"W2150625747","doi":"10.1109/wcre.2001.957839","title":"Interactive migration of legacy databases to net-centric technologies","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Schema (genetic algorithms); The Internet; XML; Schema migration; Database; Database schema; Schema evolution; XML Schema Editor; World Wide Web; Information schema; Document Structure Description; Information retrieval; Semi-structured model; Database design","score_opus":0.028365980562250346,"score_gpt":0.2655328482163803,"score_spread":0.23716686765412995,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2150625747","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":[0.16666739,0.0008257336,0.71691984,0.0021123139,0.00085516175,0.00047076526,0.0003574126,0.020384882,0.09140648],"genre_scores_gemma":[0.47668862,0.0010952884,0.46679935,0.00084360316,0.00012148581,0.0003036686,0.0011324332,0.0031454142,0.04987009],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99885166,0.00047750436,0.000074902615,0.00013075149,0.00034680442,0.000118358446],"domain_scores_gemma":[0.99783605,0.00074373157,0.00009569773,0.00080790836,0.00030429562,0.0002122398],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002237012,0.00031865417,0.00025984854,0.0006009799,0.00082714105,0.0034430283,0.001068746,0.00061546394,0.0055057174],"category_scores_gemma":[0.007143996,0.0005627718,0.0003612171,0.0006994972,0.00058207026,0.002595755,0.0050476454,0.0010270224,0.0011946753],"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":[0.0017077948,0.0006663412,0.008224698,0.00065324863,0.00013268362,0.003621862,0.022336246,0.02448512,0.05226129,0.13297169,0.056843795,0.6960953],"study_design_scores_gemma":[0.0002075574,0.00029706795,0.005571385,0.00028106547,0.000102859834,0.0011680768,0.0059367884,0.13017187,0.04098348,0.060129054,0.7550319,0.00011892915],"about_ca_topic_score_codex":0.0017860213,"about_ca_topic_score_gemma":0.0029911932,"teacher_disagreement_score":0.0055057174,"about_ca_system_score_codex":0.0006057442,"about_ca_system_score_gemma":0.0006018881,"threshold_uncertainty_score":0.018418431},"labels":[],"label_agreement":null},{"id":"W2150774720","doi":"10.1145/1142351.1142369","title":"On redundancy vs dependency preservation in normalization","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Redundancy (engineering); Computer science; Functional dependency; Dependency (UML); Normalization (sociology); Theoretical computer science; Data integrity; Data mining; Relational database; Artificial intelligence; Database","score_opus":0.006379026253693026,"score_gpt":0.21895143518283955,"score_spread":0.21257240892914653,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2150774720","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":[0.10597338,0.00234231,0.86027104,0.0041786106,0.00016182342,0.0001148987,0.00027017927,0.00039744773,0.026290273],"genre_scores_gemma":[0.7923587,0.0023135704,0.19776277,0.001013831,0.0007922925,0.00032980388,0.00030099,0.0003772935,0.004750732],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98744696,0.0041738437,0.0010449793,0.0015497777,0.0049039233,0.00088059873],"domain_scores_gemma":[0.9427324,0.038364347,0.0036109493,0.010206644,0.004544058,0.00054156774],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012600121,0.0010731571,0.0012856986,0.004002785,0.0017951081,0.00349773,0.0024776398,0.0019035076,0.0034712777],"category_scores_gemma":[0.05184603,0.00077681465,0.001782512,0.005279273,0.010104758,0.017952913,0.0038837385,0.0033254973,0.00064337923],"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":[0.0001480289,0.000060325794,0.001000522,0.00015377268,0.000033573473,0.00021058861,0.0005462907,0.017536618,0.003024336,0.93764883,0.0010168839,0.038620178],"study_design_scores_gemma":[0.00002820379,0.00013629407,0.0006058626,0.0000904906,0.000047724825,0.0006875472,0.000120818164,0.048966754,0.008713795,0.9343053,0.006242039,0.000055131994],"about_ca_topic_score_codex":0.0011993605,"about_ca_topic_score_gemma":0.0005829919,"teacher_disagreement_score":0.012600121,"about_ca_system_score_codex":0.003885357,"about_ca_system_score_gemma":0.0013045856,"threshold_uncertainty_score":0.06663662},"labels":[],"label_agreement":null},{"id":"W2151131744","doi":"10.14778/1687553.1687573","title":"Efficient index compression in DB2 LUW","year":2009,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta; IBM (Canada)","funders":"","keywords":"Computer science; Index (typography); Workload; Unix; Database; Response time; Data compression; Memory footprint; Real-time computing; Operating system","score_opus":0.007764069645988815,"score_gpt":0.22779144631109907,"score_spread":0.22002737666511027,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2151131744","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":[0.08668643,0.0019903425,0.8805865,0.00073109043,0.0001892374,0.0005210422,0.0006429768,0.019139577,0.009512804],"genre_scores_gemma":[0.29564628,0.00079229876,0.6928241,0.00070648233,0.00018268074,0.000530274,0.0018761419,0.00096589315,0.006475881],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99846834,0.00020505571,0.00018610519,0.00019707531,0.00078481017,0.00015847487],"domain_scores_gemma":[0.99794155,0.00045760773,0.00019304112,0.0006840203,0.0006279294,0.00009586716],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012099163,0.0007719572,0.00082796125,0.0016202852,0.00088386575,0.0021744706,0.0021263873,0.00083856453,0.0018031596],"category_scores_gemma":[0.004095724,0.0006388933,0.0003394597,0.0033251403,0.0006162828,0.0032875235,0.001974151,0.0009133366,0.0014613194],"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":[0.0015461638,0.00065235514,0.0046393746,0.00048993586,0.00009200629,0.0007513876,0.0006880305,0.028414445,0.16153815,0.02714741,0.037157945,0.73688275],"study_design_scores_gemma":[0.00025860907,0.00071119436,0.0022569562,0.000071029215,0.00006453464,0.0016790567,0.00032885978,0.6606423,0.26119286,0.017079836,0.055594873,0.000119949],"about_ca_topic_score_codex":0.0017306685,"about_ca_topic_score_gemma":0.0019873278,"teacher_disagreement_score":0.0021744706,"about_ca_system_score_codex":0.0007059591,"about_ca_system_score_gemma":0.001017756,"threshold_uncertainty_score":0.0063987374},"labels":[],"label_agreement":null},{"id":"W2151187218","doi":"10.1109/wpc.2001.921727","title":"Reverse engineering meets data analysis","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Online analytical processing; Reverse engineering; Computer science; Software engineering; Visualization; Sophistication; Aggregate (composite); Data visualization; Data science; Software; Data warehouse; Database; Data mining; Operating system","score_opus":0.05332572069950131,"score_gpt":0.23873727775608491,"score_spread":0.1854115570565836,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2151187218","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":[0.003912367,0.0004653194,0.9743925,0.005385996,0.00020543624,0.00012509905,0.00017167836,0.0014617014,0.013879953],"genre_scores_gemma":[0.08392084,0.0007105941,0.9063153,0.0021884155,0.00036972383,0.0002686504,0.0005390075,0.0007354811,0.0049519697],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.956816,0.017855953,0.004177556,0.006321471,0.013478052,0.0013509135],"domain_scores_gemma":[0.8965324,0.045695454,0.005438428,0.03622425,0.014981216,0.0011282802],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.021447696,0.0016130068,0.001433625,0.0035185667,0.0024174387,0.011745802,0.0023970683,0.0032962207,0.0064313496],"category_scores_gemma":[0.07755616,0.0011087249,0.0019391194,0.0041269753,0.0061730742,0.018145854,0.009088863,0.0066875913,0.005028347],"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":[0.00011221364,0.000141382,0.0044807554,0.0005453926,0.000097951335,0.00081453664,0.002182743,0.0051180376,0.004876949,0.65821844,0.012478214,0.31093338],"study_design_scores_gemma":[0.000043023058,0.00009830566,0.0008806741,0.0002809531,0.0000751601,0.0017670863,0.0010256417,0.0440466,0.014093359,0.758239,0.17935841,0.00009176502],"about_ca_topic_score_codex":0.0027284513,"about_ca_topic_score_gemma":0.0019363352,"teacher_disagreement_score":0.021447696,"about_ca_system_score_codex":0.0016626796,"about_ca_system_score_gemma":0.0055935867,"threshold_uncertainty_score":0.11342764},"labels":[],"label_agreement":null},{"id":"W2151965495","doi":"10.1109/icsm.2002.1167788","title":"From legacy to Web through interaction modeling","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":49,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Legacy system; Computer science; User interface; Reuse; Context (archaeology); World Wide Web; Web service; Interface (matter); Software engineering; Suite; Business process reengineering; Human–computer interaction; Programming language; Operating system; Engineering; Software","score_opus":0.038676230409246636,"score_gpt":0.2982459916851211,"score_spread":0.2595697612758745,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2151965495","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":[0.010280625,0.00092386967,0.9616392,0.00127996,0.00005261684,0.00006876215,0.00022816774,0.0020071785,0.023519706],"genre_scores_gemma":[0.30967867,0.0037901583,0.6632062,0.00085930777,0.00010393554,0.00045420867,0.0012450238,0.0010892211,0.019573241],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99841034,0.0006122353,0.00009704593,0.00024292772,0.00052516145,0.000112307054],"domain_scores_gemma":[0.9982035,0.00084708864,0.00009841523,0.0004920212,0.00028419166,0.00007484044],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016669022,0.0007106548,0.00042804456,0.0017439646,0.00086860603,0.004898867,0.0019280777,0.0010795724,0.0038545318],"category_scores_gemma":[0.0038864051,0.0007542123,0.001213333,0.0015596583,0.0021326544,0.006547603,0.0030963568,0.0023069233,0.0009898074],"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":[0.00006023019,0.000110663175,0.002266371,0.0003091284,0.00007653303,0.00068314606,0.0032519652,0.06927953,0.0025135784,0.78752947,0.00784694,0.12607245],"study_design_scores_gemma":[0.000025230664,0.000033731463,0.0007928429,0.00023169514,0.000084838335,0.00038426684,0.0009593593,0.42771757,0.004198395,0.40778887,0.15774325,0.000039965103],"about_ca_topic_score_codex":0.013584744,"about_ca_topic_score_gemma":0.011096345,"teacher_disagreement_score":0.013584744,"about_ca_system_score_codex":0.0013163008,"about_ca_system_score_gemma":0.0018151591,"threshold_uncertainty_score":0.027011335},"labels":[],"label_agreement":null},{"id":"W2152515015","doi":"","title":"A Generalized-Zero-Preserving Method for Compact Encoding of Concept Lattices","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University of Waterloo","funders":"","keywords":"Bit array; Encoding (memory); Computer science; Computation; Unification; Theoretical computer science; Parsing; Algorithm; Solver; Lattice (music); Join (topology); Mathematics; Artificial intelligence; Programming language; Type (biology); Combinatorics","score_opus":0.04459795572336843,"score_gpt":0.34586169321659654,"score_spread":0.3012637374932281,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2152515015","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":[0.0033692787,0.00011025583,0.9932414,0.00008794881,0.000047227593,0.000056200555,0.00023208492,0.0014979384,0.0013576989],"genre_scores_gemma":[0.054862402,0.00017228776,0.94071597,0.000081220925,0.00003641321,0.0001835621,0.000652851,0.00043114004,0.0028641073],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986557,0.0003533963,0.00016942335,0.00019974262,0.00051859074,0.00010317466],"domain_scores_gemma":[0.99791545,0.00070714956,0.00016200049,0.00076070346,0.00037934523,0.000075359145],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012829981,0.00069834216,0.0006709347,0.0012394252,0.0006697339,0.0025267354,0.0020132526,0.00057649135,0.007857123],"category_scores_gemma":[0.005157709,0.00047324196,0.0009971268,0.0025743933,0.0012373652,0.0048073316,0.0018871354,0.0017159758,0.0019670948],"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":[0.00027554014,0.00007437658,0.00029089686,0.00032689545,0.000034404686,0.00021725132,0.00044373996,0.023124922,0.01352128,0.5200788,0.008172297,0.43343958],"study_design_scores_gemma":[0.0001157714,0.0002641868,0.00018174817,0.0001660159,0.000065963795,0.0006740947,0.00024601526,0.3621789,0.042243693,0.5112195,0.08251936,0.0001247742],"about_ca_topic_score_codex":0.0014008211,"about_ca_topic_score_gemma":0.0019868568,"teacher_disagreement_score":0.007857123,"about_ca_system_score_codex":0.0011415455,"about_ca_system_score_gemma":0.001511545,"threshold_uncertainty_score":0.026284695},"labels":[],"label_agreement":null},{"id":"W2153322704","doi":"10.1109/ccece.1996.548071","title":"Reduction filters for minimizing data transfers in distributed query optimization","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Query optimization; Computer science; Heuristics; Reduction (mathematics); Sargable; Distributed database; Relational database; Database; Distributed computing; Data mining; Web search query; Information retrieval; Search engine; Mathematics","score_opus":0.07808989244243872,"score_gpt":0.27115331014976946,"score_spread":0.19306341770733074,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2153322704","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":[0.014569125,0.0002837557,0.9826399,0.000214608,0.000026477042,0.00011232548,0.000041962718,0.0004811084,0.0016308603],"genre_scores_gemma":[0.29862115,0.0005952551,0.693629,0.00022355215,0.00016004154,0.000711575,0.000293428,0.00043710243,0.005328884],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99765503,0.000801715,0.000109877124,0.00030871687,0.0008139745,0.00031063714],"domain_scores_gemma":[0.99597126,0.0028522112,0.00023746857,0.00046384477,0.0003882534,0.00008692103],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035998898,0.0012096305,0.0015982349,0.0014257731,0.0011705407,0.0012438885,0.0013065508,0.0011672559,0.002583562],"category_scores_gemma":[0.008095564,0.0005959166,0.0009351969,0.0015816061,0.0014548156,0.0023573448,0.0013298234,0.0014784244,0.00069550215],"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":[0.0007889167,0.00031674668,0.0011312971,0.0002926722,0.00009656405,0.00018590182,0.0004868094,0.6381722,0.023081074,0.10204273,0.0077689546,0.22563607],"study_design_scores_gemma":[0.000077700686,0.0001727316,0.00032545207,0.000016372227,0.000035695495,0.000084433195,0.0000944057,0.9375319,0.011014969,0.04539235,0.0052299476,0.000024100917],"about_ca_topic_score_codex":0.0038691778,"about_ca_topic_score_gemma":0.0037525622,"teacher_disagreement_score":0.0038691778,"about_ca_system_score_codex":0.0013667744,"about_ca_system_score_gemma":0.0018604154,"threshold_uncertainty_score":0.01903832},"labels":[],"label_agreement":null},{"id":"W2153676683","doi":"10.1109/time.2005.18","title":"Configuration Logic: A Multi-site Modal Logic","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Formalism (music); Modal logic; Multimodal logic; Normal modal logic; Computer science; Dynamic logic (digital electronics); Modal; Theoretical computer science; Accessibility relation; Description logic; Algorithm; Mathematics; Engineering","score_opus":0.035961033741787655,"score_gpt":0.2855665110171109,"score_spread":0.24960547727532323,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2153676683","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":[0.011123733,0.0010345705,0.94246185,0.0015010473,0.0002666713,0.00014421319,0.0007275514,0.0021386677,0.040601697],"genre_scores_gemma":[0.5345371,0.0015815785,0.44235173,0.0014687115,0.00044155482,0.0004409396,0.0009450808,0.0005092813,0.017724074],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.999009,0.00022541605,0.00007052372,0.00019453309,0.0003425486,0.0001579981],"domain_scores_gemma":[0.9994318,0.00016256169,0.0000691423,0.00012601184,0.00010930791,0.00010120577],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009735785,0.0006303083,0.0004916841,0.001500117,0.0013344752,0.0034030667,0.0025031287,0.001429642,0.01046878],"category_scores_gemma":[0.0012670936,0.00049229426,0.00088656275,0.002067854,0.003274803,0.0063292575,0.0030559418,0.0021295059,0.0021730112],"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":[0.000033134213,0.0000211231,0.00014910504,0.00008256151,0.000010315726,0.000253546,0.00016663161,0.0029599564,0.002420651,0.9739172,0.0030575553,0.016928136],"study_design_scores_gemma":[0.000035268804,0.00002923563,0.00015386206,0.00005949003,0.000027425911,0.0004536962,0.000116005365,0.024713635,0.0035910062,0.93695647,0.033827905,0.00003604411],"about_ca_topic_score_codex":0.001432568,"about_ca_topic_score_gemma":0.0013613357,"teacher_disagreement_score":0.01046878,"about_ca_system_score_codex":0.0012090927,"about_ca_system_score_gemma":0.0010970498,"threshold_uncertainty_score":0.035021544},"labels":[],"label_agreement":null},{"id":"W2154223184","doi":"10.1109/itng.2011.100","title":"Employing Frequent Pattern Mining for Finding Correlations between Tables in Relational Databases","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; Royal Bank of Canada; University of Calgary","funders":"","keywords":"Computer science; Relational database; Data mining; Database; Database design; Database schema; Relational model; Database model; View; Table (database); Row; Set (abstract data type); Information retrieval","score_opus":0.19559188536418132,"score_gpt":0.3153787295271897,"score_spread":0.11978684416300839,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2154223184","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":[0.21271595,0.0014005114,0.7797322,0.0005331633,0.00006222622,0.00037516048,0.0023285549,0.0016435795,0.0012087183],"genre_scores_gemma":[0.47641432,0.0006076242,0.51999456,0.00007808498,0.000046161666,0.00016196164,0.0022809452,0.0000563774,0.00036003423],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99425644,0.0014152534,0.00095437997,0.0011256975,0.001977921,0.0002703857],"domain_scores_gemma":[0.9790196,0.01284349,0.0035760617,0.0023792237,0.0018455131,0.00033617896],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004503091,0.0007265737,0.0010205398,0.0067134113,0.0011311425,0.0020042574,0.0015021325,0.00080271205,0.00064723974],"category_scores_gemma":[0.020293513,0.0006029024,0.0010584071,0.0070864637,0.00070242275,0.00436261,0.001105672,0.00080067356,0.0003313592],"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":[0.00095078896,0.0006096637,0.18080565,0.0014181177,0.00070746714,0.0043756147,0.0022170732,0.06910577,0.027367966,0.020441853,0.004328966,0.687671],"study_design_scores_gemma":[0.00013856283,0.0008859733,0.049004227,0.00038812315,0.00069306965,0.009014444,0.0029432294,0.7695735,0.04737412,0.105485715,0.014302223,0.00019694275],"about_ca_topic_score_codex":0.0023924,"about_ca_topic_score_gemma":0.0031697028,"teacher_disagreement_score":0.0067134113,"about_ca_system_score_codex":0.0006571465,"about_ca_system_score_gemma":0.0012525783,"threshold_uncertainty_score":0.023814857},"labels":[],"label_agreement":null},{"id":"W2154620955","doi":"10.1109/71.969122","title":"On rolling back and checkpointing in time warp","year":2001,"lang":"en","type":"article","venue":"IEEE Transactions on Parallel and Distributed Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Benchmark (surveying); Parallel computing; Execution time; Granularity; Electronic circuit; Very-large-scale integration; Algorithm; Sequential logic; Embedded system; Logic gate","score_opus":0.0150698584488355,"score_gpt":0.22991987577352946,"score_spread":0.21485001732469397,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2154620955","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":[0.05108329,0.0010845994,0.9401653,0.00039509492,0.00014244716,0.000113058384,0.000058143763,0.0021074081,0.0048505682],"genre_scores_gemma":[0.5500604,0.0011131639,0.44376394,0.0001845567,0.000111821624,0.00016390007,0.00020725884,0.000423341,0.0039716316],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99913186,0.0002818746,0.0000455357,0.00013514448,0.0002613356,0.0001443048],"domain_scores_gemma":[0.9979955,0.0010430836,0.00016109292,0.00047127396,0.00025054807,0.000078587356],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010185019,0.00082403916,0.00090132863,0.00061866886,0.0009922198,0.0010096716,0.0010917551,0.0007500305,0.0022577131],"category_scores_gemma":[0.0047220276,0.00036688446,0.0004935017,0.0009403451,0.0013634131,0.0021461924,0.0012169309,0.0013327859,0.0005266462],"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":[0.0005567667,0.00009485605,0.0012808352,0.0001331734,0.00004572787,0.00014819393,0.0003258316,0.68811774,0.008371919,0.055103455,0.0045673875,0.2412541],"study_design_scores_gemma":[0.000058852904,0.00010174127,0.00020288427,0.000018165048,0.000018359464,0.00007809647,0.00010078531,0.9601498,0.00932287,0.024084909,0.0058395187,0.000024023917],"about_ca_topic_score_codex":0.0051764753,"about_ca_topic_score_gemma":0.0026375956,"teacher_disagreement_score":0.0051764753,"about_ca_system_score_codex":0.0006642839,"about_ca_system_score_gemma":0.00082882395,"threshold_uncertainty_score":0.010292709},"labels":[],"label_agreement":null},{"id":"W2155199347","doi":"10.1109/icde.1995.380397","title":"Axiomatization of dynamic schema evolution in object bases","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":18,"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 Alberta","funders":"","keywords":"Schema evolution; Schema (genetic algorithms); Computer science; Conceptual schema; Axiom; Semi-structured model; Database schema; Star schema; Schema migration; Theoretical computer science; Information schema; Programming language; Data mining; Information retrieval; Mathematics; Database design","score_opus":0.010740347481311573,"score_gpt":0.22778559295083578,"score_spread":0.2170452454695242,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2155199347","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":[0.01632435,0.0007361695,0.94633704,0.0015622939,0.00017789972,0.00014284682,0.0005056411,0.0010461751,0.033167653],"genre_scores_gemma":[0.28757992,0.0012342029,0.691532,0.0012127107,0.00022470727,0.0004972676,0.0021968696,0.00026140458,0.015260839],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99629885,0.0010113547,0.0004612793,0.00048114193,0.0014490316,0.00029833667],"domain_scores_gemma":[0.9976133,0.00084967306,0.00016250748,0.00065239676,0.0006283574,0.00009373656],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037691253,0.00042537376,0.00044027166,0.0015235556,0.0015886432,0.003038091,0.001661886,0.0014351043,0.003299677],"category_scores_gemma":[0.0037780954,0.0007062908,0.0015951777,0.0016596365,0.0036638617,0.005528001,0.0032279184,0.0030345123,0.0009901914],"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":[0.000009727237,0.00001879688,0.00021910269,0.000049768245,0.000013831006,0.00015972549,0.0004129099,0.0033458613,0.000991143,0.98249316,0.0013287439,0.010957198],"study_design_scores_gemma":[0.0000309724,0.000028747852,0.00032832252,0.000051809588,0.000038358903,0.00042519506,0.0001313005,0.026278289,0.0024327193,0.9166089,0.053612098,0.000033274264],"about_ca_topic_score_codex":0.00583719,"about_ca_topic_score_gemma":0.00508951,"teacher_disagreement_score":0.00583719,"about_ca_system_score_codex":0.0020554124,"about_ca_system_score_gemma":0.0017949997,"threshold_uncertainty_score":0.019933283},"labels":[],"label_agreement":null},{"id":"W2155710070","doi":"10.1109/hicss.2001.927061","title":"Interoperability for accessing DBs by e-commerce applications","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; Saint Mary's University","funders":"","keywords":"Computer science; Programmer; Common Object Request Broker Architecture; Interoperability; Database; Interface (matter); Set (abstract data type); SQL; Programming language; Operating system","score_opus":0.01969676096343403,"score_gpt":0.30283020864785676,"score_spread":0.2831334476844227,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2155710070","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":[0.054788698,0.0010137731,0.8634521,0.005931849,0.00016999028,0.0005521917,0.0002123432,0.004364729,0.0695143],"genre_scores_gemma":[0.649037,0.0013113981,0.32802856,0.0017453537,0.0002860621,0.00086599425,0.0012040792,0.0015480891,0.015973484],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9735474,0.008975856,0.0037051688,0.0020828145,0.010357261,0.0013315046],"domain_scores_gemma":[0.97147906,0.008171582,0.0011705226,0.014112959,0.0042296704,0.0008361643],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.020439282,0.0005210305,0.0010087759,0.0019233411,0.0024152754,0.011913915,0.004065316,0.0038526873,0.006652989],"category_scores_gemma":[0.052667633,0.0011165023,0.0013497357,0.003311203,0.003254477,0.02128328,0.010702918,0.0041143405,0.0025443342],"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":[0.0002609848,0.00029252208,0.006058858,0.0003620738,0.00008469446,0.0013606129,0.0035230296,0.00430834,0.014224122,0.7978086,0.008428063,0.16328809],"study_design_scores_gemma":[0.0001466118,0.00017148274,0.005301377,0.00049477426,0.00020447039,0.0033154578,0.0032611084,0.08918031,0.033883993,0.62423927,0.23960505,0.00019605138],"about_ca_topic_score_codex":0.0017260564,"about_ca_topic_score_gemma":0.0010044225,"teacher_disagreement_score":0.020439282,"about_ca_system_score_codex":0.001556974,"about_ca_system_score_gemma":0.0023460435,"threshold_uncertainty_score":0.10809457},"labels":[],"label_agreement":null},{"id":"W2155971005","doi":"10.1109/ms.2007.141","title":"Open Source Software: All You Do Is Put It Together","year":2007,"lang":"en","type":"article","venue":"IEEE Software","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Athabasca University","funders":"ITEA","keywords":"Middleware (distributed applications); Computer science; Software engineering; Component (thermodynamics); Interface (matter); Software; World Wide Web; Publication; Simple (philosophy); Database; Operating system","score_opus":0.03129996086845111,"score_gpt":0.3008090885430084,"score_spread":0.2695091276745573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2155971005","genre_codex":"other","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0037599904,0.011355682,0.21521677,0.15896216,0.041965038,0.0010534409,0.004492493,0.12591189,0.43728256],"genre_scores_gemma":[0.026956487,0.015040097,0.18167737,0.055935163,0.022452045,0.0014142741,0.01588501,0.12109784,0.55954176],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99037254,0.0018111826,0.0007972545,0.000919955,0.0054122903,0.0006867607],"domain_scores_gemma":[0.9539312,0.0065056607,0.0022393106,0.015631905,0.01510341,0.0065885205],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009080488,0.0019394757,0.0015161493,0.0066201137,0.0029723013,0.0094624935,0.0027294075,0.006261405,0.15973718],"category_scores_gemma":[0.054009926,0.001314992,0.0014853722,0.0049380604,0.0033505876,0.02054347,0.01569788,0.008966748,0.27794138],"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":[0.000048624133,0.000089584726,0.0007866787,0.00036346752,0.00004619297,0.00016519209,0.0007267056,0.00010512823,0.0011671601,0.008334534,0.7134136,0.2747531],"study_design_scores_gemma":[0.000010631159,0.00002205987,0.0003635388,0.00031697776,0.000011541235,0.00021057758,0.00023164373,0.000091274356,0.0002797775,0.006363054,0.99207026,0.000028681528],"about_ca_topic_score_codex":0.0009922505,"about_ca_topic_score_gemma":0.0012894684,"teacher_disagreement_score":0.15973718,"about_ca_system_score_codex":0.0008602127,"about_ca_system_score_gemma":0.0033642966,"threshold_uncertainty_score":0.5343741},"labels":[],"label_agreement":null},{"id":"W2156317779","doi":"10.1145/1463788.1463811","title":"High performance XML parsing using parallel bit stream technology","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":46,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; British Columbia Institute of Technology","keywords":"Computer science; Byte; Parsing; XML; Programming language; Parallel computing; SIMD; Streaming XML; Operating system","score_opus":0.02711334040692692,"score_gpt":0.2397857195714074,"score_spread":0.21267237916448048,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2156317779","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":[0.024555996,0.0007346446,0.8989924,0.0004760751,0.0002865125,0.00024327874,0.0015094528,0.051820513,0.021381058],"genre_scores_gemma":[0.1937626,0.0010329599,0.77110565,0.0006149035,0.00020829859,0.00048734108,0.007465847,0.0039350693,0.02138717],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988978,0.00015814303,0.000112604,0.00017790028,0.0005558952,0.00009761342],"domain_scores_gemma":[0.99858814,0.00039857556,0.00006957081,0.00034097536,0.000563483,0.000039245293],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010854929,0.00068821013,0.0005612931,0.0010721618,0.00069592847,0.0021199458,0.0016653102,0.0007934353,0.0089928415],"category_scores_gemma":[0.002745403,0.00057206355,0.0004363321,0.002046237,0.00043983373,0.003594639,0.0012153613,0.0010832497,0.0052650236],"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":[0.0014741892,0.00025001907,0.0029197286,0.0006244798,0.00014628543,0.0009614108,0.00059989723,0.013995603,0.19089222,0.08697084,0.10231599,0.5988493],"study_design_scores_gemma":[0.00032612332,0.0002891087,0.0012016868,0.00010218936,0.000092856535,0.0010728055,0.00016086397,0.30314794,0.4827568,0.054288473,0.1564074,0.0001536177],"about_ca_topic_score_codex":0.0014142145,"about_ca_topic_score_gemma":0.0016666022,"teacher_disagreement_score":0.0089928415,"about_ca_system_score_codex":0.0006550867,"about_ca_system_score_gemma":0.0011267515,"threshold_uncertainty_score":0.030084074},"labels":[],"label_agreement":null},{"id":"W2156859522","doi":"10.1145/375663.375767","title":"Clio","year":2001,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":128,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science","score_opus":0.014526331141703978,"score_gpt":0.2461965657893796,"score_spread":0.2316702346476756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2156859522","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0049948925,0.0013413884,0.112255484,0.011382398,0.0027140474,0.0005642423,0.0060950085,0.02223571,0.83841676],"genre_scores_gemma":[0.0527436,0.0019219015,0.107661515,0.009388842,0.0013595207,0.0008368506,0.017562857,0.010419986,0.79810494],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980065,0.00032473667,0.0000856535,0.00045215304,0.00077778206,0.0003530967],"domain_scores_gemma":[0.9972952,0.00043065747,0.00011878825,0.00066392304,0.0008499374,0.00064152724],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024051538,0.0011037608,0.0005815474,0.0018680602,0.0021771933,0.009234522,0.0037607355,0.0035973932,0.28181368],"category_scores_gemma":[0.005847604,0.0005638865,0.0009278105,0.0016956207,0.0008708506,0.009410616,0.0068480605,0.0026040222,0.14727986],"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":[0.00020671348,0.00016439757,0.0013489345,0.00038049588,0.000017402961,0.0009988678,0.00062706106,0.002091675,0.004142783,0.20917998,0.5936069,0.18723483],"study_design_scores_gemma":[0.000017018101,0.000029849589,0.00022278933,0.000059263668,0.000004952578,0.00031281344,0.00015937227,0.0019624776,0.00070594705,0.014688534,0.98182124,0.000015768108],"about_ca_topic_score_codex":0.0041789445,"about_ca_topic_score_gemma":0.0055036074,"teacher_disagreement_score":0.28181368,"about_ca_system_score_codex":0.0020372644,"about_ca_system_score_gemma":0.0031282653,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W2156972533","doi":"10.14778/1920841.1920874","title":"SECRET","year":2010,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":109,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Semantics (computer science); Key (lock); Variation (astronomy); Range (aeronautics); Window (computing); World Wide Web; Programming language; Computer security; Engineering","score_opus":0.004724064018066928,"score_gpt":0.20121431826377942,"score_spread":0.19649025424571248,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2156972533","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":[0.021342011,0.0017680075,0.3278565,0.007424854,0.0017454526,0.001013293,0.032850992,0.046866663,0.5591322],"genre_scores_gemma":[0.304287,0.004110622,0.13730028,0.005588649,0.0009455418,0.0011567565,0.06285513,0.011300148,0.47245592],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99821436,0.00023428735,0.00014758248,0.00037613156,0.00082245935,0.00020524026],"domain_scores_gemma":[0.9962876,0.00059564353,0.00027185687,0.0016713516,0.00092561584,0.00024785567],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017777085,0.0006213028,0.00055393635,0.0011111324,0.00082511286,0.004968903,0.0021587599,0.001377278,0.07540943],"category_scores_gemma":[0.0073209866,0.00053195615,0.0006505111,0.0012185815,0.0008053074,0.0077379504,0.002654738,0.0011040505,0.047999013],"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":[0.00076775945,0.00012391174,0.004996776,0.00051589333,0.00004944202,0.00041492394,0.0005794838,0.008812725,0.0048578735,0.49594897,0.29093382,0.19199847],"study_design_scores_gemma":[0.000047390662,0.000054395976,0.0005317967,0.0000848311,0.000018192346,0.00047231393,0.00009469346,0.016498547,0.003647977,0.056417685,0.9220969,0.000035369212],"about_ca_topic_score_codex":0.0025196727,"about_ca_topic_score_gemma":0.0015727683,"teacher_disagreement_score":0.07540943,"about_ca_system_score_codex":0.001227042,"about_ca_system_score_gemma":0.0020634406,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W2157469509","doi":"10.1145/1066157.1066232","title":"Update-pattern-aware modeling and processing of continuous queries","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":76,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Web query classification; Online aggregation; Query optimization; Overhead (engineering); Query language; Sargable; Range query (database); Data stream mining; Spatial query; Semantics (computer science); Query expansion; Data mining; Implementation; Range (aeronautics); State (computer science); Web search query; Information retrieval; Programming language; Search engine","score_opus":0.011665700559896592,"score_gpt":0.24145984996214992,"score_spread":0.22979414940225332,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2157469509","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":[0.09693356,0.0003738664,0.89832497,0.00029097035,0.000041326777,0.00014069857,0.00037718372,0.0018123458,0.001705099],"genre_scores_gemma":[0.8124797,0.00043544546,0.18418665,0.000084855776,0.00007636208,0.000199334,0.00055866654,0.0001664234,0.0018126466],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975141,0.0004226873,0.00024825125,0.00056131114,0.0010677576,0.00018589968],"domain_scores_gemma":[0.99542147,0.0019202625,0.0005138154,0.0011335958,0.0008436353,0.00016730164],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001887341,0.0006797247,0.0008959323,0.0008839803,0.0005354117,0.0036291883,0.0023539495,0.00091713126,0.0008801512],"category_scores_gemma":[0.008514079,0.00065313204,0.0006901727,0.0016230883,0.0012684641,0.004537413,0.0011633874,0.0013917384,0.00025278807],"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":[0.00079634186,0.0003213083,0.012944318,0.00025945567,0.00010334714,0.00064284157,0.0013994429,0.7711985,0.023428192,0.07962008,0.0029370475,0.10634909],"study_design_scores_gemma":[0.000008884756,0.000030016583,0.0003701763,0.000003414342,0.0000105764175,0.0000478536,0.0000404978,0.9888349,0.0015928779,0.008340032,0.0007139385,0.000006827359],"about_ca_topic_score_codex":0.008231612,"about_ca_topic_score_gemma":0.0048546037,"teacher_disagreement_score":0.008231612,"about_ca_system_score_codex":0.0010194018,"about_ca_system_score_gemma":0.0014079417,"threshold_uncertainty_score":0.016367376},"labels":[],"label_agreement":null},{"id":"W2158008738","doi":"10.5381/jot.2004.3.7.a2","title":"Extending the Java Language with Dynamic Classification.","year":2004,"lang":"en","type":"article","venue":"The Journal of Object Technology","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Java; Programming language","score_opus":0.0071204194827191696,"score_gpt":0.25309582037273365,"score_spread":0.2459754008900145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2158008738","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":[0.0055961064,0.0005005675,0.9583604,0.0011141791,0.000588122,0.00019418115,0.00022888207,0.018211478,0.0152061675],"genre_scores_gemma":[0.08075931,0.0010162625,0.8918425,0.0022498763,0.0004793823,0.00048636663,0.0013744957,0.005660149,0.016131692],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99696726,0.00048536633,0.00047371245,0.0005357269,0.0011897398,0.00034817157],"domain_scores_gemma":[0.99413186,0.0016004128,0.000726646,0.0018300031,0.0013538221,0.00035721346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004331615,0.00071037107,0.0005808477,0.0010412104,0.000794677,0.0031736405,0.0025669816,0.0011520293,0.0026672487],"category_scores_gemma":[0.008787561,0.0007760374,0.0015004391,0.0011373357,0.0013505535,0.008087393,0.0032620123,0.0029596963,0.002530979],"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":[0.00052664545,0.00053343043,0.0057444912,0.0009434865,0.00012381173,0.0016091269,0.001766186,0.0047079427,0.037006516,0.38963243,0.066747904,0.49065804],"study_design_scores_gemma":[0.0002208412,0.0001423635,0.0013377392,0.0002923965,0.00017399063,0.002937806,0.00017734448,0.045921683,0.020720853,0.18604065,0.7418421,0.00019231075],"about_ca_topic_score_codex":0.0027135038,"about_ca_topic_score_gemma":0.0025363644,"teacher_disagreement_score":0.004331615,"about_ca_system_score_codex":0.0006761824,"about_ca_system_score_gemma":0.002617563,"threshold_uncertainty_score":0.022908092},"labels":[],"label_agreement":null},{"id":"W2158763191","doi":"10.1145/1059513.1059519","title":"An information-theoretic approach to normal forms for relational and XML data","year":2005,"lang":"en","type":"article","venue":"Journal of the ACM","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":100,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Relational database; Normalization (sociology); XML; Relational model; Database normalization; Information retrieval; Data mining; Measure (data warehouse); Theoretical computer science; Set (abstract data type); Programming language; Artificial intelligence; Cluster analysis","score_opus":0.030487403835780105,"score_gpt":0.2772800273680918,"score_spread":0.2467926235323117,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2158763191","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":[0.0030045325,0.000529638,0.9891867,0.0015669357,0.00015004385,0.00013210194,0.00017655999,0.00021848518,0.0050349473],"genre_scores_gemma":[0.09155771,0.00115669,0.8997121,0.0009830679,0.0008205055,0.0009064594,0.0005006398,0.0002863459,0.0040763975],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.95724297,0.017404156,0.005860485,0.00521352,0.013300194,0.0009787322],"domain_scores_gemma":[0.9400191,0.034249604,0.0038681268,0.013484219,0.0075639146,0.0008150239],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.028701248,0.0014308222,0.0016835356,0.006453341,0.0022667407,0.010780143,0.00417277,0.0035028625,0.0050606565],"category_scores_gemma":[0.08525213,0.001340145,0.0030287115,0.009620923,0.018874427,0.026575439,0.005448991,0.00829809,0.0017446663],"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":[0.000013563545,0.00001493412,0.00014739406,0.000052197036,0.000008794408,0.000033458004,0.00023184382,0.0021573529,0.00029169055,0.98400766,0.0007571616,0.012284057],"study_design_scores_gemma":[0.0000081629805,0.000023093762,0.000052622727,0.000041204396,0.0000070917413,0.000104456856,0.00006213294,0.01048081,0.00078314706,0.9794612,0.008956778,0.000019330555],"about_ca_topic_score_codex":0.0014480064,"about_ca_topic_score_gemma":0.0010264791,"teacher_disagreement_score":0.028701248,"about_ca_system_score_codex":0.005306572,"about_ca_system_score_gemma":0.0029255215,"threshold_uncertainty_score":0.15178853},"labels":[],"label_agreement":null},{"id":"W2159157420","doi":"10.14778/1454159.1454222","title":"Scheduling continuous queries in data stream management systems","year":2008,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Salient; Scheduling (production processes); Distributed computing; Operations research; Mathematical optimization; Artificial intelligence","score_opus":0.03159481624336894,"score_gpt":0.24339173839996645,"score_spread":0.2117969221565975,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2159157420","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":[0.12519142,0.005833382,0.8604769,0.001910274,0.00037126377,0.0003123994,0.00038907962,0.0021875224,0.003327765],"genre_scores_gemma":[0.82634693,0.0021144773,0.16849515,0.00032083123,0.00038831634,0.00019573669,0.0003881988,0.00014175285,0.0016085199],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974962,0.0009128967,0.00026095606,0.00035194986,0.0007478809,0.00023007055],"domain_scores_gemma":[0.9962631,0.002236809,0.00022262547,0.00035841615,0.00047132059,0.00044765332],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005133814,0.00048652594,0.0011424022,0.00062298117,0.0008626275,0.0027020203,0.0016323054,0.0009451196,0.0010663657],"category_scores_gemma":[0.008772746,0.0004761955,0.00038142514,0.0016864857,0.000987894,0.0021437448,0.0012604654,0.0012843033,0.00023308875],"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":[0.0024677676,0.000629263,0.0086117815,0.0009739257,0.00020583163,0.0007326429,0.001780196,0.54257566,0.038157485,0.15146603,0.021778686,0.2306207],"study_design_scores_gemma":[0.00011304617,0.00011573372,0.000594024,0.00001880353,0.00002283124,0.000059560065,0.00016318892,0.96768534,0.0031926592,0.021736855,0.0062764245,0.00002140495],"about_ca_topic_score_codex":0.0044741533,"about_ca_topic_score_gemma":0.003050505,"teacher_disagreement_score":0.005133814,"about_ca_system_score_codex":0.0014070489,"about_ca_system_score_gemma":0.0017017404,"threshold_uncertainty_score":0.027150512},"labels":[],"label_agreement":null},{"id":"W2159668267","doi":"10.1145/1065167.1065171","title":"XML data exchange","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":117,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; XML validation; Document Structure Description; XML Schema Editor; Data exchange; XML; RELAX NG; XML Schema (W3C); Information retrieval; Streaming XML; Efficient XML Interchange; Schema (genetic algorithms); XML database; Document type definition; Programming language; Database; World Wide Web","score_opus":0.056233817559141766,"score_gpt":0.2958429870641772,"score_spread":0.23960916950503547,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2159668267","genre_codex":"methods","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":[0.005715867,0.005588685,0.7978389,0.009259312,0.0017695419,0.0017423867,0.031360388,0.024148727,0.12257617],"genre_scores_gemma":[0.11409526,0.010796862,0.62544596,0.007409879,0.0016066945,0.0023113277,0.114204854,0.0065917643,0.11753739],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9902688,0.0026840223,0.0018350388,0.0014325628,0.0031836021,0.0005959519],"domain_scores_gemma":[0.9881097,0.0034630413,0.00076095486,0.005400766,0.0017250356,0.0005404767],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0068871756,0.001228133,0.0018695447,0.0036473381,0.0022929749,0.008711685,0.003997325,0.0031758344,0.032959916],"category_scores_gemma":[0.022286758,0.0010153813,0.0019938613,0.00804815,0.0016582893,0.013483077,0.008165469,0.003710324,0.0189595],"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":[0.00038265678,0.00013975616,0.0011489611,0.0011631378,0.0001658503,0.0006940318,0.00079329294,0.0076546944,0.0034543434,0.5316489,0.21699996,0.2357544],"study_design_scores_gemma":[0.000065303764,0.000050730745,0.00034063298,0.0002286726,0.000042649674,0.00063141837,0.00023659502,0.011668088,0.0040331637,0.19637373,0.7862737,0.00005536036],"about_ca_topic_score_codex":0.0025905592,"about_ca_topic_score_gemma":0.0019404413,"teacher_disagreement_score":0.032959916,"about_ca_system_score_codex":0.002118025,"about_ca_system_score_gemma":0.0026847327,"threshold_uncertainty_score":0.11026186},"labels":[],"label_agreement":null},{"id":"W2159957898","doi":"10.1109/icde.2009.173","title":"Improving the Effectiveness of XML Retrieval with User Navigation Models","year":2009,"lang":"en","type":"article","venue":"Proceedings - International Conference on Data Engineering","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Information retrieval; XML; Ranking (information retrieval); Markup language; XML Schema (W3C); Document Structure Description; XML database; XML framework; Relevance (law); Search engine; XML validation; Key (lock); Data mining; Database; XML Signature; World Wide Web","score_opus":0.032577268319563535,"score_gpt":0.26186568050244985,"score_spread":0.22928841218288631,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2159957898","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":[0.42020243,0.004370715,0.55352837,0.0008256774,0.00011265504,0.0005216509,0.00030412196,0.014251506,0.0058829687],"genre_scores_gemma":[0.6754262,0.0007305246,0.3208506,0.00015520827,0.00010130598,0.00012363984,0.0005419453,0.00033932657,0.0017313305],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9913549,0.00440307,0.0009165717,0.00075764355,0.0022486332,0.00031919937],"domain_scores_gemma":[0.96220535,0.028120212,0.0017678658,0.0036662451,0.003929857,0.00031054142],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0100063635,0.001601443,0.002157737,0.003729124,0.00079407677,0.0030360247,0.0016330656,0.0023606531,0.0013232133],"category_scores_gemma":[0.045916885,0.00062110624,0.0011072055,0.002520797,0.0007038859,0.0074168537,0.0016487286,0.001264387,0.0013065086],"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":[0.002459848,0.0014895181,0.015711999,0.00090529607,0.00038736337,0.00013819707,0.00060680654,0.11236639,0.0336543,0.004239967,0.0043350942,0.82370526],"study_design_scores_gemma":[0.00015793747,0.0011130983,0.00449206,0.000049169,0.00027618802,0.00029858205,0.0001980041,0.9534907,0.033571273,0.0034993077,0.0027342904,0.00011943322],"about_ca_topic_score_codex":0.0054768687,"about_ca_topic_score_gemma":0.0056947586,"teacher_disagreement_score":0.0100063635,"about_ca_system_score_codex":0.0009711342,"about_ca_system_score_gemma":0.001742039,"threshold_uncertainty_score":0.052919388},"labels":[],"label_agreement":null},{"id":"W2160692711","doi":"10.1109/ideas.2003.1214941","title":"Automated EJB client code generation using database query rewriting","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Rewriting; JavaBeans; Database; Programming language; SQL; Source code; Code (set theory); Software engineering; Java","score_opus":0.06415247390979074,"score_gpt":0.3114656311978749,"score_spread":0.24731315728808417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2160692711","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":[0.051285774,0.00030493608,0.8999439,0.00033995797,0.00009954195,0.00037696905,0.00057646487,0.04150794,0.0055646678],"genre_scores_gemma":[0.23697558,0.00045739542,0.73746717,0.0004069603,0.00007950623,0.00030866978,0.004303273,0.01087986,0.009121604],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99718,0.0006276333,0.00024479476,0.00046123003,0.0012963245,0.00019003442],"domain_scores_gemma":[0.993954,0.0023702874,0.00031748184,0.0015765661,0.0016458643,0.00013587305],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018845372,0.00070127996,0.0009031684,0.0008787069,0.00051139586,0.0016043283,0.0013378144,0.0009458006,0.0030458984],"category_scores_gemma":[0.0078123957,0.000681348,0.0008286376,0.00076856423,0.0007385594,0.0012773545,0.0015461007,0.0011470392,0.0030766476],"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":[0.0008645099,0.00043749312,0.0035304024,0.00061164855,0.000092146256,0.0019458125,0.0016700894,0.02795886,0.30326968,0.04717176,0.038945645,0.5735018],"study_design_scores_gemma":[0.00028489728,0.00018840682,0.0022780665,0.000082659644,0.00007428269,0.0019144162,0.00026148255,0.5108556,0.39178175,0.019667476,0.072469994,0.00014096673],"about_ca_topic_score_codex":0.001766385,"about_ca_topic_score_gemma":0.0010014462,"teacher_disagreement_score":0.0030458984,"about_ca_system_score_codex":0.0006153663,"about_ca_system_score_gemma":0.0010264375,"threshold_uncertainty_score":0.010189533},"labels":[],"label_agreement":null},{"id":"W2160836912","doi":"10.1145/956863.956898","title":"XML parsing","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":117,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada)","funders":"","keywords":"Computer science; XML validation; Streaming XML; Efficient XML Interchange; XML Schema (W3C); XML Schema Editor; XML database; Document Structure Description; Simple API for XML; Parsing; Database; XML Encryption; XML Signature; Information retrieval; XML framework; XML; Programming language; World Wide Web","score_opus":0.012970241435078281,"score_gpt":0.2293582252718944,"score_spread":0.21638798383681612,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2160836912","genre_codex":"methods","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":[0.010633454,0.0017456358,0.60134596,0.0021266532,0.0012225362,0.0014618755,0.03933866,0.17633514,0.16579008],"genre_scores_gemma":[0.101201445,0.002581486,0.54642147,0.0036625639,0.00052759657,0.00091042137,0.12506558,0.031161437,0.188468],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9976362,0.0003690386,0.0003190055,0.0005018379,0.0009521693,0.00022188111],"domain_scores_gemma":[0.9943949,0.00126973,0.00022800245,0.002334155,0.0016241123,0.00014912862],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0024392607,0.001290877,0.00087997137,0.0020314367,0.0011523892,0.0039918935,0.0022577515,0.0015047996,0.071487166],"category_scores_gemma":[0.008584016,0.0007471449,0.0011981403,0.0024417613,0.00064437825,0.0038932539,0.003211092,0.0015094603,0.07830489],"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":[0.00063298305,0.00020554673,0.0035208745,0.0010472152,0.000115473376,0.00078893825,0.0007924589,0.0031954069,0.02643517,0.0753057,0.369233,0.5187272],"study_design_scores_gemma":[0.00005332685,0.000088204644,0.0017740689,0.00015489553,0.00005135152,0.0008479715,0.00022484484,0.010794122,0.038996816,0.032256138,0.91466945,0.0000889212],"about_ca_topic_score_codex":0.0017503202,"about_ca_topic_score_gemma":0.0016885118,"teacher_disagreement_score":0.9285128,"about_ca_system_score_codex":0.0006869386,"about_ca_system_score_gemma":0.001384668,"threshold_uncertainty_score":0.23914838},"labels":[],"label_agreement":null},{"id":"W2160986485","doi":"10.1109/ccgrid.2003.1199356","title":"Parallel multi-dimensional ROLAP indexing","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; Carleton University","funders":"","keywords":"Online analytical processing; Computer science; Search engine indexing; Scalability; Materialized view; Scheme (mathematics); Database index; Index (typography); Volume (thermodynamics); Multidimensional data; Distributed computing; Data mining; Theoretical computer science; Information retrieval; Database; Data warehouse; View; Database design","score_opus":0.02563882812533246,"score_gpt":0.2604504375801941,"score_spread":0.23481160945486163,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2160986485","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":[0.038904697,0.0014629416,0.93307775,0.00056548667,0.00026374907,0.00025794763,0.0011534486,0.010322595,0.013991333],"genre_scores_gemma":[0.24835777,0.0008196965,0.7389251,0.0002196347,0.00022107169,0.00034699365,0.0040195426,0.00068057113,0.006409632],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99784446,0.00037241637,0.00018797054,0.0003212929,0.0010381516,0.00023581623],"domain_scores_gemma":[0.99614346,0.00059601106,0.00020644761,0.0021085197,0.00077010825,0.00017542014],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012341405,0.00057346217,0.0015812162,0.0015786836,0.001585414,0.0031943743,0.003272449,0.0007054244,0.0041943653],"category_scores_gemma":[0.003925578,0.00040168889,0.00081856863,0.004307759,0.0008154452,0.004200476,0.004489653,0.0010246631,0.002350607],"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":[0.0009713837,0.00046147784,0.0034351272,0.0007786737,0.00018389086,0.0005797482,0.0008554162,0.07536733,0.032786697,0.07737799,0.049513385,0.7576889],"study_design_scores_gemma":[0.00020712697,0.0002721501,0.0012458806,0.000062729334,0.00007194534,0.00094601704,0.0005721783,0.7725244,0.057556905,0.07654777,0.08988231,0.00011046836],"about_ca_topic_score_codex":0.002098832,"about_ca_topic_score_gemma":0.0022029453,"teacher_disagreement_score":0.0041943653,"about_ca_system_score_codex":0.0008233881,"about_ca_system_score_gemma":0.0014846736,"threshold_uncertainty_score":0.014031589},"labels":[],"label_agreement":null},{"id":"W2161306597","doi":"10.1109/icde.2007.368994","title":"Semantic Prefetching of Correlated Query Sequences","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Overhead (engineering); Distributed computing; Real-time computing; Database; Operating system","score_opus":0.012545986302176631,"score_gpt":0.2554909880358043,"score_spread":0.24294500173362765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2161306597","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":[0.5309406,0.001116325,0.4410165,0.0005336928,0.0001460991,0.00025978204,0.0007653535,0.021079103,0.0041425233],"genre_scores_gemma":[0.8543338,0.00026176736,0.14152098,0.00013340104,0.00009252644,0.00010327279,0.0011780385,0.0003387654,0.0020374325],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.999241,0.00014485583,0.000057038716,0.00015454553,0.0003034223,0.00009914806],"domain_scores_gemma":[0.99765944,0.0008183197,0.00021955234,0.00077371584,0.0003807235,0.00014823601],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00085996644,0.00089859887,0.0012042669,0.00076303195,0.00078754395,0.000780134,0.0015558611,0.00055204466,0.0017144596],"category_scores_gemma":[0.0047470196,0.00041990902,0.00029483173,0.0021621583,0.00050318445,0.0020589475,0.0008906009,0.0007855828,0.0005114936],"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":[0.0044192187,0.0012022124,0.020299476,0.00038456765,0.00020283913,0.0008072996,0.0005778806,0.25964603,0.15148509,0.010211251,0.0154225,0.5353417],"study_design_scores_gemma":[0.000116986805,0.00026891328,0.0021766333,0.00000700258,0.000057506397,0.00015195314,0.000065625216,0.94893724,0.039636403,0.0060349093,0.0025106543,0.000036201756],"about_ca_topic_score_codex":0.00450598,"about_ca_topic_score_gemma":0.008461211,"teacher_disagreement_score":0.00450598,"about_ca_system_score_codex":0.0006565524,"about_ca_system_score_gemma":0.0015114897,"threshold_uncertainty_score":0.008959532},"labels":[],"label_agreement":null},{"id":"W2162294668","doi":"10.1145/373626.373713","title":"The Clio project","year":2001,"lang":"en","type":"article","venue":"ACM SIGMOD Record","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":343,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Set (abstract data type); Data integration; Transformation (genetics); Data science; Software engineering; Programming language; Database","score_opus":0.031767974344315664,"score_gpt":0.29049034626259007,"score_spread":0.2587223719182744,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162294668","genre_codex":"other","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":[0.025234452,0.017048687,0.33040324,0.014100209,0.0029549962,0.002244452,0.035516497,0.13701755,0.43547997],"genre_scores_gemma":[0.101530135,0.01094154,0.36165553,0.006476815,0.0011302202,0.00350873,0.1967767,0.04293669,0.27504367],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9921158,0.0022171233,0.00037406076,0.0011825673,0.0030408183,0.0010695338],"domain_scores_gemma":[0.9905483,0.0019113199,0.0005395493,0.002748453,0.0022532272,0.0019990997],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010678826,0.0023819946,0.0010695506,0.00590226,0.0024827253,0.008610901,0.0044870893,0.003244307,0.06462744],"category_scores_gemma":[0.017023856,0.0008432479,0.0014452093,0.004840857,0.0019867085,0.009700947,0.012852394,0.0034774179,0.039841276],"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":[0.00094317005,0.0003191301,0.0024004881,0.0010526369,0.00010099943,0.00045070102,0.0015234882,0.0020249446,0.0052158725,0.11205075,0.5481361,0.32578176],"study_design_scores_gemma":[0.00015807367,0.0000936694,0.00057687465,0.0002416912,0.000031261763,0.00027208688,0.00043800718,0.0030637844,0.0019234482,0.01632028,0.9768395,0.000041346284],"about_ca_topic_score_codex":0.008760191,"about_ca_topic_score_gemma":0.005299137,"teacher_disagreement_score":0.06462744,"about_ca_system_score_codex":0.0024226175,"about_ca_system_score_gemma":0.0060404465,"threshold_uncertainty_score":0.21620029},"labels":[],"label_agreement":null},{"id":"W2162458328","doi":"10.1109/tools.1998.711010","title":"On separation between interface, implementation, and representation in object DBMSs","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":10,"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 Alberta","funders":"","keywords":"Computer science; Separation (statistics); Interface (matter); Representation (politics); Separation of concerns; Object (grammar); Programming language; Distributed computing; Parallel computing; Artificial intelligence; Machine learning; Software","score_opus":0.03765342824025583,"score_gpt":0.3617914612106032,"score_spread":0.3241380329703474,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162458328","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":[0.0035766836,0.0011623779,0.9837284,0.002970718,0.00018543586,0.00016609924,0.000053739506,0.0008426005,0.0073140287],"genre_scores_gemma":[0.09962207,0.0028458077,0.87894547,0.0032577803,0.0006760211,0.0010097768,0.0003408883,0.0013432866,0.011958918],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9724587,0.010912416,0.0029866532,0.0025159018,0.00859085,0.0025354652],"domain_scores_gemma":[0.98107076,0.008303294,0.0011102688,0.006298751,0.0021783933,0.0010386277],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.021995666,0.0021678351,0.0023013526,0.0032059802,0.0039621685,0.019073833,0.0057129995,0.008474698,0.004804672],"category_scores_gemma":[0.025976425,0.0036474771,0.0036382815,0.0039999345,0.0153083885,0.046692345,0.012637181,0.016755918,0.003061367],"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":[0.00008196961,0.00009303462,0.00027661287,0.00019051926,0.000024880681,0.0001275833,0.0011334819,0.0028501358,0.0011280995,0.9641504,0.0019457231,0.02799757],"study_design_scores_gemma":[0.00012877476,0.00020166779,0.00020808271,0.00039989065,0.000105098086,0.0004742071,0.00041673396,0.032086372,0.003765759,0.90479696,0.0573037,0.00011276991],"about_ca_topic_score_codex":0.0049033808,"about_ca_topic_score_gemma":0.0026900505,"teacher_disagreement_score":0.021995666,"about_ca_system_score_codex":0.003539973,"about_ca_system_score_gemma":0.0061022486,"threshold_uncertainty_score":0.11632556},"labels":[],"label_agreement":null},{"id":"W2163268286","doi":"10.1145/1321440.1321495","title":"Towards practically feasible answering of regular path queries in lav data integration","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Rewriting; Computer science; Complement (music); Path (computing); Theoretical computer science; Context (archaeology); Matching (statistics); Automaton; Mathematics; Programming language","score_opus":0.04593498282813204,"score_gpt":0.32644442691216147,"score_spread":0.28050944408402945,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163268286","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":[0.08064374,0.00046927345,0.9091147,0.0025986899,0.00010334641,0.00020660166,0.00038352725,0.0027688222,0.0037111933],"genre_scores_gemma":[0.4875384,0.00032142858,0.5079453,0.00067500665,0.00021871478,0.0002731576,0.0009975547,0.00037098044,0.0016595561],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9834027,0.007234551,0.0012499784,0.0028168105,0.004221498,0.0010744261],"domain_scores_gemma":[0.93993515,0.04377885,0.0018620914,0.010062685,0.0034920608,0.0008691755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007597711,0.00093339465,0.002178215,0.0012571142,0.0016273855,0.0059702336,0.003410407,0.0033533976,0.0031028986],"category_scores_gemma":[0.04730316,0.0011277555,0.0024587987,0.0021280777,0.0038128,0.010266722,0.0058202962,0.0046167737,0.0011914144],"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":[0.002800857,0.0006117304,0.005913642,0.00094702793,0.0002918092,0.00087248674,0.0027538189,0.2999288,0.034740437,0.40631816,0.014198605,0.23062268],"study_design_scores_gemma":[0.00011002662,0.00008683626,0.00024214968,0.000021584457,0.00004556401,0.00018835072,0.0002658411,0.64820826,0.0067568133,0.3413331,0.0027093175,0.000032144802],"about_ca_topic_score_codex":0.0034363447,"about_ca_topic_score_gemma":0.0038890305,"teacher_disagreement_score":0.007597711,"about_ca_system_score_codex":0.001975553,"about_ca_system_score_gemma":0.002931563,"threshold_uncertainty_score":0.04018104},"labels":[],"label_agreement":null},{"id":"W2163438246","doi":"10.14778/1687553.1687556","title":"StatAdvisor","year":2009,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada); University of Waterloo","funders":"","keywords":"Computer science; IBM; Matching (statistics); SQL; Data mining; Oracle; Key (lock); Plan (archaeology); Construct (python library); Workload; Query plan; Information retrieval; Database; Statistics; Software engineering; Web search query; Mathematics; Sargable; Search engine; Programming language","score_opus":0.00712529554645085,"score_gpt":0.21475078658725172,"score_spread":0.20762549104080086,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163438246","genre_codex":"software","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":[0.011992129,0.0013447163,0.40501705,0.001105998,0.0003892513,0.0011853796,0.038392372,0.46080488,0.0797682],"genre_scores_gemma":[0.13906278,0.0020577647,0.5529056,0.0020900583,0.00038465066,0.0027642364,0.12350705,0.070695676,0.106532186],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99764025,0.00033000633,0.00021576582,0.00070030463,0.0009472849,0.00016640445],"domain_scores_gemma":[0.9940042,0.002268154,0.0003453553,0.0020756542,0.0009519937,0.00035467595],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00264646,0.0010755545,0.001113621,0.0017615183,0.00057710876,0.0043605617,0.004647346,0.000922018,0.057755012],"category_scores_gemma":[0.014144393,0.0015193694,0.000836488,0.0021419963,0.0006690609,0.003950494,0.003846236,0.0022051907,0.02985708],"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":[0.0016705556,0.00016456154,0.00471972,0.0010444418,0.00011200043,0.0002573548,0.00043994703,0.0068552108,0.006782078,0.032517113,0.4739409,0.47149613],"study_design_scores_gemma":[0.00065123534,0.0003245173,0.0032766836,0.00026178855,0.00007430226,0.00063406955,0.0001676511,0.09421501,0.013240962,0.032924537,0.8541039,0.00012533578],"about_ca_topic_score_codex":0.0021584455,"about_ca_topic_score_gemma":0.002656563,"teacher_disagreement_score":0.057755012,"about_ca_system_score_codex":0.0010354833,"about_ca_system_score_gemma":0.0026822905,"threshold_uncertainty_score":0.19320977},"labels":[],"label_agreement":null},{"id":"W2163749338","doi":"10.1109/icac.2007.3","title":"Adaptive Learning of Metric Correlations for Temperature-Aware Database Provisioning","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":44,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Database; Bottleneck; Provisioning; Database tuning; Distributed computing; Data mining; View; Database design; Computer network","score_opus":0.0199244773694977,"score_gpt":0.28246476787086094,"score_spread":0.26254029050136324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163749338","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":[0.0354996,0.0000654034,0.9629131,0.000057816964,0.000013106689,0.000025690328,0.000024959998,0.0010942265,0.00030614645],"genre_scores_gemma":[0.72777516,0.00007035952,0.27114147,0.00005658369,0.000052811858,0.00010703937,0.00012628653,0.00016397003,0.0005063159],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99884254,0.0003671201,0.00006598414,0.00028462836,0.00035348063,0.00008625715],"domain_scores_gemma":[0.99572253,0.0019542298,0.000612876,0.0009964125,0.0005666661,0.00014725677],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018035448,0.0005859327,0.00094234565,0.0006693907,0.00039907344,0.0008756575,0.0014920415,0.00050720945,0.0006144884],"category_scores_gemma":[0.010638438,0.00050846615,0.0004645769,0.0006349349,0.00052483915,0.0017299884,0.001038043,0.0011770485,0.0002604736],"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":[0.0002651595,0.00029182376,0.006191248,0.00007090627,0.00011961995,0.00007611691,0.00017704735,0.65616137,0.022312628,0.0067116204,0.001500595,0.30612177],"study_design_scores_gemma":[0.000005098857,0.00001893395,0.00037719964,0.0000011865246,0.000003402887,0.000012296211,0.000005751983,0.9965829,0.0013938791,0.0014605218,0.00013282074,0.000005924352],"about_ca_topic_score_codex":0.0021018423,"about_ca_topic_score_gemma":0.002903953,"teacher_disagreement_score":0.0021018423,"about_ca_system_score_codex":0.00085673825,"about_ca_system_score_gemma":0.00095681194,"threshold_uncertainty_score":0.009538174},"labels":[],"label_agreement":null},{"id":"W2164875685","doi":"10.1016/j.entcs.2004.09.018","title":"Labelled Markov Processes: Stronger and Faster Approximations","year":2004,"lang":"en","type":"article","venue":"Electronic Notes in Theoretical Computer Science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Markov chain; Approximations of π; Markov process; Computer science; Markov model; Mathematics; Applied mathematics; Theoretical computer science; Algorithm; Statistics; Machine learning","score_opus":0.0054589061409852846,"score_gpt":0.23772920318290433,"score_spread":0.23227029704191904,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2164875685","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":[0.024810309,0.0006081254,0.9686419,0.0006561253,0.00014151365,0.00005692233,0.00010225833,0.0005161644,0.0044666645],"genre_scores_gemma":[0.46181133,0.00083792955,0.5278005,0.00048218208,0.00029669033,0.00018591681,0.00042047602,0.0006065119,0.0075584417],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9913345,0.0027050031,0.0005116186,0.0014240724,0.003381267,0.0006435776],"domain_scores_gemma":[0.9725079,0.017703094,0.0019523868,0.005702621,0.0014486433,0.0006853558],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008533556,0.0011666212,0.0015874283,0.0017133858,0.00089578214,0.0046252683,0.0027194952,0.0025662198,0.0077866716],"category_scores_gemma":[0.03976337,0.0009751976,0.002599873,0.0014569076,0.0031643226,0.011345412,0.004925008,0.0065756654,0.0012860126],"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":[0.0003492827,0.0000710296,0.0007962198,0.00022201355,0.00007024467,0.00013403944,0.0007551679,0.103547834,0.004926634,0.8565634,0.00090696884,0.031657062],"study_design_scores_gemma":[0.0000474541,0.00007372081,0.00022760771,0.00006795107,0.000045677396,0.000116042516,0.0001047794,0.5067923,0.002845304,0.4840656,0.0055724797,0.000041002164],"about_ca_topic_score_codex":0.0032188916,"about_ca_topic_score_gemma":0.0026772995,"teacher_disagreement_score":0.008533556,"about_ca_system_score_codex":0.0032813624,"about_ca_system_score_gemma":0.0015688908,"threshold_uncertainty_score":0.045130253},"labels":[],"label_agreement":null},{"id":"W2165691328","doi":"10.1109/ssdbm.2006.29","title":"Indexing Time-Evolving Data With Variable Lifetimes","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Search engine indexing; Partition (number theory); Computer science; Data management; Line (geometry); Index (typography); Access time; Data mining; Parallel computing; Information retrieval; Mathematics; Operating system","score_opus":0.010441507404117777,"score_gpt":0.22006111037438486,"score_spread":0.20961960297026708,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2165691328","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":[0.2921145,0.003970239,0.69732124,0.000734482,0.0001634055,0.000166047,0.0006861668,0.0016479496,0.0031959133],"genre_scores_gemma":[0.7564621,0.0020968714,0.23736823,0.0001762467,0.00017165588,0.00016486603,0.0010072164,0.0002101694,0.0023426032],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988524,0.00016882103,0.0001791442,0.000213806,0.00043643446,0.00014947559],"domain_scores_gemma":[0.992761,0.002821468,0.00084091205,0.0025707735,0.0007826882,0.00022307294],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016621889,0.00032824016,0.00091310334,0.0015570103,0.0010629143,0.0021577207,0.0016727877,0.0008081429,0.00091127434],"category_scores_gemma":[0.008432994,0.00042663488,0.00040542748,0.003859521,0.000944944,0.005481328,0.0015902983,0.0008844193,0.00030574802],"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":[0.0011187595,0.0002794522,0.016593406,0.00066410244,0.00014829524,0.0008654569,0.0022359,0.112348594,0.073683,0.14839086,0.0074871196,0.636185],"study_design_scores_gemma":[0.00013799791,0.00041489233,0.004997019,0.000092239396,0.0001475737,0.0018915443,0.0009108397,0.7249594,0.057519604,0.16445658,0.044341996,0.00013036815],"about_ca_topic_score_codex":0.0013926405,"about_ca_topic_score_gemma":0.0017373585,"teacher_disagreement_score":0.0021577207,"about_ca_system_score_codex":0.00080742355,"about_ca_system_score_gemma":0.00077759865,"threshold_uncertainty_score":0.008790612},"labels":[],"label_agreement":null},{"id":"W2165865022","doi":"","title":"Scalpel: optimizing query streams using semantic prefetching","year":2005,"lang":"en","type":"dissertation","venue":"UWSpace (University of Waterloo)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Latency (audio); Offset (computer science); Data stream mining; Context (archaeology); Database; Data mining; Operating system","score_opus":0.013889125286716389,"score_gpt":0.22223110645502078,"score_spread":0.20834198116830438,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2165865022","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":[0.31333253,0.001852072,0.6110606,0.0008114773,0.00017638472,0.00038413555,0.0011832834,0.06455406,0.0066455044],"genre_scores_gemma":[0.76937634,0.0004904836,0.22260065,0.0002978374,0.00007061304,0.00016407661,0.0017354595,0.0006395682,0.0046249935],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995721,0.000053393636,0.000029182645,0.00011468282,0.00016577965,0.00006489208],"domain_scores_gemma":[0.99921274,0.00035906446,0.00006265113,0.00011840418,0.00019251677,0.00005461679],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056461146,0.0008997044,0.00059428334,0.00071931706,0.00036606152,0.0007044789,0.0016008227,0.0005650758,0.002067906],"category_scores_gemma":[0.0028754864,0.00040424385,0.00036553928,0.0007805065,0.00042274658,0.0015516469,0.0008205461,0.0008559912,0.0005497047],"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":[0.0011485275,0.0005982829,0.012154805,0.00023785233,0.00010781286,0.00038661514,0.00026212283,0.3247591,0.06784656,0.0030755175,0.020203607,0.5692192],"study_design_scores_gemma":[0.00004332256,0.00006774885,0.00047729048,0.0000035645871,0.00000866529,0.000034280547,0.000020854877,0.98537934,0.011738284,0.0010195124,0.0011955043,0.000011554605],"about_ca_topic_score_codex":0.012977751,"about_ca_topic_score_gemma":0.019405011,"teacher_disagreement_score":0.012977751,"about_ca_system_score_codex":0.0008686288,"about_ca_system_score_gemma":0.0015904284,"threshold_uncertainty_score":0.0258044},"labels":[],"label_agreement":null},{"id":"W2166198323","doi":"10.1109/icde.1996.492113","title":"A hybrid object clustering strategy for large knowledge-based systems","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; University of Saskatchewan","keywords":"Computer science; Cluster analysis; Knowledge base; Granularity; Benchmark (surveying); Object (grammar); Data mining; Class (philosophy); Artificial intelligence; Programming language","score_opus":0.04290458978117614,"score_gpt":0.27762535105619723,"score_spread":0.2347207612750211,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2166198323","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":[0.24329013,0.00060150854,0.7452513,0.00028802088,0.000028369157,0.00030346523,0.00027197806,0.0038455136,0.0061198194],"genre_scores_gemma":[0.5294854,0.00023096021,0.4659066,0.00008149435,0.000015427575,0.00021023973,0.00069674343,0.00017462627,0.0031985494],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99894506,0.0002154992,0.000080277496,0.00015022706,0.0005117449,0.00009726398],"domain_scores_gemma":[0.9982729,0.00040767353,0.00010742482,0.0005890455,0.00049109786,0.00013174159],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011740392,0.0005478614,0.000688906,0.0012079121,0.0009675763,0.0020272501,0.001984721,0.00069067016,0.0014616519],"category_scores_gemma":[0.0027260324,0.00028157516,0.00029612757,0.0022358075,0.00065627805,0.0026699519,0.0013345706,0.000486102,0.00051921257],"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":[0.001085963,0.00060783623,0.0037803426,0.00044262817,0.0001478144,0.00039443796,0.0010050981,0.24294665,0.11915345,0.06531444,0.007781495,0.55733985],"study_design_scores_gemma":[0.00015105322,0.0007205954,0.0021581792,0.000030748553,0.000101454505,0.00040166272,0.0005863743,0.85668904,0.0896252,0.033307612,0.01613496,0.00009309811],"about_ca_topic_score_codex":0.0029850802,"about_ca_topic_score_gemma":0.0044288826,"teacher_disagreement_score":0.0029850802,"about_ca_system_score_codex":0.0011266458,"about_ca_system_score_gemma":0.0011387634,"threshold_uncertainty_score":0.008174419},"labels":[],"label_agreement":null},{"id":"W2166443874","doi":"10.1109/icde.2006.178","title":"XSEED: Accurate and Fast Cardinality Estimation for XPath Queries","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":61,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"XPath; Cardinality (data modeling); Computer science; Theoretical computer science; Algorithm; Data mining; XML; World Wide Web; XML database","score_opus":0.011320220610942008,"score_gpt":0.2552077315891909,"score_spread":0.2438875109782489,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2166443874","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":[0.038873173,0.0006524896,0.9470253,0.000215949,0.00011031457,0.00038089554,0.0028998058,0.00875676,0.0010853462],"genre_scores_gemma":[0.23423387,0.0005513241,0.7559378,0.000108876106,0.00009062363,0.0003601639,0.006472578,0.00048408922,0.0017605847],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99715745,0.0004673591,0.00046337218,0.0004380347,0.0013679678,0.00010584076],"domain_scores_gemma":[0.9929618,0.002388611,0.0007419586,0.002376372,0.0012979216,0.00023335902],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023384597,0.0009193679,0.0010235655,0.0020042984,0.00049024576,0.0018184441,0.0015916819,0.00057589443,0.0016915053],"category_scores_gemma":[0.011978524,0.0007308062,0.00054850744,0.0019239025,0.0004186037,0.004421679,0.0020327023,0.0008110451,0.00070157746],"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":[0.0011509162,0.00023304742,0.011969907,0.00071438163,0.00022988707,0.00042474474,0.0007103686,0.0932492,0.06866758,0.020644933,0.027989164,0.7740159],"study_design_scores_gemma":[0.00014137267,0.00037557454,0.0032885778,0.00007083625,0.00007272323,0.0004785875,0.00031348763,0.88462704,0.061991055,0.01833379,0.030204263,0.00010262253],"about_ca_topic_score_codex":0.0024597768,"about_ca_topic_score_gemma":0.0029189053,"teacher_disagreement_score":0.0024597768,"about_ca_system_score_codex":0.00062413496,"about_ca_system_score_gemma":0.0013047813,"threshold_uncertainty_score":0.01236707},"labels":[],"label_agreement":null},{"id":"W2166455512","doi":"10.1145/1559795.1559828","title":"Equivalence of nested queries with mixed semantics","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Conjunctive query; Equivalence (formal languages); Computer science; Encoding (memory); Theoretical computer science; Relational database; Semantics (computer science); Operational semantics; Mathematics; Discrete mathematics; Programming language; Information retrieval; Artificial intelligence","score_opus":0.009143238816432826,"score_gpt":0.2247818116203666,"score_spread":0.21563857280393375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2166455512","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":[0.15652806,0.00023744626,0.83552206,0.0011381501,0.000074104224,0.00030934648,0.0003413715,0.0014441956,0.0044054277],"genre_scores_gemma":[0.7390654,0.00021308365,0.25654432,0.00039010664,0.00011009646,0.00019856541,0.0008488052,0.00036266146,0.0022670277],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9801118,0.0055515533,0.0023777338,0.0034856722,0.006733357,0.0017398377],"domain_scores_gemma":[0.9576373,0.029453723,0.0024812948,0.004864456,0.004467784,0.0010954591],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012230389,0.0007642483,0.0013789106,0.0017666606,0.0014494066,0.0070594284,0.0029215447,0.0016056318,0.0026913623],"category_scores_gemma":[0.05787407,0.00087293546,0.002373044,0.0017457521,0.005966917,0.018099688,0.006149267,0.0032431474,0.00039467722],"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":[0.001193444,0.00041494277,0.005563215,0.0003585312,0.00016503235,0.0012584758,0.003183715,0.0536164,0.014258341,0.80850804,0.0018390703,0.109640844],"study_design_scores_gemma":[0.00007528242,0.00016846106,0.00048620568,0.000047242764,0.000091685,0.00029060032,0.000629418,0.1817657,0.019063862,0.794696,0.0026263245,0.000059145208],"about_ca_topic_score_codex":0.006389308,"about_ca_topic_score_gemma":0.003157827,"teacher_disagreement_score":0.012230389,"about_ca_system_score_codex":0.0027769976,"about_ca_system_score_gemma":0.0023233802,"threshold_uncertainty_score":0.06468123},"labels":[],"label_agreement":null},{"id":"W2167372420","doi":"10.1109/pccc.2009.5403839","title":"Caching techniques for XML message filtering","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; XPath; XML; XML Signature; Efficient XML Interchange; False sharing; XML database; XML Encryption; Streaming XML; Database; Distributed computing; Computer network; Cache; World Wide Web; CPU cache; Cache algorithms","score_opus":0.015530098162471709,"score_gpt":0.27885844072393634,"score_spread":0.26332834256146465,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2167372420","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":[0.015682466,0.0017361655,0.97616357,0.00025095555,0.000087007014,0.00016021196,0.00011922294,0.0032096787,0.0025906365],"genre_scores_gemma":[0.33588722,0.0020070903,0.652071,0.0003369413,0.00018866567,0.00027968723,0.00072954583,0.00042869285,0.008071221],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980496,0.0005240369,0.00022321938,0.00025812784,0.00073909777,0.0002059616],"domain_scores_gemma":[0.9938352,0.0021558388,0.00046279698,0.0020486952,0.0013615274,0.0001360343],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021358572,0.00067827286,0.001314063,0.0017523692,0.0013405299,0.0021109954,0.0019317146,0.0013321305,0.0024786545],"category_scores_gemma":[0.00823004,0.00057594577,0.0010962585,0.0026323413,0.00073283154,0.0039528683,0.0012429866,0.00092221616,0.000846479],"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":[0.0008530909,0.0002305907,0.0037001807,0.0006103825,0.00031363653,0.0004379199,0.00069588213,0.104603365,0.053475156,0.11764481,0.0154641615,0.7019708],"study_design_scores_gemma":[0.00015502408,0.0002758524,0.0016090105,0.000107582346,0.00027119162,0.00078155525,0.00018187455,0.83858454,0.06581913,0.047919597,0.044165492,0.00012917111],"about_ca_topic_score_codex":0.007880788,"about_ca_topic_score_gemma":0.007925481,"teacher_disagreement_score":0.007880788,"about_ca_system_score_codex":0.0017650435,"about_ca_system_score_gemma":0.0018562708,"threshold_uncertainty_score":0.015669823},"labels":[],"label_agreement":null},{"id":"W2167866332","doi":"","title":"HePToX: marrying XML and heterogeneity in your P2P databases","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":65,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Schema (genetic algorithms); XML; XML database; Information retrieval; Database; XML Schema Editor; Document Structure Description; Database schema; XML Schema (W3C); Peer-to-peer; World Wide Web; Database design; XML Encryption","score_opus":0.0429541083337019,"score_gpt":0.3032750260668475,"score_spread":0.2603209177331456,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2167866332","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":[0.04403462,0.001002308,0.90585417,0.0025628025,0.00046843378,0.00026789674,0.000741371,0.027258994,0.017809488],"genre_scores_gemma":[0.41637358,0.0013117695,0.5347553,0.0017835648,0.0003512265,0.0002488369,0.0028830224,0.002859149,0.039433565],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982333,0.00045203886,0.00010805214,0.0002640466,0.00077410846,0.00016837675],"domain_scores_gemma":[0.9972543,0.0006896637,0.00010994555,0.0014124486,0.0002477574,0.0002858668],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003493627,0.00042204713,0.0005745422,0.0006862796,0.0012046563,0.0039183525,0.0023066874,0.0011375849,0.005578838],"category_scores_gemma":[0.0056983973,0.0005620889,0.00037250825,0.0009987502,0.0014321444,0.00856452,0.006858063,0.0016507298,0.0014616763],"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":[0.0016348126,0.00022254365,0.004464183,0.0003769653,0.00014158219,0.0019118501,0.0028538145,0.017856274,0.038299747,0.26691872,0.110878244,0.5544413],"study_design_scores_gemma":[0.00029706978,0.0004818988,0.001611939,0.00014742377,0.00013023695,0.002327137,0.0014969516,0.20797917,0.05437009,0.25291926,0.4780206,0.0002182569],"about_ca_topic_score_codex":0.0025670242,"about_ca_topic_score_gemma":0.0025543226,"teacher_disagreement_score":0.005578838,"about_ca_system_score_codex":0.0006523336,"about_ca_system_score_gemma":0.0008970859,"threshold_uncertainty_score":0.018663108},"labels":[],"label_agreement":null},{"id":"W2167974132","doi":"10.1007/978-3-540-39964-3_6","title":"A Distributed Rule Mechanism for Multidatabase Systems","year":2003,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":13,"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; University of Toronto","funders":"","keywords":"Computer science; Distributed computing; Mechanism (biology); Active database; Distributed database; Distributed Computing Environment; Exception handling; Database; Data mining; Programming language","score_opus":0.018615448546552147,"score_gpt":0.24925304291487949,"score_spread":0.23063759436832734,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2167974132","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":[0.0038828219,0.00033369559,0.98545665,0.0002096041,0.00018236772,0.00016415074,0.00012423999,0.0075967535,0.0020496391],"genre_scores_gemma":[0.11619343,0.00044772073,0.8680714,0.00040664963,0.0003473828,0.00037868417,0.0008493079,0.0019459483,0.01135954],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9918399,0.0014512714,0.0014643554,0.0011656869,0.0035096882,0.000569093],"domain_scores_gemma":[0.9833598,0.0038287006,0.00052864844,0.009908284,0.0016373283,0.0007371885],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010624451,0.00077914627,0.0021635373,0.002062716,0.002666541,0.0075497557,0.011289964,0.0035384512,0.009306226],"category_scores_gemma":[0.014378679,0.0020367226,0.0021377748,0.0029957301,0.002679484,0.014246185,0.008483041,0.004786048,0.0033947004],"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":[0.0009917252,0.0006089927,0.0018227925,0.0005384931,0.0002918829,0.0008894364,0.0012558618,0.025353732,0.018414553,0.3694602,0.024881747,0.5554906],"study_design_scores_gemma":[0.0006616522,0.00038848887,0.0007518172,0.00021808842,0.00047816036,0.0015841511,0.00022104196,0.3280057,0.043027233,0.4856934,0.13867635,0.00029386437],"about_ca_topic_score_codex":0.0016732272,"about_ca_topic_score_gemma":0.0019070766,"teacher_disagreement_score":0.011289964,"about_ca_system_score_codex":0.0009917978,"about_ca_system_score_gemma":0.0018107807,"threshold_uncertainty_score":0.056188166},"labels":[],"label_agreement":null},{"id":"W2168592511","doi":"10.1109/icde.2009.39","title":"PSALM: Cardinality Estimation in the Presence of Fine-Grained Access Controls","year":2009,"lang":"en","type":"article","venue":"Proceedings - International Conference on Data Engineering","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Tuple; Cardinality (data modeling); Computer science; Exploit; Access control; Process (computing); Data access; Database; Information retrieval; Data mining; Theoretical computer science; Computer security; Mathematics; Programming language","score_opus":0.07268246504518185,"score_gpt":0.33779392153745974,"score_spread":0.2651114564922779,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2168592511","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":[0.032159436,0.0002255292,0.96515775,0.00014337903,0.000022736298,0.00006892699,0.00017034037,0.0016673271,0.000384427],"genre_scores_gemma":[0.57285005,0.00027143865,0.42495304,0.00013001269,0.00012583032,0.00020067973,0.00067357294,0.00019695934,0.00059834676],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9906784,0.0028644842,0.0007827502,0.0014286018,0.0036183512,0.00062737777],"domain_scores_gemma":[0.9524433,0.032006785,0.00408492,0.008212241,0.0025378787,0.00071491505],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006822181,0.0008132748,0.0014553901,0.0022261145,0.00078937237,0.0022704026,0.0023122851,0.0013200728,0.0007967071],"category_scores_gemma":[0.048806194,0.00081187405,0.0007298211,0.002437892,0.0014576585,0.005916325,0.0029520066,0.0022166143,0.00037886755],"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":[0.0013235796,0.00039264772,0.038736522,0.00037473408,0.00026472763,0.00064212887,0.001231311,0.52772933,0.041186877,0.0466651,0.0053998153,0.3360532],"study_design_scores_gemma":[0.000014091237,0.000045809,0.0010814352,0.000011265026,0.000011422352,0.00015287894,0.000052807205,0.981619,0.005272011,0.01078626,0.0009325743,0.000020459736],"about_ca_topic_score_codex":0.003808494,"about_ca_topic_score_gemma":0.002702204,"teacher_disagreement_score":0.006822181,"about_ca_system_score_codex":0.0011838333,"about_ca_system_score_gemma":0.0016931591,"threshold_uncertainty_score":0.036079586},"labels":[],"label_agreement":null},{"id":"W2168764534","doi":"10.1109/ideas.2003.1214912","title":"Extending XML-RL with update","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Efficient XML Interchange; XML validation; Streaming XML; XML Schema Editor; XML; Programming language; XML database; Document Structure Description; XML Schema (W3C); Data exchange; XML Encryption; Information retrieval; World Wide Web","score_opus":0.00784767869576776,"score_gpt":0.21507882937189413,"score_spread":0.20723115067612635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2168764534","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":[0.003392403,0.00047032643,0.94828117,0.00064265594,0.0002631525,0.0002273461,0.00049231254,0.031979464,0.014251148],"genre_scores_gemma":[0.11381155,0.0014401593,0.83898515,0.002332077,0.000520414,0.0005378455,0.003259175,0.011008327,0.028105313],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9926501,0.0019866824,0.0014878429,0.0010509053,0.0023490533,0.0004755071],"domain_scores_gemma":[0.99474406,0.002117723,0.00031718286,0.0016683236,0.0010045331,0.00014822658],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0066808187,0.0012629866,0.00090228673,0.0013009643,0.00072338764,0.0039857365,0.0032071886,0.0015259039,0.006198407],"category_scores_gemma":[0.009594479,0.00096463173,0.0020755117,0.0012812451,0.0020648176,0.009645934,0.005870554,0.0030036003,0.004376617],"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":[0.0004936659,0.00023963087,0.0017578831,0.001247096,0.000116935764,0.001770445,0.002722303,0.026145253,0.014716145,0.47224122,0.04297417,0.43557525],"study_design_scores_gemma":[0.00017043547,0.00017977212,0.00030388654,0.00026923264,0.00016488828,0.0011554848,0.0002753739,0.1562636,0.030918552,0.12661254,0.6834948,0.00019135675],"about_ca_topic_score_codex":0.003733082,"about_ca_topic_score_gemma":0.0025445665,"teacher_disagreement_score":0.0066808187,"about_ca_system_score_codex":0.0010479485,"about_ca_system_score_gemma":0.0018208511,"threshold_uncertainty_score":0.035331964},"labels":[],"label_agreement":null},{"id":"W2168773517","doi":"10.14778/2556549.2556568","title":"Expressiveness and complexity of order dependencies","year":2013,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada); York University; University of Toronto","funders":"","keywords":"Lexicographical order; Inference; Functional dependency; Tuple; Completeness (order theory); Computer science; Time complexity; SQL; Theoretical computer science; Dependency (UML); Class (philosophy); Rule of inference; Mathematics; Algorithm; Relational database; Discrete mathematics; Data mining; Artificial intelligence; Combinatorics; Programming language","score_opus":0.02515564258788441,"score_gpt":0.22424121724989018,"score_spread":0.19908557466200577,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2168773517","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":[0.34040356,0.0030785098,0.6165432,0.0075197727,0.00009593046,0.00025838066,0.0062181195,0.001289032,0.024593446],"genre_scores_gemma":[0.87127835,0.0019448391,0.11753345,0.00063154474,0.00021745353,0.00024963595,0.0035248627,0.0002624399,0.0043574446],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9919974,0.001620542,0.00092482165,0.0018535731,0.0028939277,0.00070961914],"domain_scores_gemma":[0.95797676,0.034866598,0.0018849559,0.0031033617,0.0015304589,0.0006378205],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003846278,0.00067100214,0.0010629285,0.0017225172,0.0013121769,0.006080746,0.0025887745,0.0015058904,0.0035912741],"category_scores_gemma":[0.02635304,0.001246442,0.0020106053,0.0034736143,0.0025661027,0.0141418455,0.0036125274,0.0040697935,0.00037268118],"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":[0.00035202413,0.00026724735,0.011607146,0.0009302885,0.00015054298,0.0006768813,0.0017179773,0.10555193,0.006507279,0.779049,0.006495326,0.08669441],"study_design_scores_gemma":[0.000034581833,0.000025691415,0.0010882108,0.000056740417,0.00006181056,0.0004949966,0.00031002017,0.12890756,0.003606773,0.85959476,0.005785014,0.00003384169],"about_ca_topic_score_codex":0.0035412044,"about_ca_topic_score_gemma":0.002841934,"teacher_disagreement_score":0.006080746,"about_ca_system_score_codex":0.0027901265,"about_ca_system_score_gemma":0.0018015492,"threshold_uncertainty_score":0.020341277},"labels":[],"label_agreement":null},{"id":"W2168910844","doi":"10.1109/icde.2007.368996","title":"A Lightweight Online Framework For Query Progress Indicators","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Query optimization; Joins; Overhead (engineering); Sargable; SQL; Query plan; Relational database management system; Data mining; Query by Example; Relational database; Web search query; Database; Information retrieval; Search engine; Programming language","score_opus":0.015438939233651597,"score_gpt":0.309161646226655,"score_spread":0.2937227069930034,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2168910844","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":[0.001883244,0.00007283022,0.99266887,0.00006284186,0.000010971729,0.00006789306,0.000085124004,0.0049170293,0.00023122692],"genre_scores_gemma":[0.14626691,0.0001663527,0.8507168,0.00007607137,0.00014106474,0.0003830239,0.00056856056,0.00069165084,0.0009896293],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9851466,0.0031768691,0.0013981998,0.002569935,0.00694272,0.0007656054],"domain_scores_gemma":[0.9645829,0.015097314,0.0050261044,0.00799228,0.00613253,0.0011688666],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01550688,0.0020957512,0.0026399486,0.004782976,0.0012528737,0.006361496,0.004896608,0.0016063673,0.0025378426],"category_scores_gemma":[0.04617638,0.0014429059,0.0013124445,0.0028850702,0.0017923829,0.0108975675,0.0045667575,0.0036221296,0.0014289531],"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":[0.0013892767,0.0005867518,0.010241495,0.0005123976,0.0001985536,0.0003413558,0.0011884585,0.170887,0.027250145,0.16136706,0.008972852,0.6170646],"study_design_scores_gemma":[0.00006118543,0.00017993414,0.00082207203,0.000046308676,0.000050077873,0.00019214686,0.0000902174,0.93917084,0.016116548,0.03419661,0.008963364,0.000110741894],"about_ca_topic_score_codex":0.006148818,"about_ca_topic_score_gemma":0.003540841,"teacher_disagreement_score":0.01550688,"about_ca_system_score_codex":0.0021139183,"about_ca_system_score_gemma":0.0043244273,"threshold_uncertainty_score":0.0820092},"labels":[],"label_agreement":null},{"id":"W2169424245","doi":"10.5555/1182635.1164177","title":"Answering tree pattern queries using views","year":2006,"lang":"en","type":"article","venue":"Very Large Data Bases","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":70,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Rewriting; Schema (genetic algorithms); Computer science; Time complexity; Tree (set theory); Theoretical computer science; Mathematics; Algorithm; Combinatorics; Programming language; Information retrieval","score_opus":0.06735454525073631,"score_gpt":0.29709100551204315,"score_spread":0.22973646026130684,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2169424245","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":[0.06990268,0.000971986,0.92400825,0.0006985263,0.00004466183,0.00012596998,0.00041417527,0.0012251046,0.0026087363],"genre_scores_gemma":[0.53073156,0.0013664652,0.46160507,0.0005156415,0.00021520571,0.00024010152,0.0021716172,0.0003971329,0.0027572692],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99623424,0.0013086679,0.00026471628,0.00079693896,0.0010893695,0.00030603402],"domain_scores_gemma":[0.98807794,0.008647798,0.00068630744,0.0016355102,0.00077119557,0.00018121282],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023971493,0.0005957028,0.0011964315,0.0009056213,0.000649592,0.0022405568,0.0017320508,0.0013661499,0.0016821304],"category_scores_gemma":[0.0125670545,0.00056865666,0.0012519641,0.0023282242,0.0011491337,0.008404446,0.0020251407,0.0018821806,0.0004800105],"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":[0.00093084143,0.0004938488,0.008150309,0.0010558042,0.00030355988,0.0010037287,0.0024136389,0.19154291,0.042370945,0.33952588,0.013674659,0.3985339],"study_design_scores_gemma":[0.000091807364,0.00029309443,0.00090466853,0.0000461338,0.00010786954,0.0006821129,0.00042462465,0.6291592,0.021055127,0.33566114,0.011526421,0.00004773899],"about_ca_topic_score_codex":0.0024204613,"about_ca_topic_score_gemma":0.0018390074,"teacher_disagreement_score":0.0024204613,"about_ca_system_score_codex":0.00092530646,"about_ca_system_score_gemma":0.0006984763,"threshold_uncertainty_score":0.012677491},"labels":[],"label_agreement":null},{"id":"W2169819748","doi":"10.1109/hicss.2000.927017","title":"Selecting a model interchange format: the SPOOL case study","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer science; Software engineering; RDF; Path (computing); Systems engineering; World Wide Web; Operating system; Engineering; Semantic Web","score_opus":0.04129178458318487,"score_gpt":0.2975806040125305,"score_spread":0.2562888194293456,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2169819748","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":[0.8294182,0.00040698034,0.11045343,0.011194032,0.0001795196,0.000978431,0.0010287219,0.0016541426,0.044686567],"genre_scores_gemma":[0.8683487,0.0004651436,0.11720076,0.0014610403,0.000048490154,0.0005776241,0.0011458719,0.0007125148,0.010039932],"study_design_codex":"design_other","study_design_gemma":"qualitative","domain_scores_codex":[0.98783,0.0073065646,0.00062032725,0.0005926648,0.002811848,0.00083861896],"domain_scores_gemma":[0.97700375,0.015919277,0.001057381,0.0028902213,0.0024205633,0.00070876774],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.016849171,0.0006693332,0.0005609553,0.0022103188,0.004489467,0.0049190805,0.0031513956,0.005263149,0.0040438427],"category_scores_gemma":[0.032430496,0.0006987086,0.00074872724,0.0027399072,0.0027915013,0.008668976,0.004172744,0.002693174,0.000984159],"study_design_candidate":"qualitative","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":[0.0029085614,0.006656897,0.067440696,0.0022459475,0.00019067519,0.058622874,0.11006047,0.027013002,0.022143265,0.2373498,0.08370319,0.3816646],"study_design_scores_gemma":[0.0007231422,0.0021741728,0.0102494685,0.0016745038,0.00026513886,0.03070279,0.12373643,0.10653541,0.077321,0.046113856,0.6000274,0.00047673547],"about_ca_topic_score_codex":0.0050049527,"about_ca_topic_score_gemma":0.008839944,"teacher_disagreement_score":0.016849171,"about_ca_system_score_codex":0.0030239753,"about_ca_system_score_gemma":0.0023673826,"threshold_uncertainty_score":0.08910799},"labels":[],"label_agreement":null},{"id":"W2170139410","doi":"10.1109/ccece.1998.685595","title":"Distributed query optimization using reduction filters","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Query optimization; Reduction (mathematics); Heuristic; Bloom filter; Distributed database; Process (computing); Sargable; Simple (philosophy); Query expansion; Distributed computing; Database; Data mining; Web search query; Information retrieval; Algorithm; Search engine; Artificial intelligence; Programming language","score_opus":0.03544025716389353,"score_gpt":0.2383878820329022,"score_spread":0.2029476248690087,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2170139410","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":[0.015126311,0.00023902356,0.9812045,0.00016165973,0.000025216745,0.00013265746,0.000067303095,0.0009976836,0.0020456403],"genre_scores_gemma":[0.31658828,0.0003412909,0.67471194,0.0001673285,0.000091566995,0.00035540527,0.00049240957,0.0002960276,0.006955671],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99793845,0.00052062277,0.00012644536,0.00042526083,0.0006937612,0.0002953837],"domain_scores_gemma":[0.9977011,0.0012687545,0.00012548953,0.00043999136,0.00038378633,0.00008083235],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00232365,0.0008976271,0.0017588867,0.0012625668,0.0010227901,0.0019239674,0.0014251942,0.0010356328,0.0030880354],"category_scores_gemma":[0.0043119662,0.00045970076,0.0009750131,0.0018535746,0.00081995665,0.0025240758,0.0018260655,0.001119814,0.00071083294],"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":[0.0008370825,0.00035211982,0.0016419794,0.00026390972,0.00015930811,0.00022378129,0.00038208615,0.45213154,0.02728444,0.0767669,0.011756118,0.42820066],"study_design_scores_gemma":[0.00007926092,0.00011023732,0.00024044816,0.000009733471,0.000036499772,0.00008415175,0.00007553204,0.9443264,0.009079172,0.041132905,0.004808026,0.000017610322],"about_ca_topic_score_codex":0.004391978,"about_ca_topic_score_gemma":0.0048499852,"teacher_disagreement_score":0.004391978,"about_ca_system_score_codex":0.0014717971,"about_ca_system_score_gemma":0.0015590837,"threshold_uncertainty_score":0.012288809},"labels":[],"label_agreement":null},{"id":"W2170699196","doi":"10.1109/ipdps.2009.5161064","title":"A partition-based approach to support streaming updates over persistent data in an active datawarehouse","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Tuple; Computer science; Partition (number theory); Overhead (engineering); Exploit; Data warehouse; Data stream; Relation (database); Join (topology); Locality; Distributed computing; Data mining; Parallel computing; Database; Operating system; Mathematics","score_opus":0.058066073068939975,"score_gpt":0.30807499269786087,"score_spread":0.2500089196289209,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2170699196","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":[0.039794702,0.00023613707,0.95656747,0.00012423961,0.00005981674,0.00012407963,0.00011522899,0.001981389,0.0009969928],"genre_scores_gemma":[0.3666259,0.000194982,0.63041383,0.000077952835,0.00009017393,0.00013703424,0.00042954338,0.00017553444,0.0018550149],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999435,0.00008966517,0.000056904708,0.0001315806,0.00021975796,0.00006696534],"domain_scores_gemma":[0.99808913,0.0005455592,0.00018147529,0.00063120463,0.00039570636,0.00015693998],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007624548,0.00038073203,0.0006862623,0.00086980243,0.0009640937,0.0015061729,0.0021009583,0.000609727,0.0012186808],"category_scores_gemma":[0.0033435107,0.00046209325,0.00042593307,0.0013717486,0.0005055896,0.0026778295,0.0013981469,0.00074389105,0.0005691609],"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":[0.0011795488,0.0006822773,0.0064701135,0.00033735996,0.00017118499,0.0005347529,0.0026089316,0.17089847,0.12923393,0.04073715,0.011767654,0.6353787],"study_design_scores_gemma":[0.00010015154,0.0005083824,0.0018521156,0.000022953605,0.00009101195,0.0005529227,0.00042098074,0.91697454,0.04326478,0.015063203,0.021076914,0.00007208157],"about_ca_topic_score_codex":0.0024112621,"about_ca_topic_score_gemma":0.0028170203,"teacher_disagreement_score":0.0024112621,"about_ca_system_score_codex":0.0004911984,"about_ca_system_score_gemma":0.00086588407,"threshold_uncertainty_score":0.004794419},"labels":[],"label_agreement":null},{"id":"W2171070728","doi":"10.1002/asi.20178","title":"An evaluation of novice end‐user computing performance: Data modeling, query writing, and comprehension","year":2005,"lang":"en","type":"article","venue":"Journal of the American Society for Information Science and Technology","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Query language; Sargable; Query expansion; Query optimization; RDF query language; Web query classification; Correctness; Query by Example; View; Information retrieval; Data modeling; Web search query; Database; Database design; Programming language; Search engine","score_opus":0.03697808276472805,"score_gpt":0.3335310400760095,"score_spread":0.29655295731128145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2171070728","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":[0.99875724,0.000022681344,0.00065991934,0.000021024722,0.0000034234042,0.00003704968,0.00003518719,0.000036769736,0.0004266735],"genre_scores_gemma":[0.9973463,0.000028825869,0.0018506575,0.000029817067,0.000005762469,0.000068255715,0.00013603248,0.000013008359,0.0005213099],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99682343,0.0015806456,0.00041367364,0.0004187747,0.00055149826,0.00021201551],"domain_scores_gemma":[0.9193835,0.05545139,0.0068597016,0.00474944,0.0070270807,0.006528893],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005609467,0.00055074284,0.0006183208,0.0006648856,0.0003116537,0.0013853428,0.00064464856,0.00064889994,0.002405027],"category_scores_gemma":[0.044541057,0.00023383352,0.00037285977,0.0003773419,0.0004950806,0.0012299868,0.0009940483,0.00080842664,0.0006434035],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.009796053,0.03150333,0.6070718,0.0010909621,0.00045166147,0.0006880168,0.026205355,0.008276344,0.060019862,0.00096638815,0.003477324,0.25045294],"study_design_scores_gemma":[0.00071706576,0.04729195,0.82528657,0.00017509877,0.00022821053,0.0007407445,0.006777421,0.057938434,0.055791557,0.0013636233,0.003457597,0.00023170222],"about_ca_topic_score_codex":0.0009349439,"about_ca_topic_score_gemma":0.0006786386,"teacher_disagreement_score":0.005609467,"about_ca_system_score_codex":0.0003833024,"about_ca_system_score_gemma":0.00047959705,"threshold_uncertainty_score":0.029666066},"labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low"},{"model":"gpt","categories":[],"domain":null,"study_design":"design_other","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low"}],"label_agreement":"split"},{"id":"W2171361281","doi":"10.1109/cmpsac.1979.762509","title":"An algorithm for tree-query membership of a distributed query","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":114,"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 Alberta","funders":"","keywords":"Joins; Computer science; Transitive closure; Query optimization; Spatial query; Algorithm; Join (topology); Query language; Sargable; Theoretical computer science; Graph; Data mining; Mathematics; Web search query; Search engine; Discrete mathematics; Information retrieval; Combinatorics","score_opus":0.018443163278605512,"score_gpt":0.2780235606922443,"score_spread":0.2595803974136388,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2171361281","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":[0.0028690037,0.00017624223,0.986312,0.00033037103,0.00007583721,0.0005582795,0.00039678888,0.0054836925,0.0037977307],"genre_scores_gemma":[0.05435363,0.00010900061,0.9381337,0.00018209517,0.000051408417,0.0005763364,0.0015038964,0.00044512303,0.0046446603],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9972971,0.0005526343,0.00025824702,0.00061185507,0.000982825,0.00029737692],"domain_scores_gemma":[0.99768,0.00090488174,0.0001332649,0.0005588319,0.0006002114,0.00012274514],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002134301,0.0009898405,0.0011436407,0.0015289859,0.0013068003,0.0023536326,0.0028367483,0.0018754,0.016242772],"category_scores_gemma":[0.006084029,0.0005777018,0.0008820095,0.0018448716,0.00093834894,0.0039509633,0.0036349331,0.0017370732,0.006592229],"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":[0.00088865514,0.0004407359,0.0012959088,0.00052574434,0.00011076269,0.00023024464,0.00074453175,0.031054806,0.014675401,0.10842973,0.06858222,0.7730213],"study_design_scores_gemma":[0.0004993933,0.00046674264,0.0005502796,0.00010271792,0.00008878327,0.00067238417,0.00037771923,0.7087933,0.016506223,0.15614888,0.115671284,0.00012233562],"about_ca_topic_score_codex":0.0030980455,"about_ca_topic_score_gemma":0.003137215,"teacher_disagreement_score":0.016242772,"about_ca_system_score_codex":0.0016049822,"about_ca_system_score_gemma":0.0022164034,"threshold_uncertainty_score":0.0543375},"labels":[],"label_agreement":null},{"id":"W2171577968","doi":"10.1109/edoc.1998.723254","title":"A development framework for building fine-grained CORBA/sup (R)/ applications","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Open Text (Canada)","funders":"","keywords":"Common Object Request Broker Architecture; Interoperable Object Reference; Computer science; Distributed object; Object (grammar); Object request broker; Distributed computing; Artificial intelligence","score_opus":0.03726696071768712,"score_gpt":0.2811678489222592,"score_spread":0.2439008882045721,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2171577968","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":[0.0010474992,0.000097017684,0.9784849,0.00014258893,0.000051391093,0.00037362758,0.000071706156,0.017514572,0.002216557],"genre_scores_gemma":[0.020596454,0.00024693017,0.97163695,0.00017181996,0.000038169048,0.00047477405,0.0005532638,0.002388007,0.003893605],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99806434,0.00040359775,0.00023520239,0.0003601865,0.0007061346,0.00023052123],"domain_scores_gemma":[0.9970162,0.0005103215,0.00020100921,0.0010159151,0.000867453,0.00038906868],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004719075,0.001083162,0.00066780567,0.0010607394,0.0012267821,0.0023119664,0.0030731221,0.0012362135,0.00463954],"category_scores_gemma":[0.0055110822,0.0013153696,0.0012202262,0.00074947934,0.001216417,0.0026070336,0.0022466923,0.0026763743,0.004756798],"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":[0.0002366673,0.0005477161,0.002277815,0.0010714183,0.00013133496,0.0011393871,0.0016178165,0.049491968,0.09490777,0.24379067,0.07054495,0.53424245],"study_design_scores_gemma":[0.00020691313,0.00042050646,0.0016809306,0.00032217638,0.00011184066,0.0013966158,0.00021080386,0.25374144,0.04465404,0.07812612,0.618936,0.00019256212],"about_ca_topic_score_codex":0.0053388383,"about_ca_topic_score_gemma":0.0036571906,"teacher_disagreement_score":0.0053388383,"about_ca_system_score_codex":0.0011545302,"about_ca_system_score_gemma":0.0033451682,"threshold_uncertainty_score":0.02495718},"labels":[],"label_agreement":null},{"id":"W2172023492","doi":"10.1109/ccece.2005.1557333","title":"Building data warehouses with incremental maintenance for decision support","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Data warehouse; Computer science; Decision support system; Dimensional modeling; Process (computing); Database; Data science; Online analytical processing; Data mining; Warehouse","score_opus":0.027409093640796196,"score_gpt":0.28704588150087074,"score_spread":0.25963678786007455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2172023492","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":[0.024816979,0.00045569564,0.96668464,0.0005078188,0.000048321566,0.0002963936,0.0003892912,0.0046405434,0.0021603627],"genre_scores_gemma":[0.09416047,0.0003719808,0.90374035,0.00007957564,0.000032909837,0.00012695213,0.00092557643,0.00013619092,0.00042607158],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.998591,0.00036063907,0.00022980438,0.00023938643,0.00049463945,0.000084581516],"domain_scores_gemma":[0.9949273,0.002009033,0.00036479585,0.0017270776,0.0008486693,0.00012313627],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002691636,0.0006632721,0.0006011821,0.0017390208,0.00062126014,0.0030964422,0.0022265213,0.00076648296,0.0012626108],"category_scores_gemma":[0.010749032,0.0008415226,0.0011401387,0.002393494,0.0005482464,0.0039994367,0.001840538,0.0012164598,0.0006708097],"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":[0.00033781907,0.0005343326,0.0072389366,0.00089743675,0.00035294564,0.0012905864,0.0015147366,0.112802476,0.028851045,0.055478193,0.014858244,0.7758433],"study_design_scores_gemma":[0.00015883097,0.0002794475,0.0021504143,0.00016071626,0.00035652702,0.0010097803,0.00045282714,0.8129906,0.044697158,0.08016494,0.057459813,0.0001188606],"about_ca_topic_score_codex":0.0017886789,"about_ca_topic_score_gemma":0.0023798132,"teacher_disagreement_score":0.0030964422,"about_ca_system_score_codex":0.00048394108,"about_ca_system_score_gemma":0.0011533062,"threshold_uncertainty_score":0.01423496},"labels":[],"label_agreement":null},{"id":"W2172255090","doi":"10.1145/604131.604132","title":"The essence of XML","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":91,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bell (Canada)","funders":"","keywords":"XPath; Computer science; XML Schema Editor; Document Structure Description; XQuery; XML validation; XML Schema (W3C); Programming language; Information retrieval; Streaming XML; Efficient XML Interchange; RELAX NG; XML; Document type definition; World Wide Web","score_opus":0.007156136601419543,"score_gpt":0.2220908766250974,"score_spread":0.21493474002367788,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2172255090","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":[0.0062095136,0.032453544,0.5992003,0.03829521,0.005170429,0.0004905732,0.0038792791,0.0035378444,0.3107632],"genre_scores_gemma":[0.15876447,0.045971688,0.5721908,0.028396746,0.0066832774,0.001278128,0.0077782064,0.0024417138,0.176495],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99434507,0.0018062075,0.0005734952,0.0008578605,0.0021449928,0.00027236878],"domain_scores_gemma":[0.9938698,0.002516529,0.00046521064,0.0020270112,0.00085510145,0.0002663858],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0041338876,0.00081039383,0.0007966631,0.0027103722,0.0021241442,0.009873691,0.0022875476,0.0032474047,0.011861395],"category_scores_gemma":[0.011754533,0.0005778995,0.0009147483,0.0046638143,0.0072363494,0.0146243945,0.0055583767,0.004628268,0.0069095655],"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":[0.000017117038,0.000012209499,0.00021384783,0.00023629816,0.00001696198,0.00012129923,0.0010462877,0.0004464433,0.00061949337,0.924259,0.019959137,0.0530518],"study_design_scores_gemma":[0.000006205039,0.000016461037,0.00014793476,0.00027726367,0.000009802385,0.00035291445,0.00029570278,0.0005364102,0.00044609074,0.24310759,0.75478613,0.00001746714],"about_ca_topic_score_codex":0.002615817,"about_ca_topic_score_gemma":0.0014189193,"teacher_disagreement_score":0.011861395,"about_ca_system_score_codex":0.0014926532,"about_ca_system_score_gemma":0.0028419732,"threshold_uncertainty_score":0.039680302},"labels":[],"label_agreement":null},{"id":"W2177409362","doi":"10.1109/iccitechnol.2011.5762659","title":"Relational universal index structure for evaluating XML twig queries","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; XML database; Twig; Relational database; Streaming XML; XML; Information retrieval; Efficient XML Interchange; Document Structure Description; Index (typography); XML validation; XML Encryption; XML Schema Editor; Database; Relational database management system; Data mining; World Wide Web","score_opus":0.08697232584387544,"score_gpt":0.2874972902655849,"score_spread":0.20052496442170947,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2177409362","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":[0.047858402,0.001203606,0.93359387,0.00026133814,0.00010978926,0.00046512403,0.0021771106,0.009294983,0.0050358223],"genre_scores_gemma":[0.2704164,0.00057405274,0.7206278,0.00013229252,0.000088137924,0.00041187607,0.0056072306,0.0003972644,0.0017449606],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99656904,0.00054783386,0.0007057494,0.0003355148,0.0016422755,0.0001994675],"domain_scores_gemma":[0.9942152,0.0019379884,0.0005646288,0.0013084667,0.0017571781,0.00021657473],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003029907,0.0005473695,0.0013139278,0.0034363724,0.0007856079,0.0027731168,0.0017162748,0.0007251723,0.0030450008],"category_scores_gemma":[0.012705721,0.00031428272,0.0005214434,0.004084319,0.0006306346,0.004158998,0.0015129887,0.0006599306,0.0010593988],"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":[0.001661267,0.00040555972,0.012633714,0.0012656536,0.00023570764,0.0007965959,0.0010448341,0.061662775,0.07870207,0.121193364,0.026158307,0.6942401],"study_design_scores_gemma":[0.0002622917,0.0009107967,0.004716284,0.00022212225,0.00022871466,0.0013196177,0.00067452237,0.7708914,0.10522304,0.0581212,0.05725512,0.00017488179],"about_ca_topic_score_codex":0.0039442265,"about_ca_topic_score_gemma":0.003868599,"teacher_disagreement_score":0.0039442265,"about_ca_system_score_codex":0.0013547344,"about_ca_system_score_gemma":0.0019131463,"threshold_uncertainty_score":0.016023874},"labels":[],"label_agreement":null},{"id":"W2184321453","doi":"10.82308/9761","title":"A proposed framework for analytical processing of information in the dairy industry using multidimensional data models","year":2013,"lang":"en","type":"article","venue":"eScholarship@McGill (McGill)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Data warehouse; Normalization (sociology); Computer science; Online analytical processing; Data extraction; Multidimensional data; Dairy industry; Data mining; Data science; Operations research; Engineering; Political science","score_opus":0.07184335346737536,"score_gpt":0.30094161828164884,"score_spread":0.22909826481427348,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2184321453","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":[0.0008316047,0.00033732373,0.9953112,0.0006973634,0.000050971244,0.0001390213,0.0001638982,0.00036172903,0.0021069818],"genre_scores_gemma":[0.037532073,0.0010205711,0.95707726,0.00025418092,0.00011652221,0.00039283515,0.0006374022,0.00007567406,0.0028934472],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9968882,0.0010307326,0.0003047921,0.00053854566,0.00104055,0.00019708382],"domain_scores_gemma":[0.9978951,0.0007513869,0.00019450086,0.0003132716,0.0006722889,0.00017342773],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005273589,0.0012742674,0.0010104948,0.002952728,0.0013451031,0.0073743165,0.0045609646,0.002390797,0.003757441],"category_scores_gemma":[0.0057545085,0.00082892075,0.0028242627,0.004290672,0.0015810061,0.0055408026,0.0041601215,0.002226601,0.0019273997],"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":[0.00008264884,0.0001522122,0.002167687,0.00047390253,0.0001878088,0.0010628678,0.000821806,0.18883166,0.0030633358,0.69420457,0.009291728,0.09965993],"study_design_scores_gemma":[0.000019165433,0.00005770209,0.00025910942,0.0001561321,0.000049483035,0.00029311675,0.000227658,0.8036473,0.0009794983,0.157078,0.0371886,0.000044203014],"about_ca_topic_score_codex":0.012144104,"about_ca_topic_score_gemma":0.011776083,"teacher_disagreement_score":0.012144104,"about_ca_system_score_codex":0.0021962046,"about_ca_system_score_gemma":0.0039946944,"threshold_uncertainty_score":0.027889788},"labels":[],"label_agreement":null},{"id":"W2184503304","doi":"","title":"Index Structures for XML Data","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; XML database; Efficient XML Interchange; Streaming XML; Relational database; XML Schema Editor; Database; Information retrieval; Document Structure Description; XML validation; Index (typography); XML; XML Encryption; Data mining; XML Schema (W3C); World Wide Web","score_opus":0.041260938229368646,"score_gpt":0.2905059993223343,"score_spread":0.24924506109296563,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2184503304","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":[0.0048785596,0.006559854,0.95451975,0.0017810585,0.0008992204,0.00065416336,0.0060137245,0.008136855,0.016556839],"genre_scores_gemma":[0.048863538,0.007146804,0.9061918,0.0012128965,0.00090096146,0.001299567,0.020624483,0.001815176,0.011944637],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9966389,0.0006228624,0.0007329404,0.00032075847,0.0015301232,0.000154387],"domain_scores_gemma":[0.9931318,0.0025316246,0.0008520185,0.0019815294,0.0012762762,0.00022674698],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024777928,0.00079505384,0.0011272571,0.004999098,0.0015479648,0.004571783,0.002020817,0.0014862707,0.010010329],"category_scores_gemma":[0.013596117,0.0006973725,0.0009572488,0.008563633,0.0010175873,0.0071146484,0.003106906,0.0022113454,0.0060433503],"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":[0.0002773331,0.00019692925,0.0013558656,0.0019667502,0.00014139956,0.0007463263,0.0010410704,0.008539138,0.018202,0.41337535,0.121699706,0.43245807],"study_design_scores_gemma":[0.00015022018,0.00024779583,0.0007686748,0.00063663576,0.00009469922,0.0017364591,0.0003252442,0.045366872,0.02076687,0.2738366,0.65594,0.00012993507],"about_ca_topic_score_codex":0.0012932934,"about_ca_topic_score_gemma":0.0013754115,"teacher_disagreement_score":0.010010329,"about_ca_system_score_codex":0.0010412371,"about_ca_system_score_gemma":0.001632628,"threshold_uncertainty_score":0.033487916},"labels":[],"label_agreement":null},{"id":"W2185709469","doi":"","title":"DEVELOPMENT OF NETWORK-BASED GISERVICES IN SUPPORT OF ONLINE GEOCOMPUTING","year":2000,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Geoprocessing; Computer science; Distributed GIS; Web service; Web Coverage Service; Database; World Wide Web; The Internet; Service (business); AM/FM/GIS; Geographic information system; Computer network; Web mapping; Web server; Geography; GIS applications; Cartography","score_opus":0.016334438817451384,"score_gpt":0.25632114202452383,"score_spread":0.23998670320707244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2185709469","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":[0.080386855,0.00053637585,0.8778228,0.00071603653,0.00027953205,0.0011440075,0.0002638122,0.014952395,0.023898134],"genre_scores_gemma":[0.22030511,0.0009007812,0.7581069,0.00033021037,0.0000919327,0.00053245935,0.0020025682,0.0008813331,0.016848724],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991171,0.00018383548,0.00008466345,0.00012253967,0.00033202162,0.00015981076],"domain_scores_gemma":[0.9974896,0.0004966657,0.00013100027,0.0006231601,0.00074484874,0.0005147083],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032700764,0.0003125014,0.00039485443,0.0007062636,0.0007969555,0.0017393817,0.0031606758,0.0011403201,0.0027768828],"category_scores_gemma":[0.003474012,0.00042802052,0.00041093436,0.00089102186,0.0004783757,0.0029218157,0.0018620196,0.0013916848,0.0016430059],"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":[0.00096085836,0.0021675467,0.01128762,0.0007780477,0.0001313944,0.0024401601,0.0024150412,0.04623238,0.11836371,0.15600199,0.023597673,0.6356237],"study_design_scores_gemma":[0.00035943594,0.00075745676,0.0077635227,0.0004699506,0.00017233915,0.0015537151,0.001153716,0.4070737,0.11759102,0.041514825,0.42136598,0.0002243396],"about_ca_topic_score_codex":0.0033995174,"about_ca_topic_score_gemma":0.003374211,"teacher_disagreement_score":0.0033995174,"about_ca_system_score_codex":0.00082981534,"about_ca_system_score_gemma":0.0020952795,"threshold_uncertainty_score":0.01729399},"labels":[],"label_agreement":null},{"id":"W2186137066","doi":"10.4018/978-1-61520-727-5.ch005","title":"Index Structures for XML Databases","year":2010,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; XML database; XML Schema Editor; Efficient XML Interchange; Streaming XML; XML validation; XML; Information retrieval; Search engine indexing; Document Structure Description; Database; XML Signature; XML Encryption; World Wide Web","score_opus":0.025896970270216216,"score_gpt":0.2763241173556742,"score_spread":0.250427147085458,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2186137066","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":[0.0024169097,0.02723625,0.835306,0.0038269646,0.0020073578,0.00087862683,0.005341707,0.007407609,0.11557859],"genre_scores_gemma":[0.033907708,0.032459415,0.8335263,0.0023650404,0.00171077,0.0018583146,0.0154360235,0.0024865814,0.07624989],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9974934,0.00055645173,0.00044260727,0.00024365383,0.0011421345,0.00012177123],"domain_scores_gemma":[0.9978119,0.00072867394,0.00017046121,0.000727006,0.00047443176,0.000087407396],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022762367,0.001037781,0.0011478799,0.0035986973,0.0018423663,0.008069556,0.002666404,0.0019519011,0.023933362],"category_scores_gemma":[0.008684409,0.0009273487,0.0011830211,0.0088604735,0.0013232864,0.01064818,0.003279217,0.0027243,0.017091332],"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":[0.000042538257,0.00004804786,0.0001887866,0.0008190323,0.000040981777,0.00021995888,0.00051699486,0.0020676423,0.001997944,0.67383826,0.09458248,0.22563742],"study_design_scores_gemma":[0.000025933803,0.000026742746,0.000117300464,0.0003864507,0.000022710388,0.00059497706,0.00013791432,0.0059752106,0.0015953206,0.27686518,0.7142222,0.00003003363],"about_ca_topic_score_codex":0.0014191712,"about_ca_topic_score_gemma":0.0013899428,"teacher_disagreement_score":0.023933362,"about_ca_system_score_codex":0.0018913614,"about_ca_system_score_gemma":0.0019800097,"threshold_uncertainty_score":0.08006501},"labels":[],"label_agreement":null},{"id":"W2186780785","doi":"","title":"AUTONOMIC WORKLOAD MANAGEMENT FOR DATABASE MANAGEMENT SYSTEMS","year":2014,"lang":"en","type":"dissertation","venue":"QSpace (Queen's University Library)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Queen's University","keywords":"Workload; Database; Computer science; Operating system","score_opus":0.007045717252563233,"score_gpt":0.19812953136388453,"score_spread":0.1910838141113213,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2186780785","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":[0.08951999,0.0016656964,0.8969617,0.00071000785,0.00010367949,0.00043100902,0.000088851586,0.004869116,0.0056500155],"genre_scores_gemma":[0.7818986,0.0006656727,0.21507075,0.0002005185,0.0001179974,0.00023839266,0.00021235523,0.00014564637,0.001450104],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99835867,0.0004317112,0.0001620148,0.00023567508,0.0006832181,0.00012874258],"domain_scores_gemma":[0.9979417,0.00060402934,0.00028686042,0.0003928227,0.0005953758,0.00017927641],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002707097,0.00049393845,0.0005769251,0.00078007375,0.0008707138,0.0025034954,0.0014946195,0.00045967693,0.00042572382],"category_scores_gemma":[0.005480262,0.00033213056,0.00029973235,0.0006716813,0.0004833178,0.0017794525,0.0009779022,0.0006953322,0.00017797697],"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":[0.00037804735,0.00047884282,0.015831541,0.00032928342,0.00011133444,0.00027626005,0.0010533571,0.17552122,0.06837853,0.037388947,0.0061647925,0.69408774],"study_design_scores_gemma":[0.000034489174,0.00016950638,0.0038958169,0.00006028871,0.00003901849,0.0001978639,0.00015646085,0.9495653,0.014909814,0.020825265,0.010101317,0.000044883804],"about_ca_topic_score_codex":0.001669456,"about_ca_topic_score_gemma":0.0015504793,"teacher_disagreement_score":0.002707097,"about_ca_system_score_codex":0.00088421244,"about_ca_system_score_gemma":0.00120685,"threshold_uncertainty_score":0.014316678},"labels":[],"label_agreement":null},{"id":"W2186907183","doi":"","title":"Queries, data, and statistics: pick two","year":2010,"lang":"en","type":"dissertation","venue":"TSpace","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Query optimization; Computer science; Sargable; Query plan; Web query classification; Online aggregation; View; Query expansion; RDF query language; Query language; Web search query; Spatial query; Relational database; Information retrieval; Data mining; Range query (database); Database; Database design; Search engine","score_opus":0.02144048080707711,"score_gpt":0.3554014626551403,"score_spread":0.33396098184806317,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2186907183","genre_codex":"methods","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":[0.022027362,0.0015481625,0.9542749,0.007178159,0.00023419173,0.00033713225,0.00032054208,0.0028297817,0.011249699],"genre_scores_gemma":[0.28954637,0.0013968177,0.6850612,0.0021440135,0.0004949665,0.00047316033,0.00086031767,0.0010512397,0.018971939],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9850826,0.004048496,0.0010059988,0.0028294544,0.005752098,0.0012813214],"domain_scores_gemma":[0.97985625,0.010687377,0.0013382747,0.0046159406,0.0017891093,0.0017130022],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00850763,0.0020767327,0.0022171754,0.0027606245,0.0029706694,0.013264405,0.0023301025,0.0041680825,0.008234922],"category_scores_gemma":[0.029869093,0.0023284766,0.002676798,0.0027654609,0.009243304,0.02339769,0.008378405,0.007622321,0.0021143158],"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":[0.0012727038,0.00043055275,0.007151981,0.00042992336,0.00016147915,0.00078585185,0.0021851745,0.021143494,0.008018747,0.80186754,0.0122804,0.14427212],"study_design_scores_gemma":[0.00023193465,0.0004525796,0.0033923509,0.0003186086,0.00025298054,0.001184512,0.0016197448,0.1734656,0.019315908,0.704993,0.094482765,0.0002900447],"about_ca_topic_score_codex":0.006294768,"about_ca_topic_score_gemma":0.0045111333,"teacher_disagreement_score":0.013264405,"about_ca_system_score_codex":0.003087108,"about_ca_system_score_gemma":0.0069269706,"threshold_uncertainty_score":0.044993162},"labels":[],"label_agreement":null},{"id":"W2188953292","doi":"","title":"Discovering and using semantics for database schemas","year":2007,"lang":"en","type":"article","venue":"TSpace","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Information retrieval; Database schema; Conceptual schema; Data integration; Data exchange; Semi-structured model; Information schema; Database; Relational database; XML Schema Editor; Schema (genetic algorithms); XML; Database design; World Wide Web","score_opus":0.04763921371606723,"score_gpt":0.37093696763246725,"score_spread":0.32329775391640003,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2188953292","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":[0.0046678404,0.0006867595,0.9891399,0.0012005351,0.000069896516,0.00024683503,0.00037746853,0.0013176894,0.0022930384],"genre_scores_gemma":[0.045874335,0.0012442241,0.94932854,0.0003114676,0.00005841975,0.00022775179,0.0014026786,0.0004678532,0.0010846752],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.97081304,0.010726543,0.0047060847,0.0032614453,0.0096555175,0.0008374594],"domain_scores_gemma":[0.9603746,0.017390275,0.0026657651,0.011793841,0.0070842886,0.00069119135],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.026209509,0.0014221566,0.0015169226,0.009106625,0.0030602845,0.015613484,0.005359144,0.0026726678,0.0025334503],"category_scores_gemma":[0.067490675,0.0027660038,0.004336574,0.0067356043,0.005064268,0.038144022,0.008951604,0.0047155507,0.0012360493],"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":[0.00006879682,0.00009059953,0.0022337297,0.00060702243,0.00013661712,0.0003484584,0.003556676,0.009794054,0.003034302,0.84416986,0.0040386333,0.13192125],"study_design_scores_gemma":[0.000060749007,0.000080177066,0.0004441118,0.0010259147,0.00016132902,0.00083562924,0.0025905678,0.11279051,0.016508127,0.70352453,0.16185407,0.00012422142],"about_ca_topic_score_codex":0.0051993574,"about_ca_topic_score_gemma":0.005205663,"teacher_disagreement_score":0.026209509,"about_ca_system_score_codex":0.0036816667,"about_ca_system_score_gemma":0.007585525,"threshold_uncertainty_score":0.13861078},"labels":[],"label_agreement":null},{"id":"W2189589159","doi":"","title":"Discovery of causality and acausality from temporal sequential data","year":2005,"lang":"en","type":"dissertation","venue":"oURspace (University of Regina)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Merge (version control); Causality (physics); Computer science; Set (abstract data type); Data mining; Sequence (biology); Quality (philosophy); Theoretical computer science; Artificial intelligence; Programming language; Information retrieval; Epistemology","score_opus":0.028240577352422743,"score_gpt":0.26147808510744636,"score_spread":0.2332375077550236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2189589159","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":[0.037635747,0.0005389121,0.9577522,0.0005395405,0.00005053626,0.00030485695,0.0010677015,0.0011515291,0.0009588776],"genre_scores_gemma":[0.17019266,0.0007054954,0.82421935,0.00016990316,0.00011335987,0.00033276275,0.003124525,0.00021639679,0.00092549645],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98130155,0.0048646554,0.0023352138,0.0037250903,0.0073493626,0.00042412072],"domain_scores_gemma":[0.8434847,0.12160499,0.011473906,0.013320212,0.008988708,0.0011274844],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.014618464,0.0011149596,0.0016955757,0.008423334,0.00168243,0.0047386982,0.002259254,0.001224897,0.0021922563],"category_scores_gemma":[0.110593,0.0014877009,0.0028758736,0.004760061,0.0026688385,0.009755792,0.0031091087,0.0030783096,0.0005399298],"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":[0.0009052207,0.0004318181,0.041644026,0.0020788934,0.00057671865,0.0014488221,0.004577781,0.051398955,0.011741409,0.18303338,0.0035256022,0.6986374],"study_design_scores_gemma":[0.00016748557,0.000288171,0.0067687393,0.0005979852,0.00032922262,0.0010850679,0.0012502391,0.39127716,0.020139944,0.54603726,0.031876367,0.00018234996],"about_ca_topic_score_codex":0.00372815,"about_ca_topic_score_gemma":0.004962144,"teacher_disagreement_score":0.014618464,"about_ca_system_score_codex":0.0012522688,"about_ca_system_score_gemma":0.0038674506,"threshold_uncertainty_score":0.0773108},"labels":[],"label_agreement":null},{"id":"W2197954473","doi":"","title":"Accelerating analytic queries in OLTP environment using DB2 shadow tables","year":2014,"lang":"en","type":"article","venue":"Computer Science and Software Engineering","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada)","funders":"","keywords":"Online transaction processing; Online analytical processing; Computer science; Transaction processing; Database; Shadow (psychology); Lag; Transactional leadership; Business intelligence; Data warehouse; Database transaction; Operating system","score_opus":0.013789970991884762,"score_gpt":0.20811854441318228,"score_spread":0.19432857342129753,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2197954473","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":[0.108013995,0.0025978659,0.6860771,0.00079117017,0.00068074703,0.00047639987,0.006191844,0.17889291,0.01627802],"genre_scores_gemma":[0.43989912,0.001145971,0.53266776,0.00043280702,0.00023470336,0.00027825858,0.012064301,0.0043571573,0.008919832],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9968977,0.00041183035,0.00031291967,0.0006673777,0.0013379696,0.00037220694],"domain_scores_gemma":[0.99427104,0.0015499404,0.00026825018,0.002139298,0.0013695764,0.0004018982],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022973074,0.0017747815,0.0010200551,0.002232522,0.0011678793,0.0054527754,0.0029409467,0.000677932,0.010912976],"category_scores_gemma":[0.007598153,0.0010440989,0.0007536871,0.004449649,0.00051108614,0.006646633,0.0029608756,0.0014761025,0.005155437],"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":[0.0050435276,0.0008786129,0.021145368,0.0010708133,0.00034935478,0.001358645,0.0015339628,0.044599485,0.08531756,0.027885146,0.10631745,0.7045001],"study_design_scores_gemma":[0.00067120756,0.0006485119,0.0063823424,0.00011483905,0.00021860168,0.00080678257,0.00088626274,0.7491995,0.09886966,0.02397223,0.11803074,0.00019927784],"about_ca_topic_score_codex":0.012114758,"about_ca_topic_score_gemma":0.008098957,"teacher_disagreement_score":0.012114758,"about_ca_system_score_codex":0.0012394045,"about_ca_system_score_gemma":0.0027965007,"threshold_uncertainty_score":0.036507547},"labels":[],"label_agreement":null},{"id":"W2198114485","doi":"10.3233/978-1-60750-588-4-686","title":"Ghost Charts and Shadow Records: Implication for System Design","year":2010,"lang":"en","type":"article","venue":"Studies in health technology and informatics","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Shadow (psychology); Computer science; Data science; Psychology; Psychoanalysis","score_opus":0.04522201087327562,"score_gpt":0.3446843461079621,"score_spread":0.2994623352346865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2198114485","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":[0.12170591,0.0018447587,0.81651115,0.027521636,0.00040453565,0.0019355976,0.0003383889,0.0018751423,0.027862785],"genre_scores_gemma":[0.54736143,0.0005182162,0.44605508,0.0016352641,0.00008390917,0.0010861092,0.00019607578,0.00025256298,0.0028114065],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9092197,0.07164386,0.0050070807,0.0032811787,0.009239857,0.0016084487],"domain_scores_gemma":[0.64721656,0.30330673,0.011619537,0.018935317,0.01601036,0.0029115716],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.051217873,0.00062296545,0.0009011561,0.0014305462,0.003524157,0.011843262,0.0028232504,0.003578894,0.0057215677],"category_scores_gemma":[0.27570325,0.0014069076,0.0007255414,0.0019356036,0.0103854565,0.019769887,0.005193158,0.0025310018,0.0007992362],"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":[0.0014297101,0.0005831228,0.038393464,0.0043355795,0.00020856885,0.001300652,0.12675525,0.026187487,0.0048742765,0.43427122,0.014211551,0.34744906],"study_design_scores_gemma":[0.0009309708,0.0020780663,0.011712653,0.002804979,0.00039150822,0.002515985,0.054220576,0.13431108,0.009590882,0.6419762,0.1390468,0.00042032433],"about_ca_topic_score_codex":0.005064252,"about_ca_topic_score_gemma":0.0035335252,"teacher_disagreement_score":0.051217873,"about_ca_system_score_codex":0.00375765,"about_ca_system_score_gemma":0.00912368,"threshold_uncertainty_score":0.2708692},"labels":[],"label_agreement":null},{"id":"W2199534348","doi":"10.1109/bigdata.2015.7363783","title":"Slingshot: A modular framework for designing data processing systems","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Database; Online transaction processing; Relational database; Leverage (statistics); Relational database management system; Flexibility (engineering); Modular design; Online analytical processing; Computer architecture; Transaction processing; Data warehouse; Programming language; Database transaction; Artificial intelligence","score_opus":0.1895178401194428,"score_gpt":0.3517411089889238,"score_spread":0.162223268869481,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2199534348","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":[0.0015505537,0.00020653092,0.9619753,0.00012463468,0.000036261426,0.00025219627,0.0007417542,0.03212319,0.0029896842],"genre_scores_gemma":[0.030910682,0.00053273985,0.9482279,0.00030854472,0.000048374048,0.00076710805,0.004205605,0.0082108965,0.0067882854],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986137,0.00021397987,0.00017730743,0.00026513528,0.00056678127,0.00016317355],"domain_scores_gemma":[0.9989649,0.0003514083,0.00007266688,0.00030726704,0.00019709943,0.00010673589],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022705605,0.0015336499,0.0007955741,0.0013635631,0.0007071657,0.003637934,0.0040894174,0.0012944908,0.011843759],"category_scores_gemma":[0.0034740912,0.001999752,0.002705771,0.0008748898,0.0015436485,0.003926673,0.0032541116,0.0025621513,0.0060907085],"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":[0.0007731048,0.00034750355,0.0037434157,0.0027674886,0.00046386133,0.0013195163,0.002061443,0.12037408,0.05153235,0.23514348,0.12172775,0.45974603],"study_design_scores_gemma":[0.00031224894,0.00026601664,0.0013710735,0.00047886168,0.00017193677,0.0010373715,0.00026111756,0.31227818,0.04319255,0.11376211,0.5266364,0.00023216702],"about_ca_topic_score_codex":0.0036048377,"about_ca_topic_score_gemma":0.0051226234,"teacher_disagreement_score":0.011843759,"about_ca_system_score_codex":0.0010280242,"about_ca_system_score_gemma":0.0021351927,"threshold_uncertainty_score":0.039621353},"labels":[],"label_agreement":null},{"id":"W2205888399","doi":"10.1007/978-3-642-22913-8_13","title":"Integrating Content and Structure into a Comprehensive Framework for XML Document Similarity Represented in 3D Space","year":2011,"lang":"en","type":"book-chapter","venue":"Studies in computational intelligence","topic":"Advanced Database Systems and Queries","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":"Western University; University of Calgary","funders":"","keywords":"Similarity (geometry); Information retrieval; XML; Computer science; Document Structure Description; Space (punctuation); Content (measure theory); Artificial intelligence; World Wide Web; Mathematics","score_opus":0.1521001211996631,"score_gpt":0.3777508043083698,"score_spread":0.22565068310870673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2205888399","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":[0.0016194192,0.00030813564,0.9955421,0.00013171304,0.00003201106,0.00006025904,0.00010899709,0.0007276816,0.0014697064],"genre_scores_gemma":[0.043360747,0.0006182687,0.95293546,0.0000861527,0.00006364903,0.00018212125,0.0005224855,0.00023798211,0.0019931537],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99838996,0.00031222677,0.00023980615,0.00021417056,0.0007783959,0.000065437795],"domain_scores_gemma":[0.9984902,0.00040551403,0.0001401917,0.00039535135,0.00046698976,0.00010175894],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020297843,0.0006480143,0.0011919797,0.0042971307,0.0010347806,0.0043474566,0.0025232814,0.0014657695,0.0027117792],"category_scores_gemma":[0.005304677,0.0006603537,0.0017782671,0.004697873,0.0021474436,0.00771933,0.0033387933,0.0015438609,0.0012067575],"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":[0.000042445397,0.00007812787,0.0011317338,0.00032541115,0.00008417745,0.00025846245,0.0010063319,0.02726901,0.008283452,0.69454265,0.0066324105,0.26034576],"study_design_scores_gemma":[0.000015958218,0.00011612768,0.0010874628,0.0002218388,0.00013387596,0.0008563875,0.000537988,0.36882755,0.010337667,0.52066994,0.09710967,0.00008562997],"about_ca_topic_score_codex":0.0043557202,"about_ca_topic_score_gemma":0.005624688,"teacher_disagreement_score":0.0043557202,"about_ca_system_score_codex":0.0012656956,"about_ca_system_score_gemma":0.0013839488,"threshold_uncertainty_score":0.010734677},"labels":[],"label_agreement":null},{"id":"W2207319399","doi":"","title":"Automata methods and techniques for graph-structured data","year":2011,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Theoretical computer science; Graph database; Materialized view; Time complexity; Graph; Focus (optics); Automaton; Data mining; Algorithm; Database design; View","score_opus":0.05464972520677573,"score_gpt":0.39504877275826084,"score_spread":0.3403990475514851,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2207319399","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":[0.00086468225,0.0008088219,0.9946878,0.00067546574,0.00014809512,0.00013729896,0.00023933263,0.00052625546,0.0019122313],"genre_scores_gemma":[0.050195366,0.0022236502,0.9394886,0.0007217559,0.00051817537,0.0009641058,0.0010411349,0.00042445015,0.004422748],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.992144,0.0024878292,0.0010920459,0.001685309,0.0022878207,0.00030295824],"domain_scores_gemma":[0.9805699,0.013502478,0.00083939906,0.0031712505,0.0016202084,0.00029665898],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0058265054,0.001858403,0.0016186206,0.0050910288,0.0017742284,0.005597843,0.004377309,0.0029299995,0.007055115],"category_scores_gemma":[0.021616885,0.0017098173,0.006724999,0.0043498185,0.0045021223,0.010248703,0.0057976684,0.0077747293,0.0027523322],"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":[0.000050011684,0.000055978493,0.0004435912,0.00058164285,0.00013230127,0.00020808175,0.0008410659,0.053052858,0.0016005937,0.8724798,0.005548921,0.06500508],"study_design_scores_gemma":[0.000028000963,0.000025595635,0.00006952176,0.0000977875,0.000032012278,0.0000963577,0.000107537846,0.16513221,0.00077003683,0.8161972,0.017413678,0.000030095818],"about_ca_topic_score_codex":0.0048267613,"about_ca_topic_score_gemma":0.0043302043,"teacher_disagreement_score":0.007055115,"about_ca_system_score_codex":0.0036167607,"about_ca_system_score_gemma":0.0024600646,"threshold_uncertainty_score":0.030813873},"labels":[],"label_agreement":null},{"id":"W2211823484","doi":"10.1109/icde.1994.283003","title":"Exploiting uniqueness in query optimization","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Query optimization; Computer science; Uniqueness; Sargable; Query language; Web search query; Information retrieval; Mathematics; Search engine","score_opus":0.027190032918063062,"score_gpt":0.21861618337538868,"score_spread":0.1914261504573256,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2211823484","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":[0.055558626,0.0006235853,0.93414843,0.0009579189,0.000053068077,0.00019137868,0.00018529558,0.001956421,0.0063252407],"genre_scores_gemma":[0.5625144,0.00051500835,0.43226653,0.0007124821,0.00011367447,0.00021085207,0.00038225352,0.0007332153,0.0025515014],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9864028,0.0054215835,0.0011453164,0.0018095608,0.0035141564,0.0017066858],"domain_scores_gemma":[0.9747014,0.01815338,0.0011885315,0.0038976688,0.0017605766,0.00029845347],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010689168,0.0010518673,0.0015721921,0.0016962554,0.0020922727,0.0037742208,0.002580061,0.0015864915,0.00326538],"category_scores_gemma":[0.036517262,0.0011571319,0.0020372742,0.0024708596,0.0048666573,0.013449535,0.008625708,0.0023397862,0.0009151267],"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":[0.001382447,0.0003187306,0.018075142,0.00087702717,0.00035439292,0.0016778848,0.0018126401,0.102044985,0.032164406,0.5295329,0.008859485,0.30289993],"study_design_scores_gemma":[0.00015463709,0.0004228876,0.001699834,0.00015193464,0.00029317985,0.0013698493,0.00082389824,0.38680834,0.07128573,0.51998436,0.01683036,0.00017499716],"about_ca_topic_score_codex":0.0026757964,"about_ca_topic_score_gemma":0.0021279398,"teacher_disagreement_score":0.010689168,"about_ca_system_score_codex":0.0012008899,"about_ca_system_score_gemma":0.0027049633,"threshold_uncertainty_score":0.056530416},"labels":[],"label_agreement":null},{"id":"W2212059455","doi":"","title":"Sibling-First Data Organization: For Efficient XML Data Processing","year":2010,"lang":"en","type":"book","venue":"The Atrium (University of Guelph)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"XPath; Computer science; Streaming XML; XML database; Simple API for XML; XML validation; Instruction prefetch; Information retrieval; Database; Efficient XML Interchange; XML Schema (W3C); Parsing; XML; XML Signature; XML Encryption; Data mining; Programming language; Operating system","score_opus":0.03919957152339935,"score_gpt":0.242517714357651,"score_spread":0.20331814283425165,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2212059455","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":[0.0065842792,0.009826742,0.91771287,0.001099648,0.001011298,0.0004945316,0.0015058449,0.009856151,0.051908582],"genre_scores_gemma":[0.031536806,0.005933886,0.8823318,0.0009533763,0.00039845635,0.00024350038,0.0042602066,0.0015637912,0.07277816],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99947876,0.000057494988,0.000042188974,0.000086396336,0.00029598974,0.000039254606],"domain_scores_gemma":[0.99952185,0.000086651824,0.000026697882,0.00017196688,0.00016273595,0.0000301263],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000581897,0.00052163977,0.000447466,0.0011699409,0.0004091417,0.0013273282,0.0014330654,0.000607567,0.013142652],"category_scores_gemma":[0.0012877377,0.00042344513,0.00059118157,0.0042060846,0.00036953695,0.0029568693,0.0010835174,0.0007908778,0.008523411],"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":[0.00009049009,0.000045214314,0.00041396107,0.000721496,0.000027199012,0.0002186266,0.00024794982,0.0020057734,0.019957935,0.051490527,0.17751196,0.7472689],"study_design_scores_gemma":[0.000049876526,0.0000911838,0.0007230116,0.00013067956,0.000027466054,0.0017641826,0.00008005043,0.021569137,0.020586466,0.024919305,0.9300177,0.00004100814],"about_ca_topic_score_codex":0.0014536933,"about_ca_topic_score_gemma":0.0022833082,"teacher_disagreement_score":0.013142652,"about_ca_system_score_codex":0.0006835268,"about_ca_system_score_gemma":0.0010080914,"threshold_uncertainty_score":0.04396653},"labels":[],"label_agreement":null},{"id":"W2222013231","doi":"10.1007/978-3-642-41924-9_6","title":"Is Traditional Conceptual Modeling Becoming Obsolete?","year":2013,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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":"Memorial University of Newfoundland","funders":"","keywords":"Computer science; Conceptual model; Conceptual framework; Conceptual schema; Domain model; Domain (mathematical analysis); Data science; Management science; Systems modeling; Knowledge management; Software engineering; Domain knowledge; Engineering; Database; Epistemology","score_opus":0.06451264271496192,"score_gpt":0.25754507734681814,"score_spread":0.1930324346318562,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2222013231","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":[0.021752521,0.023297722,0.468581,0.320709,0.0048860162,0.000057715857,0.00081752246,0.003425244,0.15647328],"genre_scores_gemma":[0.6022359,0.035065223,0.2542701,0.05044605,0.0075764447,0.00029173438,0.0022655881,0.0027793404,0.045069605],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9864166,0.005351959,0.00073189783,0.0016959151,0.0052296305,0.00057410577],"domain_scores_gemma":[0.94067043,0.033346366,0.0023319512,0.0138854245,0.008416203,0.001349568],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.024672914,0.0007096809,0.0011787422,0.0029637897,0.0016031883,0.013544101,0.0055358973,0.0033486504,0.013542299],"category_scores_gemma":[0.045559306,0.0009579782,0.0012598329,0.0039963056,0.0131393755,0.046404127,0.005026806,0.007193791,0.005443696],"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":[0.000034291326,0.00003636266,0.0006145652,0.00021958892,0.000025519825,0.00003733373,0.0009473463,0.0005200633,0.00019583595,0.85600686,0.02036464,0.120997526],"study_design_scores_gemma":[0.0000150193255,0.00001429147,0.00022918003,0.00023900782,0.000022563801,0.00012877617,0.00083799084,0.0030688115,0.00026999117,0.84677607,0.14837915,0.000019035304],"about_ca_topic_score_codex":0.005016892,"about_ca_topic_score_gemma":0.0030478192,"teacher_disagreement_score":0.024672914,"about_ca_system_score_codex":0.0045384336,"about_ca_system_score_gemma":0.0052053193,"threshold_uncertainty_score":0.1304844},"labels":[],"label_agreement":null},{"id":"W2225413612","doi":"10.1007/978-1-4614-0992-2_8","title":"Adopting XML for Large-Scale Information","year":2011,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Efficient XML Interchange; XML database; Computer science; XML Schema Editor; XML validation; Streaming XML; XML Signature; XML Encryption; Document Structure Description; XML framework; XML; Database; Information retrieval; World Wide Web","score_opus":0.02274660689841248,"score_gpt":0.22800844686739508,"score_spread":0.2052618399689826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2225413612","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":[0.0025410627,0.021311829,0.7542809,0.0064791627,0.002009847,0.00019129996,0.00053836586,0.004349933,0.2082976],"genre_scores_gemma":[0.030498372,0.034048542,0.6446018,0.0036937338,0.0012539594,0.00031206236,0.002366701,0.002562154,0.28066263],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988864,0.00023482795,0.00011248208,0.00013304307,0.0005795409,0.000053707277],"domain_scores_gemma":[0.9988532,0.00055063487,0.000036241254,0.0003553393,0.00017275923,0.000031831074],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00162681,0.0009320199,0.00051281333,0.0014562233,0.000638973,0.0050971988,0.0014906512,0.0015163241,0.014735223],"category_scores_gemma":[0.0030234882,0.000711048,0.0006817254,0.004386577,0.0013530297,0.011832212,0.0024716766,0.0028434896,0.008752671],"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":[0.000014562473,0.000034956218,0.00013677157,0.0004317157,0.000016603719,0.00017018664,0.00071966584,0.0013258309,0.0035446004,0.5041162,0.089156784,0.40033215],"study_design_scores_gemma":[0.0000068385025,0.000017574463,0.0001406038,0.00023014456,0.000019541832,0.0004648747,0.00015333376,0.0048263385,0.003118443,0.16243805,0.8285617,0.000022563669],"about_ca_topic_score_codex":0.0011407601,"about_ca_topic_score_gemma":0.0013341671,"teacher_disagreement_score":0.014735223,"about_ca_system_score_codex":0.0009604462,"about_ca_system_score_gemma":0.0008630645,"threshold_uncertainty_score":0.049294233},"labels":[],"label_agreement":null},{"id":"W2227742643","doi":"","title":"Online Internet Communication Using an XML Compressor","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Acadia University","funders":"","keywords":"Computer science; XML; Efficient XML Interchange; Streaming XML; The Internet; XML Schema Editor; Database; World Wide Web; Information retrieval","score_opus":0.08526161187156972,"score_gpt":0.3315921807968003,"score_spread":0.2463305689252306,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2227742643","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":[0.3873468,0.0009803339,0.5355973,0.001698148,0.00032147177,0.00063366443,0.0010617479,0.05073446,0.02162613],"genre_scores_gemma":[0.84929144,0.00028201166,0.13888077,0.00042207402,0.00016819751,0.00015727482,0.0010741536,0.0007416525,0.00898237],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99875355,0.00022873469,0.000100837955,0.00014816807,0.0006403629,0.00012842077],"domain_scores_gemma":[0.9965911,0.0011639849,0.00022697894,0.0011683947,0.00065766374,0.00019180412],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00089053804,0.00064931257,0.0005318766,0.0011170215,0.0007827265,0.0013619569,0.0013523361,0.00061195734,0.0074749077],"category_scores_gemma":[0.0033813657,0.00024080837,0.00020956575,0.0015555115,0.0008026081,0.002796796,0.0014437098,0.0008773746,0.00083402515],"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":[0.004401409,0.0007273863,0.009359415,0.0003493041,0.0001349145,0.0016336439,0.0010141146,0.02643678,0.18990631,0.027690306,0.034224045,0.7041225],"study_design_scores_gemma":[0.00026205368,0.0006119934,0.0025697052,0.000061058236,0.00008891472,0.0009307446,0.00042437212,0.5246195,0.41337702,0.009353494,0.047591243,0.00010991215],"about_ca_topic_score_codex":0.0023142232,"about_ca_topic_score_gemma":0.0017840221,"teacher_disagreement_score":0.0074749077,"about_ca_system_score_codex":0.0008741211,"about_ca_system_score_gemma":0.0007404425,"threshold_uncertainty_score":0.025006056},"labels":[],"label_agreement":null},{"id":"W2240092424","doi":"10.1007/978-1-4419-8834-8_14","title":"Parallel Database Systems","year":2011,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Online analytical processing; Online transaction processing; Computer science; Database; Transaction processing; Data warehouse; Database transaction; Terabyte; Line (geometry); Operating system","score_opus":0.04413962934122752,"score_gpt":0.23718189471453271,"score_spread":0.1930422653733052,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2240092424","genre_codex":"methods","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":[0.0026208272,0.016547622,0.51063615,0.0030166344,0.0031395087,0.00046289386,0.0023133573,0.014291999,0.44697103],"genre_scores_gemma":[0.03281276,0.019186443,0.27337962,0.0015155288,0.0019561788,0.00044915927,0.0076840413,0.002640218,0.6603761],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99865025,0.00014576643,0.00009364805,0.00027549217,0.0007539569,0.00008084423],"domain_scores_gemma":[0.9989925,0.00016241215,0.000027247243,0.0004771112,0.00028660626,0.000054021155],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000959558,0.001390732,0.0012365927,0.0014729039,0.0011285723,0.004770631,0.002170713,0.0009388381,0.067780346],"category_scores_gemma":[0.002373876,0.001238224,0.0007581305,0.00383722,0.0009767774,0.005365744,0.002365369,0.002389336,0.054007076],"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":[0.00007254722,0.00006785465,0.0001689755,0.0005108924,0.000046274035,0.000081149745,0.00015500668,0.0023330622,0.0032171856,0.17418848,0.3158218,0.5033368],"study_design_scores_gemma":[0.000022076256,0.000025332285,0.00018338399,0.00008173861,0.000026971811,0.0002709351,0.000031917756,0.006142902,0.0021398752,0.106819265,0.88423944,0.000016122525],"about_ca_topic_score_codex":0.0012753352,"about_ca_topic_score_gemma":0.0013735514,"teacher_disagreement_score":0.067780346,"about_ca_system_score_codex":0.001074053,"about_ca_system_score_gemma":0.0015211384,"threshold_uncertainty_score":0.22674787},"labels":[],"label_agreement":null},{"id":"W22428428","doi":"10.5406/amerjpsyc.125.1.0081","title":"ToXgene: An extensible template-based data generator for XML.","year":2002,"lang":"en","type":"article","venue":"International Workshop on the Web and Databases","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":75,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; XML; XML Schema (W3C); Programming language; Document Structure Description; XML framework; XML validation; Streaming XML; Template; Efficient XML Interchange; XML database; Simple API for XML; XML Schema Editor; Generator (circuit theory); Information retrieval; Database; XML Signature; World Wide Web","score_opus":0.16131708299049405,"score_gpt":0.3313494144327971,"score_spread":0.17003233144230304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W22428428","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":[0.0024517446,0.0004497876,0.59718513,0.00045230828,0.00031150525,0.0007441584,0.025963677,0.3664173,0.006024287],"genre_scores_gemma":[0.06097235,0.0015639637,0.6452275,0.0020585735,0.00020801793,0.0033586419,0.12875846,0.12921761,0.028634919],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99756014,0.0005124312,0.00051107246,0.00044772474,0.00080441794,0.00016423408],"domain_scores_gemma":[0.99421704,0.003233286,0.00046950896,0.0012544962,0.0005764277,0.00024924174],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006962028,0.0022213915,0.0010498611,0.0025572195,0.000747564,0.003859675,0.0048945104,0.0029064394,0.045425583],"category_scores_gemma":[0.015500096,0.0019405613,0.002184336,0.0020739716,0.0012233357,0.0054502594,0.0045205024,0.0023435068,0.025317468],"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":[0.0028595233,0.0004192192,0.0063776514,0.0041029686,0.00040593502,0.0033546733,0.001971868,0.013159567,0.033100627,0.07217791,0.43909445,0.4229756],"study_design_scores_gemma":[0.00087421987,0.00061456655,0.0031728235,0.0011350628,0.00016926673,0.003656376,0.00048703115,0.099494524,0.063119724,0.09333717,0.7334827,0.00045645435],"about_ca_topic_score_codex":0.0017347547,"about_ca_topic_score_gemma":0.0014138079,"teacher_disagreement_score":0.045425583,"about_ca_system_score_codex":0.0010973488,"about_ca_system_score_gemma":0.0016055392,"threshold_uncertainty_score":0.15196377},"labels":[],"label_agreement":null},{"id":"W2246590112","doi":"10.1145/2783702.2783708","title":"New Research Directions in Knowledge Discovery and Allied Spheres","year":2015,"lang":"en","type":"article","venue":"ACM SIGKDD Explorations Newsletter","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Systems, Applications & Products in Data Processing (Canada)","funders":"Agence Nationale de la Recherche","keywords":"Computer science; Knowledge extraction; Data science; Schema (genetic algorithms); Viewpoints; Domain knowledge; Realm; Point (geometry); Information retrieval; World Wide Web; Knowledge management; Data mining","score_opus":0.16935484731935074,"score_gpt":0.3730839166959473,"score_spread":0.20372906937659657,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2246590112","genre_codex":"review","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0068165557,0.57272446,0.14813036,0.20584884,0.0050191046,0.000086446635,0.0002321893,0.00027163522,0.060870484],"genre_scores_gemma":[0.20227464,0.58101714,0.15102687,0.023852764,0.027740642,0.00037785096,0.0005170411,0.00019622683,0.012996862],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.986639,0.006915032,0.0007385156,0.0020965224,0.0029512197,0.00065970886],"domain_scores_gemma":[0.8842483,0.098851494,0.0019931677,0.006030641,0.005607362,0.0032690784],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.024995016,0.0012125365,0.0028783195,0.00869273,0.0036734862,0.017859032,0.0038532726,0.0077083693,0.008291723],"category_scores_gemma":[0.028530773,0.0010048059,0.0023222067,0.012552004,0.02812273,0.059678964,0.0076047215,0.01203755,0.0019524985],"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":[0.000035236833,0.00006969159,0.00041087053,0.00075934693,0.00003244476,0.000082700615,0.0008407016,0.00047932033,0.00009636361,0.93866205,0.0067653526,0.05176594],"study_design_scores_gemma":[0.000015792582,0.000025267778,0.0001934253,0.00045083024,0.000014382215,0.00011665377,0.0009895836,0.0024910334,0.000095177165,0.9366944,0.058886796,0.000026638965],"about_ca_topic_score_codex":0.002929097,"about_ca_topic_score_gemma":0.00189987,"teacher_disagreement_score":0.024995016,"about_ca_system_score_codex":0.006219712,"about_ca_system_score_gemma":0.0065509756,"threshold_uncertainty_score":0.13218784},"labels":[],"label_agreement":null},{"id":"W2251728956","doi":"10.1007/978-3-642-32627-1_2","title":"Metrics for Measuring the Performance of the Mixed Workload CH-benCHmark","year":2012,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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":"Systems, Applications & Products in Data Processing (Canada)","funders":"","keywords":"Computer science; Benchmark (surveying); Workload; Volume (thermodynamics); Metric (unit); Transaction processing; Database; Database transaction; Transaction data; Data mining; Distributed computing; Operating system","score_opus":0.02573232686720677,"score_gpt":0.23397248491671546,"score_spread":0.20824015804950868,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2251728956","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":[0.6975305,0.012301798,0.1939331,0.00079790864,0.001040415,0.0014220069,0.034501012,0.022186136,0.036287155],"genre_scores_gemma":[0.8411573,0.0011277874,0.11555705,0.00023544265,0.00022792524,0.0009809455,0.033639774,0.0015291433,0.005544608],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99091876,0.0015627034,0.0011448738,0.0010305736,0.004741719,0.0006013519],"domain_scores_gemma":[0.98296607,0.0060113496,0.0018027119,0.0029607357,0.0053368234,0.0009224129],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003232635,0.0024746174,0.0009689323,0.0063562626,0.00072105095,0.0019958415,0.00257744,0.0011437568,0.0035776277],"category_scores_gemma":[0.014905187,0.00044079596,0.00056893425,0.007868085,0.00060591166,0.0022548083,0.0011572058,0.0012518502,0.0014615601],"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":[0.0055853906,0.0024896448,0.07680732,0.003712676,0.0010728154,0.00035607014,0.00066139764,0.14695776,0.1544229,0.019049933,0.104468614,0.48441553],"study_design_scores_gemma":[0.0003957294,0.0062879627,0.08566003,0.00032406207,0.00043880608,0.0013268689,0.0007146891,0.66633993,0.18838137,0.013628372,0.036086734,0.00041548174],"about_ca_topic_score_codex":0.003304856,"about_ca_topic_score_gemma":0.0037674427,"teacher_disagreement_score":0.0063562626,"about_ca_system_score_codex":0.0012817406,"about_ca_system_score_gemma":0.0012511077,"threshold_uncertainty_score":0.017095983},"labels":[],"label_agreement":null},{"id":"W2268009556","doi":"10.14288/1.0086621","title":"Incorporating semantic integrity constraints in a database schema","year":2008,"lang":"en","type":"article","venue":"cIRcle (University of British Columbia)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Data integrity; Database schema; Database; Information retrieval; Database design","score_opus":0.018872232105163495,"score_gpt":0.19826579160276214,"score_spread":0.17939355949759864,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2268009556","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":[0.009046219,0.00052369654,0.9655824,0.0015101546,0.00017248333,0.00034519535,0.00064429844,0.0018261087,0.020349437],"genre_scores_gemma":[0.10486943,0.0013226207,0.8830495,0.00090590824,0.00011678772,0.000335794,0.0022566395,0.00030068963,0.0068426593],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9909054,0.0027992418,0.0015614921,0.0011145845,0.0033296696,0.00028957622],"domain_scores_gemma":[0.9891745,0.0021643199,0.0009504712,0.005135642,0.0023702246,0.00020496402],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0074478895,0.0007221461,0.0007116226,0.0020823188,0.00089636433,0.0074405964,0.002300199,0.002774882,0.0033151489],"category_scores_gemma":[0.012702563,0.0011340771,0.0015081313,0.0024475825,0.0015448704,0.012697553,0.0028194888,0.0026430653,0.0016181167],"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":[0.00007695912,0.00015407165,0.0018551183,0.00027330004,0.000089829264,0.00040497023,0.0013948687,0.026379084,0.00888102,0.868047,0.0063327434,0.086111024],"study_design_scores_gemma":[0.00009701418,0.000248738,0.0010417502,0.00065430667,0.00022917846,0.0014720104,0.00080207596,0.25968844,0.034368373,0.23229183,0.4689341,0.00017229513],"about_ca_topic_score_codex":0.002816901,"about_ca_topic_score_gemma":0.003169608,"teacher_disagreement_score":0.0074478895,"about_ca_system_score_codex":0.0013325003,"about_ca_system_score_gemma":0.003903926,"threshold_uncertainty_score":0.039388657},"labels":[],"label_agreement":null},{"id":"W2269983853","doi":"10.82308/40022","title":"Lock-based concurrency control for XML","year":2006,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; XML validation; Efficient XML Interchange; Streaming XML; XML database; XML Schema Editor; XML Encryption; Database; XML Signature; Non-lock concurrency control; Document Structure Description; Concurrency control; Programming language; Multiversion concurrency control; XML; Distributed concurrency control; World Wide Web; Database transaction","score_opus":0.013040810148608898,"score_gpt":0.24769300251193188,"score_spread":0.234652192363323,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2269983853","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":[0.01657666,0.0013133924,0.9678086,0.0003604122,0.00016639635,0.00035382246,0.00014259617,0.0034499322,0.009828266],"genre_scores_gemma":[0.5578728,0.0012723646,0.42127573,0.0003335449,0.00023476162,0.0011114676,0.000608324,0.00078841083,0.016502598],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9949562,0.0010883508,0.0005020255,0.00067796384,0.002277869,0.00049759686],"domain_scores_gemma":[0.9917964,0.0035011836,0.0004985764,0.0025175284,0.0013470924,0.00033919426],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005094704,0.00069806736,0.00073256274,0.0010870617,0.0014641582,0.0037316743,0.0029155668,0.00071952894,0.0058608474],"category_scores_gemma":[0.0134535665,0.0006867252,0.0006881796,0.0012448487,0.0023009125,0.0053338115,0.0035522997,0.0027029687,0.00085362303],"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":[0.0009435411,0.0003341016,0.0020640313,0.000526696,0.00008223392,0.00034088735,0.0013907619,0.0578196,0.038094178,0.6223341,0.010992284,0.26507762],"study_design_scores_gemma":[0.0007247362,0.0004067942,0.0007017534,0.00014828725,0.00010914804,0.00047580156,0.00026929873,0.50240844,0.07738435,0.35111228,0.066106595,0.00015250928],"about_ca_topic_score_codex":0.003659431,"about_ca_topic_score_gemma":0.0027822384,"teacher_disagreement_score":0.0058608474,"about_ca_system_score_codex":0.0019020495,"about_ca_system_score_gemma":0.0024887896,"threshold_uncertainty_score":0.026943684},"labels":[],"label_agreement":null},{"id":"W2281141245","doi":"","title":"Relational OLAP query optimization","year":2014,"lang":"en","type":"article","venue":"Computer Science and Software Engineering","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada)","funders":"","keywords":"Online analytical processing; Computer science; Business intelligence; Big data; Analytics; Scalability; Relational database; Business analytics; IBM; Data science; Database; Data warehouse; Relational database management system; In-Memory Processing; Cache; Data mining; World Wide Web; Business analysis; Operating system; Business model; Search engine","score_opus":0.009063631404206088,"score_gpt":0.19012765371002063,"score_spread":0.18106402230581453,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2281141245","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":[0.018460734,0.0026352904,0.90807873,0.0018866288,0.00036551268,0.0009752491,0.008312583,0.02222512,0.03706009],"genre_scores_gemma":[0.24786007,0.0022329353,0.70242405,0.0013937723,0.00025802292,0.0008983757,0.020089088,0.0035794184,0.021264235],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99453074,0.00080917164,0.0005411102,0.00096598285,0.0024877423,0.00066529645],"domain_scores_gemma":[0.9974674,0.00051206286,0.00012807878,0.0007120848,0.0010610407,0.0001193837],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002255907,0.0019810267,0.0014985935,0.0020582676,0.001626765,0.005693198,0.0037322345,0.0010933809,0.015269313],"category_scores_gemma":[0.005602912,0.00058115454,0.0017120562,0.0045967796,0.00070589076,0.004751302,0.003908089,0.0022695109,0.006235554],"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":[0.0014357563,0.0006261648,0.0042132195,0.0018969722,0.00041055115,0.0011584944,0.00091073813,0.10330864,0.03543208,0.12413429,0.21427046,0.5122026],"study_design_scores_gemma":[0.00023016083,0.0002683403,0.0016602853,0.00011744707,0.00015943366,0.0014534491,0.0015174949,0.66323066,0.038294457,0.092139386,0.2007554,0.00017342511],"about_ca_topic_score_codex":0.011484891,"about_ca_topic_score_gemma":0.009067275,"teacher_disagreement_score":0.015269313,"about_ca_system_score_codex":0.0016853926,"about_ca_system_score_gemma":0.0031327861,"threshold_uncertainty_score":0.051080942},"labels":[],"label_agreement":null},{"id":"W2284149529","doi":"","title":"Merging Multidimensional Data Models: A Practical Approach for Schema and Data Instances","year":2013,"lang":"en","type":"article","venue":"Databases, Knowledge, and Data Applications","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa; University of Calgary","funders":"","keywords":"Data warehouse; Computer science; Online analytical processing; Data integration; Star schema; Merge (version control); Dimensional modeling; Multidimensional data; Data modeling; Data mining; Schema (genetic algorithms); IDEF1X; Database; Information retrieval; Database schema; Ontology-based data integration; Database design","score_opus":0.16826272271503157,"score_gpt":0.38738882376441247,"score_spread":0.2191261010493809,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2284149529","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":[0.00062499434,0.0001232562,0.9974704,0.00037848382,0.00001875371,0.000097090946,0.00003862431,0.00034729787,0.00090106664],"genre_scores_gemma":[0.0076683434,0.0001210016,0.9913449,0.000072327464,0.000014325039,0.00008436509,0.00012197458,0.00008608805,0.00048673508],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9872247,0.005669208,0.0009270884,0.0014524345,0.0043332763,0.0003932126],"domain_scores_gemma":[0.98868996,0.0028393702,0.00062022015,0.0058824224,0.0015364508,0.00043170812],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01560092,0.0012585171,0.0014537382,0.0034945984,0.0025944405,0.009935672,0.006417024,0.0037244041,0.005970836],"category_scores_gemma":[0.023271484,0.0024119779,0.0031780787,0.0069929003,0.002962185,0.016553774,0.014126371,0.0069217505,0.0019765387],"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":[0.00014127254,0.00016403117,0.0012739132,0.00048244372,0.00021665716,0.00049144746,0.0022219454,0.032613207,0.006084543,0.604746,0.011347082,0.34021753],"study_design_scores_gemma":[0.00008165325,0.00014619956,0.00041705335,0.0003730639,0.00015619244,0.0012255583,0.0020521216,0.35827073,0.012826464,0.44983605,0.17448561,0.00012934221],"about_ca_topic_score_codex":0.0027234915,"about_ca_topic_score_gemma":0.0042253737,"teacher_disagreement_score":0.01560092,"about_ca_system_score_codex":0.0024492224,"about_ca_system_score_gemma":0.0036445686,"threshold_uncertainty_score":0.08250654},"labels":[],"label_agreement":null},{"id":"W2285296088","doi":"10.11575/prism/30303","title":"A Lightweight Framework for Exchanging Web Data","year":2007,"lang":"en","type":"article","venue":"PRISM (University of Calgary)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Computer science; Data exchange; XML; Schema (genetic algorithms); Casual; Data mining; Database; Information retrieval; World Wide Web","score_opus":0.024084560676709717,"score_gpt":0.24507720240993194,"score_spread":0.22099264173322222,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2285296088","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":[0.001192874,0.00006516511,0.9926352,0.00015086963,0.000048248894,0.0001762582,0.000115762065,0.0047562607,0.0008593777],"genre_scores_gemma":[0.033376515,0.00019208236,0.9598008,0.00020618003,0.00010257305,0.0005254545,0.0010814359,0.00079976255,0.0039151907],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99466974,0.0011489193,0.00081039267,0.00071165664,0.0022555927,0.0004036678],"domain_scores_gemma":[0.9937975,0.0011762179,0.0004318658,0.003398438,0.000711879,0.00048418593],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006303268,0.0009964164,0.0014919555,0.0030634431,0.002505281,0.006446132,0.0051964526,0.0030120984,0.005273349],"category_scores_gemma":[0.009420462,0.0013516839,0.0022267099,0.0030902398,0.0017737935,0.00973786,0.008544294,0.0036355203,0.0036997946],"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":[0.00044063295,0.00059373147,0.0021192196,0.0007965914,0.00023481563,0.0015305476,0.0018038059,0.025313517,0.032486163,0.4507033,0.030209325,0.45376843],"study_design_scores_gemma":[0.0002457471,0.00025604348,0.00083119987,0.00033644083,0.00020570375,0.0021089318,0.00047169244,0.35731983,0.03784541,0.28276372,0.31726718,0.00034809753],"about_ca_topic_score_codex":0.004058098,"about_ca_topic_score_gemma":0.0032418238,"teacher_disagreement_score":0.006446132,"about_ca_system_score_codex":0.0013927155,"about_ca_system_score_gemma":0.0037122176,"threshold_uncertainty_score":0.03333527},"labels":[],"label_agreement":null},{"id":"W2293055137","doi":"","title":"Low-cost queryable linked data through triple pattern fragments","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"SPARQL; Computer science; Metadata; Server; Linked data; Database; Graph; Operating system; World Wide Web; RDF; Semantic Web","score_opus":0.04317385355380802,"score_gpt":0.2897115325790043,"score_spread":0.24653767902519627,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2293055137","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":[0.09329776,0.00029220042,0.795769,0.00072895305,0.00008772946,0.0006637288,0.0034407931,0.09705902,0.008660887],"genre_scores_gemma":[0.62241584,0.00031297698,0.34938163,0.0005902473,0.00006630024,0.00049851247,0.011731681,0.0063251955,0.008677633],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9950163,0.0008772109,0.00033638993,0.00058750674,0.0028720812,0.00031062434],"domain_scores_gemma":[0.99191463,0.002568115,0.00038466713,0.0035539814,0.0012609629,0.0003176482],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003151736,0.00073480426,0.00089355925,0.00091812236,0.0006685813,0.0032283743,0.0021688484,0.00093026774,0.005366332],"category_scores_gemma":[0.009662862,0.0006035523,0.0007940608,0.0018612914,0.0013354255,0.006105074,0.00406099,0.0014127513,0.0024112402],"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":[0.007975412,0.0011970802,0.03298453,0.0014134792,0.000644237,0.00465936,0.0027706837,0.05863724,0.24840935,0.10662427,0.08793311,0.4467512],"study_design_scores_gemma":[0.00035450316,0.00041483465,0.0041231494,0.00011080728,0.00009172152,0.001196251,0.00066611625,0.60816437,0.24927148,0.07017654,0.06524388,0.00018628023],"about_ca_topic_score_codex":0.0042838855,"about_ca_topic_score_gemma":0.0039270534,"teacher_disagreement_score":0.005366332,"about_ca_system_score_codex":0.0010065488,"about_ca_system_score_gemma":0.0012133301,"threshold_uncertainty_score":0.017952144},"labels":[],"label_agreement":null},{"id":"W2294609220","doi":"","title":"Data science workshop: experience driven analytics","year":2015,"lang":"en","type":"article","venue":"Computer Science and Software Engineering","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; University of Ottawa; Carleton University","funders":"","keywords":"Online analytical processing; Computer science; Analytics; Data warehouse; Online transaction processing; Database; Aggregate (composite); Data cube; Dimension (graph theory); Transaction processing; Cloud computing; Data analysis; Database transaction; Data science; Data mining","score_opus":0.06070804803407396,"score_gpt":0.28793344351230693,"score_spread":0.22722539547823298,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2294609220","genre_codex":"methods","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":[0.027284019,0.030357057,0.5472791,0.11087032,0.037173204,0.002081054,0.021695627,0.01842809,0.20483145],"genre_scores_gemma":[0.14208505,0.024137069,0.34397975,0.013652302,0.013430586,0.001507249,0.060808886,0.005733486,0.39466566],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99574065,0.00092819816,0.00027005098,0.0007545125,0.0019195678,0.00038711325],"domain_scores_gemma":[0.98987305,0.0017397963,0.0002049711,0.0016067597,0.0039056144,0.0026698355],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012715756,0.0012244753,0.0012755012,0.0018739945,0.0011756569,0.007821223,0.0035092616,0.0019502623,0.04537036],"category_scores_gemma":[0.008931638,0.0007091039,0.0011525177,0.002974242,0.00079377065,0.0064563686,0.0063526235,0.0039573726,0.02765095],"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":[0.00025978993,0.00027976607,0.0013684923,0.0004267148,0.00006567297,0.00022805312,0.00035694538,0.002441782,0.0036734233,0.018623559,0.71953017,0.25274563],"study_design_scores_gemma":[0.000065179505,0.0001346108,0.0010058907,0.00015827469,0.000023490436,0.00021416525,0.00035498608,0.016421575,0.0033949185,0.022270786,0.95591116,0.0000449837],"about_ca_topic_score_codex":0.0013291592,"about_ca_topic_score_gemma":0.002586921,"teacher_disagreement_score":0.04537036,"about_ca_system_score_codex":0.0015883332,"about_ca_system_score_gemma":0.0033845229,"threshold_uncertainty_score":0.151779},"labels":[],"label_agreement":null},{"id":"W2294688766","doi":"10.5441/002/edbt.2014.81","title":"Business-Intelligence Queries with Order Dependencies in DB2","year":2014,"lang":"en","type":"article","venue":"Movebank","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University; University of Toronto","funders":"","keywords":"Computer science; Functional dependency; Dependency (UML); Query optimization; Online analytical processing; Exploit; Data integrity; Theoretical computer science; Data mining; Relational database; Data warehouse; Database; Artificial intelligence","score_opus":0.007416451325730401,"score_gpt":0.20796420647002162,"score_spread":0.2005477551442912,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2294688766","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":[0.07150158,0.00177514,0.71159625,0.002536674,0.00024120531,0.00071057386,0.029054081,0.15271449,0.029870093],"genre_scores_gemma":[0.26991722,0.0011850051,0.6393968,0.00191892,0.00015613933,0.0008800323,0.06429668,0.012075926,0.01017332],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99075454,0.0015705182,0.0010678588,0.0016177677,0.004446959,0.0005423139],"domain_scores_gemma":[0.9945648,0.0021389374,0.00035953597,0.0018495495,0.00082878565,0.00025848168],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0045312117,0.0023005414,0.00147502,0.0021067746,0.0018310205,0.007261616,0.004534801,0.0015780359,0.006351278],"category_scores_gemma":[0.010205933,0.0023423645,0.0021510473,0.0057737445,0.0020198876,0.011996663,0.0041936766,0.0036016414,0.0025803875],"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":[0.004767509,0.0013436596,0.017875697,0.0020779415,0.00047252342,0.0017830466,0.0034869735,0.10681895,0.040342256,0.2836576,0.22909519,0.30827862],"study_design_scores_gemma":[0.0010383341,0.00028238376,0.0049943337,0.00024004826,0.00023018914,0.0011540265,0.0009530153,0.39624316,0.08544061,0.16711378,0.34194058,0.00036948378],"about_ca_topic_score_codex":0.030228583,"about_ca_topic_score_gemma":0.026710374,"teacher_disagreement_score":0.030228583,"about_ca_system_score_codex":0.0033901234,"about_ca_system_score_gemma":0.004019684,"threshold_uncertainty_score":0.060105264},"labels":[],"label_agreement":null},{"id":"W2294817016","doi":"","title":"Parallel data cubes on multi-core processors with multiple disks","year":2011,"lang":"en","type":"article","venue":"Conference of the Centre for Advanced Studies on Collaborative Research","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Online analytical processing; Computer science; Data cube; Very large database; Cube (algebra); Sorting; Parallel computing; Speedup; Data warehouse; Aggregate (composite); sort; Oracle; Multi-core processor; Core (optical fiber); Database; Data mining; Algorithm","score_opus":0.40457689833356214,"score_gpt":0.43351304344215824,"score_spread":0.0289361451085961,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2294817016","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":[0.2146156,0.0010719633,0.75867844,0.000737468,0.0003406213,0.0005463301,0.0005992074,0.009750824,0.01365954],"genre_scores_gemma":[0.2865381,0.00035431128,0.7053082,0.00021084702,0.00006577806,0.00053139596,0.0010986465,0.00027710426,0.0056155403],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983639,0.0003730362,0.00014776882,0.00023738117,0.00066813047,0.00020969563],"domain_scores_gemma":[0.9970789,0.0008928155,0.00015062274,0.0008619198,0.00085476704,0.00016106367],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001264908,0.0008784395,0.00093510293,0.000922967,0.001144825,0.0014246276,0.0024513612,0.00062323565,0.004960289],"category_scores_gemma":[0.0034212065,0.0006378648,0.0008508766,0.0025548963,0.0006777014,0.0024217027,0.0018909628,0.001118086,0.0014139627],"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":[0.0028986195,0.0006273958,0.00477258,0.0006749802,0.00027073766,0.0007520723,0.0006842083,0.43475762,0.050835945,0.03698437,0.031009106,0.43573236],"study_design_scores_gemma":[0.00035623106,0.00043177893,0.00081840093,0.000027897888,0.000040286064,0.00019686065,0.0001962988,0.93685967,0.030048123,0.015574714,0.015401678,0.000048016904],"about_ca_topic_score_codex":0.0052952603,"about_ca_topic_score_gemma":0.0059595914,"teacher_disagreement_score":0.0052952603,"about_ca_system_score_codex":0.0010121762,"about_ca_system_score_gemma":0.0016226557,"threshold_uncertainty_score":0.016593874},"labels":[],"label_agreement":null},{"id":"W2296281099","doi":"10.1109/icde.1991.131503","title":"Modeling transition","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Abstraction; Formalism (music); Domain (mathematical analysis); Inference; Theoretical computer science; Transition (genetics); Programming language; Mechanism (biology); Data mining; Artificial intelligence; Mathematics","score_opus":0.031139751457325778,"score_gpt":0.22130794437391388,"score_spread":0.1901681929165881,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2296281099","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":[0.0037664117,0.00038472816,0.94236225,0.001174948,0.00019193793,0.0002068953,0.0005694422,0.0012015437,0.050141826],"genre_scores_gemma":[0.28601018,0.0019700795,0.63382494,0.0011829482,0.00037061752,0.0013883043,0.0037396809,0.0012311741,0.070282005],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973387,0.0006375486,0.00023689737,0.00078085565,0.00060801266,0.00039792314],"domain_scores_gemma":[0.996305,0.0014705535,0.0002540439,0.0011805022,0.00060290704,0.00018705282],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030553988,0.0011815019,0.0006056877,0.0016951326,0.0015999166,0.0056913365,0.003332837,0.0022297143,0.01814992],"category_scores_gemma":[0.0077274134,0.000825626,0.003011431,0.0013962687,0.0035008327,0.010493923,0.0046736193,0.003518575,0.0049564587],"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":[0.000015415586,0.000017926328,0.00017282125,0.000040918105,0.0000087587105,0.00010719128,0.00034629364,0.008120579,0.00030950338,0.98285496,0.0018995361,0.006106133],"study_design_scores_gemma":[0.000019071022,0.000026895428,0.00009086553,0.00008856514,0.000030556806,0.00022246255,0.00019409599,0.06739524,0.0012465691,0.8196939,0.11096892,0.000022944603],"about_ca_topic_score_codex":0.007900232,"about_ca_topic_score_gemma":0.0045107007,"teacher_disagreement_score":0.01814992,"about_ca_system_score_codex":0.0026767002,"about_ca_system_score_gemma":0.0032131379,"threshold_uncertainty_score":0.060717523},"labels":[],"label_agreement":null},{"id":"W2296703446","doi":"10.14778/2733004.2733009","title":"TPC-DI","year":2014,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":69,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Master data; Data warehouse; Variety (cybernetics); Data integration; Enterprise data management; Data management; Context (archaeology); Data science; Analytics; Business intelligence; Database; Enterprise information system","score_opus":0.006928866262876887,"score_gpt":0.2013198379173866,"score_spread":0.19439097165450972,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2296703446","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":[0.013979112,0.0015715489,0.09517548,0.0055435025,0.0035152866,0.0028844238,0.06193112,0.10828101,0.7071185],"genre_scores_gemma":[0.10627417,0.0013807261,0.14459471,0.004662905,0.0012735728,0.0029160436,0.3662708,0.024935499,0.34769166],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99076676,0.0012007505,0.0004622287,0.0014036495,0.004890568,0.0012761155],"domain_scores_gemma":[0.9750421,0.0015451125,0.00049336295,0.005772541,0.012720103,0.0044267476],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0069417832,0.0016049867,0.0012673294,0.003791661,0.0022642575,0.009134666,0.004887708,0.0026565706,0.12481578],"category_scores_gemma":[0.016582849,0.0008613786,0.0006813039,0.005635035,0.0008406202,0.0059934,0.005385824,0.0041100583,0.11615886],"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":[0.0007983202,0.00052179385,0.0019534102,0.00024935522,0.000030260375,0.0001364402,0.0001593814,0.0014175405,0.0048169605,0.019726016,0.81573945,0.15445094],"study_design_scores_gemma":[0.00019770494,0.00029182778,0.0025947841,0.00008864598,0.000017293629,0.00031134425,0.00011980312,0.011242148,0.007570408,0.0043197167,0.9731886,0.000057741276],"about_ca_topic_score_codex":0.01548752,"about_ca_topic_score_gemma":0.008852303,"teacher_disagreement_score":0.12481578,"about_ca_system_score_codex":0.005099148,"about_ca_system_score_gemma":0.009570589,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W2303002424","doi":"","title":"Data Semantics Revisited: Databases and the Semantic Web","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Semantics (computer science); Database; Semantic Web; Computer science; World Wide Web; Programming language","score_opus":0.04146368355573276,"score_gpt":0.28746961735796317,"score_spread":0.2460059338022304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2303002424","genre_codex":"commentary","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":[0.004768054,0.2914692,0.13199629,0.46676633,0.009608193,0.00005835507,0.00041169947,0.00037826513,0.09454358],"genre_scores_gemma":[0.4087059,0.2765309,0.09743124,0.10993203,0.041054696,0.00043473553,0.0011199255,0.0009874142,0.063803315],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99163204,0.003949935,0.00045115245,0.0009799197,0.0026282633,0.00035875107],"domain_scores_gemma":[0.9892135,0.007160001,0.00029859348,0.0009186353,0.0017849348,0.0006243369],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013873268,0.0008629083,0.0019042885,0.004514213,0.004321597,0.022580218,0.0022260784,0.008288443,0.009094808],"category_scores_gemma":[0.018608311,0.0010843581,0.0014156597,0.008662843,0.017292371,0.047637887,0.006090905,0.012488435,0.0019802153],"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":[0.000017480561,0.0000066323037,0.00006287318,0.00010534349,0.000011887443,0.00004950585,0.0005508813,0.00034700602,0.0000849237,0.95719707,0.02506569,0.01650077],"study_design_scores_gemma":[0.000008301481,0.000004617857,0.00004668285,0.00016557469,0.0000075193993,0.00008157846,0.0005535498,0.00073070097,0.0000870604,0.84874,0.14956523,0.000009151593],"about_ca_topic_score_codex":0.0076811356,"about_ca_topic_score_gemma":0.005624342,"teacher_disagreement_score":0.022580218,"about_ca_system_score_codex":0.006024364,"about_ca_system_score_gemma":0.0042429124,"threshold_uncertainty_score":0.07336968},"labels":[],"label_agreement":null},{"id":"W2306825702","doi":"","title":"Index Selection for Embedded Control Applications using Description Logics","year":2002,"lang":"en","type":"article","venue":"DigitalCommons - CalPoly (California State Polytechnic University)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Database transaction; Semantic reasoner; Schema (genetic algorithms); Workload; Partition (number theory); Set (abstract data type); Index (typography); Theoretical computer science; Data mining; Database; Artificial intelligence; Information retrieval; Mathematics; Programming language","score_opus":0.02994066810853368,"score_gpt":0.2220414517365907,"score_spread":0.19210078362805702,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2306825702","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":[0.02711139,0.0006691873,0.9679139,0.00055968645,0.000021147258,0.00017056601,0.00022089623,0.0011245201,0.002208796],"genre_scores_gemma":[0.35732168,0.00082673825,0.63785183,0.0002802215,0.000042756412,0.00021993433,0.00087476615,0.00016629495,0.0024158666],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9985051,0.00044998396,0.00012971643,0.0002752489,0.00048223865,0.0001577008],"domain_scores_gemma":[0.9967045,0.002480001,0.00023892599,0.00026878263,0.00022077556,0.000087019034],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022672443,0.00066746207,0.0008295801,0.0009766286,0.0006723096,0.0023413752,0.0014886516,0.000817352,0.0024698703],"category_scores_gemma":[0.005600203,0.000618025,0.0009975372,0.0011858784,0.0011191916,0.0029392655,0.0012359669,0.0011056662,0.00029101915],"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":[0.0005327168,0.0002581842,0.0024893526,0.0009827096,0.00014425519,0.00091239484,0.0005721922,0.4340006,0.018530667,0.15417431,0.0059456914,0.38145694],"study_design_scores_gemma":[0.00007599151,0.000062539264,0.0001733055,0.00004256514,0.00004585146,0.00013866952,0.00013950904,0.90982395,0.0061855363,0.07769862,0.005594915,0.00001852061],"about_ca_topic_score_codex":0.0049938164,"about_ca_topic_score_gemma":0.005653986,"teacher_disagreement_score":0.0049938164,"about_ca_system_score_codex":0.001666319,"about_ca_system_score_gemma":0.0017667902,"threshold_uncertainty_score":0.012090087},"labels":[],"label_agreement":null},{"id":"W2316031931","doi":"","title":"Improved Prediction of IDA*'s Performance via -Truncation","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":10,"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 Regina; University of Alberta","funders":"","keywords":"Discretization; Truncation (statistics); Discretization error; Computer science; Line (geometry); Truncation error; Algorithm; Econometrics; Machine learning; Artificial intelligence; Mathematical optimization; Mathematics; Applied mathematics","score_opus":0.02141632184068523,"score_gpt":0.20146523884676334,"score_spread":0.1800489170060781,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2316031931","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":[0.7092667,0.0016453138,0.27175358,0.0019750395,0.0002723064,0.00012484884,0.0021788282,0.0064133513,0.006370036],"genre_scores_gemma":[0.9568433,0.0001470484,0.041289944,0.00010626658,0.00004094981,0.000037705708,0.0008573124,0.000099314304,0.0005782291],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978689,0.00052155595,0.00013858026,0.0005461371,0.0005850912,0.0003396766],"domain_scores_gemma":[0.9763594,0.014846747,0.0010911938,0.004541817,0.0022899064,0.00087094103],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005165381,0.0008845061,0.0012623107,0.0007914656,0.00070813583,0.0014393678,0.0020891628,0.001323613,0.0015298431],"category_scores_gemma":[0.025711538,0.00048664605,0.0004553936,0.00079679146,0.00075438083,0.0030602438,0.0013641599,0.0027469455,0.0009203022],"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":[0.0010628334,0.00019833622,0.03290243,0.00012224677,0.00006568469,0.00009381516,0.00023673735,0.8744136,0.005533406,0.005804404,0.008472988,0.07109353],"study_design_scores_gemma":[0.000011923447,0.00003701641,0.0011468692,0.0000059620224,0.0000046881946,0.000018400451,0.000019745228,0.9943996,0.0019016066,0.0021727025,0.00027095748,0.000010458127],"about_ca_topic_score_codex":0.010752403,"about_ca_topic_score_gemma":0.008498842,"teacher_disagreement_score":0.010752403,"about_ca_system_score_codex":0.0019247769,"about_ca_system_score_gemma":0.0025081984,"threshold_uncertainty_score":0.027317464},"labels":[],"label_agreement":null},{"id":"W2323560162","doi":"10.3166/jesa.45.141-156","title":"Identification des états équivalents dans l’approche modale","year":2011,"lang":"fr","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Humanities; Philosophy","score_opus":0.06363292696721069,"score_gpt":0.27852493694182195,"score_spread":0.21489200997461128,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2323560162","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":[0.100076,0.0002847912,0.8424477,0.0009988239,0.00044881352,0.00045449453,0.000919654,0.0050796717,0.049290005],"genre_scores_gemma":[0.54640156,0.00029943284,0.41008106,0.00046583498,0.00020158991,0.00045108912,0.002221623,0.001374444,0.038503405],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99048597,0.0029090806,0.00051641825,0.0018120796,0.0036296537,0.000646774],"domain_scores_gemma":[0.9930761,0.0032347047,0.00026193124,0.0014174352,0.0018398733,0.00016989307],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035146666,0.0012358163,0.0008306409,0.002283696,0.0015406345,0.0054199398,0.0014081844,0.00281207,0.033674564],"category_scores_gemma":[0.018195271,0.00059607107,0.0015723071,0.0011008222,0.0016884763,0.004996895,0.0022725554,0.0027329286,0.0067225816],"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":[0.0045185606,0.0010225518,0.0066761593,0.00085580756,0.00028926742,0.0022553657,0.0022778332,0.04557963,0.06673431,0.2382437,0.017444327,0.6141025],"study_design_scores_gemma":[0.0004950694,0.001183031,0.0058218422,0.00042768675,0.00036621987,0.002206641,0.0027071885,0.55874556,0.124235995,0.14150761,0.16208464,0.00021856939],"about_ca_topic_score_codex":0.003370743,"about_ca_topic_score_gemma":0.003082004,"teacher_disagreement_score":0.033674564,"about_ca_system_score_codex":0.0011757744,"about_ca_system_score_gemma":0.0014253197,"threshold_uncertainty_score":0.11265266},"labels":[],"label_agreement":null},{"id":"W2329267345","doi":"10.2316/p.2010.724-009","title":"Investigating the 2-Way Semijoin for Distributed Query Optimization","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"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":"Natural Sciences and Engineering Research Council of Canada","keywords":"Query optimization; Computer science; Sargable; Distributed computing; Information retrieval; Web search query; Search engine","score_opus":0.015807543206053702,"score_gpt":0.24948249867791897,"score_spread":0.23367495547186526,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2329267345","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":[0.15467559,0.0010574036,0.8372582,0.0006376978,0.00013882312,0.00014000374,0.00007356988,0.00070729776,0.0053114407],"genre_scores_gemma":[0.73920524,0.0003306521,0.2561062,0.00020946508,0.00015774235,0.00009868347,0.0001419403,0.00026797602,0.003482111],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99441767,0.0025583021,0.00021732692,0.0006252509,0.0016653351,0.0005162098],"domain_scores_gemma":[0.98829585,0.008408913,0.0004853639,0.0015195515,0.0010076271,0.00028262712],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0069737146,0.0006067386,0.0015355372,0.00043155314,0.0011416429,0.0026052573,0.002225114,0.0013201168,0.0031703068],"category_scores_gemma":[0.017348835,0.0005893498,0.0008895344,0.000840434,0.0012249028,0.004924599,0.0019901358,0.0016589438,0.00041766698],"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":[0.003552318,0.0007565212,0.009437717,0.0007859167,0.00034973092,0.0004230982,0.002525865,0.45152867,0.039999157,0.2906946,0.0071357563,0.19281065],"study_design_scores_gemma":[0.00008112675,0.0002313715,0.00041645297,0.000011541807,0.000040316838,0.00012412328,0.00029035044,0.9318028,0.004037469,0.0613948,0.0015514746,0.000018166402],"about_ca_topic_score_codex":0.0024216992,"about_ca_topic_score_gemma":0.003106553,"teacher_disagreement_score":0.0069737146,"about_ca_system_score_codex":0.00076433754,"about_ca_system_score_gemma":0.0019732304,"threshold_uncertainty_score":0.03688097},"labels":[],"label_agreement":null},{"id":"W2333804416","doi":"10.5963/ijcsai0204001","title":"Efficient Streaming Algorithms for Tree Matching Problems","year":2012,"lang":"en","type":"article","venue":"International Journal of Computer Science and Artificial Intelligence","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Computer science; Node (physics); XML; Tree (set theory); Overhead (engineering); Matching (statistics); Focus (optics); Theoretical computer science; Data structure; Algorithm; Data mining; Mathematics; Programming language","score_opus":0.051595295629546394,"score_gpt":0.3265719468394973,"score_spread":0.2749766512099509,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2333804416","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":[0.011884323,0.0016214915,0.98179907,0.00035651337,0.00009320731,0.0001747174,0.00024494802,0.001179595,0.002646091],"genre_scores_gemma":[0.10872012,0.0016683507,0.8839803,0.00022603273,0.00026627272,0.000417092,0.0014356743,0.0003504638,0.0029356768],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99847716,0.00040077275,0.00015934357,0.00032063713,0.00046363205,0.00017838794],"domain_scores_gemma":[0.9969309,0.0019663859,0.00023741646,0.00034072256,0.0003887706,0.00013588871],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024107068,0.0015189904,0.0016712865,0.0021703702,0.000975567,0.0016458789,0.002703555,0.0017979471,0.0055630277],"category_scores_gemma":[0.008935644,0.00067742245,0.0011457027,0.0045237094,0.0006265625,0.006106932,0.0018938249,0.0020466861,0.0014733004],"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":[0.00057418237,0.00039398932,0.0016475917,0.00090431375,0.0001456071,0.0001529306,0.0003458411,0.28776783,0.007218817,0.096975476,0.017999606,0.58587384],"study_design_scores_gemma":[0.00010997081,0.00007773929,0.00014628604,0.000021729156,0.000022965824,0.000121200006,0.000053824147,0.90731615,0.0014332889,0.08732112,0.0033627057,0.000012967228],"about_ca_topic_score_codex":0.0023566263,"about_ca_topic_score_gemma":0.0022667397,"teacher_disagreement_score":0.0055630277,"about_ca_system_score_codex":0.0013186296,"about_ca_system_score_gemma":0.0014032786,"threshold_uncertainty_score":0.01861018},"labels":[],"label_agreement":null},{"id":"W2334113034","doi":"10.1007/s00165-016-0367-1","title":"On the formal analysis of Gaussian optical systems in HOL","year":2016,"lang":"en","type":"article","venue":"Formal Aspects of Computing","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Gaussian beam; Computer science; Pathfinder; Gaussian; Optics; Automated theorem proving; HOL; Transformation (genetics); Beam (structure); Physics; Theoretical computer science; Programming language","score_opus":0.012538693863415691,"score_gpt":0.24390707376104223,"score_spread":0.23136837989762654,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2334113034","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":[0.051516574,0.00045539413,0.9375534,0.0011607518,0.000042735403,0.0001291677,0.0002963976,0.00082267093,0.008022893],"genre_scores_gemma":[0.75759506,0.00064062595,0.23611078,0.000528682,0.00017939652,0.00022483451,0.0005448855,0.00024510614,0.003930568],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9953294,0.0015257305,0.00044410815,0.00049759366,0.001608092,0.0005950786],"domain_scores_gemma":[0.9847782,0.010975165,0.0009570468,0.0015974079,0.0013790493,0.00031317736],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00751276,0.000586341,0.00061531964,0.0020702523,0.0015632794,0.0050642826,0.0019544563,0.00086905644,0.0030445866],"category_scores_gemma":[0.011049904,0.000575645,0.001803878,0.0024191064,0.005290889,0.008076491,0.0035073028,0.0021069169,0.0003956031],"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":[0.000030408622,0.000041837102,0.0005658855,0.000075200216,0.000015002152,0.00016782261,0.0005713549,0.011053305,0.00076843624,0.9784958,0.0004339523,0.007780948],"study_design_scores_gemma":[0.00003723684,0.000037013328,0.00038105657,0.0000542821,0.000035139663,0.00012481936,0.00026076188,0.11438462,0.0024377285,0.8743015,0.0079177385,0.000028163247],"about_ca_topic_score_codex":0.00591773,"about_ca_topic_score_gemma":0.004065986,"teacher_disagreement_score":0.00751276,"about_ca_system_score_codex":0.0031613233,"about_ca_system_score_gemma":0.002098778,"threshold_uncertainty_score":0.03973174},"labels":[],"label_agreement":null},{"id":"W2345986584","doi":"10.5539/cis.v9n2p156","title":"System Architecture for Approximate Query Processing","year":2016,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Font; Span (engineering); Architecture; Database; Artificial intelligence","score_opus":0.010264482629595005,"score_gpt":0.23627841351114134,"score_spread":0.22601393088154634,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2345986584","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":[0.012257445,0.0009313183,0.84635323,0.0011899492,0.00034208232,0.0008335483,0.0023042138,0.11339976,0.022388551],"genre_scores_gemma":[0.36636087,0.0015640846,0.5612967,0.0015083519,0.00052975456,0.0016548763,0.015208511,0.004018685,0.047858134],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977297,0.00039287037,0.00026523252,0.00057304866,0.000796325,0.00024284965],"domain_scores_gemma":[0.9976683,0.00046374399,0.00010408693,0.00069388014,0.00089002214,0.00017999296],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023586417,0.0011083368,0.0013541494,0.0026179848,0.0012530122,0.005666189,0.004362453,0.0022716345,0.036626413],"category_scores_gemma":[0.0060634073,0.00085772417,0.0010131766,0.0026010938,0.0008332299,0.004501281,0.0032037133,0.0018491582,0.024626197],"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":[0.0026204574,0.0007238562,0.005081849,0.0016372269,0.0003959413,0.001152729,0.0015683448,0.06415046,0.063367315,0.061859768,0.17887342,0.6185687],"study_design_scores_gemma":[0.00023627715,0.000439373,0.0016571283,0.000140121,0.00023391045,0.0006815527,0.00036374896,0.7903622,0.034115285,0.028010909,0.14358331,0.0001762407],"about_ca_topic_score_codex":0.0118035395,"about_ca_topic_score_gemma":0.0050259857,"teacher_disagreement_score":0.036626413,"about_ca_system_score_codex":0.0018304748,"about_ca_system_score_gemma":0.0027134132,"threshold_uncertainty_score":0.1225276},"labels":[],"label_agreement":null},{"id":"W2359125958","doi":"","title":"A Study of Multi-join Queries Optimization in Distributed Database","year":2005,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Join (topology); Sequence (biology); Selection (genetic algorithm); Database; Ideal (ethics); Greedy algorithm; Distributed database; Data mining; Algorithm; Artificial intelligence","score_opus":0.01967973938383153,"score_gpt":0.27882972337835604,"score_spread":0.2591499839945245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2359125958","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":[0.014814218,0.0019397568,0.98044777,0.00035486557,0.000044882596,0.00003911009,0.000018654511,0.000052504005,0.0022882975],"genre_scores_gemma":[0.5856743,0.004145344,0.40403908,0.00029208683,0.0006246378,0.00014289827,0.00009770852,0.00018862427,0.0047952738],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99773455,0.00092431414,0.00007346638,0.0004191039,0.0006922321,0.00015630198],"domain_scores_gemma":[0.99673504,0.0026401677,0.00014174337,0.0001344401,0.000262657,0.000085871165],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025353297,0.0007743668,0.0013385969,0.0004715217,0.000738507,0.0012287333,0.0015298984,0.0012017648,0.0014822868],"category_scores_gemma":[0.0047364635,0.0005186353,0.0006036717,0.0015658686,0.0010653305,0.002875157,0.00067557115,0.0017842182,0.00025325993],"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":[0.00018023474,0.00021351845,0.00088846986,0.00032616509,0.00008996783,0.00009787733,0.00019766504,0.80252457,0.0039014576,0.08845644,0.0024283058,0.10069537],"study_design_scores_gemma":[0.000016707794,0.00010533851,0.00018401662,0.000008749788,0.000015166902,0.00005078132,0.000026475218,0.9793802,0.00092986855,0.017313814,0.0019596308,0.000009287358],"about_ca_topic_score_codex":0.0015680664,"about_ca_topic_score_gemma":0.00085971,"teacher_disagreement_score":0.0025353297,"about_ca_system_score_codex":0.001140073,"about_ca_system_score_gemma":0.000837502,"threshold_uncertainty_score":0.013408244},"labels":[],"label_agreement":null},{"id":"W2373792090","doi":"","title":"Research on the Index Model of Encrypted XML Database","year":2010,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Database; XML database; View; XML Encryption; Information retrieval; Database security; Index (typography); Encryption; XML; Database index; Query optimization; Database design; Data mining; World Wide Web; Computer security; Search engine indexing","score_opus":0.057022191803391915,"score_gpt":0.33776759424349984,"score_spread":0.2807454024401079,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2373792090","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":[0.026078638,0.003947991,0.9376171,0.0017020516,0.00037919782,0.00021921458,0.0003246894,0.00068354496,0.029047599],"genre_scores_gemma":[0.6983385,0.012479344,0.25074145,0.0008208987,0.00096834044,0.0007227079,0.00142663,0.0002677842,0.03423425],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99703205,0.0004814625,0.00032003722,0.0004467513,0.0014881928,0.00023141835],"domain_scores_gemma":[0.99803895,0.00044492172,0.00015796664,0.0005157733,0.0007598651,0.00008249135],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002283421,0.00039874887,0.0006641016,0.0014254418,0.0010750112,0.0041467026,0.002162953,0.0009758278,0.004123299],"category_scores_gemma":[0.005183456,0.0003354558,0.00092329236,0.0021710703,0.0012073813,0.01574928,0.001338727,0.0015392092,0.0010676591],"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":[0.00010269104,0.000056227345,0.0010538446,0.00016207079,0.000030329771,0.00022564048,0.00041077,0.01617632,0.0034790176,0.9320499,0.0043959282,0.041857246],"study_design_scores_gemma":[0.0000904276,0.00020424169,0.00064367935,0.00011948129,0.00008666639,0.001164474,0.00032907765,0.5111778,0.009892463,0.42206457,0.05413255,0.00009466109],"about_ca_topic_score_codex":0.0043491763,"about_ca_topic_score_gemma":0.0014431105,"teacher_disagreement_score":0.0043491763,"about_ca_system_score_codex":0.0026133696,"about_ca_system_score_gemma":0.0018175408,"threshold_uncertainty_score":0.01896137},"labels":[],"label_agreement":null},{"id":"W2383580647","doi":"","title":"A Novel Aggregation Algorithm for Online Analytical Processing Query Evaluation","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"CAE (Canada)","funders":"","keywords":"Computer science; Online analytical processing; Online aggregation; Sorting; Sorting algorithm; sort; Key (lock); Query optimization; Aggregate (composite); Data mining; Schema (genetic algorithms); Algorithm; Join (topology); Table (database); SQL; Data warehouse; Theoretical computer science; Information retrieval; Database; Query by Example; Web search query; Search engine","score_opus":0.07987215920354403,"score_gpt":0.3293050287235504,"score_spread":0.24943286952000637,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2383580647","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":[0.0035366213,0.00018122356,0.99347335,0.00006705119,0.00006488661,0.00007731674,0.00005699837,0.0014174582,0.0011250753],"genre_scores_gemma":[0.06492763,0.00020671477,0.93177134,0.00008761665,0.000099745615,0.00014871439,0.00030772842,0.00010343277,0.0023471282],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982387,0.00024131159,0.00016264101,0.0002472835,0.0010217839,0.000088349414],"domain_scores_gemma":[0.9987244,0.0002375396,0.00008735927,0.00020229288,0.0007032295,0.000045110013],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012216567,0.0007651293,0.00081435265,0.0018618266,0.00083519454,0.0014866373,0.0010495116,0.0005878925,0.0022587508],"category_scores_gemma":[0.0025121109,0.00033792885,0.00052726705,0.0022731188,0.00039681682,0.0023723205,0.0010160345,0.0008034234,0.0010128181],"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":[0.0002805403,0.00012315252,0.000960348,0.00013457441,0.000061305414,0.00009559615,0.00016898692,0.02284628,0.030416235,0.027296163,0.012236115,0.9053807],"study_design_scores_gemma":[0.000081260805,0.00021507598,0.00078646507,0.00002286826,0.000059498067,0.0005636821,0.00009501093,0.9080303,0.034698255,0.01664199,0.03874512,0.000060444363],"about_ca_topic_score_codex":0.002005158,"about_ca_topic_score_gemma":0.0017539022,"teacher_disagreement_score":0.0022587508,"about_ca_system_score_codex":0.00081321434,"about_ca_system_score_gemma":0.0010245845,"threshold_uncertainty_score":0.0075562596},"labels":[],"label_agreement":null},{"id":"W2385460516","doi":"","title":"Verifying the Counter XML Rewriting Attacks Model Based on PI-Calculus","year":2008,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Rewriting; Pi calculus; XML; Programming language; Theoretical computer science; Calculus (dental); World Wide Web","score_opus":0.02362079727842146,"score_gpt":0.25686214943718616,"score_spread":0.2332413521587647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2385460516","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":[0.10154685,0.0001194297,0.8875764,0.0004893072,0.00011934057,0.00021007175,0.00020028141,0.0028396277,0.0068986868],"genre_scores_gemma":[0.85160065,0.00022464796,0.14401396,0.00016574725,0.000096731535,0.00022310796,0.00025458328,0.00019431744,0.0032262716],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9946765,0.0009243844,0.00038406288,0.0008411728,0.002585308,0.0005886468],"domain_scores_gemma":[0.9953754,0.0019719512,0.00066830125,0.0010499205,0.0008165692,0.00011777647],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026434462,0.0006289024,0.00091224426,0.0010229094,0.0011764063,0.002306422,0.0015442829,0.0014217314,0.0016994842],"category_scores_gemma":[0.008082777,0.00044125458,0.0019865476,0.00051160355,0.002477173,0.0040736767,0.0014785364,0.0019148417,0.00034104218],"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":[0.00041935468,0.00019603084,0.0043052984,0.00030361416,0.00015319328,0.0022669875,0.00094318955,0.17409272,0.055383988,0.7293054,0.0019648818,0.030665312],"study_design_scores_gemma":[0.00012051336,0.0001617707,0.00054769183,0.0000329019,0.00014027952,0.0005282937,0.000081680555,0.7421464,0.046217855,0.20344222,0.006510136,0.00007030052],"about_ca_topic_score_codex":0.006792399,"about_ca_topic_score_gemma":0.0025667567,"teacher_disagreement_score":0.006792399,"about_ca_system_score_codex":0.0015272704,"about_ca_system_score_gemma":0.0029967485,"threshold_uncertainty_score":0.013980091},"labels":[],"label_agreement":null},{"id":"W2395061090","doi":"10.5281/zenodo.3781970","title":"IRBs and Data Sharing","year":2009,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Institute for Public Safety Research and Treatment","funders":"","keywords":"Computer science","score_opus":0.07585414218617643,"score_gpt":0.2907520570970493,"score_spread":0.2148979149108729,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2395061090","genre_codex":"methods","genre_gemma":"commentary","domain_codex":null,"domain_gemma":"reproducibility","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":"reproducibility","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.053981684,0.016714562,0.7479883,0.019964363,0.004713671,0.00043589066,0.00104375,0.0048636375,0.15029405],"genre_scores_gemma":[0.7464598,0.0054887845,0.13390818,0.0030114993,0.0025619084,0.0005435804,0.0019507192,0.0022869487,0.10378861],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9856382,0.005903964,0.0009847844,0.0019198831,0.0040980903,0.0014551041],"domain_scores_gemma":[0.9733969,0.007725826,0.0011380785,0.012732347,0.0036716396,0.0013351346],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.014618274,0.0010069722,0.0025374892,0.002406968,0.0032606686,0.009835794,0.0033112108,0.0020604136,0.035552654],"category_scores_gemma":[0.027371932,0.0009062017,0.001017788,0.0065355333,0.0036033068,0.015279907,0.0072452305,0.0038981966,0.007844064],"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":[0.0005911068,0.00010199708,0.0010658867,0.00024765407,0.000078485995,0.00012424229,0.0006606798,0.008418367,0.0025944163,0.8415985,0.032405406,0.11211327],"study_design_scores_gemma":[0.000091625116,0.00014042172,0.0005358253,0.00013257386,0.00009364207,0.00034065725,0.0005623314,0.051125582,0.0041753175,0.78842515,0.15431643,0.000060458016],"about_ca_topic_score_codex":0.0032646272,"about_ca_topic_score_gemma":0.0017546804,"teacher_disagreement_score":0.9853817,"about_ca_system_score_codex":0.0032566446,"about_ca_system_score_gemma":0.0030395123,"threshold_uncertainty_score":0.118935466},"labels":[],"label_agreement":null},{"id":"W2396060534","doi":"","title":"Constructions and Bounds for Splitting and Separating Systems.","year":2015,"lang":"en","type":"article","venue":"Ars Combinatoria","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Mathematics; Combinatorics","score_opus":0.025603991039013358,"score_gpt":0.2728381107831731,"score_spread":0.24723411974415974,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2396060534","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":[0.036589574,0.0051822597,0.7384467,0.005354419,0.0006542845,0.0002462315,0.0023906648,0.002703869,0.20843205],"genre_scores_gemma":[0.55676574,0.004742744,0.36016372,0.002509403,0.0010848191,0.00078461034,0.005733403,0.001987539,0.06622806],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99348176,0.0013188797,0.00063273474,0.0012047474,0.0022851299,0.0010767519],"domain_scores_gemma":[0.9807585,0.011738565,0.00092785823,0.003537879,0.0018231763,0.001213979],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004983395,0.0015100145,0.0013010962,0.0042118225,0.0037903553,0.009524514,0.0037481277,0.0024085885,0.025370557],"category_scores_gemma":[0.021548193,0.0019584144,0.0024788845,0.00686848,0.005052411,0.026413819,0.010612654,0.009731094,0.007403781],"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":[0.00003927469,0.000040023697,0.0002813121,0.00012745404,0.000014643502,0.000044196066,0.00030850898,0.000806496,0.00066454086,0.97844964,0.0063689966,0.012854928],"study_design_scores_gemma":[0.000011880829,0.000012907506,0.0001989601,0.00006693182,0.000030223107,0.00014357713,0.00013078544,0.0030737997,0.0010350639,0.9783952,0.016876686,0.000023947945],"about_ca_topic_score_codex":0.0028646295,"about_ca_topic_score_gemma":0.003133675,"teacher_disagreement_score":0.025370557,"about_ca_system_score_codex":0.0045216656,"about_ca_system_score_gemma":0.0023891542,"threshold_uncertainty_score":0.08487302},"labels":[],"label_agreement":null},{"id":"W2396403785","doi":"","title":"Tree Inclusion Checking Revisited.","year":2015,"lang":"en","type":"article","venue":"International Conference on Data Technologies and Applications","topic":"Advanced Database Systems and Queries","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 Winnipeg","funders":"","keywords":"Computer science; Inclusion (mineral); Tree (set theory); Mathematics; Geology; Combinatorics","score_opus":0.13027297376736238,"score_gpt":0.35051796064361623,"score_spread":0.22024498687625385,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2396403785","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":[0.057845213,0.0044065383,0.85493815,0.026449332,0.0034548866,0.0003113675,0.0018605399,0.006519731,0.04421413],"genre_scores_gemma":[0.6032213,0.0026258717,0.3567968,0.0075715026,0.0021403064,0.00026715078,0.0033958256,0.0034237998,0.020557417],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.98120016,0.0054559945,0.0010461533,0.0026965481,0.0070575722,0.0025435335],"domain_scores_gemma":[0.86718625,0.09129005,0.0032401194,0.021361247,0.015001733,0.001920678],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015600875,0.0009157555,0.0026965176,0.0040026633,0.0057032784,0.008170205,0.0069105434,0.0047777384,0.011463835],"category_scores_gemma":[0.10720522,0.0016052466,0.003553095,0.006496309,0.006629393,0.023484103,0.012227116,0.010460248,0.0030885688],"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":[0.00075128145,0.00020888669,0.0067225657,0.000533016,0.00021496447,0.001327745,0.0014975466,0.009340276,0.0035514245,0.74681723,0.055347685,0.17368747],"study_design_scores_gemma":[0.00007055373,0.000050142386,0.00094015326,0.00029059942,0.00019979579,0.00073969126,0.00048650653,0.0445901,0.008100884,0.91923654,0.025226291,0.000068644455],"about_ca_topic_score_codex":0.009595865,"about_ca_topic_score_gemma":0.010835603,"teacher_disagreement_score":0.015600875,"about_ca_system_score_codex":0.0026448686,"about_ca_system_score_gemma":0.005276048,"threshold_uncertainty_score":0.0825063},"labels":[],"label_agreement":null},{"id":"W2398876418","doi":"","title":"On Conditional Chase Termination.","year":2011,"lang":"en","type":"article","venue":"AMW","topic":"Advanced Database Systems and Queries","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":"Concordia University","funders":"","keywords":"Computer science; Chase","score_opus":0.030194407157634627,"score_gpt":0.2364884310248795,"score_spread":0.20629402386724485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2398876418","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":[0.023032863,0.0027643705,0.8529133,0.0072200308,0.0017729864,0.00029806865,0.00094238017,0.0050058193,0.10605013],"genre_scores_gemma":[0.60341674,0.0035389825,0.26080146,0.0080005005,0.0035696232,0.0014511065,0.004229369,0.0050852676,0.109906875],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99212974,0.002460778,0.0005432827,0.0010795712,0.0024673871,0.0013191494],"domain_scores_gemma":[0.9669893,0.021425487,0.0008394711,0.0061655724,0.0036941173,0.0008861578],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008843668,0.0013003343,0.0018656942,0.002377816,0.0034441166,0.004397799,0.003202281,0.0028546727,0.018651152],"category_scores_gemma":[0.038544077,0.0012086476,0.001785145,0.002409047,0.0064355256,0.017717004,0.010176212,0.0083951,0.0051742876],"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":[0.00033728892,0.000080007165,0.0008467354,0.00017128578,0.00004909779,0.00023882287,0.0005431516,0.0032137656,0.0011375715,0.9320893,0.024114236,0.03717882],"study_design_scores_gemma":[0.00006151879,0.000029174882,0.00016482387,0.000053855532,0.000046655707,0.00013250324,0.00007697282,0.015851947,0.0010020635,0.96963376,0.012924775,0.000022101043],"about_ca_topic_score_codex":0.0031685745,"about_ca_topic_score_gemma":0.0038664057,"teacher_disagreement_score":0.018651152,"about_ca_system_score_codex":0.0025192676,"about_ca_system_score_gemma":0.002484208,"threshold_uncertainty_score":0.06239432},"labels":[],"label_agreement":null},{"id":"W2399302330","doi":"","title":"SQL Azure as a Self-Managing Database Service: Lessons Learned and Challenges Ahead.","year":2011,"lang":"en","type":"article","venue":"IEEE Data(base) Engineering Bulletin","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Cloud computing; SQL; Database; Business Intelligence Markup Language; World Wide Web; Operating system; Server; Client–server model","score_opus":0.09523740754811952,"score_gpt":0.27009911694624955,"score_spread":0.17486170939813003,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2399302330","genre_codex":"commentary","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":[0.09821295,0.13532364,0.13074605,0.5163519,0.0046304,0.00023863344,0.0005571847,0.004326109,0.10961309],"genre_scores_gemma":[0.54870784,0.13460985,0.21537565,0.034564584,0.0036815265,0.00017203962,0.0015312682,0.0011597264,0.060197476],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99785966,0.00054038665,0.00012238314,0.00020340574,0.0009537514,0.00032034962],"domain_scores_gemma":[0.99429274,0.001342565,0.00016221916,0.00055809267,0.0017643915,0.0018799215],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009485122,0.00048778832,0.00028676412,0.0005932195,0.000929609,0.006436925,0.0026124797,0.002923283,0.0032862069],"category_scores_gemma":[0.00791933,0.00027055264,0.00029225225,0.0012299488,0.0021495025,0.014224385,0.0017271494,0.003930403,0.0017230995],"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":[0.00023245103,0.0004444562,0.0076266476,0.00057610916,0.000035498488,0.00049023033,0.0027889416,0.0020388702,0.0057718516,0.17340569,0.22279797,0.5837912],"study_design_scores_gemma":[0.000078998426,0.00074018526,0.005728803,0.00083118153,0.000046693513,0.0016410736,0.005205719,0.013735393,0.0074544484,0.0631524,0.9012618,0.00012317601],"about_ca_topic_score_codex":0.007825424,"about_ca_topic_score_gemma":0.007816554,"teacher_disagreement_score":0.009485122,"about_ca_system_score_codex":0.0013618285,"about_ca_system_score_gemma":0.0035913785,"threshold_uncertainty_score":0.050162733},"labels":[],"label_agreement":null},{"id":"W2399823331","doi":"","title":"Exploratory Search in Databases and the Web.","year":2014,"lang":"en","type":"article","venue":"EDBT/ICDT Workshops","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; XQuery; SPARQL; Query language; Information retrieval; World Wide Web; Web search query; Information needs; Exploratory search; SQL; Web query classification; Ontology; Database; XML database; RDF; XML; Semantic Web; Search engine","score_opus":0.022983218702252922,"score_gpt":0.2597078134539714,"score_spread":0.2367245947517185,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2399823331","genre_codex":"review","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":[0.012486725,0.39932495,0.22457641,0.055210467,0.0034539397,0.00041745827,0.003906577,0.005388933,0.29523453],"genre_scores_gemma":[0.21599121,0.27902123,0.31118876,0.017089447,0.0066509764,0.0012382327,0.010768361,0.0015584852,0.15649326],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9947389,0.0025644007,0.00038165992,0.0005583603,0.0014892868,0.000267337],"domain_scores_gemma":[0.99060225,0.0062709567,0.0005083693,0.0012424809,0.00092767685,0.00044819582],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0063974196,0.0010163428,0.0015285427,0.0062205256,0.0022039823,0.012305781,0.0021987222,0.0046639335,0.021721754],"category_scores_gemma":[0.016384702,0.00084566075,0.001102983,0.012697475,0.004707072,0.02454728,0.0061974647,0.0023070693,0.008790053],"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":[0.00007936739,0.0000635594,0.0014922522,0.001785859,0.00007800438,0.00047245092,0.0021671986,0.0010641714,0.00049750064,0.630625,0.1259051,0.23576954],"study_design_scores_gemma":[0.000025108551,0.00003213939,0.0008803459,0.00083065865,0.00004171786,0.001062976,0.0017161943,0.004365047,0.00043417397,0.5388437,0.4517258,0.000042091473],"about_ca_topic_score_codex":0.0037870908,"about_ca_topic_score_gemma":0.0052580805,"teacher_disagreement_score":0.021721754,"about_ca_system_score_codex":0.0025568071,"about_ca_system_score_gemma":0.0028944912,"threshold_uncertainty_score":0.072666466},"labels":[],"label_agreement":null},{"id":"W2400360421","doi":"","title":"On Construction of Holistic Synopses under the Duplicate Semantics of Streaming Queries.","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Semantics (computer science); Database transaction; Focus (optics); Query language; Data stream mining; Space (punctuation); Database; Query optimization; Information retrieval; Transaction log; Data mining; Theoretical computer science; Programming language","score_opus":0.01588177931298521,"score_gpt":0.24659286251573062,"score_spread":0.23071108320274542,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2400360421","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":[0.041876625,0.00051527476,0.951684,0.0005094689,0.00006424153,0.0002111443,0.00043310242,0.0004281885,0.0042779213],"genre_scores_gemma":[0.48257095,0.0011820942,0.5075777,0.00059134816,0.0002455186,0.0006493236,0.0021042873,0.00030161013,0.0047771786],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9954288,0.0012107401,0.00048684454,0.00083882874,0.0016457319,0.00038901047],"domain_scores_gemma":[0.9819672,0.010163727,0.00160807,0.0032261359,0.0023086572,0.0007261846],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005091017,0.0005836597,0.0009377402,0.0013770361,0.0012171796,0.0020731033,0.0010877578,0.000957506,0.0029615953],"category_scores_gemma":[0.025955193,0.0006588475,0.0010241191,0.0019039724,0.0025143165,0.010281205,0.0054780403,0.0020018981,0.00055863115],"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":[0.00032024458,0.00012621786,0.0032937392,0.0004544727,0.000101709295,0.0005888984,0.001817349,0.05317737,0.015645605,0.8054267,0.0054281154,0.11361957],"study_design_scores_gemma":[0.000050686573,0.0002606919,0.0008045957,0.00009918206,0.000060952796,0.000561775,0.0007781104,0.20756762,0.0097456,0.7663883,0.013636371,0.00004617856],"about_ca_topic_score_codex":0.00083572196,"about_ca_topic_score_gemma":0.0007541307,"teacher_disagreement_score":0.005091017,"about_ca_system_score_codex":0.00094363367,"about_ca_system_score_gemma":0.0011278308,"threshold_uncertainty_score":0.026924193},"labels":[],"label_agreement":null},{"id":"W2401927767","doi":"","title":"Counting embeddings of a chain into a binary tree.","year":2009,"lang":"en","type":"article","venue":"Ars Combinatoria","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Mathematics; Binary tree; Random binary tree; Tree (set theory); Chain (unit); Binary number; Combinatorics; Arithmetic; Physics","score_opus":0.008191358697005907,"score_gpt":0.24616541993636018,"score_spread":0.23797406123935427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2401927767","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":[0.21187553,0.0015174154,0.6874078,0.0022808549,0.00049089786,0.00023987851,0.0034975575,0.0016470045,0.09104301],"genre_scores_gemma":[0.6616236,0.0012458871,0.2864447,0.000550575,0.000486813,0.0003971653,0.0051940735,0.0010005438,0.0430567],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.997154,0.000675498,0.00030962125,0.00060900144,0.0008589526,0.0003929231],"domain_scores_gemma":[0.98630047,0.007377635,0.0010982559,0.0023977214,0.0016700078,0.0011558384],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016741452,0.0008428443,0.0008545223,0.0034133354,0.0019952033,0.0048477943,0.0021371066,0.001819465,0.019048288],"category_scores_gemma":[0.01831245,0.000923507,0.00089871144,0.0049107876,0.0022179869,0.014873756,0.0041318447,0.0026879124,0.0031796577],"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":[0.0001895632,0.00010880209,0.0029149135,0.00033454454,0.00004645278,0.00019432303,0.0005416811,0.002773174,0.0025991953,0.9238663,0.010724243,0.055706855],"study_design_scores_gemma":[0.00002022129,0.00004420832,0.0006792043,0.00009581719,0.000056093864,0.00039667918,0.0002577991,0.019630278,0.002248847,0.9608679,0.01567991,0.000023067158],"about_ca_topic_score_codex":0.0011364844,"about_ca_topic_score_gemma":0.0018821904,"teacher_disagreement_score":0.019048288,"about_ca_system_score_codex":0.0014017939,"about_ca_system_score_gemma":0.00076169084,"threshold_uncertainty_score":0.06372291},"labels":[],"label_agreement":null},{"id":"W2402131239","doi":"","title":"Using Stream Features for Instant Document Ranking.","year":2013,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Instant; Ranking (information retrieval); Computer science; Information retrieval; Biology; Food science","score_opus":0.019285954457138023,"score_gpt":0.258074460615428,"score_spread":0.23878850615828998,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2402131239","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":[0.1665869,0.010792264,0.6837096,0.0017521984,0.0035039708,0.0010286865,0.04257726,0.075717576,0.014331502],"genre_scores_gemma":[0.50465715,0.0021005622,0.4249919,0.00035237614,0.0017884285,0.00044819832,0.04635348,0.0013430327,0.017964859],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987268,0.00026019485,0.00013300001,0.00021240413,0.00052029017,0.0001472812],"domain_scores_gemma":[0.9955503,0.0018905216,0.00033203428,0.0006595121,0.0013262335,0.0002413618],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001502176,0.0012191253,0.0014809826,0.0076205935,0.0006014738,0.002369244,0.0010818152,0.0011914275,0.0068967897],"category_scores_gemma":[0.00814811,0.00035571252,0.0007234452,0.005498448,0.00018661506,0.003453563,0.000770733,0.0009969268,0.0063103116],"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":[0.0024444098,0.0004554152,0.0055491067,0.00042374863,0.00021774072,0.00021770067,0.000076392935,0.008657623,0.014855215,0.0023330827,0.09060733,0.87416226],"study_design_scores_gemma":[0.000556799,0.0013278993,0.01222334,0.000113626265,0.00037568738,0.00084515807,0.00034626486,0.8561141,0.04936957,0.022151204,0.056411967,0.00016439777],"about_ca_topic_score_codex":0.006239112,"about_ca_topic_score_gemma":0.011272168,"teacher_disagreement_score":0.0076205935,"about_ca_system_score_codex":0.00051937636,"about_ca_system_score_gemma":0.0009280625,"threshold_uncertainty_score":0.023072064},"labels":[],"label_agreement":null},{"id":"W2404347187","doi":"","title":"Einsatz automatischer Indexierungsverfahren in der Datenbank PSYNDEX.","year":2007,"lang":"de","type":"article","venue":"Ingénierie des systèmes d information","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Art","score_opus":0.01602212849959554,"score_gpt":0.2533070138789862,"score_spread":0.23728488537939066,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2404347187","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":[0.12742437,0.0036119,0.790264,0.0020258874,0.0005976622,0.00082826085,0.005341133,0.05718536,0.012721498],"genre_scores_gemma":[0.37031403,0.0013044876,0.61058736,0.0004757243,0.00012634372,0.00044983384,0.007600135,0.0015428188,0.0075993123],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9952394,0.0012375545,0.0006492833,0.00076049514,0.001860046,0.0002531611],"domain_scores_gemma":[0.9901079,0.005470828,0.0004460729,0.0024994388,0.0012642137,0.00021153987],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004257236,0.0008597338,0.0010154006,0.0022899103,0.0005712302,0.0039321226,0.0011832933,0.0011476465,0.004465903],"category_scores_gemma":[0.016524851,0.0006001207,0.0005436476,0.0022834733,0.0007555363,0.0043335278,0.002535151,0.00208865,0.0043561338],"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":[0.0029212653,0.00064645207,0.0068659894,0.0009063222,0.0003221597,0.00069604476,0.000855622,0.017272927,0.075852536,0.020245558,0.026587809,0.8468273],"study_design_scores_gemma":[0.0009789506,0.00067802495,0.007934432,0.00036936405,0.00049747556,0.0014917061,0.0009490537,0.3885213,0.42448464,0.07382756,0.100000374,0.00026709287],"about_ca_topic_score_codex":0.003081787,"about_ca_topic_score_gemma":0.0029597739,"teacher_disagreement_score":0.004465903,"about_ca_system_score_codex":0.0006568788,"about_ca_system_score_gemma":0.0019551485,"threshold_uncertainty_score":0.022514641},"labels":[],"label_agreement":null},{"id":"W2404568588","doi":"10.13140/rg.2.1.1009.0007","title":"A Model-Driven Solution for Financial Data Representation Expressed in FIXML","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Modularity (biology); Representation (politics); Transformation (genetics); Programming language; Set (abstract data type); Code (set theory); External Data Representation; Data mining; Theoretical computer science; Artificial intelligence","score_opus":0.08810088202502438,"score_gpt":0.3225617215637276,"score_spread":0.23446083953870323,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2404568588","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":[0.0021269151,0.000034717737,0.98955053,0.00019781411,0.000037326347,0.00009840319,0.0002735078,0.0067337924,0.00094692915],"genre_scores_gemma":[0.07400936,0.00016480651,0.91757005,0.0003685228,0.000039475704,0.0004031613,0.0022780744,0.0021601021,0.0030063828],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9963509,0.0009694633,0.00043012048,0.00051836687,0.0014707291,0.00026041592],"domain_scores_gemma":[0.99559814,0.0012968802,0.00033587814,0.0018432455,0.0008338408,0.000091978756],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037984252,0.0010791653,0.00068480993,0.002011254,0.0009597181,0.0040333993,0.0027225967,0.0018680984,0.0038996614],"category_scores_gemma":[0.009488115,0.0009036022,0.002251964,0.001403745,0.0012406288,0.0045433803,0.0034256089,0.0034257567,0.0017687549],"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":[0.0005026061,0.0004189856,0.003706376,0.0011192014,0.00028106009,0.0019379557,0.0021766787,0.12721328,0.046081897,0.4136355,0.026036428,0.37689003],"study_design_scores_gemma":[0.00007596785,0.00013979558,0.000429402,0.00025322786,0.00014141471,0.0008540603,0.00038851702,0.6595163,0.09603423,0.10812593,0.13389777,0.0001434165],"about_ca_topic_score_codex":0.0024997008,"about_ca_topic_score_gemma":0.0030680234,"teacher_disagreement_score":0.0040333993,"about_ca_system_score_codex":0.0013071607,"about_ca_system_score_gemma":0.0023480756,"threshold_uncertainty_score":0.020088255},"labels":[],"label_agreement":null},{"id":"W2406071341","doi":"","title":"Structural Repairs of Multidimensional Databases.","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Schema (genetic algorithms); Materialized view; Correctness; Data warehouse; Rewriting; Data integrity; Database; Information retrieval; Data mining; Theoretical computer science; Programming language; View; Database design","score_opus":0.05936411771898818,"score_gpt":0.2631854752121849,"score_spread":0.2038213574931967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2406071341","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":[0.1609599,0.00082168484,0.8265022,0.0011343154,0.00029886098,0.00029944815,0.0005424364,0.003473548,0.005967628],"genre_scores_gemma":[0.760816,0.0002486107,0.23358938,0.00022400125,0.0000504316,0.00016187747,0.0006886186,0.0002837269,0.003937393],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9962955,0.0011598264,0.00039689176,0.00056144403,0.0013130752,0.00027321605],"domain_scores_gemma":[0.98676515,0.00498543,0.0012624064,0.0052258517,0.0014076757,0.00035350135],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0044635697,0.00046491562,0.00064966816,0.00088388816,0.0009891725,0.0019825555,0.0023562978,0.0011988744,0.0034111817],"category_scores_gemma":[0.01967997,0.00054953445,0.0008914091,0.00089423254,0.0022434914,0.0041534854,0.00444842,0.0015427065,0.00043457313],"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":[0.00090363115,0.00029974364,0.008227711,0.0007616119,0.00016101725,0.0016436466,0.003996405,0.23123479,0.02652805,0.5762636,0.00885196,0.14112791],"study_design_scores_gemma":[0.00010487272,0.00032873364,0.0014000539,0.0001256143,0.00009848715,0.00121115,0.0013752899,0.57351756,0.04790923,0.33368433,0.04017815,0.00006644302],"about_ca_topic_score_codex":0.0018508874,"about_ca_topic_score_gemma":0.0012636774,"teacher_disagreement_score":0.0044635697,"about_ca_system_score_codex":0.001226066,"about_ca_system_score_gemma":0.00084175076,"threshold_uncertainty_score":0.023605883},"labels":[],"label_agreement":null},{"id":"W2406907785","doi":"10.4242/balisagevol4.cameron01","title":"Parallel Bit Stream Technology as a Foundation for XML Parsing Performance","year":2009,"lang":"en","type":"article","venue":"Balisage series on markup technologies","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Parsing; SIMD; Byte; Compiler; XML; Bitstream; Automatic summarization; Programming language; Simple API for XML; Computer architecture; Stream processing; Parallel computing; Operating system; Efficient XML Interchange; Artificial intelligence; XML Signature","score_opus":0.013928012532668961,"score_gpt":0.25957456622759684,"score_spread":0.24564655369492788,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2406907785","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":[0.03247726,0.009916172,0.8894401,0.0023941302,0.00073701836,0.000235877,0.00074998813,0.00886827,0.0551811],"genre_scores_gemma":[0.32525504,0.014707964,0.63959664,0.00083219475,0.00050755515,0.0004032494,0.0016972651,0.001816779,0.015183371],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990182,0.00013639117,0.00011560167,0.00013436233,0.00053085666,0.0000645255],"domain_scores_gemma":[0.9974948,0.0011059718,0.000121744575,0.00040309998,0.00082470203,0.000049781047],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016335734,0.0005809961,0.0005983858,0.0010346264,0.00046876218,0.0029930025,0.0011846963,0.00076874555,0.0088625755],"category_scores_gemma":[0.006073335,0.0005562291,0.00039401127,0.001907339,0.0007227131,0.005178384,0.0007820007,0.0016850693,0.0036558926],"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":[0.0007394789,0.0001304403,0.0015342669,0.0012236385,0.00005321451,0.00051500596,0.00041728315,0.02952498,0.19273576,0.3345457,0.016773159,0.42180702],"study_design_scores_gemma":[0.00008469303,0.00045843422,0.0012650613,0.00038087388,0.00013694524,0.0013369008,0.00022931167,0.26365742,0.37938023,0.1893987,0.16352223,0.00014926151],"about_ca_topic_score_codex":0.00093655364,"about_ca_topic_score_gemma":0.0006477581,"teacher_disagreement_score":0.0088625755,"about_ca_system_score_codex":0.00092787907,"about_ca_system_score_gemma":0.0011195857,"threshold_uncertainty_score":0.029648304},"labels":[],"label_agreement":null},{"id":"W2406990242","doi":"10.4242/balisagevol3.muldner01","title":"XSAQCT: XML Queryable Compressor","year":2009,"lang":"en","type":"article","venue":"Balisage series on markup technologies","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Acadia University","funders":"","keywords":"Computer science; XML; Database; Gas compressor; Accounting; Software engineering; World Wide Web; Engineering; Business; Mechanical engineering","score_opus":0.009228316138441564,"score_gpt":0.22979839607798255,"score_spread":0.22057007993954098,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2406990242","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":[0.031259574,0.0019971973,0.69327605,0.0012068137,0.0005075391,0.0012552085,0.017994283,0.23521854,0.017284814],"genre_scores_gemma":[0.3593138,0.0031442903,0.50900364,0.0023055435,0.0005295068,0.0016054433,0.052034676,0.017662395,0.05440074],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99814653,0.0001641092,0.00019486403,0.00019683263,0.0011531496,0.00014454684],"domain_scores_gemma":[0.9977946,0.0006887353,0.00014430007,0.00057025533,0.00067468546,0.00012740547],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013464045,0.0012939353,0.00078098266,0.0018425041,0.0005806288,0.001678065,0.0024655939,0.0011646793,0.020469157],"category_scores_gemma":[0.005213108,0.00040439877,0.0005735611,0.0025182732,0.0011524189,0.003200038,0.0018687849,0.0012675414,0.0038616904],"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":[0.0043262118,0.00024823225,0.0033417142,0.001983983,0.00018595974,0.0012284304,0.0009822974,0.012631389,0.15668939,0.04886974,0.23739117,0.53212154],"study_design_scores_gemma":[0.00074683956,0.00080910255,0.0023704632,0.0001993226,0.00013804436,0.001924884,0.0004163267,0.18792345,0.32749635,0.019424865,0.45827073,0.00027963487],"about_ca_topic_score_codex":0.005795692,"about_ca_topic_score_gemma":0.003264559,"teacher_disagreement_score":0.020469157,"about_ca_system_score_codex":0.00094902894,"about_ca_system_score_gemma":0.0010862541,"threshold_uncertainty_score":0.06847614},"labels":[],"label_agreement":null},{"id":"W2407149601","doi":"","title":"Maximum Minimal k-rankings of Cycles.","year":2013,"lang":"en","type":"article","venue":"Ars Combinatoria","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Mathematics; Statistics","score_opus":0.00956610690804818,"score_gpt":0.22578229488137028,"score_spread":0.2162161879733221,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2407149601","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":[0.43298715,0.006155238,0.22848627,0.006799836,0.00075585255,0.0005720291,0.03677086,0.003845758,0.28362703],"genre_scores_gemma":[0.8608766,0.0013984035,0.08193772,0.000996351,0.0002868967,0.00026154547,0.014085417,0.00079074554,0.03936629],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9982514,0.00048322778,0.00016293618,0.00037886252,0.00032170513,0.00040189258],"domain_scores_gemma":[0.99359137,0.002785741,0.0005495443,0.00097297406,0.0011363032,0.0009641041],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010243868,0.0008286274,0.0011348817,0.0024390926,0.0024714167,0.005413882,0.001484721,0.0013292524,0.023290027],"category_scores_gemma":[0.009650408,0.00073798216,0.00093691587,0.0030368401,0.001206353,0.006721595,0.0020381147,0.0015840689,0.0045636785],"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":[0.0011572056,0.00026342488,0.005018924,0.0018998513,0.00017104673,0.00047741632,0.00080860965,0.0065441076,0.008723434,0.80341285,0.06913021,0.10239293],"study_design_scores_gemma":[0.0000896146,0.000082132145,0.001854526,0.0001959776,0.000099792276,0.0006262683,0.00060654513,0.008871398,0.004418435,0.94599557,0.037096597,0.000063334024],"about_ca_topic_score_codex":0.0021405667,"about_ca_topic_score_gemma":0.0058882628,"teacher_disagreement_score":0.023290027,"about_ca_system_score_codex":0.0017856506,"about_ca_system_score_gemma":0.0016780804,"threshold_uncertainty_score":0.07791293},"labels":[],"label_agreement":null},{"id":"W2407655771","doi":"","title":"Kinetic Data Structures on The Move.","year":2013,"lang":"en","type":"article","venue":"Canadian Conference on Computational Geometry","topic":"Advanced Database Systems and Queries","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 Victoria","funders":"","keywords":"Kinetic energy; Computer science; Physics; Classical mechanics","score_opus":0.05671062729089524,"score_gpt":0.2630991015320934,"score_spread":0.2063884742411982,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2407655771","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":[0.016714612,0.01134273,0.7675817,0.015935656,0.0053050104,0.000335098,0.021054277,0.026556214,0.13517472],"genre_scores_gemma":[0.35284325,0.012184786,0.36682168,0.0047672903,0.0024842345,0.0008255128,0.040076282,0.008955782,0.21104118],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99685365,0.00052656257,0.00046551393,0.0006063733,0.0012109645,0.0003370691],"domain_scores_gemma":[0.99292254,0.0015017,0.00042594242,0.0034947484,0.0012023158,0.00045258453],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024413385,0.0010069185,0.0015495584,0.0023699428,0.0028853389,0.009031907,0.0046230163,0.0025693865,0.050038874],"category_scores_gemma":[0.013284384,0.0013943943,0.0016033525,0.0052791922,0.002679275,0.027560007,0.006663138,0.0037579478,0.020332145],"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":[0.0002583632,0.000029524761,0.0003889158,0.0002497845,0.00003644424,0.0001266398,0.00027724457,0.0024469127,0.00084313133,0.8701762,0.0830829,0.042083893],"study_design_scores_gemma":[0.000080229525,0.000047127724,0.00022567052,0.00018280151,0.00006428954,0.00030813634,0.00030762103,0.013048147,0.0032407965,0.6172215,0.3652073,0.00006625008],"about_ca_topic_score_codex":0.008327978,"about_ca_topic_score_gemma":0.009337267,"teacher_disagreement_score":0.050038874,"about_ca_system_score_codex":0.0020402838,"about_ca_system_score_gemma":0.0031640474,"threshold_uncertainty_score":0.16739672},"labels":[],"label_agreement":null},{"id":"W2408609218","doi":"","title":"Dynamic View Selection for OLAP.","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Materialized view; Online analytical processing; Data warehouse; Computer science; Aggregate (composite); Selection (genetic algorithm); Task (project management); Set (abstract data type); Information retrieval; Order (exchange); Data mining; Database; View; Artificial intelligence","score_opus":0.007237351536765393,"score_gpt":0.26512639138262023,"score_spread":0.2578890398458548,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2408609218","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":[0.004305118,0.0028883743,0.91344327,0.0016808554,0.000334021,0.0003035764,0.004104438,0.05788266,0.015057697],"genre_scores_gemma":[0.102434926,0.001717319,0.8703578,0.00079125346,0.00025559237,0.00042656192,0.010568015,0.0032675539,0.010180948],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991239,0.00029265956,0.000066120345,0.00012931248,0.0003357045,0.00005231717],"domain_scores_gemma":[0.99855596,0.00056273554,0.00008965032,0.0004655646,0.00017861753,0.00014742954],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016041831,0.0011045961,0.000649157,0.001119927,0.0006041422,0.0025139758,0.0017809549,0.0009500988,0.021556946],"category_scores_gemma":[0.004346697,0.0007446404,0.0005654721,0.0018270288,0.00045708581,0.003064987,0.0022895017,0.001817944,0.009607179],"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":[0.0005471071,0.00018836207,0.00135438,0.00045364466,0.00012324845,0.0003200001,0.00017499788,0.024610175,0.006689431,0.05923263,0.26445082,0.6418552],"study_design_scores_gemma":[0.0001429205,0.00008140127,0.0010299672,0.0001598786,0.00004410382,0.00048525978,0.00012978319,0.6167493,0.0055427495,0.16664602,0.20893015,0.000058483365],"about_ca_topic_score_codex":0.0043082153,"about_ca_topic_score_gemma":0.0065423576,"teacher_disagreement_score":0.021556946,"about_ca_system_score_codex":0.00076822337,"about_ca_system_score_gemma":0.0007761136,"threshold_uncertainty_score":0.07211518},"labels":[],"label_agreement":null},{"id":"W2413266452","doi":"10.29173/cais735","title":"A Retrieval Model for Common Textual Database Management Systems","year":2013,"lang":"en","type":"article","venue":"Proceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSI","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer science; Information retrieval; Process (computing); Quality (philosophy); Relevance (law); Cognitive models of information retrieval; Class (philosophy); Database; Human–computer information retrieval; Information system; Search engine; Artificial intelligence","score_opus":0.02835470561654809,"score_gpt":0.25495330042048264,"score_spread":0.22659859480393454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2413266452","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":[0.017011387,0.0011407385,0.9433213,0.0021269112,0.000117183445,0.00038464548,0.00069338933,0.0010735492,0.03413096],"genre_scores_gemma":[0.53596145,0.002345054,0.40528095,0.0011714576,0.0004654016,0.0013881796,0.0031911582,0.00050822477,0.04968822],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99643874,0.00088309246,0.0004357292,0.0006213921,0.0012369354,0.00038413674],"domain_scores_gemma":[0.9973126,0.0010037795,0.00029447075,0.00051697297,0.0007422392,0.00012986285],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032991893,0.0009647623,0.00084118504,0.001919073,0.0013266602,0.006696628,0.0034686842,0.0032278204,0.009084706],"category_scores_gemma":[0.0067646713,0.0005542656,0.0015912578,0.002001842,0.002646839,0.012693106,0.0025045732,0.0020636125,0.0032868753],"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":[0.0000659348,0.000057442376,0.00040824115,0.00015815429,0.000021208873,0.00023553685,0.00063487573,0.062178623,0.0014985634,0.9098996,0.0037874444,0.021054424],"study_design_scores_gemma":[0.000048478836,0.00007293773,0.0001468407,0.000076323944,0.00003177098,0.00021616959,0.00023297119,0.6051724,0.0010879195,0.3603164,0.032559425,0.000038396058],"about_ca_topic_score_codex":0.009201881,"about_ca_topic_score_gemma":0.0050328914,"teacher_disagreement_score":0.009201881,"about_ca_system_score_codex":0.004088363,"about_ca_system_score_gemma":0.0022562903,"threshold_uncertainty_score":0.030391335},"labels":[],"label_agreement":null},{"id":"W2440046523","doi":"10.1145/2882903.2903735","title":"Towards a Hybrid Design for Fast Query Processing in DB2 with BLU Acceleration Using Graphical Processing Units","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada)","funders":"","keywords":"Computer science; Kernel (algebra); Relational database management system; sort; Acceleration; Central processing unit; Set (abstract data type); Metadata; Speedup; Parallel computing; Relational database; Performance improvement; Instruction set; Operating system; Database; Programming language","score_opus":0.06590376357629602,"score_gpt":0.28747447696616546,"score_spread":0.22157071338986944,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2440046523","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":[0.054081727,0.00074084394,0.9220222,0.00036756773,0.00011458215,0.00014667808,0.00023825807,0.016185872,0.0061022337],"genre_scores_gemma":[0.35488683,0.00036284732,0.63438785,0.00083376723,0.00007072249,0.0002116484,0.000998737,0.0016287096,0.00661896],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987482,0.00017476428,0.00009054157,0.00020297233,0.0005936078,0.00018989743],"domain_scores_gemma":[0.9989918,0.0001898121,0.0000779147,0.00028947994,0.00036258472,0.00008837451],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00095366116,0.00084541464,0.0005230807,0.00071999873,0.000468202,0.0021739574,0.0039916164,0.0006057716,0.003835769],"category_scores_gemma":[0.002005446,0.0006347374,0.00065212505,0.0013458495,0.00052319036,0.0023694513,0.0012236363,0.0011521687,0.002088814],"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":[0.0042276345,0.000841049,0.013531571,0.0010272834,0.0005422592,0.0008498705,0.0012381485,0.07619141,0.35478723,0.041330997,0.051260196,0.45417237],"study_design_scores_gemma":[0.0002926697,0.0010163509,0.002874533,0.00005861192,0.00017769625,0.0006848485,0.00023223263,0.74891984,0.17999372,0.009031771,0.056578364,0.00013929805],"about_ca_topic_score_codex":0.004018138,"about_ca_topic_score_gemma":0.0041352776,"teacher_disagreement_score":0.004018138,"about_ca_system_score_codex":0.0010766556,"about_ca_system_score_gemma":0.00076665176,"threshold_uncertainty_score":0.012831926},"labels":[],"label_agreement":null},{"id":"W2440178963","doi":"10.5555/1182635.1164191","title":"Full disjunctions: polynomial-delay iterators in action","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Tuple; Extension (predicate logic); Time complexity; Relation (database); Associative property; Polynomial; Algorithm; Operator (biology); Theoretical computer science; Mathematics; Data mining; Programming language; Discrete mathematics","score_opus":0.012172557426112238,"score_gpt":0.24473799762780624,"score_spread":0.232565440201694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2440178963","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":[0.008672943,0.00015305771,0.98292613,0.00008612534,0.000027923234,0.00009769281,0.00014919507,0.004895668,0.0029913194],"genre_scores_gemma":[0.09460935,0.00015003914,0.89886624,0.0001235228,0.00004075506,0.00012471786,0.00055777514,0.0011193672,0.0044082934],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977106,0.00048541423,0.00022891152,0.0004465272,0.00086580176,0.00026271108],"domain_scores_gemma":[0.9973302,0.001392361,0.00020281736,0.0006592068,0.00030433806,0.00011102722],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023094576,0.0010980405,0.0008925076,0.0010413998,0.000901616,0.0027442416,0.0021977245,0.000903892,0.008393401],"category_scores_gemma":[0.005138353,0.000751374,0.0011216913,0.0016325093,0.001973039,0.005214772,0.003540412,0.0019729834,0.003472393],"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":[0.0017739079,0.00022858805,0.0022937388,0.00062093197,0.000112259404,0.0004164746,0.001249098,0.042983044,0.0540054,0.18104781,0.013195162,0.7020736],"study_design_scores_gemma":[0.00020511044,0.0003368562,0.0005887218,0.00011624448,0.00011867667,0.0006698754,0.00032676218,0.55543137,0.11578348,0.26770383,0.058602344,0.000116689094],"about_ca_topic_score_codex":0.0018698251,"about_ca_topic_score_gemma":0.0026307567,"teacher_disagreement_score":0.008393401,"about_ca_system_score_codex":0.0010714955,"about_ca_system_score_gemma":0.0011987431,"threshold_uncertainty_score":0.028078735},"labels":[],"label_agreement":null},{"id":"W2460411447","doi":"10.1145/2938503.2938515","title":"Optimizing Druid with Roaring bitmaps","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université TÉLUQ; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Bitmap; Computer science; Search engine indexing; Terabyte; Online analytical processing; Computer graphics (images); Parallel computing; Data mining; Information retrieval; Data warehouse; Operating system","score_opus":0.011104755948545063,"score_gpt":0.21122622988930553,"score_spread":0.20012147394076046,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2460411447","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":[0.38049126,0.0043276288,0.5124825,0.00088428135,0.0005531623,0.0008642098,0.0030777184,0.0805712,0.016748033],"genre_scores_gemma":[0.55682135,0.0006522515,0.43231758,0.00035211252,0.000058246056,0.00039704796,0.003657472,0.0014412896,0.0043026274],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979183,0.0002934519,0.00022741022,0.00027395092,0.0009631933,0.00032362563],"domain_scores_gemma":[0.9955929,0.0013336091,0.00030495017,0.0015047798,0.0010336274,0.00023013908],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012516243,0.0013372666,0.0009850744,0.0013163848,0.0006290013,0.002365784,0.0030882396,0.0006922751,0.0049293917],"category_scores_gemma":[0.0074696383,0.00049637817,0.0005328044,0.0036341355,0.000688997,0.0048589758,0.0021766266,0.0010548302,0.0023301633],"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":[0.0037841033,0.0011071517,0.006753785,0.0010483647,0.00019055077,0.00047951814,0.0008598811,0.10430374,0.10153425,0.013505793,0.04096129,0.7254716],"study_design_scores_gemma":[0.0004366211,0.0010626687,0.0027018767,0.000061882,0.000093720766,0.0005924844,0.0006955942,0.76536685,0.18046695,0.0080091385,0.040349633,0.00016262569],"about_ca_topic_score_codex":0.00457505,"about_ca_topic_score_gemma":0.003545152,"teacher_disagreement_score":0.0049293917,"about_ca_system_score_codex":0.0010718722,"about_ca_system_score_gemma":0.00151924,"threshold_uncertainty_score":0.01649046},"labels":[],"label_agreement":null},{"id":"W2464118519","doi":"10.1007/978-0-387-39940-9_2541","title":"Electronic Data Capture","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":13,"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","score_opus":0.01934210422805181,"score_gpt":0.246143606261461,"score_spread":0.2268015020334092,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2464118519","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006157981,0.0039224587,0.2469675,0.0010982128,0.0014200273,0.0014450212,0.03889798,0.023668267,0.67642266],"genre_scores_gemma":[0.028022498,0.0047048153,0.09912187,0.0011116168,0.00035273697,0.000707361,0.04668358,0.0026347486,0.81666076],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989454,0.00007648288,0.00007537162,0.00021187316,0.0006204849,0.00007038975],"domain_scores_gemma":[0.998295,0.0003057533,0.0000540467,0.0006971139,0.00058617955,0.00006183627],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010675006,0.00083319424,0.00063178816,0.004390133,0.0008749511,0.0031833323,0.0014859883,0.0007758038,0.21293439],"category_scores_gemma":[0.0025921909,0.0006025482,0.0005176495,0.00500515,0.00039015728,0.0025327322,0.0021222217,0.00082073023,0.14715989],"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":[0.000111547735,0.00006664358,0.00091526425,0.0005059691,0.000020255311,0.00017252319,0.00016451323,0.00041378624,0.010372367,0.019050675,0.33582795,0.6323786],"study_design_scores_gemma":[0.000012817128,0.000032628923,0.0013981542,0.00014918161,0.000016841437,0.00043921362,0.000096281685,0.0011386812,0.015071055,0.0037176511,0.9779018,0.000025713647],"about_ca_topic_score_codex":0.0013229696,"about_ca_topic_score_gemma":0.0021294227,"teacher_disagreement_score":0.21293439,"about_ca_system_score_codex":0.00057794055,"about_ca_system_score_gemma":0.0009882852,"threshold_uncertainty_score":0.71233654},"labels":[],"label_agreement":null},{"id":"W2474818566","doi":"","title":"A new algorithm for tree mapping in XML databases","year":2007,"lang":"en","type":"article","venue":"Internet, Multimedia Systems and Applications","topic":"Advanced Database Systems and Queries","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 Winnipeg","funders":"","keywords":"Computer science; XML database; XML; Database; Information retrieval; World Wide Web","score_opus":0.03050215525600394,"score_gpt":0.29483713580597654,"score_spread":0.2643349805499726,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2474818566","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":[0.002045106,0.00025099036,0.9945052,0.00009446652,0.00010198809,0.00007050415,0.00014345777,0.0021761484,0.000612184],"genre_scores_gemma":[0.014802267,0.00019776363,0.9823728,0.00008181795,0.000051226394,0.00011696487,0.0005356189,0.0003364894,0.0015051184],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974597,0.00042780227,0.00035490177,0.00060514413,0.0010052382,0.00014717756],"domain_scores_gemma":[0.9965062,0.0014216871,0.00014545472,0.0009190769,0.0008645546,0.00014308881],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002116793,0.0010141351,0.0014595045,0.003516847,0.001304867,0.00376249,0.0030484449,0.001920702,0.0076696803],"category_scores_gemma":[0.009282675,0.00090005173,0.001268843,0.004675039,0.00091346627,0.0076615373,0.003580852,0.0023910347,0.0031549432],"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":[0.00031064238,0.0001663556,0.0008782136,0.00029968063,0.00009889084,0.00012905708,0.00023770011,0.02090923,0.0084227575,0.043119203,0.017438656,0.90798956],"study_design_scores_gemma":[0.00020772482,0.00021350599,0.00076402724,0.00013525177,0.00014587863,0.0009051839,0.00023558723,0.7668133,0.018609617,0.15794294,0.05392144,0.0001055959],"about_ca_topic_score_codex":0.0022723402,"about_ca_topic_score_gemma":0.0027930415,"teacher_disagreement_score":0.0076696803,"about_ca_system_score_codex":0.0010228704,"about_ca_system_score_gemma":0.0014459698,"threshold_uncertainty_score":0.025657654},"labels":[],"label_agreement":null},{"id":"W2475399949","doi":"10.2495/dne-v11-n3-275-283","title":"Towards anticipate detection of complex event processing rules with probabilistic modelling","year":2016,"lang":"en","type":"article","venue":"International Journal of Design & Nature and Ecodynamics","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"European Regional Development Fund; Horizon 2020 Framework Programme; Ministerio de Economía y Competitividad; European Commission","keywords":"Computer science; Event (particle physics); Probabilistic logic; Complex event processing; Data mining; Artificial intelligence; Process (computing); Programming language; Physics","score_opus":0.024562738450060555,"score_gpt":0.27364892051845646,"score_spread":0.24908618206839592,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2475399949","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":[0.0055617024,0.0001024548,0.9923833,0.00012140936,0.000022861865,0.000069059315,0.000053705746,0.0012799427,0.00040558117],"genre_scores_gemma":[0.26358384,0.0003705954,0.7334432,0.00021396695,0.00009972181,0.00024330293,0.00041168762,0.00022553834,0.0014080529],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99461174,0.0012447119,0.00045621025,0.00091399386,0.0024948022,0.00027855812],"domain_scores_gemma":[0.9873553,0.007519705,0.0012036778,0.0019197424,0.0016933348,0.00030827304],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0048241485,0.001159355,0.0013502642,0.0016527033,0.0005043528,0.0041847527,0.0029615248,0.0018807155,0.0017032024],"category_scores_gemma":[0.020962963,0.0011710826,0.0019784265,0.0009836508,0.00093293504,0.0036209095,0.0026065586,0.0030299344,0.0012391773],"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":[0.0010772238,0.0006555731,0.0094565265,0.00068416045,0.0003453442,0.0010965683,0.0009559761,0.42946437,0.05750468,0.082497165,0.0048245923,0.41143784],"study_design_scores_gemma":[0.000017111983,0.00004840529,0.00025813066,0.000014644291,0.000028140308,0.00009062638,0.000020416475,0.98170656,0.005710782,0.010399001,0.0016867135,0.000019364452],"about_ca_topic_score_codex":0.0030283043,"about_ca_topic_score_gemma":0.002099598,"teacher_disagreement_score":0.0048241485,"about_ca_system_score_codex":0.0007452779,"about_ca_system_score_gemma":0.0021651706,"threshold_uncertainty_score":0.025512815},"labels":[],"label_agreement":null},{"id":"W2477249044","doi":"10.1007/b12013","title":"Advanced Conceptual Modeling Techniques","year":2003,"lang":"en","type":"book","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":32,"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","score_opus":0.01698056878085206,"score_gpt":0.25908060649740583,"score_spread":0.24210003771655378,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2477249044","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":[0.00048450427,0.0008476039,0.965638,0.000493708,0.00016492858,0.000061887156,0.0002995893,0.0011129946,0.030896802],"genre_scores_gemma":[0.037795648,0.0044663283,0.88180256,0.00045138784,0.00036426022,0.00034993066,0.0026062874,0.0009300629,0.071233556],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99838126,0.0003499232,0.00014632096,0.00033445674,0.00070944073,0.00007860828],"domain_scores_gemma":[0.9987581,0.00036392765,0.000054567732,0.00047695855,0.00031326097,0.000033242577],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018063232,0.0017261064,0.00094453496,0.0026423554,0.0011181415,0.004291538,0.0025561908,0.0010796532,0.032108217],"category_scores_gemma":[0.003761059,0.0010570287,0.0026827087,0.0032958712,0.0012911869,0.007531096,0.0025048817,0.0032793107,0.015885945],"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":[0.000007919633,0.000021867101,0.00006261806,0.0001485687,0.000023731218,0.000043793072,0.00020507173,0.0018474356,0.0007626333,0.864587,0.016488727,0.11580063],"study_design_scores_gemma":[0.000009372153,0.00001336908,0.00008655265,0.00011462962,0.00005588451,0.00021147411,0.00009960515,0.020875463,0.0017475674,0.6879875,0.28877985,0.000018801247],"about_ca_topic_score_codex":0.0016817806,"about_ca_topic_score_gemma":0.0015407585,"teacher_disagreement_score":0.032108217,"about_ca_system_score_codex":0.0012216775,"about_ca_system_score_gemma":0.001386293,"threshold_uncertainty_score":0.107412696},"labels":[],"label_agreement":null},{"id":"W2478675278","doi":"10.4018/978-1-61520-727-5.ch001","title":"XML Native Storage and Query Processing","year":2010,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; XML database; Database; Streaming XML; Efficient XML Interchange; RSS; Information retrieval; XML; Storage model; Information repository; Search engine indexing; Computer data storage; World Wide Web; Operating system","score_opus":0.014346885343866383,"score_gpt":0.2473628501887707,"score_spread":0.2330159648449043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2478675278","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":[0.006096805,0.0070580523,0.8507384,0.0014699404,0.0007715217,0.0007757896,0.0057349694,0.028793562,0.09856105],"genre_scores_gemma":[0.08321594,0.013008949,0.74227107,0.0024783565,0.00090064947,0.0010953264,0.019679226,0.005489043,0.13186151],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99792117,0.0003807878,0.00031514603,0.00032848885,0.000876261,0.00017820769],"domain_scores_gemma":[0.9976451,0.00057869934,0.00008987546,0.00096124137,0.00066698337,0.000058140522],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002686498,0.0009836433,0.0008736752,0.0022094713,0.0009133792,0.006827527,0.0029901422,0.0012917195,0.017973354],"category_scores_gemma":[0.0050362926,0.0005893624,0.00096706103,0.0045165434,0.0008566252,0.0063408916,0.0027462807,0.0012286514,0.01423154],"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":[0.0002377048,0.0001472607,0.0005904944,0.0014981349,0.00006058409,0.00047181745,0.0016190856,0.003677591,0.017430523,0.2273718,0.16658244,0.58031255],"study_design_scores_gemma":[0.000052503277,0.00009549305,0.0005574671,0.0003692565,0.000054181844,0.0016444323,0.0006101859,0.028255895,0.033344835,0.066928916,0.86798805,0.000098684],"about_ca_topic_score_codex":0.0019820123,"about_ca_topic_score_gemma":0.0013381884,"teacher_disagreement_score":0.017973354,"about_ca_system_score_codex":0.0012690241,"about_ca_system_score_gemma":0.0014423707,"threshold_uncertainty_score":0.0601269},"labels":[],"label_agreement":null},{"id":"W2482011423","doi":"10.1007/b13249","title":"Group Communications and Charges. Technology and Business Models","year":2003,"lang":"en","type":"book","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Group (periodic table); Business; Engineering; Telecommunications; Physics","score_opus":0.01850584541743928,"score_gpt":0.24481284783904403,"score_spread":0.22630700242160476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2482011423","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0045407605,0.024690907,0.008924458,0.011879933,0.002665637,0.000053404638,0.0004080243,0.00027425474,0.9465627],"genre_scores_gemma":[0.1851543,0.020875352,0.0033130562,0.002006389,0.0025131733,0.000117541385,0.0004614791,0.00017157994,0.7853871],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99936277,0.0001389567,0.000018544973,0.0000611404,0.00034435306,0.00007431556],"domain_scores_gemma":[0.99914765,0.000331789,0.000109333756,0.00011682376,0.00021373565,0.00008072198],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055296073,0.0010587828,0.0004880811,0.0017294466,0.0013834046,0.004676526,0.00095341675,0.0019660036,0.054976787],"category_scores_gemma":[0.0035838343,0.00031833566,0.00035119176,0.0034189865,0.0014894216,0.0045098593,0.000908246,0.001780048,0.017163157],"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":[0.00003058705,0.000030004994,0.00016266927,0.00007469579,0.000004857375,0.000051896517,0.00012300757,0.00098713,0.00012366779,0.794743,0.12569016,0.07797821],"study_design_scores_gemma":[0.000025203102,0.000031007887,0.0004004647,0.00011002826,0.000014290265,0.0002671058,0.00019003873,0.0015170693,0.00022141547,0.418791,0.57842153,0.000010858323],"about_ca_topic_score_codex":0.004001287,"about_ca_topic_score_gemma":0.0038286427,"teacher_disagreement_score":0.054976787,"about_ca_system_score_codex":0.0027927028,"about_ca_system_score_gemma":0.001868689,"threshold_uncertainty_score":0.18391567},"labels":[],"label_agreement":null},{"id":"W2483744253","doi":"10.4018/978-1-59140-384-5.ch005","title":"Fuzzy Information Modeling with the UML","year":2005,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Applications of UML; Class diagram; Unified Modeling Language; UML tool; Computer science; Object Constraint Language; Conceptual model; Conceptual schema; Fuzzy logic; Systems Modeling Language; Data mining; Data modeling; Programming language; Software engineering; Class (philosophy); Data model (GIS); Database; Software; Artificial intelligence; Linguistics","score_opus":0.013912184367588948,"score_gpt":0.22123696214800007,"score_spread":0.2073247777804111,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2483744253","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":[0.002062487,0.0019720632,0.95783985,0.00092234043,0.00013176238,0.00011116645,0.00028771756,0.0006169248,0.036055755],"genre_scores_gemma":[0.08030471,0.0043423288,0.8911819,0.00030626805,0.00019130805,0.00042895396,0.0006834355,0.00017630866,0.022384807],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9988319,0.00042253284,0.00010088781,0.00013192098,0.00046321147,0.00004963507],"domain_scores_gemma":[0.9991897,0.00044706912,0.000056990877,0.00012920993,0.00014665636,0.000030514038],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016904168,0.000827019,0.00047200892,0.0015875892,0.00076933624,0.0036044281,0.0014183464,0.0013512167,0.0062191174],"category_scores_gemma":[0.0028912812,0.0005386845,0.0013097086,0.0014593641,0.0009789253,0.0038190607,0.0014312201,0.0015237586,0.001736626],"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":[0.00001548718,0.000017313832,0.000089326706,0.00010541682,0.000013734667,0.00011076061,0.0005421435,0.01557549,0.0012052368,0.92637926,0.0046998034,0.051245995],"study_design_scores_gemma":[0.0000180405,0.000023460861,0.00010817096,0.0002194978,0.00002842991,0.0002244743,0.00013435596,0.14778146,0.0020941223,0.61703724,0.23230039,0.000030432298],"about_ca_topic_score_codex":0.0042843106,"about_ca_topic_score_gemma":0.003108222,"teacher_disagreement_score":0.0062191174,"about_ca_system_score_codex":0.0018932194,"about_ca_system_score_gemma":0.0011632412,"threshold_uncertainty_score":0.020805001},"labels":[],"label_agreement":null},{"id":"W24855575","doi":"10.4018/978-1-59140-041-7.ch004","title":"XML Schema Integration to Facilitate E-Commerce","year":2011,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Laurentian University","funders":"","keywords":"XML Schema Editor; RELAX NG; Computer science; Document Structure Description; Efficient XML Interchange; XML validation; cXML; Data integration; Streaming XML; XML Schema (W3C); Information retrieval; XML; Database; XML Encryption; World Wide Web","score_opus":0.05823858107678097,"score_gpt":0.25858944278171,"score_spread":0.200350861704929,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W24855575","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":[0.0018160363,0.004163751,0.93293506,0.0033306086,0.0009104213,0.0006066166,0.0012067071,0.0066958303,0.048334967],"genre_scores_gemma":[0.026522852,0.007833146,0.9313769,0.0026293308,0.000499503,0.0006141953,0.0084391115,0.0018289489,0.020256028],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9951755,0.001759459,0.0007299891,0.00047986183,0.001674353,0.00018083202],"domain_scores_gemma":[0.99569356,0.0014927997,0.0002884791,0.0013349141,0.0010320169,0.0001582112],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0059215017,0.0010692067,0.0008486584,0.0031987848,0.00092371117,0.0056311674,0.0022253108,0.0024693415,0.0116597405],"category_scores_gemma":[0.009961881,0.0009002755,0.0016163874,0.0061434843,0.0012611306,0.008518065,0.0042933193,0.004481295,0.007497416],"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":[0.00007348622,0.00020434869,0.0007111706,0.00081714574,0.00012730382,0.0006885826,0.0013583632,0.006388894,0.008531151,0.6319318,0.07108408,0.27808362],"study_design_scores_gemma":[0.00004965196,0.00004164512,0.0005022606,0.00075223146,0.00006429762,0.0009053176,0.00026381164,0.021552945,0.005866947,0.15863037,0.8113223,0.000048292186],"about_ca_topic_score_codex":0.0018980363,"about_ca_topic_score_gemma":0.0015769252,"teacher_disagreement_score":0.0116597405,"about_ca_system_score_codex":0.0012695228,"about_ca_system_score_gemma":0.0024730198,"threshold_uncertainty_score":0.039005697},"labels":[],"label_agreement":null},{"id":"W2486448704","doi":"10.1007/978-3-319-32207-0_5","title":"On the Performance of Query Rewriting in Vertically Distributed Cloud Databases","year":2016,"lang":"en","type":"book-chapter","venue":"Studies in computational intelligence","topic":"Advanced Database Systems and Queries","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":"Memorial University of Newfoundland","funders":"","keywords":"Computer science; Cloud computing; Scalability; Distributed computing; Big data; Partition (number theory); Metadata; Database; Distributed database; Rewriting; Data mining","score_opus":0.09609457328884347,"score_gpt":0.3390809980474887,"score_spread":0.24298642475864524,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2486448704","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":[0.66636235,0.028364643,0.24200073,0.0068117706,0.0014720069,0.00025876827,0.0015493149,0.009468203,0.043712292],"genre_scores_gemma":[0.9465361,0.0021580483,0.044378016,0.00038559778,0.00042279417,0.00006704562,0.0010998312,0.0009705719,0.0039819446],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9765702,0.007897045,0.0014804441,0.0022933425,0.00876764,0.0029912735],"domain_scores_gemma":[0.938259,0.044603564,0.0015153826,0.0092365425,0.0053443173,0.001041235],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012295793,0.0017939439,0.0025606917,0.0015110839,0.0016055484,0.0053448705,0.003954838,0.0022461945,0.0068209404],"category_scores_gemma":[0.059455138,0.0008360513,0.0006726464,0.005730304,0.002534153,0.0089386515,0.002914942,0.0026856842,0.0017222704],"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":[0.00838267,0.0009775265,0.012486932,0.0008316725,0.0003611296,0.0004104691,0.0014040546,0.41248223,0.035749782,0.081757195,0.04678728,0.3983691],"study_design_scores_gemma":[0.00015011852,0.00027294026,0.0015606945,0.000037551396,0.00008970245,0.00013534568,0.00029916104,0.96410596,0.007438638,0.023893768,0.0019771254,0.00003897606],"about_ca_topic_score_codex":0.015475165,"about_ca_topic_score_gemma":0.0090050455,"teacher_disagreement_score":0.015475165,"about_ca_system_score_codex":0.0041426932,"about_ca_system_score_gemma":0.004020148,"threshold_uncertainty_score":0.06502718},"labels":[],"label_agreement":null},{"id":"W2487245625","doi":"10.4018/978-1-4666-8841-4.ch008","title":"Databases and Information Systems","year":2015,"lang":"en","type":"book-chapter","venue":"Advances in business information systems and analytics book series","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Moncton","funders":"","keywords":"Computer science; Information system; Database; Relation (database); Management information systems; Process (computing); Database testing; Database design; Data science; View; Engineering","score_opus":0.022227593520584,"score_gpt":0.25212376684622934,"score_spread":0.22989617332564533,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2487245625","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014744068,0.40785456,0.06533956,0.0382257,0.010213794,0.000307456,0.0026724562,0.0014270727,0.47248498],"genre_scores_gemma":[0.074467145,0.44584465,0.115201056,0.039056648,0.023268247,0.0013059911,0.0075074933,0.0011876491,0.2921612],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.991591,0.002807552,0.0009194092,0.001323216,0.002977916,0.00038098477],"domain_scores_gemma":[0.99411535,0.003182417,0.000412479,0.0009942901,0.00095531216,0.00034009374],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004047097,0.001581433,0.002114723,0.005569795,0.0028525274,0.018444875,0.0024897002,0.004179635,0.040227666],"category_scores_gemma":[0.009011507,0.00071705057,0.00071731233,0.013862952,0.007507518,0.018103309,0.0067210505,0.0056963307,0.017136145],"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":[0.00001001784,0.000015374912,0.00014918833,0.00074955495,0.000021734271,0.0000953394,0.0005731482,0.0002459282,0.00013467648,0.81671643,0.11201741,0.06927126],"study_design_scores_gemma":[0.0000046699815,0.000008992975,0.00009345051,0.00037280665,0.000005964334,0.00017754029,0.00019674966,0.00015683648,0.000054322227,0.18434978,0.8145701,0.00000877803],"about_ca_topic_score_codex":0.002816202,"about_ca_topic_score_gemma":0.002189393,"teacher_disagreement_score":0.040227666,"about_ca_system_score_codex":0.0045232223,"about_ca_system_score_gemma":0.0053879553,"threshold_uncertainty_score":0.13457501},"labels":[],"label_agreement":null},{"id":"W2488719221","doi":"10.4018/978-1-60566-242-8.ch070","title":"On the Query Evaluation in XML Databases","year":2009,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Joins; Computer science; Twig; XML; XML database; XPath; Matching (statistics); Query optimization; Query language; Database; Theoretical computer science; Information retrieval; Data mining; Mathematics; Programming language; World Wide Web","score_opus":0.04637975800712896,"score_gpt":0.29100031065429993,"score_spread":0.24462055264717097,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2488719221","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":[0.01279057,0.024338467,0.92493254,0.0033915238,0.00044600197,0.00037994838,0.0005986487,0.0022111256,0.030911174],"genre_scores_gemma":[0.16833842,0.020667428,0.7658527,0.001722061,0.0010863239,0.0006226756,0.0022195259,0.0011579562,0.03833304],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99258786,0.0029553873,0.00054630655,0.0007162129,0.0028676249,0.00032666032],"domain_scores_gemma":[0.99433976,0.0042338376,0.00010747222,0.000647172,0.0005633103,0.00010848209],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005307941,0.0014504747,0.0021749216,0.0016344811,0.0009863211,0.0055433363,0.0029889373,0.001604808,0.008606767],"category_scores_gemma":[0.012277461,0.00065338484,0.00094264554,0.005360092,0.0018843999,0.00870563,0.00291276,0.0024330576,0.0026461293],"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":[0.00052502414,0.00016871844,0.0009948956,0.0011524328,0.00008563716,0.0004295308,0.00067236676,0.034181785,0.0038246277,0.23076423,0.06011022,0.6670906],"study_design_scores_gemma":[0.00013425422,0.00015253529,0.00077641907,0.00047871622,0.00010071972,0.0010103012,0.00052067183,0.5657597,0.0074955015,0.29611328,0.12740198,0.0000558663],"about_ca_topic_score_codex":0.0038634262,"about_ca_topic_score_gemma":0.0023616056,"teacher_disagreement_score":0.008606767,"about_ca_system_score_codex":0.0020481192,"about_ca_system_score_gemma":0.0012050134,"threshold_uncertainty_score":0.0287925},"labels":[],"label_agreement":null},{"id":"W2493612689","doi":"10.4018/978-1-60566-242-8.ch069","title":"An Overview on Signature File Techniques","year":2009,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Computer science; Information retrieval; Inverted index; Tuple; Relational database; Signature (topology); Set (abstract data type); XML; View; Database; Data mining; Search engine indexing; Database design; World Wide Web; Programming language","score_opus":0.023691544376818315,"score_gpt":0.2821231702567879,"score_spread":0.2584316258799696,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2493612689","genre_codex":"methods","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0019234106,0.04272131,0.90594935,0.0013537349,0.00096123817,0.00045153228,0.0013948209,0.0073079243,0.037936743],"genre_scores_gemma":[0.026555358,0.05255423,0.86988777,0.0011969964,0.0014509164,0.0007273241,0.0044136047,0.002718684,0.040495105],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99445444,0.0008961811,0.00052464486,0.0005686907,0.0031989615,0.00035711558],"domain_scores_gemma":[0.994118,0.0024221588,0.00033099073,0.0014739268,0.0014862665,0.00016871128],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00356418,0.0015041147,0.0017473059,0.009386749,0.0013896278,0.0065061925,0.005998857,0.0031713755,0.022515144],"category_scores_gemma":[0.009320679,0.0010513334,0.0022579397,0.018048184,0.0019210367,0.014846721,0.003562184,0.0031998828,0.022474505],"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":[0.00015077564,0.00011084319,0.0003612204,0.0010589808,0.000040050523,0.00025599345,0.00029610778,0.0020260012,0.004206215,0.10789847,0.043719333,0.83987594],"study_design_scores_gemma":[0.000053276726,0.00013156397,0.00042501703,0.000733687,0.000048882433,0.003165356,0.00023586243,0.01642338,0.015564198,0.11054339,0.8525282,0.00014717937],"about_ca_topic_score_codex":0.0025165777,"about_ca_topic_score_gemma":0.0010332346,"teacher_disagreement_score":0.022515144,"about_ca_system_score_codex":0.002158883,"about_ca_system_score_gemma":0.0023330117,"threshold_uncertainty_score":0.07532066},"labels":[],"label_agreement":null},{"id":"W2496281881","doi":"10.1007/978-3-319-16106-8_9","title":"Dynamic Matching and Weaving Semantics in $$\\lambda $$-Calculus","year":2015,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Database Systems and Queries","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":"Ericsson (Canada); École de Technologie Supérieure; Concordia University","funders":"","keywords":"Weaving; Church encoding; Typed lambda calculus; Simply typed lambda calculus; Lambda; Calculus (dental); Matching (statistics); Semantics (computer science); Computer science; Programming language; Mathematics; Lambda calculus; Physics; Engineering; Medicine; Optics","score_opus":0.020871242996082735,"score_gpt":0.25682031338570405,"score_spread":0.23594907038962132,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2496281881","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":[0.016345344,0.0044025476,0.83906394,0.0032075632,0.0011093894,0.00009438815,0.0003364305,0.0016380192,0.13380241],"genre_scores_gemma":[0.5130065,0.0079075005,0.3309534,0.0015227401,0.0015369483,0.0003158608,0.0009482527,0.0017994691,0.1420093],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99790996,0.00034006173,0.00016747868,0.0004049538,0.00086174434,0.00031576343],"domain_scores_gemma":[0.9994821,0.0001865918,0.000029956645,0.00013082505,0.00013288016,0.000037816997],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017824298,0.0010273634,0.0010836486,0.0018242794,0.0029686266,0.0063149687,0.0027563258,0.001910845,0.008903041],"category_scores_gemma":[0.0027787557,0.0011364856,0.0018915226,0.004295868,0.0055251475,0.013929029,0.0034683954,0.0045944084,0.0028293773],"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":[0.00000832593,0.0000072946286,0.000018813533,0.000022303284,0.0000031747325,0.000018844708,0.00013030479,0.00034046645,0.00024319267,0.9895878,0.0013083027,0.008311211],"study_design_scores_gemma":[0.0000047288872,0.0000030957483,0.000020050666,0.000015007232,0.0000087692,0.00003295135,0.000035373727,0.0017721782,0.00045240152,0.9801078,0.017537398,0.000010322734],"about_ca_topic_score_codex":0.005618992,"about_ca_topic_score_gemma":0.003325483,"teacher_disagreement_score":0.008903041,"about_ca_system_score_codex":0.0037066012,"about_ca_system_score_gemma":0.002110731,"threshold_uncertainty_score":0.029783607},"labels":[],"label_agreement":null},{"id":"W2501485207","doi":"","title":"Making XML an information modeling language","year":2004,"lang":"en","type":"article","venue":"National University of Singapore","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; XML; Efficient XML Interchange; Document Structure Description; XML Schema Editor; XML validation; Streaming XML; XML Signature; XML Schema (W3C); XML Encryption; XML framework; Representation (politics); The Internet; Information retrieval; Programming language; World Wide Web","score_opus":0.03179662518591535,"score_gpt":0.26092312476205826,"score_spread":0.2291264995761429,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2501485207","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":[0.0029321,0.00024862695,0.9777892,0.0030586887,0.00045783404,0.0000891718,0.000622847,0.006147505,0.008654011],"genre_scores_gemma":[0.076147385,0.0011661309,0.88698715,0.0018616627,0.00039546977,0.00027316198,0.0040464853,0.0037870808,0.025335453],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9950604,0.0016202278,0.00075358513,0.000772295,0.0015593516,0.00023404007],"domain_scores_gemma":[0.99219936,0.0027023663,0.0003957186,0.0031808864,0.0012425061,0.0002791271],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00707746,0.00092232914,0.00068723195,0.002054016,0.0012838372,0.00708999,0.0024943193,0.0019874894,0.0070681814],"category_scores_gemma":[0.011446443,0.0014701883,0.0021722938,0.0020764295,0.0023289155,0.014333892,0.0037425589,0.0046880483,0.0045661875],"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":[0.00007054784,0.00009436383,0.00088972144,0.00022866286,0.000071325674,0.0004568602,0.0011360768,0.0090115415,0.0056240386,0.8311966,0.030228445,0.120991886],"study_design_scores_gemma":[0.000032885357,0.00004872332,0.00022393369,0.00023580715,0.00018926454,0.00039016493,0.00038317023,0.055335607,0.023669725,0.39344603,0.52596986,0.00007481885],"about_ca_topic_score_codex":0.0028193884,"about_ca_topic_score_gemma":0.0021431788,"teacher_disagreement_score":0.00708999,"about_ca_system_score_codex":0.0011065471,"about_ca_system_score_gemma":0.0020853311,"threshold_uncertainty_score":0.03742963},"labels":[],"label_agreement":null},{"id":"W2503947316","doi":"10.1145/3062341.3062348","title":"HoTTSQL: proving query rewrites with univalent SQL semantics","year":2017,"lang":"en","type":"preprint","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":59,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Defense Advanced Research Projects Agency; Alberta Innovates - Technology Futures; U.S. Department of Energy; National Science Foundation","keywords":"Computer science; SQL; Query optimization; Programming language; Query language; Conjunctive query; Query by Example; Sargable; Spatial query; Tuple; Database; Theoretical computer science; Relational database; Information retrieval; Web search query; Mathematics","score_opus":0.024316012657663734,"score_gpt":0.2649466878078302,"score_spread":0.24063067515016648,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2503947316","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":[0.016451873,0.00020280275,0.9679319,0.0006832114,0.00014542631,0.00017267941,0.0007707886,0.010752346,0.00288898],"genre_scores_gemma":[0.41542065,0.0005165492,0.56903315,0.0021803274,0.00045361993,0.00048178362,0.00407345,0.0040851617,0.0037553352],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9815766,0.0041041262,0.0019527606,0.0026755896,0.007969209,0.0017217193],"domain_scores_gemma":[0.9605822,0.024813645,0.0018393658,0.0070143035,0.00524446,0.0005059699],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009620759,0.0015590272,0.0014511283,0.0021236087,0.001803024,0.006583423,0.0049217003,0.0022074739,0.006667248],"category_scores_gemma":[0.04159945,0.001864477,0.0051162406,0.0015360928,0.0057407566,0.011021972,0.0072448156,0.00544017,0.0015293793],"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":[0.0005113912,0.0005603297,0.011344849,0.0016272775,0.00062036456,0.0018066115,0.0022934857,0.08297489,0.034394793,0.7164148,0.02157189,0.1258793],"study_design_scores_gemma":[0.0002556006,0.00023682447,0.0015399026,0.00023329108,0.00040033192,0.00076480326,0.0006493999,0.42138708,0.07712004,0.47575277,0.021474943,0.00018503916],"about_ca_topic_score_codex":0.009136915,"about_ca_topic_score_gemma":0.007550788,"teacher_disagreement_score":0.009620759,"about_ca_system_score_codex":0.0028341464,"about_ca_system_score_gemma":0.005908461,"threshold_uncertainty_score":0.050880015},"labels":[],"label_agreement":null},{"id":"W2505195002","doi":"10.4018/978-1-60960-475-2.ch012","title":"Making Query Coding in SQL Easier by Implementing the SQL Divide Keyword","year":2011,"lang":"en","type":"book-chapter","venue":"Advances in data mining and database management book series","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Query by Example; Computer science; SQL; Sargable; Query optimization; Data definition language; Relational algebra; SQL/PSM; Stored procedure; Null (SQL); Programming language; Codd's theorem; Relational database; Theoretical computer science; Database; Relational model; Information retrieval; Web search query; Relational calculus","score_opus":0.056401074241403205,"score_gpt":0.29732572923735834,"score_spread":0.24092465499595514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2505195002","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":[0.004279618,0.00015657108,0.9677211,0.00029065882,0.00014200111,0.00021924498,0.00050972216,0.020589214,0.006091971],"genre_scores_gemma":[0.08416232,0.00074717856,0.8891094,0.0015260397,0.00017824229,0.00039329953,0.0033522502,0.010538248,0.0099930875],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9965216,0.0007134448,0.00052888703,0.0007335275,0.0012485818,0.00025407175],"domain_scores_gemma":[0.99640346,0.0013306763,0.000180629,0.0010844936,0.00088789576,0.00011283989],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028792159,0.0010427872,0.0006527832,0.0007869667,0.00046112714,0.003536881,0.0017457254,0.00078775827,0.009729238],"category_scores_gemma":[0.00611162,0.0008041882,0.0014880628,0.00096117024,0.0012388799,0.0043732584,0.0026645244,0.0034570948,0.005658854],"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":[0.00073750725,0.0004598764,0.0035751925,0.0020573125,0.00018244048,0.001183936,0.0048305346,0.014555838,0.14590615,0.38923776,0.07293635,0.36433715],"study_design_scores_gemma":[0.0001928642,0.00035506123,0.0015211365,0.00044835857,0.00020446212,0.0017792063,0.00088430586,0.124515414,0.18885668,0.09554929,0.58546215,0.00023109585],"about_ca_topic_score_codex":0.0018388805,"about_ca_topic_score_gemma":0.0018964616,"teacher_disagreement_score":0.009729238,"about_ca_system_score_codex":0.0007281649,"about_ca_system_score_gemma":0.0015987394,"threshold_uncertainty_score":0.032547534},"labels":[],"label_agreement":null},{"id":"W2505390411","doi":"10.1007/978-3-642-12200-2","title":"LATIN 2010: Theoretical Informatics","year":2010,"lang":"en","type":"book","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":49,"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; Informatics; Artificial intelligence; Electrical engineering","score_opus":0.00900212692324291,"score_gpt":0.23800924670896806,"score_spread":0.22900711978572516,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2505390411","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0016294867,0.047226828,0.0905168,0.013606805,0.007167759,0.000037015372,0.0008937796,0.0014607551,0.8374608],"genre_scores_gemma":[0.057699792,0.05600112,0.051464885,0.0052379384,0.017540697,0.000345298,0.0027484307,0.0027631482,0.8061988],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99937844,0.00018794343,0.000028811917,0.00014848802,0.00021878362,0.000037536454],"domain_scores_gemma":[0.9995103,0.00016926491,0.000029738821,0.000118990676,0.00010784867,0.00006388548],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006658898,0.0011751284,0.0015517052,0.0022824167,0.001478513,0.005629902,0.0010856428,0.0009985414,0.063565515],"category_scores_gemma":[0.0017233791,0.00062712916,0.00084698695,0.0049317614,0.0019420221,0.0048440117,0.0019615132,0.004031367,0.030539837],"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":[0.000012902607,0.000014702097,0.000071014096,0.00024668482,0.000012865105,0.000019195515,0.00012094234,0.000579969,0.00027855614,0.65142417,0.25412086,0.093098216],"study_design_scores_gemma":[0.000008156161,0.00000837438,0.00015762179,0.00012677182,0.000009173315,0.00008915055,0.000044047578,0.0010139338,0.00011515065,0.4237649,0.5746554,0.000007323962],"about_ca_topic_score_codex":0.0011292262,"about_ca_topic_score_gemma":0.0013045209,"teacher_disagreement_score":0.063565515,"about_ca_system_score_codex":0.0032429134,"about_ca_system_score_gemma":0.0016106716,"threshold_uncertainty_score":0.21264786},"labels":[],"label_agreement":null},{"id":"W2509488145","doi":"","title":"Production Systems and Rete Algorithm Formalisation","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Prevention of Organ Failure","funders":"","keywords":"Computer science; Implementation; Production (economics); Algorithm; Theoretical computer science; Production system (computer science); Programming language; Process (computing)","score_opus":0.013862229772896542,"score_gpt":0.22822350254878654,"score_spread":0.21436127277589,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2509488145","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":[0.0064841146,0.0020535022,0.9499639,0.001979008,0.00028616935,0.00007802393,0.000106220774,0.0007040829,0.038344935],"genre_scores_gemma":[0.46432045,0.0022671744,0.4685579,0.0012448529,0.00085318834,0.00035700362,0.00067674834,0.0011965014,0.060526144],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9948084,0.0019326608,0.00033155023,0.0011015383,0.0014135934,0.00041223585],"domain_scores_gemma":[0.990117,0.0065502888,0.00029649012,0.0017752817,0.0011299809,0.00013086616],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006443818,0.00093388127,0.0007839372,0.0020444638,0.0014522334,0.0047867,0.0018388543,0.0021369674,0.011899752],"category_scores_gemma":[0.018613454,0.0009767351,0.0018752482,0.0012739985,0.007230487,0.011485996,0.003276665,0.005687757,0.0028324234],"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":[0.00002861066,0.00001523863,0.0001508098,0.00006804762,0.000018276873,0.00008811149,0.0003544624,0.0047770985,0.00044579484,0.9750405,0.001784931,0.017228162],"study_design_scores_gemma":[0.000021244145,0.000027276488,0.00011313114,0.00005709559,0.000021657055,0.00017685356,0.00010021573,0.02689407,0.0019269717,0.94587654,0.024759112,0.000025915702],"about_ca_topic_score_codex":0.0035078828,"about_ca_topic_score_gemma":0.0027335135,"teacher_disagreement_score":0.011899752,"about_ca_system_score_codex":0.0020306122,"about_ca_system_score_gemma":0.0014823723,"threshold_uncertainty_score":0.03980857},"labels":[],"label_agreement":null},{"id":"W2521682114","doi":"10.1145/2967499","title":"Attributed Graph Rewriting for Complex Event Processing Self-Management","year":2016,"lang":"en","type":"article","venue":"ACM Transactions on Autonomous and Adaptive Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Control reconfiguration; Rewriting; Complex event processing; Graph rewriting; Graph; Formalism (music); Theoretical computer science; Distributed computing; Data science; Process (computing); Programming language","score_opus":0.032994234526794876,"score_gpt":0.2653379391501241,"score_spread":0.23234370462332923,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2521682114","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":[0.0037461563,0.00023935246,0.9898606,0.00039660512,0.00011576084,0.00012765781,0.00021583209,0.0015729067,0.003725183],"genre_scores_gemma":[0.21549174,0.0011528801,0.76799965,0.0005992522,0.00024255869,0.00050758594,0.0017306485,0.0012551281,0.011020585],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9965443,0.0011241838,0.000384546,0.0007492315,0.0009929491,0.00020481208],"domain_scores_gemma":[0.995424,0.0019678082,0.00035024015,0.0012863768,0.00081768143,0.00015388867],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029878616,0.0008026964,0.00049998524,0.0013314944,0.0007622242,0.0023273805,0.0017564093,0.00083894137,0.003424523],"category_scores_gemma":[0.0074872323,0.00043657323,0.0017512761,0.0012597811,0.0019081251,0.0031745383,0.0021173733,0.0023617977,0.0013138164],"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":[0.00006257353,0.00009820999,0.00056859123,0.00022744961,0.00006574124,0.00043104455,0.0008918535,0.08176455,0.0073484583,0.82840836,0.0054554343,0.07467775],"study_design_scores_gemma":[0.000037863647,0.00006307236,0.00020395067,0.0000595039,0.00006541285,0.00025428346,0.00014572931,0.31894678,0.009452414,0.6069129,0.06380156,0.000056458706],"about_ca_topic_score_codex":0.006512974,"about_ca_topic_score_gemma":0.005196219,"teacher_disagreement_score":0.006512974,"about_ca_system_score_codex":0.0024699362,"about_ca_system_score_gemma":0.0020882455,"threshold_uncertainty_score":0.017920792},"labels":[],"label_agreement":null},{"id":"W2521822164","doi":"","title":"On formal methods of multidimensional databases","year":2006,"lang":"en","type":"article","venue":"TSpace","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Online analytical processing; Computer science; Query language; Query optimization; Set (abstract data type); Theoretical computer science; Automatic summarization; Database; Information retrieval; Programming language; Data warehouse","score_opus":0.033868887923193765,"score_gpt":0.3811435747733233,"score_spread":0.3472746868501295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2521822164","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":[0.002562146,0.008110519,0.96503097,0.004068519,0.0006976281,0.00013598347,0.00025350915,0.0004225638,0.01871813],"genre_scores_gemma":[0.14655262,0.010006094,0.8151389,0.002667078,0.0018869466,0.001320125,0.0007045321,0.00061447953,0.021109227],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99092686,0.004285764,0.0010427411,0.0010672394,0.0023024941,0.0003749126],"domain_scores_gemma":[0.9882217,0.0076619526,0.00050099334,0.0018757398,0.0014517856,0.0002877684],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012143851,0.0014995171,0.0014296583,0.0031855102,0.0020953345,0.006997153,0.0030964406,0.0021259615,0.0071040457],"category_scores_gemma":[0.013823906,0.0010410456,0.0041671228,0.0031893798,0.0108941505,0.012494012,0.0064428654,0.0072011813,0.0014515193],"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":[0.000004489288,0.0000070575525,0.000055678694,0.00006262841,0.000008314718,0.00004565304,0.00040920216,0.0009538988,0.00015751254,0.99341077,0.000676794,0.004207884],"study_design_scores_gemma":[0.000015027561,0.000011630198,0.000050111317,0.000120032535,0.000012680158,0.000087196466,0.0001295482,0.007411258,0.00032058413,0.94433236,0.047492784,0.000016842707],"about_ca_topic_score_codex":0.0033799696,"about_ca_topic_score_gemma":0.002385704,"teacher_disagreement_score":0.012143851,"about_ca_system_score_codex":0.005748709,"about_ca_system_score_gemma":0.0029310875,"threshold_uncertainty_score":0.06422359},"labels":[],"label_agreement":null},{"id":"W2522795258","doi":"10.4242/balisagevol10.cameron01","title":"icXML: Accelerating a Commercial XML Parser Using SIMD and Multicore Technologies","year":2013,"lang":"en","type":"article","venue":"Balisage series on markup technologies","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; SIMD; XML; Parsing; Pipeline (software); Simple API for XML; Programming language; XML framework; Multi-core processor; Parallel computing; Software engineering; XML Signature; Operating system; Efficient XML Interchange","score_opus":0.032674047108623594,"score_gpt":0.25233480553892,"score_spread":0.21966075843029642,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2522795258","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":[0.0413374,0.00087265985,0.744373,0.0010242754,0.00042912713,0.0006576342,0.0021573084,0.18394819,0.025200477],"genre_scores_gemma":[0.09749367,0.00049395947,0.86611414,0.0007246871,0.00008350095,0.00036713938,0.006767032,0.010067682,0.017888194],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99847203,0.00021312862,0.00011163952,0.0002806925,0.00077434233,0.00014806415],"domain_scores_gemma":[0.9977254,0.0005461783,0.000156966,0.0006251706,0.0008168743,0.00012932919],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027505897,0.00090536976,0.0004450667,0.0011034639,0.00059382844,0.0019887895,0.0028755192,0.0009820533,0.010206964],"category_scores_gemma":[0.0044083633,0.00072139164,0.0006397155,0.0015526805,0.0006067259,0.0034765918,0.001317626,0.001602887,0.0039887438],"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":[0.0014937938,0.00047585825,0.0054776357,0.0010589847,0.00019955635,0.0010407721,0.001267365,0.016688215,0.1755327,0.05292619,0.14770898,0.59612995],"study_design_scores_gemma":[0.0005980068,0.0006288977,0.0035828096,0.00017400691,0.00009538662,0.0010771403,0.0002866265,0.32059982,0.3600838,0.012566847,0.30008146,0.00022523582],"about_ca_topic_score_codex":0.004285934,"about_ca_topic_score_gemma":0.0048208027,"teacher_disagreement_score":0.010206964,"about_ca_system_score_codex":0.0014111928,"about_ca_system_score_gemma":0.0022391246,"threshold_uncertainty_score":0.034145713},"labels":[],"label_agreement":null},{"id":"W2524241157","doi":"","title":"XML: Future of E-Content Business","year":2003,"lang":"en","type":"article","venue":"The Journal of Internet Banking and Commerce","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; XML; Entertainment; World Wide Web; XML Schema Editor; Electronic business; Efficient XML Interchange; The Internet; cXML; Business model; XML Signature; Business; Marketing; Political science","score_opus":0.024516037337008523,"score_gpt":0.23677758188649833,"score_spread":0.2122615445494898,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2524241157","genre_codex":"review","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":[0.0120945,0.2813498,0.21947835,0.19320463,0.012340357,0.00025129147,0.0010823997,0.003437562,0.2767611],"genre_scores_gemma":[0.12601908,0.4012956,0.29088655,0.028691938,0.016951386,0.00041138186,0.0030795683,0.0011059955,0.13155845],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9966433,0.0011075767,0.00035688063,0.00035324934,0.0013078026,0.00023116538],"domain_scores_gemma":[0.9938896,0.002499144,0.0003748103,0.00082877884,0.0017886775,0.0006190891],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0069597345,0.00057266525,0.00046939825,0.0021950535,0.0011972282,0.009273563,0.00196604,0.0049432926,0.012928247],"category_scores_gemma":[0.0077600842,0.0004243509,0.0006101426,0.003695761,0.0028109883,0.022891616,0.0030076397,0.0036656447,0.006657657],"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":[0.00005942193,0.000062147046,0.0007843232,0.00050785893,0.000016029766,0.00021020664,0.000826622,0.00089796475,0.0017689868,0.5147688,0.06886092,0.4112367],"study_design_scores_gemma":[0.0000090608855,0.000039739327,0.0003505335,0.0004287781,0.000010480083,0.0004950604,0.00039516052,0.002147706,0.00066591863,0.08696702,0.90846515,0.000025375943],"about_ca_topic_score_codex":0.0014998235,"about_ca_topic_score_gemma":0.00067891926,"teacher_disagreement_score":0.012928247,"about_ca_system_score_codex":0.0019587863,"about_ca_system_score_gemma":0.0026624596,"threshold_uncertainty_score":0.04324931},"labels":[],"label_agreement":null},{"id":"W2527695466","doi":"10.1109/bigdatacongress.2016.23","title":"QDrill: Query-Based Distributed Consumable Analytics for Big Data","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada); Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Analytics; Big data; Scalability; SQL; Database; Data science; Data mining","score_opus":0.11203431012449337,"score_gpt":0.2994594151444289,"score_spread":0.18742510501993553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2527695466","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":[0.011623393,0.0006685451,0.5564164,0.000817799,0.0001965651,0.0005728502,0.005261913,0.4199761,0.004466528],"genre_scores_gemma":[0.28757325,0.00070396834,0.63683856,0.0024256597,0.00018122229,0.001011091,0.03930483,0.022138823,0.009822605],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99554473,0.00072676246,0.00043801914,0.0011324993,0.0018435369,0.00031439765],"domain_scores_gemma":[0.9916489,0.0028927373,0.00040673593,0.003382888,0.0010672896,0.0006014048],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0046289996,0.0020493085,0.0010913886,0.0017649309,0.0007543338,0.0038095089,0.0079589905,0.001197781,0.010692659],"category_scores_gemma":[0.012507373,0.0013499536,0.0013872405,0.002275416,0.0016838851,0.006735148,0.008263028,0.002935404,0.0054342397],"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":[0.0038282964,0.0013496394,0.01258226,0.0024031682,0.0007090888,0.0011089428,0.0011724231,0.0583518,0.040304165,0.0337364,0.36948368,0.47497007],"study_design_scores_gemma":[0.0009327146,0.00033565573,0.0033709544,0.00011234409,0.0001037595,0.00044433709,0.0003111098,0.83283955,0.032391377,0.03917403,0.08977379,0.00021033743],"about_ca_topic_score_codex":0.007770457,"about_ca_topic_score_gemma":0.009167301,"teacher_disagreement_score":0.010692659,"about_ca_system_score_codex":0.0016603771,"about_ca_system_score_gemma":0.0024182643,"threshold_uncertainty_score":0.035770476},"labels":[],"label_agreement":null},{"id":"W2532983500","doi":"10.1109/vnis.1989.98774","title":"Thrusts of the Michigan program in intelligent vehicle-highway systems","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Complementarity (molecular biology); Software deployment; Automotive industry; Intelligent transportation system; Extrapolation; Transport engineering; Computer science; Engineering; Operations research; Aeronautics; Engineering management; Software engineering; Aerospace engineering","score_opus":0.016341573430097577,"score_gpt":0.25456530874876826,"score_spread":0.2382237353186707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2532983500","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008312596,0.0057669817,0.018622162,0.13531522,0.00677824,0.00024958226,0.0016706911,0.0012221539,0.8220623],"genre_scores_gemma":[0.04550433,0.0067812246,0.011851086,0.003026597,0.0047737337,0.00015045075,0.0013254688,0.00025483305,0.92633224],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984688,0.00024954707,0.00004651177,0.0001734659,0.00089644163,0.00016521162],"domain_scores_gemma":[0.99713206,0.00037545618,0.000090817426,0.00014160806,0.0010935566,0.001166432],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032799684,0.00058784074,0.00036708702,0.001231383,0.0015250948,0.002889599,0.00069856714,0.0014625159,0.089501575],"category_scores_gemma":[0.002907024,0.00020427656,0.00016812162,0.0011740325,0.0005707989,0.0019349186,0.0015382372,0.0014687476,0.020811284],"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":[0.00006978973,0.00016854079,0.001974244,0.00006869358,0.0000056605554,0.00013775472,0.00026639854,0.00035042933,0.0011672215,0.055651452,0.77831584,0.16182409],"study_design_scores_gemma":[0.000011127305,0.00008117633,0.0012240427,0.00005693071,0.0000049499135,0.00010705878,0.0001289608,0.001714042,0.0010104624,0.0027475916,0.9929055,0.000008105206],"about_ca_topic_score_codex":0.0076393895,"about_ca_topic_score_gemma":0.023845144,"teacher_disagreement_score":0.089501575,"about_ca_system_score_codex":0.00211972,"about_ca_system_score_gemma":0.003767074,"threshold_uncertainty_score":0.2994126},"labels":[],"label_agreement":null},{"id":"W2533455878","doi":"","title":"Monte carlo algorithms for expected utility estimation in dynamic purchasing","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Purchasing; Bundle; Mathematical optimization; Computer science; Expected utility hypothesis; Decision tree; Tree (set theory); Probabilistic logic; Monte Carlo method; Operations research; Mathematics; Mathematical economics; Economics; Data mining; Artificial intelligence; Operations management","score_opus":0.022491047355664717,"score_gpt":0.2958132646444979,"score_spread":0.2733222172888332,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2533455878","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":[0.0032084216,0.00035791504,0.99466056,0.00015500093,0.000028434406,0.000066462446,0.00005517518,0.0003100798,0.0011580577],"genre_scores_gemma":[0.21053885,0.0009783482,0.78302246,0.0002969557,0.00017505421,0.0007915533,0.0006764641,0.00029673925,0.0032236078],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9961771,0.0022335753,0.0001807999,0.000563932,0.0005615845,0.00028307864],"domain_scores_gemma":[0.9659504,0.030708201,0.00091590977,0.0010150194,0.0010834406,0.00032704268],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0076977704,0.0014980272,0.0027306098,0.002424981,0.001214406,0.0023314827,0.0034374113,0.0022070413,0.0063162735],"category_scores_gemma":[0.03324803,0.0015382372,0.0013402195,0.002993647,0.002272269,0.0038701813,0.0022134685,0.0040521338,0.0014751281],"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":[0.00012119785,0.00009346154,0.0007798127,0.00008713301,0.00006107249,0.000048618524,0.00006854284,0.8934935,0.00018152807,0.06213546,0.0014118436,0.041517787],"study_design_scores_gemma":[0.00001921667,0.000011717051,0.000052596384,0.000013544762,0.0000065357544,0.00001173001,0.0000072031794,0.9604828,0.000098000004,0.03886147,0.0004275481,0.000007651995],"about_ca_topic_score_codex":0.009490952,"about_ca_topic_score_gemma":0.009428381,"teacher_disagreement_score":0.009490952,"about_ca_system_score_codex":0.0028356155,"about_ca_system_score_gemma":0.0030658483,"threshold_uncertainty_score":0.04071021},"labels":[],"label_agreement":null},{"id":"W2550949057","doi":"10.3166/isi.21.3.53-74","title":"Leveraging efficient indexing schema to support multigraph query answering","year":2016,"lang":"fr","type":"article","venue":"Ingénierie des systèmes d information","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Agence Nationale de la Recherche","keywords":"Multigraph; Computer science; Schema (genetic algorithms); Information retrieval; Search engine indexing; Theoretical computer science; Graph","score_opus":0.02760337618346825,"score_gpt":0.2537739087169518,"score_spread":0.22617053253348357,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2550949057","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":[0.019470252,0.0015296355,0.89446974,0.0026103463,0.00062394363,0.000488494,0.007830282,0.062183768,0.010793597],"genre_scores_gemma":[0.10513021,0.0012295569,0.8363009,0.0009584784,0.0002306809,0.0002644888,0.041789863,0.004080524,0.01001533],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973022,0.00047337156,0.00041314473,0.0005343016,0.001101505,0.00017546582],"domain_scores_gemma":[0.99414873,0.0009690519,0.00016684872,0.0032250802,0.0012981044,0.00019224144],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024132277,0.0006750424,0.0012011451,0.0035438624,0.0009666824,0.0056177666,0.0031762617,0.0016668006,0.0069752242],"category_scores_gemma":[0.008494836,0.0010329674,0.001274123,0.0050883605,0.0006383723,0.008122372,0.003684776,0.0018307623,0.0053170295],"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":[0.00072016264,0.0006932547,0.0044386555,0.00076444674,0.00030317894,0.00041344715,0.0007994798,0.021228213,0.06089681,0.096803755,0.19889441,0.61404413],"study_design_scores_gemma":[0.0002419987,0.00019895167,0.001597481,0.00021688464,0.00024190985,0.00063248334,0.00047803874,0.5737683,0.07357506,0.09412583,0.25473443,0.0001887195],"about_ca_topic_score_codex":0.008201776,"about_ca_topic_score_gemma":0.011657109,"teacher_disagreement_score":0.008201776,"about_ca_system_score_codex":0.001191793,"about_ca_system_score_gemma":0.0025414072,"threshold_uncertainty_score":0.023334503},"labels":[],"label_agreement":null},{"id":"W2561049123","doi":"","title":"XML: Future of E-Content Business -- The Impact of XML on Entertainment and Media Industry","year":2003,"lang":"en","type":"article","venue":"The Journal of Internet Banking and Commerce","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; XML; Entertainment; XML Schema Editor; Efficient XML Interchange; World Wide Web; cXML; XML Signature; Political science","score_opus":0.025983537595651078,"score_gpt":0.2616666233477178,"score_spread":0.2356830857520667,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2561049123","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":[0.018832857,0.531618,0.08642219,0.18396525,0.013076988,0.000086362306,0.001793853,0.00263435,0.16157018],"genre_scores_gemma":[0.16253674,0.52695745,0.1214435,0.024779921,0.021924073,0.00014513865,0.0045156414,0.0012165303,0.13648106],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99880874,0.0003762633,0.00014758253,0.00015370072,0.00039594955,0.00011783608],"domain_scores_gemma":[0.9952317,0.0024694148,0.00031580406,0.0003908193,0.0010375842,0.0005546489],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003917331,0.00061477686,0.00059598533,0.002113682,0.00077479053,0.009604838,0.0015080982,0.0047006896,0.018894443],"category_scores_gemma":[0.004619779,0.00041977613,0.00053840905,0.004728751,0.0027726698,0.027841393,0.0016708107,0.002602081,0.005040366],"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":[0.00012231128,0.000098600096,0.0013690677,0.0007621918,0.000026147361,0.00016153543,0.00079200696,0.0011736973,0.0022673514,0.46508196,0.101502344,0.4266428],"study_design_scores_gemma":[0.000021487394,0.000055695702,0.0015709514,0.00082945847,0.000022305714,0.00047833653,0.0008601477,0.0032526248,0.0012772561,0.121277906,0.87032026,0.000033452987],"about_ca_topic_score_codex":0.0024819274,"about_ca_topic_score_gemma":0.001989723,"teacher_disagreement_score":0.018894443,"about_ca_system_score_codex":0.0019476014,"about_ca_system_score_gemma":0.0016745117,"threshold_uncertainty_score":0.06320816},"labels":[],"label_agreement":null},{"id":"W2563061479","doi":"10.4018/ijdwm.2017010103","title":"Multidimensional Business Benchmarking Analysis on Data Warehouses","year":2016,"lang":"en","type":"article","venue":"International Journal of Data Warehousing and Mining","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Benchmarking; Computer science; Data warehouse; Benchmark (surveying); Business intelligence; Aggregate (composite); Data science; Online analytical processing; Scalability; Context (archaeology); Analytics; Data mining; Set (abstract data type); Data cube; Business analytics; Database; Business model; Business analysis","score_opus":0.07877539273770963,"score_gpt":0.3369665008377868,"score_spread":0.25819110810007717,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2563061479","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":[0.18950121,0.0014641678,0.7927939,0.0013462465,0.00011892451,0.00029622065,0.0029558926,0.0042427485,0.0072806724],"genre_scores_gemma":[0.7060626,0.00062936667,0.28718823,0.00018645961,0.00007014289,0.0002444963,0.0042979945,0.00020971756,0.0011110449],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9903724,0.0038766635,0.0010121873,0.00085923384,0.003293048,0.00058638933],"domain_scores_gemma":[0.98683447,0.0055390764,0.0013182099,0.0026601884,0.003193167,0.00045489497],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0063793585,0.0011461142,0.0015809444,0.0072269933,0.001283545,0.0057437615,0.0016171526,0.0009431065,0.0016566489],"category_scores_gemma":[0.026753856,0.00060865516,0.0014657519,0.01271202,0.00092455506,0.0062984196,0.0029835806,0.0012139919,0.0005106635],"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":[0.0004513291,0.0005223983,0.030466205,0.0006274617,0.0003760735,0.00081881165,0.0010486683,0.4264714,0.0065292786,0.21223573,0.014185863,0.30626684],"study_design_scores_gemma":[0.000013000462,0.00006998915,0.002777654,0.000062189,0.000026593758,0.00010565216,0.0005291358,0.90337557,0.0030621698,0.08623685,0.0037138455,0.000027378992],"about_ca_topic_score_codex":0.004634885,"about_ca_topic_score_gemma":0.0035079862,"teacher_disagreement_score":0.0072269933,"about_ca_system_score_codex":0.0016417728,"about_ca_system_score_gemma":0.0011962724,"threshold_uncertainty_score":0.03373766},"labels":[],"label_agreement":null},{"id":"W2564774002","doi":"","title":"Access methods for xml query optimization","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; XML database; Streaming XML; Efficient XML Interchange; XML validation; Query optimization; XQuery; Information retrieval; XML Encryption; XML Schema Editor; XPath; Query language; Document Structure Description; Database; XML Signature; XML; World Wide Web","score_opus":0.029593967740245506,"score_gpt":0.38594223777263215,"score_spread":0.3563482700323866,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2564774002","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":[0.0017295853,0.0007776231,0.9874893,0.00052515196,0.00007334744,0.00022835164,0.00022263938,0.0024592225,0.006494809],"genre_scores_gemma":[0.087943934,0.0017833102,0.8875643,0.0010322819,0.0004138062,0.0010254165,0.0014340386,0.0017876267,0.017015362],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9893958,0.002873649,0.0010481696,0.0010742098,0.005062566,0.0005456372],"domain_scores_gemma":[0.99426234,0.003053064,0.00034558764,0.0013009125,0.00090798707,0.00013004256],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006211254,0.0013236646,0.0010042771,0.0019501017,0.0010633072,0.0044650235,0.0024800133,0.0013659131,0.01211598],"category_scores_gemma":[0.013396642,0.000789869,0.0018418465,0.0032259247,0.0019917428,0.0056666373,0.004290629,0.0034577455,0.0034191683],"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":[0.00030681622,0.00017504777,0.0007181589,0.0006601365,0.000115578856,0.0002539714,0.0008073528,0.02430279,0.007246812,0.627516,0.032981515,0.30491588],"study_design_scores_gemma":[0.00017566214,0.00020253856,0.00040316247,0.00022081706,0.000102836675,0.00067911186,0.00040290997,0.32222164,0.01292964,0.469816,0.19274028,0.00010538346],"about_ca_topic_score_codex":0.0025690882,"about_ca_topic_score_gemma":0.00250013,"teacher_disagreement_score":0.01211598,"about_ca_system_score_codex":0.0018335119,"about_ca_system_score_gemma":0.0018971323,"threshold_uncertainty_score":0.040531993},"labels":[],"label_agreement":null},{"id":"W2576743109","doi":"10.1145/3012408.3012412","title":"MHDeS","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada); University of New Brunswick","funders":"","keywords":"Computer science; Java; Programming language; Implementation; Graph; Operating system; Theoretical computer science","score_opus":0.00952085500084597,"score_gpt":0.21768228867068923,"score_spread":0.20816143366984324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2576743109","genre_codex":"software","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":[0.0137560805,0.001614786,0.25134543,0.0017953695,0.002417794,0.0008234167,0.061123963,0.3450371,0.32208607],"genre_scores_gemma":[0.1254313,0.001713362,0.15409829,0.003521604,0.0006942913,0.0013559137,0.10193034,0.060962204,0.55029273],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988954,0.00013161621,0.00009256808,0.00025897712,0.00049047923,0.00013097012],"domain_scores_gemma":[0.9984403,0.0002506036,0.00007824309,0.00076517,0.00037787686,0.00008780468],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008895437,0.0010494312,0.0006802405,0.0010204351,0.00071303215,0.0021581561,0.0022975882,0.0009535544,0.15405622],"category_scores_gemma":[0.003362107,0.0008691546,0.0008350819,0.00057312945,0.00044926812,0.0036237128,0.0038058807,0.0014956291,0.07740446],"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":[0.0010803947,0.00015156409,0.0018711839,0.0010795573,0.00008416566,0.00028214263,0.00041460697,0.0020016767,0.009653516,0.07467183,0.7057628,0.20294656],"study_design_scores_gemma":[0.00006711746,0.00003461068,0.00034891948,0.00007259135,0.00001915005,0.00012122667,0.000047560916,0.0023830633,0.008851766,0.009042177,0.9789882,0.000023521872],"about_ca_topic_score_codex":0.0015295999,"about_ca_topic_score_gemma":0.0022460278,"teacher_disagreement_score":0.8459438,"about_ca_system_score_codex":0.00085216836,"about_ca_system_score_gemma":0.0010982659,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W2580158205","doi":"10.29173/cais736","title":"Modelling Information Retrieval in an Object-Oriented Database Environment","year":2013,"lang":"en","type":"article","venue":"Proceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSI","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Information retrieval; Standardization; Pascal (unit); Class hierarchy; Relational database; Class (philosophy); Object (grammar); Database; Object-oriented programming; Programming language; Artificial intelligence","score_opus":0.019565291717432622,"score_gpt":0.2272451826914066,"score_spread":0.20767989097397396,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2580158205","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":[0.01661261,0.0043524597,0.93594444,0.0031164465,0.0001919153,0.0004875252,0.00040455334,0.0013544619,0.037535597],"genre_scores_gemma":[0.1821585,0.00696688,0.76543075,0.0007134914,0.0003647725,0.0008354226,0.0017186201,0.0005354509,0.04127612],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9959015,0.001480384,0.0004474209,0.00044836916,0.0013629198,0.00035929788],"domain_scores_gemma":[0.9967338,0.0015896929,0.00025641444,0.00057983585,0.0006076085,0.00023261548],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005942266,0.0008382485,0.000981012,0.0023884973,0.0016792815,0.012261083,0.0048662024,0.0030222076,0.0042910594],"category_scores_gemma":[0.0066754855,0.0009732122,0.0014192951,0.004717561,0.0034642448,0.010037722,0.003638558,0.0019197427,0.002856704],"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":[0.00009604595,0.00011266012,0.0010502927,0.00030929534,0.000060619288,0.0009306807,0.0023823744,0.051349934,0.0021490154,0.89370376,0.004535207,0.043320123],"study_design_scores_gemma":[0.00016563757,0.00014121812,0.00046077024,0.0002742869,0.00014156994,0.0008828701,0.0009967193,0.260162,0.0027265337,0.4367277,0.29721504,0.00010565508],"about_ca_topic_score_codex":0.015419296,"about_ca_topic_score_gemma":0.012053195,"teacher_disagreement_score":0.015419296,"about_ca_system_score_codex":0.0034783331,"about_ca_system_score_gemma":0.0029452648,"threshold_uncertainty_score":0.03142613},"labels":[],"label_agreement":null},{"id":"W2580755146","doi":"","title":"Summarization-process information and nonfinancial information new cost and revenue accounting provides: possibilities of XML-based cost and revenue accounting","year":2008,"lang":"en","type":"article","venue":"Accounting","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Cost accounting; Accounting; Revenue; Accounting information system; Business; Automatic summarization; Throughput accounting; Process (computing); Computer science; Revenue recognition; Information retrieval; Accounting management; Financial accounting","score_opus":0.010827886538119976,"score_gpt":0.23394437970421483,"score_spread":0.22311649316609486,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2580755146","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":[0.038707737,0.0019058962,0.92437595,0.0025726827,0.0004136109,0.0003060985,0.0034641158,0.010327309,0.017926654],"genre_scores_gemma":[0.30916327,0.003473367,0.65091807,0.0008262927,0.00087214116,0.00020797078,0.013195717,0.0019899197,0.01935318],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981762,0.0006121898,0.00032067808,0.00019715336,0.0006066071,0.000087174456],"domain_scores_gemma":[0.9926963,0.0028670137,0.0005708285,0.0023068984,0.0014442162,0.0001147926],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003981729,0.00079111534,0.00081429136,0.004035969,0.0006448363,0.0055088717,0.0009213955,0.000881489,0.0066782157],"category_scores_gemma":[0.008644011,0.00042326478,0.00083928194,0.004182256,0.0005738094,0.0070968918,0.0009650711,0.0011149378,0.0026497683],"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":[0.00058787747,0.0003375705,0.0043822876,0.000836007,0.0001525097,0.0005315005,0.0023467436,0.010338669,0.026484465,0.14592043,0.018557385,0.7895247],"study_design_scores_gemma":[0.00015759449,0.0004576629,0.010556895,0.00071993895,0.0011047715,0.0011769774,0.0017761535,0.23041332,0.12776683,0.29513302,0.33043185,0.0003049329],"about_ca_topic_score_codex":0.0014384023,"about_ca_topic_score_gemma":0.0012513394,"teacher_disagreement_score":0.0066782157,"about_ca_system_score_codex":0.0008681034,"about_ca_system_score_gemma":0.00093408243,"threshold_uncertainty_score":0.022340894},"labels":[],"label_agreement":null},{"id":"W2583640897","doi":"10.1109/bigdata.2016.7840873","title":"A glue language for event stream processing","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"GLUE; Computer science; Stream processing; Event (particle physics); Programming language; Parallel computing; Composite material; Materials science","score_opus":0.01108382682491594,"score_gpt":0.28034023746817666,"score_spread":0.2692564106432607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2583640897","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":[0.0006947559,0.00006395449,0.99093974,0.00009832317,0.000072103176,0.000115320916,0.00026093915,0.0057899696,0.0019649263],"genre_scores_gemma":[0.037504643,0.0005045201,0.9472704,0.00056551443,0.00015924452,0.00060288096,0.0029095868,0.004531164,0.005952012],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9960288,0.00071222946,0.00093903637,0.00061238464,0.0014607605,0.00024675205],"domain_scores_gemma":[0.9971902,0.0009295342,0.00022518661,0.00075513107,0.00068834523,0.00021167261],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004247391,0.0012634667,0.0010998652,0.0018942497,0.0009930279,0.0040181307,0.0024455518,0.0013340355,0.008903427],"category_scores_gemma":[0.008070434,0.0011661984,0.0023035149,0.0018940143,0.0017030004,0.0072233337,0.00531871,0.0033278074,0.0051430184],"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":[0.00043230582,0.00019288424,0.0014522092,0.000936098,0.0001387978,0.0015008459,0.001978557,0.014656934,0.029913662,0.728504,0.036405906,0.1838878],"study_design_scores_gemma":[0.00014657348,0.00019853571,0.00060651306,0.00041469137,0.00014927238,0.0016869879,0.0003617944,0.16813721,0.045597646,0.30798608,0.47452223,0.0001923487],"about_ca_topic_score_codex":0.0013301014,"about_ca_topic_score_gemma":0.0011198262,"teacher_disagreement_score":0.008903427,"about_ca_system_score_codex":0.00074135995,"about_ca_system_score_gemma":0.0025698645,"threshold_uncertainty_score":0.029784858},"labels":[],"label_agreement":null},{"id":"W2588114856","doi":"10.29173/cais314","title":"Applications of SQL for Informetric Data Processing","year":2013,"lang":"fr","type":"article","venue":"Proceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSI","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"SQL; Computer science; Relational database; Informetrics; Data definition language; Raw data; Database; Data mining; Programming language; Bibliometrics","score_opus":0.05025230150364443,"score_gpt":0.2873013640178965,"score_spread":0.2370490625142521,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2588114856","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":[0.0026222141,0.000944555,0.9439144,0.0017860404,0.00031330084,0.0003943517,0.001568268,0.0299843,0.018472662],"genre_scores_gemma":[0.05858026,0.002455263,0.91367584,0.0020977138,0.0006845533,0.00049839803,0.0064086453,0.0059287157,0.009670515],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.987743,0.003967795,0.0025284623,0.0010965191,0.004276941,0.0003873448],"domain_scores_gemma":[0.9808828,0.0102535235,0.0006960758,0.004316131,0.003335125,0.0005163033],"candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.009930317,0.0012031256,0.00081768935,0.0032340384,0.0010267807,0.0064347205,0.002659263,0.0012600085,0.013027442],"category_scores_gemma":[0.022434423,0.0011053181,0.0014807371,0.004533204,0.0016439838,0.006727213,0.0044808933,0.0026906647,0.010035457],"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":[0.00057757203,0.0002546323,0.0034136977,0.0015154895,0.00013848383,0.0013706972,0.0031872492,0.0049915123,0.01809817,0.32805404,0.11128665,0.5271118],"study_design_scores_gemma":[0.0001558392,0.00017864224,0.0013704599,0.0005103975,0.0000793425,0.002139118,0.0009178065,0.073252305,0.02997014,0.19124497,0.70001966,0.00016136856],"about_ca_topic_score_codex":0.0014812357,"about_ca_topic_score_gemma":0.00080544595,"teacher_disagreement_score":0.996766,"about_ca_system_score_codex":0.0009576346,"about_ca_system_score_gemma":0.002170588,"threshold_uncertainty_score":0.052517116},"labels":[],"label_agreement":null},{"id":"W2594194814","doi":"","title":"From relations to multi-dimensional maps: a SQL-to-HBase transformation methodology","year":2016,"lang":"en","type":"article","venue":"Computer Science and Software Engineering","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":7,"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 Alberta","funders":"","keywords":"Computer science; SQL; Schema (genetic algorithms); Relational database; Database; Transformation (genetics); Data transformation; Information retrieval; Data mining; Data warehouse; Chemistry","score_opus":0.030779734824526787,"score_gpt":0.26529136068886133,"score_spread":0.23451162586433455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2594194814","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":[0.0010704412,0.000061385465,0.9947877,0.00019424052,0.00003602318,0.000119571494,0.000101394755,0.0024752798,0.001153889],"genre_scores_gemma":[0.039736964,0.00025879018,0.9550689,0.00022021061,0.000049289334,0.00025817662,0.00063366914,0.0012071639,0.002566759],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99453753,0.0013711761,0.0006201121,0.00076914835,0.0024359268,0.00026620302],"domain_scores_gemma":[0.9943514,0.001499087,0.0002961741,0.0024763425,0.0012036006,0.00017331558],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0062493472,0.00073822134,0.0005773354,0.0021511344,0.0008541486,0.004166549,0.0030460868,0.0010699114,0.0037002566],"category_scores_gemma":[0.010180656,0.0010623469,0.0019690795,0.00209318,0.0017114335,0.005417344,0.0040926556,0.0030581786,0.0024314437],"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":[0.00014517155,0.00047644923,0.0029273683,0.0006806685,0.0002287723,0.0010015727,0.0031630595,0.025393499,0.021991143,0.50297433,0.018482663,0.42253542],"study_design_scores_gemma":[0.00008529644,0.0002095,0.0015085611,0.00028606076,0.00016785608,0.0020497458,0.0014081398,0.2380048,0.10145797,0.30276042,0.3518932,0.00016846694],"about_ca_topic_score_codex":0.0018789656,"about_ca_topic_score_gemma":0.002152363,"teacher_disagreement_score":0.0062493472,"about_ca_system_score_codex":0.00078761455,"about_ca_system_score_gemma":0.0022759833,"threshold_uncertainty_score":0.03305012},"labels":[],"label_agreement":null},{"id":"W2605173963","doi":"","title":"Secondary Indexing Techniques for Key-Value Stores: Two Rings To Rule Them All.","year":2017,"lang":"en","type":"article","venue":"EDBT/ICDT Workshops","topic":"Advanced Database Systems and Queries","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":"McGill University","funders":"","keywords":"Search engine indexing; Key (lock); Computer science; Value (mathematics); Data mining; Information retrieval; Computer security; Machine learning","score_opus":0.032432494250130395,"score_gpt":0.3175627532824926,"score_spread":0.2851302590323622,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605173963","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":[0.006994478,0.0016611265,0.97268236,0.0013003127,0.0007623214,0.00034607993,0.0007687218,0.006940218,0.008544316],"genre_scores_gemma":[0.1124449,0.0018755012,0.8586373,0.0012108452,0.0011431084,0.00047219888,0.002061185,0.0018051318,0.020349935],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98842245,0.0022296181,0.0019983402,0.0016460998,0.0047376654,0.0009657124],"domain_scores_gemma":[0.966004,0.0059488746,0.0016740349,0.020343414,0.0051804977,0.0008491487],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006996805,0.0013640494,0.0024436784,0.0033344992,0.0034169673,0.0077641103,0.0051128077,0.0022946487,0.010063939],"category_scores_gemma":[0.029061384,0.0015909927,0.002181783,0.0045683077,0.004048429,0.020097503,0.0078043155,0.004616158,0.011100228],"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":[0.00090257986,0.00046022763,0.0029587229,0.0007685919,0.00016640451,0.00047664213,0.0012365857,0.003994507,0.020010296,0.43860617,0.073765844,0.45665342],"study_design_scores_gemma":[0.00022621383,0.0007062305,0.0009763154,0.00053974724,0.00041629156,0.0024194212,0.00077698845,0.06726802,0.071227625,0.6238146,0.23130713,0.0003214236],"about_ca_topic_score_codex":0.0016212441,"about_ca_topic_score_gemma":0.0025122352,"teacher_disagreement_score":0.010063939,"about_ca_system_score_codex":0.001085266,"about_ca_system_score_gemma":0.0043285373,"threshold_uncertainty_score":0.0370031},"labels":[],"label_agreement":null},{"id":"W2608676843","doi":"10.11575/prism/30313","title":"UNITY - A DATABASE INTEGRATION TOOL","year":2000,"lang":"en","type":"article","venue":"PRISM (University of Calgary)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Database; Computer science","score_opus":0.011265116678368882,"score_gpt":0.20063807981380677,"score_spread":0.1893729631354379,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2608676843","genre_codex":"methods","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0066339453,0.00066571037,0.73116815,0.0002900375,0.00015851881,0.00047126113,0.003091184,0.24409783,0.013423377],"genre_scores_gemma":[0.11440804,0.0010079062,0.8215625,0.0007333834,0.00012471327,0.00075528864,0.019843368,0.018956939,0.022607855],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9959693,0.00060520304,0.0006169748,0.00070187176,0.0018620121,0.0002446074],"domain_scores_gemma":[0.99687564,0.00086519023,0.0002584209,0.0009606503,0.0007441255,0.00029585356],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003899361,0.00127933,0.0012933464,0.0029925401,0.0009287149,0.0044816635,0.0043251766,0.001197705,0.012481991],"category_scores_gemma":[0.010164974,0.0014719518,0.0017127262,0.0023951272,0.0007949455,0.006496574,0.0068954024,0.0024920437,0.007964266],"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":[0.0009823135,0.00034635502,0.004107923,0.0014780182,0.00033603833,0.0015021292,0.00245701,0.015033425,0.03151316,0.10402629,0.1752773,0.66294],"study_design_scores_gemma":[0.00038800846,0.00037447433,0.003989647,0.00054393715,0.00023912544,0.0026423829,0.0007467182,0.16974168,0.051320624,0.06942656,0.7001609,0.00042587027],"about_ca_topic_score_codex":0.002761475,"about_ca_topic_score_gemma":0.002147047,"teacher_disagreement_score":0.012481991,"about_ca_system_score_codex":0.00076738815,"about_ca_system_score_gemma":0.0021492776,"threshold_uncertainty_score":0.04175639},"labels":[],"label_agreement":null},{"id":"W2612373057","doi":"","title":"Resource Trees and XML Data Transformations - abstract","year":2005,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Prevention of Organ Failure","funders":"","keywords":"Computer science; XML; Efficient XML Interchange; Information retrieval; Database; World Wide Web","score_opus":0.025342561197006962,"score_gpt":0.25060751618218624,"score_spread":0.2252649549851793,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2612373057","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":[0.015528515,0.000506545,0.9731223,0.00089686265,0.000080061116,0.00009428441,0.0003099461,0.001815075,0.007646359],"genre_scores_gemma":[0.42722696,0.0009331526,0.5575754,0.0010283914,0.00012158812,0.00036085802,0.0013128062,0.0008095237,0.010631345],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.994087,0.001950898,0.0005114654,0.0007611029,0.002275189,0.00041441937],"domain_scores_gemma":[0.9946629,0.0025591513,0.0006095349,0.0010184892,0.0009954424,0.00015444207],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0041620582,0.0006389752,0.00056340784,0.0024495916,0.0012750062,0.003809802,0.0016713412,0.0015181849,0.0033756467],"category_scores_gemma":[0.007018296,0.0006421381,0.0013320213,0.0027850312,0.003914208,0.010659474,0.0030824346,0.002387308,0.0008414083],"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":[0.00006809645,0.000031848787,0.0005251275,0.00012634542,0.000019640134,0.0003247981,0.00038154505,0.008756638,0.0036230104,0.96395683,0.00172234,0.02046389],"study_design_scores_gemma":[0.00003349785,0.000053498134,0.0002950248,0.00013954176,0.00004899256,0.00048335796,0.00024384446,0.10659957,0.018140512,0.8156528,0.05824575,0.000063689535],"about_ca_topic_score_codex":0.0048889862,"about_ca_topic_score_gemma":0.002177643,"teacher_disagreement_score":0.0048889862,"about_ca_system_score_codex":0.0021088868,"about_ca_system_score_gemma":0.0018147323,"threshold_uncertainty_score":0.02201134},"labels":[],"label_agreement":null},{"id":"W2612396350","doi":"10.1145/3035918.3058736","title":"In-Browser Interactive SQL Analytics with Afterburner","year":2017,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"JavaScript; Computer science; SQL; Exploit; Benchmark (surveying); Operating system; Analytics; Relational database management system; Curiosity; Database; Relational database; Programming language","score_opus":0.014198968329285825,"score_gpt":0.2791832672794731,"score_spread":0.2649842989501873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2612396350","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":[0.056867592,0.0004553663,0.47383067,0.00064282137,0.00017790918,0.00019567995,0.0023888699,0.44355744,0.021883674],"genre_scores_gemma":[0.45156762,0.0005675559,0.44860226,0.0009412279,0.00010332798,0.00029358765,0.0081968,0.05918489,0.030542718],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99924123,0.00015928509,0.000042660922,0.00018149948,0.00027383916,0.00010147523],"domain_scores_gemma":[0.9971942,0.0015166283,0.00007431925,0.0008655777,0.00018207256,0.00016722677],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016766143,0.0012103308,0.0006288005,0.00055552676,0.00041787626,0.0021514928,0.0018387336,0.000985865,0.022135837],"category_scores_gemma":[0.0033460653,0.00084294385,0.00080929726,0.00042929052,0.00069986156,0.0033985903,0.0038403175,0.0018404988,0.0050393087],"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":[0.008060989,0.0017371716,0.013171534,0.0016451672,0.0005002806,0.0033453242,0.008895578,0.018940555,0.21985567,0.06540123,0.22062984,0.43781668],"study_design_scores_gemma":[0.00090345135,0.0004179948,0.00516133,0.00033821,0.0001437798,0.0016908274,0.0010710595,0.37695152,0.25073704,0.039823502,0.322475,0.00028625477],"about_ca_topic_score_codex":0.0018666115,"about_ca_topic_score_gemma":0.0033186579,"teacher_disagreement_score":0.022135837,"about_ca_system_score_codex":0.00040944605,"about_ca_system_score_gemma":0.0006603351,"threshold_uncertainty_score":0.07405174},"labels":[],"label_agreement":null},{"id":"W2613944953","doi":"","title":"Types for REWERSE reasoning and query languages I3-D4","year":2005,"lang":"fr","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Prevention of Organ Failure","funders":"","keywords":"Computer science; Artificial intelligence; Natural language processing","score_opus":0.01582523575379233,"score_gpt":0.2532818451922444,"score_spread":0.23745660943845207,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2613944953","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":[0.003981362,0.0020681734,0.9677711,0.008930087,0.0007757233,0.000135416,0.00049789506,0.0018494803,0.013990625],"genre_scores_gemma":[0.21938442,0.004200779,0.7164081,0.008829853,0.0034223036,0.0008691458,0.0026952925,0.0032403648,0.04094973],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9808647,0.006257841,0.0025795677,0.0024560348,0.006215039,0.0016268028],"domain_scores_gemma":[0.9651249,0.019290755,0.0011139277,0.007708556,0.0058910595,0.00087077456],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.016646085,0.0016658169,0.0022839014,0.0031867449,0.002939792,0.012415258,0.00668223,0.0059312745,0.021234326],"category_scores_gemma":[0.032710657,0.0039675203,0.0055223787,0.00499639,0.0075347573,0.032493345,0.006638968,0.017749822,0.004104361],"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":[0.00005455485,0.000033598506,0.00034892335,0.00024604588,0.00002736321,0.00009544571,0.0007801728,0.0016553213,0.0007552081,0.97553295,0.00680499,0.013665372],"study_design_scores_gemma":[0.0000367664,0.000025118457,0.00028152045,0.00014955759,0.000046577767,0.00014416211,0.00030924488,0.008631511,0.0017832356,0.9546727,0.03386399,0.00005547385],"about_ca_topic_score_codex":0.009335847,"about_ca_topic_score_gemma":0.005044184,"teacher_disagreement_score":0.021234326,"about_ca_system_score_codex":0.0074565127,"about_ca_system_score_gemma":0.0034428453,"threshold_uncertainty_score":0.088033974},"labels":[],"label_agreement":null},{"id":"W2614522653","doi":"","title":"A relaxation of Coq's guard condition","year":2012,"lang":"fr","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Prevention of Organ Failure","funders":"","keywords":"Guard (computer science); Proof assistant; Computer science; Programming language; Algebraic number; Commutative property; Dependency (UML); Theoretical computer science; Calculus (dental); Algebra over a field; Discrete mathematics; Mathematics; Artificial intelligence; Pure mathematics; Mathematical proof; Geometry","score_opus":0.021178251451653356,"score_gpt":0.24623988839821898,"score_spread":0.2250616369465656,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2614522653","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":[0.05338791,0.0019772598,0.7689237,0.024785187,0.004993735,0.00020554083,0.0013258549,0.0032957112,0.14110512],"genre_scores_gemma":[0.80302423,0.0012299304,0.1411316,0.0059892884,0.0041007944,0.0004652267,0.0012620824,0.0026574354,0.04013937],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9920736,0.0021782843,0.00041820624,0.002007966,0.0016908472,0.0016311647],"domain_scores_gemma":[0.9513724,0.032151613,0.0012559216,0.008790682,0.004379312,0.0020501271],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008822897,0.0014875223,0.002409941,0.0018754686,0.0033550537,0.0055586533,0.004637948,0.004146899,0.032728378],"category_scores_gemma":[0.051927596,0.0009491026,0.002101269,0.0032283803,0.006015941,0.01807407,0.0076970705,0.0126484195,0.0049317945],"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":[0.0007632934,0.00008807248,0.00037702956,0.0002374913,0.000035988814,0.00021352427,0.00031806045,0.0045352066,0.0017412219,0.9295631,0.03161356,0.030513488],"study_design_scores_gemma":[0.00015461308,0.00006349334,0.0001633046,0.00005660128,0.000050341114,0.00017709463,0.00013594604,0.05590422,0.0019709428,0.9289452,0.012336933,0.00004136732],"about_ca_topic_score_codex":0.0048317206,"about_ca_topic_score_gemma":0.002208436,"teacher_disagreement_score":0.032728378,"about_ca_system_score_codex":0.0033379938,"about_ca_system_score_gemma":0.004723047,"threshold_uncertainty_score":0.109487295},"labels":[],"label_agreement":null},{"id":"W2614742302","doi":"10.1145/3055167.3055170","title":"Data Statistics Adviser in Database Management Systems","year":2017,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Citation; Computer science; Library science; Database; Operations research; Engineering","score_opus":0.06376761428939949,"score_gpt":0.32870917425830193,"score_spread":0.26494155996890245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2614742302","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":[0.0015391043,0.0108655095,0.19049641,0.057650983,0.011949061,0.0015309278,0.036848504,0.25088698,0.4382325],"genre_scores_gemma":[0.022039289,0.0168848,0.09189995,0.018831562,0.015880648,0.002234862,0.06254128,0.08171274,0.6879749],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9778502,0.0054805353,0.0025713886,0.002675234,0.0102576995,0.0011649142],"domain_scores_gemma":[0.8850215,0.03348908,0.0040065176,0.03489713,0.032471534,0.01011432],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.025650073,0.0023847043,0.003710923,0.006887387,0.002684586,0.012517395,0.00477394,0.005678172,0.46934506],"category_scores_gemma":[0.104212835,0.0022578838,0.001067103,0.016878566,0.0017994617,0.02555615,0.009432203,0.0065575643,0.53534144],"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":[0.000042591077,0.000026101681,0.00022291495,0.00015959618,0.0000077816685,0.000017912975,0.00006174854,0.00009911774,0.00022892884,0.0035551833,0.9340637,0.06151446],"study_design_scores_gemma":[0.000030486364,0.000013992511,0.0002771727,0.00014805808,0.000007938377,0.000034811306,0.000037779715,0.0006807418,0.00045868396,0.0038162472,0.9944759,0.000018167299],"about_ca_topic_score_codex":0.0030946338,"about_ca_topic_score_gemma":0.0029024016,"teacher_disagreement_score":0.46934506,"about_ca_system_score_codex":0.0028705893,"about_ca_system_score_gemma":0.010341374,"threshold_uncertainty_score":0.75691485},"labels":[],"label_agreement":null},{"id":"W2616344723","doi":"10.1016/s0304-3975(02)00739-9","title":"Algebraic rewritings for optimizing regular path queries","year":2003,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":20,"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":"Rewriting; Computer science; Tuple; Materialized view; Query optimization; Query language; Algebraic number; Conjunctive query; Theoretical computer science; Relational algebra; Relational database; Mathematics; View; Programming language; Database; Discrete mathematics; Database design","score_opus":0.009068548688099044,"score_gpt":0.24208067029440322,"score_spread":0.2330121216063042,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2616344723","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":[0.042199295,0.00070819556,0.9366866,0.0006101238,0.0002277895,0.0001906857,0.0003658019,0.004841672,0.01416991],"genre_scores_gemma":[0.5163768,0.00080621446,0.46816412,0.00038153798,0.00037870352,0.00020981768,0.0010086844,0.0013749764,0.0112991715],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9960718,0.00083453197,0.00030892706,0.0005118702,0.0018829511,0.0003898581],"domain_scores_gemma":[0.9951167,0.002608103,0.0003034591,0.0010327093,0.00080291915,0.00013610479],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019821941,0.00071197737,0.0011504381,0.0012472395,0.0009707087,0.0023452735,0.0017982603,0.0008654593,0.0052680536],"category_scores_gemma":[0.010668861,0.0006748896,0.0014148025,0.0023307975,0.0017561753,0.004809086,0.0019932173,0.0027222757,0.001221858],"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":[0.00040433605,0.00018157376,0.0007603621,0.0003680663,0.00008310357,0.00025109446,0.0006591782,0.038994595,0.009722778,0.71998125,0.010874269,0.21771936],"study_design_scores_gemma":[0.0001043829,0.00013174502,0.00026748565,0.00004043848,0.00013786457,0.0002268035,0.00018397578,0.19672018,0.010534527,0.7751298,0.016465863,0.000056857156],"about_ca_topic_score_codex":0.002459833,"about_ca_topic_score_gemma":0.003497991,"teacher_disagreement_score":0.0052680536,"about_ca_system_score_codex":0.0013895803,"about_ca_system_score_gemma":0.0011703912,"threshold_uncertainty_score":0.017623425},"labels":[],"label_agreement":null},{"id":"W2616960942","doi":"10.11159/cca17.107","title":"Rule Based Systems in a Distributed Environment: Survey","year":2017,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Electrical Engineering and Computer Systems and Science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science","score_opus":0.01051152400412043,"score_gpt":0.21188962687874702,"score_spread":0.2013781028746266,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2616960942","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":[0.011670846,0.5853491,0.3529732,0.0067459918,0.0013989016,0.00043152942,0.00063168665,0.0013706557,0.039428137],"genre_scores_gemma":[0.12655033,0.649261,0.20655742,0.0019496132,0.003199723,0.0003986505,0.0019086215,0.0002904041,0.009884117],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99647814,0.00059262046,0.00046389012,0.00070894655,0.0015900462,0.00016640824],"domain_scores_gemma":[0.99136823,0.005309752,0.00037114436,0.0008263666,0.0018903529,0.00023425443],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036936745,0.00086125795,0.0018663069,0.0033994236,0.0008698894,0.004732118,0.0037872887,0.002131503,0.0035949892],"category_scores_gemma":[0.0084660845,0.00094617956,0.0012937197,0.009466266,0.0012442914,0.0068559744,0.0016414999,0.0018650566,0.0026764544],"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":[0.000086519445,0.00033457452,0.0044149673,0.0040430874,0.00019078741,0.00032813268,0.00030705036,0.026131103,0.00087810267,0.044853233,0.018267768,0.9001647],"study_design_scores_gemma":[0.000063732004,0.00032940495,0.0038810284,0.0023959088,0.00021456365,0.0025506227,0.0008817638,0.14642867,0.0027140467,0.12791017,0.71249163,0.00013836517],"about_ca_topic_score_codex":0.004278901,"about_ca_topic_score_gemma":0.002105543,"teacher_disagreement_score":0.004732118,"about_ca_system_score_codex":0.0013759073,"about_ca_system_score_gemma":0.0027701396,"threshold_uncertainty_score":0.01953423},"labels":[],"label_agreement":null},{"id":"W2623177735","doi":"","title":"EB3TG : Un outil de génération de transactions de base de données relationnelle pour EB3","year":2006,"lang":"fr","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Humanities; Philosophy; Computer science","score_opus":0.01966756260049348,"score_gpt":0.22370941947886697,"score_spread":0.20404185687837348,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2623177735","genre_codex":"methods","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024291743,0.00043702748,0.83160084,0.00037408364,0.00035302015,0.00041629196,0.006495865,0.13047476,0.0055564144],"genre_scores_gemma":[0.19045617,0.0006179294,0.7138347,0.00047496456,0.0002609754,0.0009919269,0.034426417,0.03998545,0.018951423],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.996425,0.00069142703,0.00035959404,0.0007271065,0.0014828701,0.00031405865],"domain_scores_gemma":[0.99366075,0.002589176,0.00023566453,0.0021786317,0.0010552368,0.00028057932],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003039479,0.003020253,0.0014553546,0.0021573983,0.001023213,0.004370483,0.0022729372,0.0021972384,0.028081587],"category_scores_gemma":[0.011504325,0.002115788,0.0025836085,0.0017459956,0.0010439438,0.003739488,0.0029057707,0.002929161,0.012027726],"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":[0.0072474666,0.0006534166,0.008832216,0.00214286,0.0006844627,0.0016404302,0.00155859,0.056722607,0.09204793,0.035543635,0.13226408,0.6606624],"study_design_scores_gemma":[0.0018539155,0.00085707504,0.0049822335,0.0003778604,0.0004412532,0.0015345494,0.0005449062,0.5038985,0.1888519,0.052463748,0.24387844,0.0003156296],"about_ca_topic_score_codex":0.004537628,"about_ca_topic_score_gemma":0.0025817035,"teacher_disagreement_score":0.028081587,"about_ca_system_score_codex":0.0009500509,"about_ca_system_score_gemma":0.001444176,"threshold_uncertainty_score":0.093942285},"labels":[],"label_agreement":null},{"id":"W2624689822","doi":"10.1016/j.procs.2017.05.370","title":"On Continuous Queries in Stream Processing","year":2017,"lang":"en","type":"article","venue":"Procedia Computer Science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Correctness; Tuple; Workflow; Stream processing; Sequence (biology); Database; Distributed computing; Programming language","score_opus":0.014333403024423848,"score_gpt":0.2740356315100061,"score_spread":0.2597022284855822,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2624689822","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":[0.00791,0.004810114,0.971202,0.0039158845,0.0005178432,0.00017798465,0.00021866342,0.00049774966,0.010749656],"genre_scores_gemma":[0.38921794,0.01061285,0.5722518,0.004693099,0.0064297263,0.00094571087,0.0013518477,0.0011073533,0.013389593],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9752315,0.00784561,0.0026152148,0.0032103779,0.009609312,0.0014879943],"domain_scores_gemma":[0.94872516,0.036844507,0.0021266001,0.0049498198,0.006186154,0.0011678233],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01755936,0.0018693018,0.0019051307,0.0033723086,0.0025024642,0.007711806,0.0035511437,0.0034365323,0.0038273751],"category_scores_gemma":[0.04400385,0.0012248999,0.00252259,0.0062115504,0.012028315,0.0198438,0.0073105497,0.009342989,0.0009450764],"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":[0.00009525922,0.00004367349,0.0007076344,0.00019171233,0.00002641109,0.00029101572,0.0006110743,0.01376646,0.00073348574,0.9661975,0.0027591616,0.014576593],"study_design_scores_gemma":[0.00004045612,0.00006958226,0.00023988888,0.00010589032,0.00003105984,0.00027328872,0.00014070864,0.09256797,0.0010837483,0.88806325,0.017345257,0.000039003902],"about_ca_topic_score_codex":0.0062096287,"about_ca_topic_score_gemma":0.0021671474,"teacher_disagreement_score":0.01755936,"about_ca_system_score_codex":0.0045575025,"about_ca_system_score_gemma":0.002950309,"threshold_uncertainty_score":0.09286392},"labels":[],"label_agreement":null},{"id":"W2627491027","doi":"10.1007/978-1-4614-8265-9","title":"Encyclopedia of Database Systems","year":2018,"lang":"en","type":"book","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":198,"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":"Encyclopedia; Computer science; Database; Information retrieval; World Wide Web; Data science; Library science","score_opus":0.01370649012213741,"score_gpt":0.23789433404053073,"score_spread":0.22418784391839333,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2627491027","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012554002,0.21483481,0.098288685,0.0062512476,0.024604965,0.000848518,0.017945277,0.01705879,0.6189123],"genre_scores_gemma":[0.0048986915,0.1441244,0.048859682,0.0036828644,0.007940912,0.0006041507,0.022315802,0.0037322324,0.7638413],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9973617,0.00025667535,0.00033354087,0.00042311064,0.0014921275,0.0001328599],"domain_scores_gemma":[0.99644417,0.00083918235,0.00023400417,0.0007499361,0.0013419691,0.00039078845],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012395764,0.0024609799,0.0036988615,0.007989234,0.0009412155,0.009988345,0.0027319046,0.0011261313,0.17066069],"category_scores_gemma":[0.004588716,0.0010092724,0.00096405006,0.016732398,0.0011466821,0.0055844467,0.0029686987,0.0027683065,0.17559604],"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":[0.000019429048,0.000044880002,0.00012481787,0.00114522,0.000025907902,0.00004792647,0.000045253444,0.00037274024,0.0006540956,0.011182447,0.7464613,0.2398759],"study_design_scores_gemma":[0.000006752096,0.000010814234,0.00019757674,0.0002801434,0.000012003715,0.0001934521,0.000021510732,0.00032633415,0.00013623106,0.0051384144,0.9936661,0.000010600881],"about_ca_topic_score_codex":0.002198255,"about_ca_topic_score_gemma":0.0025431775,"teacher_disagreement_score":0.17066069,"about_ca_system_score_codex":0.0019676087,"about_ca_system_score_gemma":0.0043165055,"threshold_uncertainty_score":0.5709169},"labels":[],"label_agreement":null},{"id":"W263422535","doi":"","title":"Algebraic Signatures for Scalable Web Data Integration for Electronic Commerce Transactions","year":2005,"lang":"en","type":"article","venue":"Journal of electronic commerce research","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Data integration; Web service; Information integration; Scalability; World Wide Web; Database","score_opus":0.08506810424651903,"score_gpt":0.4020548808054217,"score_spread":0.3169867765589026,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W263422535","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":[0.022047985,0.0001073092,0.9720178,0.00041692783,0.00006685188,0.0002417893,0.0002007465,0.0016256056,0.00327505],"genre_scores_gemma":[0.3214107,0.00022627067,0.67326117,0.00025156594,0.00011259613,0.00041145165,0.0009074287,0.00032217058,0.0030966967],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.98763764,0.0025642016,0.002223205,0.0012876842,0.0055378727,0.00074937526],"domain_scores_gemma":[0.9861448,0.004625742,0.0015735966,0.00378136,0.003410278,0.0004642555],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0069479328,0.0005275621,0.0012060957,0.002523291,0.002051006,0.0067109824,0.0021740596,0.0015989427,0.0023672453],"category_scores_gemma":[0.019582093,0.0008733606,0.0024627575,0.0034542554,0.0036542814,0.010646894,0.007337611,0.0030469208,0.0010052162],"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":[0.00013851971,0.00010957538,0.0009683241,0.00014240305,0.000047586916,0.0003113712,0.0006514538,0.037395176,0.00436526,0.90047324,0.0022317271,0.053165372],"study_design_scores_gemma":[0.0000770557,0.00009228088,0.00022805369,0.00007928101,0.000060172308,0.00034154658,0.000316792,0.40765232,0.01071621,0.5566081,0.0237499,0.00007837276],"about_ca_topic_score_codex":0.003350019,"about_ca_topic_score_gemma":0.0024363003,"teacher_disagreement_score":0.0069479328,"about_ca_system_score_codex":0.0025544406,"about_ca_system_score_gemma":0.0041304613,"threshold_uncertainty_score":0.036744654},"labels":[],"label_agreement":null},{"id":"W2690508998","doi":"","title":"Resource Trees: Models and Separation Logic","year":2008,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Prevention of Organ Failure","funders":"","keywords":"Computer science; Resource (disambiguation); Artificial intelligence","score_opus":0.027936196402144845,"score_gpt":0.25504138565731704,"score_spread":0.2271051892551722,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2690508998","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":[0.008659923,0.004277072,0.957175,0.0048583327,0.00026395122,0.00005210674,0.00060362765,0.00073887367,0.023371115],"genre_scores_gemma":[0.5239388,0.01153081,0.40613464,0.0024041561,0.0022036755,0.0004472743,0.0029091584,0.0012939996,0.04913759],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9973978,0.00080909755,0.00018561618,0.00053670345,0.0008296445,0.00024110025],"domain_scores_gemma":[0.9957425,0.002692768,0.000294705,0.0006470776,0.0003647947,0.0002580996],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032201388,0.0013507342,0.0015892491,0.0021417008,0.0018502286,0.008450112,0.0031462575,0.003000017,0.010299193],"category_scores_gemma":[0.00705019,0.0015066987,0.0019429678,0.005630436,0.004686008,0.01955658,0.0034608322,0.00741227,0.0027242026],"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":[0.000018705166,0.000014602037,0.000056518067,0.00005832437,0.000008165543,0.00003131074,0.00011439371,0.0036185451,0.00017397088,0.9855621,0.0026040555,0.007739232],"study_design_scores_gemma":[0.0000068652334,0.000003719181,0.000019920286,0.000014894455,0.000007300626,0.000036899128,0.00002521719,0.011432436,0.00013021099,0.9825394,0.005776334,0.000006670061],"about_ca_topic_score_codex":0.0042342483,"about_ca_topic_score_gemma":0.0026213138,"teacher_disagreement_score":0.010299193,"about_ca_system_score_codex":0.003721861,"about_ca_system_score_gemma":0.0023844456,"threshold_uncertainty_score":0.034454286},"labels":[],"label_agreement":null},{"id":"W2729865853","doi":"","title":"Algebraic Informatics, 5th International Conference on Algebraic Informatics, CAI 2013","year":2013,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Informatics; Algebraic number; Computer science; Mathematics; Engineering","score_opus":0.01939366350587453,"score_gpt":0.24359474554915256,"score_spread":0.22420108204327802,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2729865853","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017796254,0.10725568,0.18884437,0.037613083,0.06514928,0.00044891093,0.004160767,0.0076629366,0.57106876],"genre_scores_gemma":[0.0821511,0.045734197,0.078596786,0.0016919172,0.018279556,0.0003740983,0.00605089,0.0023992269,0.7647223],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986504,0.00021148179,0.00008682888,0.00030527267,0.00060947106,0.00013655346],"domain_scores_gemma":[0.99833316,0.00022620344,0.000053701133,0.0003013112,0.0007476053,0.00033805068],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002231785,0.0011251952,0.0015832365,0.0037998797,0.0020723073,0.006833379,0.0014393316,0.0009268889,0.10474546],"category_scores_gemma":[0.0032288146,0.00041349445,0.0008868948,0.004495329,0.0014447551,0.004504632,0.0035454351,0.0033696184,0.023540862],"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":[0.00011265741,0.00010707211,0.00073876156,0.00067278807,0.00004659904,0.0000962673,0.0003278166,0.0011649227,0.0018117423,0.10483691,0.57005125,0.32003325],"study_design_scores_gemma":[0.000023563356,0.00005237655,0.0016549827,0.00030298438,0.00002487057,0.00027418183,0.00022620661,0.0035573773,0.00124196,0.036520593,0.95609987,0.000021032669],"about_ca_topic_score_codex":0.00399884,"about_ca_topic_score_gemma":0.008163562,"teacher_disagreement_score":0.10474546,"about_ca_system_score_codex":0.0044541634,"about_ca_system_score_gemma":0.0045988923,"threshold_uncertainty_score":0.3504085},"labels":[],"label_agreement":null},{"id":"W2731866483","doi":"10.29007/53fk","title":"An Interpolation-based Compiler and Optimizer for Relational Queries (System design Report)","year":2018,"lang":"en","type":"article","venue":"Kalpa publications in computing","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Compiler; Programming language; Query language; Schema (genetic algorithms); Predicate (mathematical logic); Query optimization; Relational database; First-order logic; Theoretical computer science; Information retrieval","score_opus":0.049010262807066066,"score_gpt":0.3170783455920585,"score_spread":0.26806808278499245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2731866483","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":[0.0097823385,0.00009452851,0.94755983,0.00012791246,0.000041087656,0.00023061092,0.00042763332,0.039011445,0.002724586],"genre_scores_gemma":[0.13343064,0.0001331141,0.8556955,0.00020698499,0.00003492918,0.00036675337,0.0013627452,0.0045947847,0.0041746236],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.998855,0.00023372403,0.00010793811,0.00020236196,0.00043413977,0.0001668844],"domain_scores_gemma":[0.99883515,0.00043611758,0.00009379982,0.00029446135,0.00029405247,0.00004639604],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017490317,0.0005648806,0.00050034706,0.00054375804,0.0003460954,0.001269758,0.0014909776,0.0004537976,0.00713334],"category_scores_gemma":[0.0034427585,0.00070920895,0.00081837253,0.0006049812,0.00063009874,0.0016290295,0.0008594381,0.0012745964,0.002506095],"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":[0.0016829234,0.00065957394,0.0052754115,0.0007857758,0.0001793644,0.0005441519,0.0010703849,0.14284483,0.10448837,0.17267779,0.071942344,0.4978491],"study_design_scores_gemma":[0.00021184313,0.00042186424,0.0011845164,0.000065513195,0.00009848407,0.00028730024,0.00011545787,0.77367723,0.13278438,0.025573473,0.065457836,0.000122044956],"about_ca_topic_score_codex":0.003176633,"about_ca_topic_score_gemma":0.0023406667,"teacher_disagreement_score":0.00713334,"about_ca_system_score_codex":0.0010298078,"about_ca_system_score_gemma":0.0023633218,"threshold_uncertainty_score":0.023863375},"labels":[],"label_agreement":null},{"id":"W2735993833","doi":"","title":"EB 3 attribute definitions: Formal language and application","year":2005,"lang":"en","type":"preprint","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Computer science; Programming language; Formal language","score_opus":0.024470109332207016,"score_gpt":0.26888830014509535,"score_spread":0.24441819081288835,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2735993833","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":[0.0018417162,0.0007953055,0.9863942,0.00062603835,0.000096549236,0.00008668628,0.0003765843,0.0009868975,0.00879597],"genre_scores_gemma":[0.10552721,0.002233084,0.87903506,0.0010549717,0.0002542245,0.00071227463,0.0015312895,0.0011300802,0.008521865],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99799407,0.0006638243,0.0003084086,0.00029380294,0.0005794082,0.0001605202],"domain_scores_gemma":[0.99717355,0.0016067416,0.00023287263,0.00029768876,0.00060577586,0.00008340678],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003917273,0.0008934273,0.00055524067,0.001428309,0.00087136525,0.0028445565,0.0018669306,0.0010849843,0.00594848],"category_scores_gemma":[0.0062532425,0.0009301809,0.0011273689,0.0020736775,0.0031921857,0.0042708437,0.0026175354,0.003472751,0.0021858998],"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":[0.00002906686,0.00003009073,0.00016300516,0.00018885519,0.000008843462,0.00014585139,0.0009177912,0.004397131,0.0020591787,0.9508508,0.0058237687,0.035385683],"study_design_scores_gemma":[0.000042558884,0.000044064687,0.00019281091,0.0002524707,0.00001749477,0.0005134377,0.00022819714,0.032074317,0.0056945714,0.7009953,0.2598967,0.000048147413],"about_ca_topic_score_codex":0.0032939687,"about_ca_topic_score_gemma":0.0011369516,"teacher_disagreement_score":0.00594848,"about_ca_system_score_codex":0.0013011347,"about_ca_system_score_gemma":0.0015780599,"threshold_uncertainty_score":0.020716786},"labels":[],"label_agreement":null},{"id":"W2741049205","doi":"10.1007/978-3-319-64471-4_9","title":"Past Indeterminacy in Data Warehouse Design","year":2017,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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":"Université de Sherbrooke","funders":"","keywords":"Computer science; Data warehouse; Schema (genetic algorithms); Schema evolution; Scalability; Implementation; Indeterminacy (philosophy); Traceability; Database schema; Data integrity; Data mining; Information retrieval; Database; Programming language; Software engineering; Database design","score_opus":0.06570883046719668,"score_gpt":0.29485987039674727,"score_spread":0.2291510399295506,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2741049205","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":[0.03989425,0.008058886,0.92005897,0.002587721,0.00023930393,0.000049958413,0.000099671335,0.00040477954,0.028606527],"genre_scores_gemma":[0.7716819,0.0031943878,0.2151001,0.00033173908,0.00028879163,0.00008708091,0.00015020554,0.00022557579,0.008940254],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9967063,0.0014105003,0.00030826364,0.00040912657,0.0009912824,0.00017459004],"domain_scores_gemma":[0.99018234,0.006078129,0.00048094406,0.0018997106,0.0010940339,0.00026496575],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0057985694,0.00063783344,0.000727543,0.00092456175,0.0010457359,0.004880063,0.001787489,0.0008143061,0.0030036003],"category_scores_gemma":[0.021657435,0.0012021667,0.0006385807,0.0017736802,0.002923739,0.009386004,0.0018923817,0.0029128664,0.00045534477],"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":[0.00015352204,0.000035924382,0.0010557832,0.00024374823,0.000036351907,0.00013972302,0.0007106733,0.021810904,0.000838395,0.8653498,0.0033661707,0.10625897],"study_design_scores_gemma":[0.00002198815,0.000049492028,0.00022293738,0.000126225,0.00004097938,0.00019760689,0.00011780441,0.076578386,0.001343092,0.9029211,0.018353853,0.000026498854],"about_ca_topic_score_codex":0.0011286502,"about_ca_topic_score_gemma":0.0015983377,"teacher_disagreement_score":0.0057985694,"about_ca_system_score_codex":0.0021682025,"about_ca_system_score_gemma":0.0014172812,"threshold_uncertainty_score":0.030666113},"labels":[],"label_agreement":null},{"id":"W2754080593","doi":"10.1109/mic.2017.3481351","title":"The Lambda and the Kappa","year":2017,"lang":"en","type":"article","venue":"IEEE Internet Computing","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":66,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Lambda; Kappa; Computer science; World Wide Web; Computer security; Physics; Mathematics","score_opus":0.014179568173659843,"score_gpt":0.2645233826542149,"score_spread":0.25034381448055504,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2754080593","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":[0.008767341,0.0434398,0.09736317,0.32760274,0.029429901,0.00006654294,0.00053928816,0.0011702148,0.49162096],"genre_scores_gemma":[0.4465208,0.022461277,0.041283198,0.11643468,0.031006431,0.00034034697,0.00034279516,0.0021138473,0.33949664],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98874694,0.004949893,0.0005575437,0.0018146657,0.002848726,0.001082234],"domain_scores_gemma":[0.97153574,0.016440438,0.0014419449,0.0037720567,0.004395489,0.002414388],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011623228,0.0009864273,0.0014650605,0.0023903297,0.007161236,0.012499971,0.0016536061,0.0048425156,0.046479635],"category_scores_gemma":[0.048171278,0.000888289,0.0013399433,0.002161929,0.03146335,0.032425635,0.006514526,0.016253732,0.014960909],"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":[0.000059503167,0.000010987923,0.00021934955,0.000059084217,0.000013354236,0.000036502654,0.00074122986,0.000049319275,0.000093774244,0.9313835,0.052203313,0.0151301045],"study_design_scores_gemma":[0.000031850515,0.000014530352,0.0001761794,0.00011152431,0.000013347095,0.00011411767,0.00066091603,0.00010101118,0.00014374928,0.7762552,0.2223445,0.00003307252],"about_ca_topic_score_codex":0.0067188446,"about_ca_topic_score_gemma":0.0037890107,"teacher_disagreement_score":0.046479635,"about_ca_system_score_codex":0.003915019,"about_ca_system_score_gemma":0.0046207285,"threshold_uncertainty_score":0.15548992},"labels":[],"label_agreement":null},{"id":"W2754950504","doi":"10.1145/3129292.3129297","title":"Towards Dynamic Data Placement for Polystore Ingestion","year":2017,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Bell Canada Enterprises; Intel Corporation; National Science Foundation","keywords":"Workload; Computer science; Data warehouse; Latency (audio); Benchmark (surveying); Context (archaeology); Database; Dynamic data; Distributed computing; Operating system","score_opus":0.06506270214730049,"score_gpt":0.35134320219533305,"score_spread":0.28628050004803257,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2754950504","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":[0.54582316,0.0013145342,0.4261962,0.0011196523,0.00027811513,0.00037281937,0.0010951717,0.012167505,0.011632881],"genre_scores_gemma":[0.5721636,0.0004581284,0.4218446,0.00026093898,0.000057397137,0.0001357016,0.0020392928,0.00063690386,0.0024033955],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99869764,0.00019668174,0.00016164486,0.00023532224,0.00048313086,0.00022551112],"domain_scores_gemma":[0.9972579,0.0005458383,0.00028178468,0.0010334038,0.00067143544,0.00020969598],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010158815,0.00077829434,0.0005977579,0.0008401786,0.00095780985,0.0020623961,0.0023042602,0.0008704342,0.0016477485],"category_scores_gemma":[0.004224236,0.00051578804,0.00042534783,0.0019541373,0.0007170799,0.0026202928,0.002167624,0.0009470427,0.00073303544],"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":[0.0013511641,0.00089741993,0.020214869,0.0008059141,0.000121209254,0.0009850508,0.0010136127,0.20541234,0.32419592,0.02591851,0.024233356,0.39485055],"study_design_scores_gemma":[0.0001478544,0.0006589296,0.004429385,0.00005268142,0.000052491152,0.0006278448,0.00097371265,0.7950495,0.15348412,0.017242199,0.027204292,0.000077004894],"about_ca_topic_score_codex":0.0028408964,"about_ca_topic_score_gemma":0.0054135327,"teacher_disagreement_score":0.0028408964,"about_ca_system_score_codex":0.00093534304,"about_ca_system_score_gemma":0.00213172,"threshold_uncertainty_score":0.0067864656},"labels":[],"label_agreement":null},{"id":"W2759878005","doi":"10.1002/spe.2560","title":"Roaring bitmaps: Implementation of an optimized software library","year":2018,"lang":"en","type":"article","venue":"Software Practice and Experience","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":48,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick; Université TÉLUQ; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Bitmap; Oracle; Microsoft Visual Studio; Software; Benchmark (surveying); Visual Basic for Applications; Index (typography)","score_opus":0.015491083339612195,"score_gpt":0.32155551221457046,"score_spread":0.30606442887495827,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2759878005","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":[0.018535636,0.000384354,0.49391332,0.00023331633,0.0001143575,0.00030211624,0.0025669911,0.4703999,0.013549967],"genre_scores_gemma":[0.214784,0.00059071544,0.66779894,0.0006177231,0.000119688004,0.0009752933,0.018410128,0.07489552,0.021807978],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99760485,0.00028883968,0.00023105962,0.0004144481,0.0011010651,0.00035960067],"domain_scores_gemma":[0.9970483,0.00076594215,0.00020229205,0.0007958866,0.0010045494,0.00018300994],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015004599,0.001687872,0.0008735271,0.001960703,0.00073531736,0.002471064,0.0040878346,0.0008213064,0.025096506],"category_scores_gemma":[0.0057207784,0.0013209424,0.0010164576,0.0027359556,0.0008849145,0.0033801605,0.0022517294,0.0014903871,0.015282793],"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":[0.0020036635,0.00052566774,0.005239822,0.00077604165,0.00022878987,0.00041045705,0.00067784317,0.040756084,0.03302092,0.026920198,0.23094594,0.65849465],"study_design_scores_gemma":[0.0006800354,0.00038407382,0.003621538,0.00018479646,0.00012982354,0.0005056568,0.00023333398,0.58786005,0.15513366,0.021120597,0.22974479,0.00040163242],"about_ca_topic_score_codex":0.007964541,"about_ca_topic_score_gemma":0.0056774667,"teacher_disagreement_score":0.025096506,"about_ca_system_score_codex":0.0015439654,"about_ca_system_score_gemma":0.0029298298,"threshold_uncertainty_score":0.08395618},"labels":[],"label_agreement":null},{"id":"W2767795900","doi":"10.1109/softwaremining.2017.8100847","title":"Mining temporal intervals from real-time system traces","year":2017,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Jet Propulsion Laboratory","keywords":"Computer science; TRACE (psycholinguistics); Data mining; Time series; Interval (graph theory); Algorithm; Theoretical computer science; Artificial intelligence; Machine learning; Mathematics","score_opus":0.025776668816872114,"score_gpt":0.2749838062221876,"score_spread":0.24920713740531547,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2767795900","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":[0.022500085,0.00011385791,0.975083,0.00007164122,0.000014003634,0.000059765556,0.0003567181,0.0014222777,0.00037859046],"genre_scores_gemma":[0.2760521,0.00015856202,0.72090673,0.000053903685,0.000031345277,0.00015924334,0.0019979621,0.00010214965,0.0005379014],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99845994,0.00017477383,0.00019263332,0.00039650608,0.0006859614,0.00009027268],"domain_scores_gemma":[0.99510753,0.0026511876,0.0007321444,0.0006895205,0.0006959671,0.00012360665],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012564241,0.0007336323,0.0005760292,0.002495994,0.0003732387,0.0009934055,0.0016064522,0.0005841096,0.0008724058],"category_scores_gemma":[0.0094415415,0.0003439983,0.0006648014,0.001792133,0.00047552216,0.0019707237,0.0009487564,0.0009370468,0.00033742166],"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":[0.00033426366,0.00034537265,0.020592475,0.00044043976,0.00017723851,0.0008553445,0.00061383593,0.19578432,0.021695938,0.023795994,0.00360221,0.73176265],"study_design_scores_gemma":[0.000020494479,0.00006915521,0.0013592611,0.00002243305,0.00002446691,0.00027330092,0.00008410858,0.9680858,0.008768692,0.018645726,0.0026312172,0.00001530697],"about_ca_topic_score_codex":0.0020903163,"about_ca_topic_score_gemma":0.0031314697,"teacher_disagreement_score":0.002495994,"about_ca_system_score_codex":0.0004248674,"about_ca_system_score_gemma":0.0011512553,"threshold_uncertainty_score":0.006644666},"labels":[],"label_agreement":null},{"id":"W2787433245","doi":"","title":"Towards an Integration of Knowledge in OLAP Cubes Exploratory Analysis","year":2005,"lang":"en","type":"article","venue":"E-ti","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Online analytical processing; Data cube; Data warehouse; Computer science; Multidimensional data; Cube (algebra); Process (computing); Extension (predicate logic); Set (abstract data type); Data mining; Multidimensional analysis; Knowledge extraction; Database; Data science; Information retrieval; Mathematics","score_opus":0.029594703279364386,"score_gpt":0.30110820582302344,"score_spread":0.2715135025436591,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2787433245","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":[0.0038387112,0.00022531404,0.99369013,0.0004461099,0.000016223894,0.00006464128,0.000046517867,0.0002893004,0.001382953],"genre_scores_gemma":[0.04699518,0.00044461744,0.95119005,0.00015977662,0.000040977913,0.00012889397,0.00021941167,0.00009070779,0.0007302996],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99328375,0.0023470304,0.00059357757,0.00087129185,0.0026018918,0.00030245562],"domain_scores_gemma":[0.9946949,0.0020984174,0.0004482226,0.0014289786,0.0010519048,0.00027767266],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008178084,0.0010007733,0.0011919343,0.003896577,0.0015123679,0.009230762,0.0020534962,0.0014506751,0.0011871533],"category_scores_gemma":[0.011981628,0.0009399345,0.002007478,0.004969825,0.0033791761,0.0103746075,0.008432392,0.0031798978,0.00058271334],"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":[0.00017108535,0.00023842303,0.0034698818,0.0008484081,0.0003173509,0.0009793908,0.006188096,0.033869646,0.011636737,0.61399144,0.00327322,0.32501632],"study_design_scores_gemma":[0.00003480623,0.00011450396,0.0012286182,0.00044676766,0.00018795858,0.00048178004,0.0018453023,0.28684032,0.011362943,0.6304543,0.06691912,0.00008359659],"about_ca_topic_score_codex":0.0029895457,"about_ca_topic_score_gemma":0.0023330627,"teacher_disagreement_score":0.009230762,"about_ca_system_score_codex":0.0011071571,"about_ca_system_score_gemma":0.0023191308,"threshold_uncertainty_score":0.043250382},"labels":[],"label_agreement":null},{"id":"W2791546773","doi":"10.1007/s10703-018-0317-z","title":"Inferring event stream abstractions","year":2018,"lang":"en","type":"article","venue":"Formal Methods in System Design","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":15,"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":"Air Force Office of Scientific Research","keywords":"Computer science; Programming language; Scala; Event (particle physics); Specification language; Notation; Theoretical computer science; Java","score_opus":0.06975814659087953,"score_gpt":0.3957318738214263,"score_spread":0.3259737272305468,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2791546773","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":[0.027351934,0.00012154426,0.9654915,0.00032154357,0.000084602696,0.00013406476,0.0008037666,0.0032126957,0.0024784],"genre_scores_gemma":[0.4322628,0.0003874589,0.5593423,0.00018721819,0.00012554093,0.00015990029,0.0031356574,0.0005913973,0.003807746],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9957445,0.0010247463,0.00029967935,0.0008816755,0.0016797611,0.00036960893],"domain_scores_gemma":[0.9902749,0.005704624,0.00061860896,0.002055868,0.0011139561,0.00023211821],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037642315,0.0011667791,0.0008603725,0.0031267798,0.00090203574,0.0032420703,0.001698623,0.0014685666,0.004587329],"category_scores_gemma":[0.02323595,0.0011335986,0.0024418219,0.0017427863,0.0011561656,0.0046076123,0.003133629,0.0025383811,0.0011910411],"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":[0.0010074791,0.00050122256,0.032939103,0.00077235687,0.0004833917,0.0016425884,0.0016406055,0.19061181,0.026361926,0.4178826,0.011739188,0.3144177],"study_design_scores_gemma":[0.000055012762,0.00006239318,0.001928612,0.00007948748,0.00015908516,0.00018552349,0.00023039787,0.75301766,0.018725544,0.2110302,0.014489277,0.00003677159],"about_ca_topic_score_codex":0.00436613,"about_ca_topic_score_gemma":0.005088728,"teacher_disagreement_score":0.004587329,"about_ca_system_score_codex":0.0013449609,"about_ca_system_score_gemma":0.0024304816,"threshold_uncertainty_score":0.019907355},"labels":[],"label_agreement":null},{"id":"W2791839450","doi":"10.3233/fi-2019-1819","title":"Universal (and Existential) Nulls","year":2019,"lang":"en","type":"preprint","venue":"Fundamenta Informaticae","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Existentialism; Set (abstract data type); Mathematics; Star (game theory); Representation (politics); Discrete mathematics; Combinatorics; Algebra over a field; Computer science; Pure mathematics; Programming language","score_opus":0.015533828793069648,"score_gpt":0.2409121959049102,"score_spread":0.22537836711184056,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2791839450","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":[0.057429794,0.0012826172,0.92818534,0.0013425526,0.00013465853,0.00016097761,0.0011737092,0.0013044192,0.008985827],"genre_scores_gemma":[0.6252995,0.0018469631,0.3604153,0.0007315135,0.00024501618,0.00021647464,0.0022109386,0.00044163986,0.008592654],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98892015,0.0018021443,0.0016042963,0.0021356037,0.004705402,0.0008323535],"domain_scores_gemma":[0.97997457,0.008405737,0.0013523188,0.0066404385,0.0031746887,0.00045231153],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008734024,0.00067963207,0.0014867717,0.0018447418,0.0014725785,0.005310525,0.0029320843,0.0012097291,0.004421897],"category_scores_gemma":[0.021502407,0.000658356,0.0020555945,0.0030505979,0.0046770186,0.01665904,0.0042969617,0.0020938006,0.0007994762],"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":[0.00018024616,0.000038970637,0.0024002749,0.0003483403,0.00006625323,0.00045493688,0.0008330247,0.004992286,0.005851672,0.9118175,0.0022981386,0.07071829],"study_design_scores_gemma":[0.000026958376,0.000080316386,0.00094939605,0.00018830097,0.00014403898,0.001034241,0.00064264564,0.053219475,0.024489082,0.8813446,0.037780788,0.00010021621],"about_ca_topic_score_codex":0.0025125495,"about_ca_topic_score_gemma":0.0018262289,"teacher_disagreement_score":0.008734024,"about_ca_system_score_codex":0.0021230015,"about_ca_system_score_gemma":0.0026685428,"threshold_uncertainty_score":0.04619044},"labels":[],"label_agreement":null},{"id":"W2795407832","doi":"","title":"SCOR/IODE/MBLWHOI Library collaboration on data publication [poster]","year":2011,"lang":"en","type":"article","venue":"Open Access Server of the Woods Hole Scientific Community (Woods Hole Scientific Community)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; World Wide Web; Library science","score_opus":0.23686786733796542,"score_gpt":0.37095164518740487,"score_spread":0.13408377784943945,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2795407832","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0037167403,0.0072579444,0.010401533,0.06424647,0.03191615,0.0010251093,0.07508239,0.019170543,0.7871831],"genre_scores_gemma":[0.016799735,0.0046026646,0.013167621,0.0062690205,0.0075286236,0.00037814674,0.05343766,0.009344351,0.8884722],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9930727,0.0011872025,0.00042471522,0.00077829865,0.0033941043,0.0011430668],"domain_scores_gemma":[0.9663666,0.0035417997,0.001225759,0.005000579,0.015374889,0.008490338],"candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0144589245,0.0011418648,0.0015497414,0.007957282,0.003433144,0.012202424,0.0015758225,0.0019983316,0.49750954],"category_scores_gemma":[0.020043222,0.000557458,0.0011977204,0.010002449,0.0007852318,0.0058716703,0.007839716,0.002434412,0.3241431],"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":[0.00012998794,0.000023311843,0.00033633673,0.00015316716,0.000009111741,0.00003313875,0.000103530016,0.000022509079,0.00033419643,0.0010851902,0.9628421,0.03492733],"study_design_scores_gemma":[0.000015844143,0.000012540599,0.0005730657,0.00006737656,0.000007299731,0.00002990946,0.00010978943,0.00006345181,0.00043727874,0.00032658438,0.99834573,0.000011090665],"about_ca_topic_score_codex":0.0101420665,"about_ca_topic_score_gemma":0.0231507,"teacher_disagreement_score":0.98779756,"about_ca_system_score_codex":0.0038487727,"about_ca_system_score_gemma":0.010435706,"threshold_uncertainty_score":0.7167417},"labels":[],"label_agreement":null},{"id":"W2800591543","doi":"","title":"Information Without Borders: The Challenge of Connecting Disparate Data and Information Resources (Invited Presentation)","year":2017,"lang":"en","type":"article","venue":"97th American Meteorological Society Annual Meeting","topic":"Advanced Database Systems and Queries","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 Calgary","funders":"","keywords":"Presentation (obstetrics); Disparate system; Computer science; Data science; World Wide Web; Information retrieval; Internet privacy; Database; Medicine","score_opus":0.02312927445586413,"score_gpt":0.301116236131399,"score_spread":0.2779869616755348,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2800591543","genre_codex":"commentary","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":[0.00185982,0.034818675,0.018213654,0.84973925,0.08007917,0.00006856831,0.00023647053,0.00028453046,0.014699821],"genre_scores_gemma":[0.07539226,0.112834565,0.043548007,0.3342098,0.32674918,0.0003667471,0.0011259434,0.0012455006,0.10452794],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9967482,0.0012626473,0.00015107088,0.00039700206,0.0009997989,0.00044137155],"domain_scores_gemma":[0.98867756,0.0064569325,0.0003996628,0.0005536869,0.0017729222,0.0021391152],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010362009,0.00056974933,0.0007503201,0.0009910294,0.0030928073,0.013454097,0.0014741584,0.0072679156,0.011399209],"category_scores_gemma":[0.02060414,0.00058727956,0.0005809266,0.0015075274,0.0035606136,0.027405733,0.006680442,0.009482372,0.0038670667],"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":[0.00004183651,0.000017297567,0.00019258159,0.00021799224,0.000017035241,0.00014470624,0.0008467843,0.00022360959,0.00041747373,0.031240828,0.9095334,0.057106536],"study_design_scores_gemma":[0.000011947069,0.00001673016,0.00029696833,0.00022132802,0.000015605157,0.0001926426,0.0017928357,0.0005733809,0.0002897219,0.050669964,0.9458932,0.000025499647],"about_ca_topic_score_codex":0.0029069989,"about_ca_topic_score_gemma":0.005672527,"teacher_disagreement_score":0.013454097,"about_ca_system_score_codex":0.0015938985,"about_ca_system_score_gemma":0.0036395192,"threshold_uncertainty_score":0.054800212},"labels":[],"label_agreement":null},{"id":"W2803123410","doi":"10.1145/3206333.3206338","title":"Distribution-Aware Stream Partitioning for Distributed Stream Processing Systems","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Stateful firewall; Computer science; Distributed computing; Stream processing; Key (lock); Overhead (engineering); Workload; Cluster (spacecraft); Real-time computing; Computer network; Operating system","score_opus":0.020123718417623997,"score_gpt":0.27589370074873165,"score_spread":0.25576998233110765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2803123410","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":[0.049943656,0.0014083687,0.9421844,0.0004180592,0.00015172496,0.00014323446,0.0002330032,0.003006257,0.0025112887],"genre_scores_gemma":[0.7523091,0.000982288,0.24177065,0.00016309817,0.00016762198,0.00020500136,0.0008495459,0.00043258877,0.003120105],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992539,0.00014674623,0.000069708876,0.00013516215,0.00026857114,0.00012585637],"domain_scores_gemma":[0.9988446,0.00031892443,0.000094993615,0.00029790736,0.00033848363,0.00010495099],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000763193,0.0005329306,0.0007040848,0.00067005545,0.0008714761,0.0010498421,0.0012153317,0.00038434705,0.0014257221],"category_scores_gemma":[0.002682159,0.00037010334,0.00029855306,0.0009983786,0.00040339038,0.0013976124,0.0012344263,0.0006806636,0.0005600575],"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":[0.0013936145,0.0003256853,0.005761127,0.00047299542,0.00013621658,0.00033184735,0.0004416122,0.3856797,0.093586065,0.025078509,0.021522371,0.46527022],"study_design_scores_gemma":[0.00007421878,0.00007225412,0.00078762526,0.000014525533,0.000027924698,0.00016107481,0.00008273429,0.9560787,0.01846505,0.016275065,0.007943756,0.000017039447],"about_ca_topic_score_codex":0.001714032,"about_ca_topic_score_gemma":0.002748887,"teacher_disagreement_score":0.001714032,"about_ca_system_score_codex":0.0009481677,"about_ca_system_score_gemma":0.001060851,"threshold_uncertainty_score":0.006879449},"labels":[],"label_agreement":null},{"id":"W2817113361","doi":"10.1145/3216122.3216157","title":"A useful four-valued database logic","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Truth value; SQL; Computer science; Negation; Relational database; Constructive; Theoretical computer science; Intuitionistic logic; Logical consequence; Propositional calculus; Programming language; Artificial intelligence; Data mining","score_opus":0.05408212891216195,"score_gpt":0.28754151078918194,"score_spread":0.23345938187701998,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2817113361","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":[0.01621825,0.0044569257,0.9040822,0.004974332,0.00057616126,0.0001538997,0.0012188636,0.0007615977,0.06755781],"genre_scores_gemma":[0.3317571,0.0039245305,0.641399,0.0024691322,0.0004711399,0.00021256862,0.0012078453,0.00012905116,0.018429583],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9982747,0.00053410575,0.00018731147,0.0003168875,0.0005458089,0.00014125588],"domain_scores_gemma":[0.9988815,0.0003732515,0.00011755328,0.00018455742,0.0003269314,0.00011619139],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00278932,0.0006020841,0.0005752293,0.002149164,0.0015153115,0.00519388,0.0016200352,0.001023174,0.004478135],"category_scores_gemma":[0.0029944612,0.00036575715,0.0011079314,0.0033429896,0.003027983,0.006186642,0.0023277171,0.0020861954,0.001157138],"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":[0.000014052131,0.000006553859,0.00006328917,0.000044209468,0.0000046710647,0.000074973475,0.00016655926,0.00078465044,0.0008521655,0.98601556,0.0013583221,0.010614903],"study_design_scores_gemma":[0.00001509356,0.000025672145,0.00006316977,0.0000474136,0.000015804313,0.00020697997,0.00013318453,0.009665671,0.0012046777,0.915763,0.072836734,0.000022601445],"about_ca_topic_score_codex":0.002969019,"about_ca_topic_score_gemma":0.0016229663,"teacher_disagreement_score":0.00519388,"about_ca_system_score_codex":0.0022301269,"about_ca_system_score_gemma":0.0022478784,"threshold_uncertainty_score":0.016180754},"labels":[],"label_agreement":null},{"id":"W28634153","doi":"10.2196/mhealth.6497","title":"Model Driven Architecture in Adaptive Library Generation","year":2008,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Architecture; Computer science; Geography","score_opus":0.07859032508813274,"score_gpt":0.31963828411284345,"score_spread":0.2410479590247107,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W28634153","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":[0.02716427,0.00011703608,0.96721005,0.00031302412,0.000030623913,0.0002518383,0.00009050905,0.0015074502,0.0033151796],"genre_scores_gemma":[0.60893965,0.00014230581,0.38528416,0.00018396185,0.000021459737,0.0007094073,0.0003093305,0.00021693233,0.0041927565],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99751806,0.0014579905,0.000110409266,0.00033578323,0.00041216324,0.00016570679],"domain_scores_gemma":[0.9937902,0.0048749247,0.00016563396,0.00050545984,0.0005333143,0.00013047062],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0047227177,0.0005566027,0.0006545684,0.00084273465,0.00062137865,0.0014736882,0.0020097387,0.0013934566,0.005770086],"category_scores_gemma":[0.014518185,0.0007104374,0.000940161,0.0007229828,0.0011814411,0.0018142305,0.0019793306,0.0013101789,0.0008940405],"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":[0.00034321213,0.00023858587,0.0032818452,0.00013379358,0.00007305132,0.00019003084,0.0006827492,0.8285273,0.0028214685,0.052452672,0.0015998556,0.109655485],"study_design_scores_gemma":[0.000027862008,0.000035720877,0.00010698267,0.0000067675956,0.000008588428,0.000021956306,0.000025595697,0.9846556,0.00048565105,0.013759384,0.0008600956,0.0000058384403],"about_ca_topic_score_codex":0.012353157,"about_ca_topic_score_gemma":0.01139959,"teacher_disagreement_score":0.012353157,"about_ca_system_score_codex":0.001748906,"about_ca_system_score_gemma":0.001878421,"threshold_uncertainty_score":0.024976373},"labels":[],"label_agreement":null},{"id":"W2885407484","doi":"10.1145/3234200.3234225","title":"Flowtree","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Banting and Best Diabetes Centre, University of Toronto; Bundesministerium für Bildung und Forschung; H2020 European Research Council; Leibniz-Gemeinschaft; Gottfried Wilhelm Leibniz Universität Hannover; Deutsche Forschungsgemeinschaft","keywords":"Computer science","score_opus":0.010163966469509452,"score_gpt":0.24160139074522058,"score_spread":0.23143742427571112,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2885407484","genre_codex":"software","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":[0.012273283,0.0019085004,0.32552722,0.0018944378,0.0010003023,0.00091845123,0.23146641,0.32756376,0.09744768],"genre_scores_gemma":[0.09691993,0.0024300332,0.29969895,0.0018157616,0.00026912548,0.0010529588,0.514954,0.030899577,0.05195978],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99956244,0.000042096526,0.000037624046,0.00015125894,0.00012789597,0.00007865687],"domain_scores_gemma":[0.9990761,0.00024631715,0.000045616354,0.00029273966,0.00025684136,0.000082253406],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007136504,0.0014898877,0.00069046486,0.0025052559,0.0009618307,0.0029283992,0.0018458766,0.0010464032,0.072532676],"category_scores_gemma":[0.0037937043,0.00080959423,0.0012044212,0.0019489189,0.0005236314,0.0046960227,0.0019949605,0.0013937843,0.035447314],"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":[0.0004993885,0.00014224401,0.0022437007,0.00092732545,0.000087051834,0.00017546692,0.00024863717,0.007978348,0.003598331,0.039100856,0.72336304,0.22163574],"study_design_scores_gemma":[0.00015067699,0.000072594485,0.0012929654,0.00025545192,0.000043729022,0.00025329678,0.00017841959,0.050532553,0.0062427525,0.07942178,0.86147696,0.000078854995],"about_ca_topic_score_codex":0.0059943264,"about_ca_topic_score_gemma":0.008244164,"teacher_disagreement_score":0.072532676,"about_ca_system_score_codex":0.0010734976,"about_ca_system_score_gemma":0.0017318223,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W2888965704","doi":"10.14778/3236187.3236194","title":"AIDA","year":2018,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Relational database management system; Software portability; Python (programming language); Relational database; Relational algebra; Programming language; Database; Interpreter","score_opus":0.00852893521103026,"score_gpt":0.21841857042476365,"score_spread":0.20988963521373338,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2888965704","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00747207,0.0024893198,0.2056506,0.007660657,0.0050496613,0.00074673473,0.042618386,0.20260952,0.5257031],"genre_scores_gemma":[0.0705134,0.0032599121,0.21552445,0.007878522,0.001965403,0.0014924802,0.098367825,0.04472743,0.5562706],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99639857,0.000597229,0.00026659484,0.0007886833,0.0014610722,0.000487828],"domain_scores_gemma":[0.99374557,0.0008677373,0.00033279016,0.0021963534,0.0019166265,0.0009409485],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003540876,0.0013170977,0.0010858942,0.00279815,0.0020263223,0.008149847,0.0043229554,0.0021592786,0.3098894],"category_scores_gemma":[0.010562313,0.001018634,0.0016467504,0.0025822327,0.0011098001,0.006514131,0.009118358,0.0027957894,0.27864206],"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":[0.0005312364,0.00015831884,0.0021330304,0.00076399616,0.00007108122,0.00040543906,0.0005305134,0.0012481669,0.004152074,0.072373606,0.67466784,0.24296477],"study_design_scores_gemma":[0.000028436607,0.000025872498,0.0004138921,0.00007755937,0.000018059109,0.0002650226,0.00006736766,0.0014577701,0.0016072784,0.009335069,0.98667836,0.000025305793],"about_ca_topic_score_codex":0.0022739258,"about_ca_topic_score_gemma":0.0021767707,"teacher_disagreement_score":0.3098894,"about_ca_system_score_codex":0.0017455793,"about_ca_system_score_gemma":0.004076868,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W2890833781","doi":"","title":"Simulation Games for Active Learning of ERP Concepts.","year":2018,"lang":"en","type":"article","venue":"Journal of the Association for Information Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Computer science; Active learning (machine learning); Human–computer interaction; Knowledge management; Artificial intelligence","score_opus":0.015347689844053264,"score_gpt":0.2987679515053765,"score_spread":0.2834202616613232,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890833781","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":[0.027506687,0.004218478,0.61971205,0.0036075055,0.0021380205,0.0034176891,0.003832971,0.018044293,0.31752232],"genre_scores_gemma":[0.18029372,0.0049986145,0.6232807,0.0016230035,0.00027519214,0.009865152,0.00471644,0.001664919,0.17328224],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999526,0.00018465589,0.000029160157,0.00006746941,0.00013567893,0.000056968045],"domain_scores_gemma":[0.9989293,0.0006202184,0.000047851183,0.00007412021,0.00011333846,0.00021510813],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00081752107,0.0019111043,0.0005350056,0.0007932913,0.00040655935,0.0019597076,0.0019807187,0.0014784829,0.08628353],"category_scores_gemma":[0.0033783412,0.0004909463,0.00084552454,0.0003930115,0.00053639215,0.001524369,0.0023862487,0.0019443635,0.014130702],"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":[0.0011298025,0.0029798227,0.0015439816,0.0025215987,0.00012077781,0.0006105031,0.001811169,0.03648571,0.019360948,0.12429059,0.21887675,0.59026843],"study_design_scores_gemma":[0.0006458362,0.0010031078,0.0019376784,0.0009377582,0.00008090949,0.0006009791,0.00039903822,0.09108968,0.009180741,0.09289409,0.8011214,0.000108738124],"about_ca_topic_score_codex":0.00068163703,"about_ca_topic_score_gemma":0.0015588076,"teacher_disagreement_score":0.08628353,"about_ca_system_score_codex":0.00065043516,"about_ca_system_score_gemma":0.000967385,"threshold_uncertainty_score":0.28864717},"labels":[],"label_agreement":null},{"id":"W2891253163","doi":"","title":"Chasing Polarized Order Dependencies.","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Lexicographical order; Functional dependency; Dependency (UML); Dependency theory (database theory); Tuple; Computer science; Theoretical computer science; Order (exchange); Data mining; Relational database; Artificial intelligence; Mathematics; Discrete mathematics; Combinatorics","score_opus":0.019429497852234332,"score_gpt":0.2535721010897048,"score_spread":0.23414260323747046,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891253163","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":[0.24976502,0.00048426504,0.7236265,0.001967513,0.00048743683,0.00062001706,0.002695945,0.0019003759,0.018452948],"genre_scores_gemma":[0.7869216,0.0002777153,0.20438258,0.0007563886,0.00020058938,0.0003788699,0.0021624828,0.00036710736,0.004552604],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99220604,0.0019844647,0.00041810016,0.0013082082,0.0032650717,0.000818079],"domain_scores_gemma":[0.9356659,0.044166166,0.0027332455,0.008186312,0.007987134,0.001261141],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0051108063,0.00061751076,0.0008515851,0.0022572728,0.0022609914,0.0024456158,0.0014441988,0.0010881143,0.004730419],"category_scores_gemma":[0.040557824,0.00087070005,0.0012657925,0.0021328998,0.0032354034,0.007822644,0.004745576,0.0038119364,0.0007260532],"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":[0.0017314545,0.0005764661,0.026517292,0.0006943395,0.00021700418,0.0017460106,0.0014181522,0.018746777,0.028610041,0.70424765,0.013270494,0.20222428],"study_design_scores_gemma":[0.00013288828,0.00036814236,0.0034187383,0.00014882213,0.00015945027,0.0012996036,0.000922475,0.1490398,0.061320093,0.7577476,0.02531183,0.00013058858],"about_ca_topic_score_codex":0.0022485564,"about_ca_topic_score_gemma":0.0033521215,"teacher_disagreement_score":0.0051108063,"about_ca_system_score_codex":0.0011951078,"about_ca_system_score_gemma":0.0031890676,"threshold_uncertainty_score":0.027028799},"labels":[],"label_agreement":null},{"id":"W2898297547","doi":"10.1145/3276945.3276951","title":"HorseIR: bringing array programming languages together with database query processing","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Relational database management system; Compiler; SQL; Parallel computing; Database; Programming language; Relational database; Query optimization; Query plan; Bottleneck; Optimizing compiler; Sargable; Information retrieval; Web search query; Search engine","score_opus":0.012042476861580175,"score_gpt":0.26791929147857324,"score_spread":0.2558768146169931,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2898297547","genre_codex":"methods","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016589327,0.00027681186,0.92837787,0.00033603082,0.00013017027,0.00012361234,0.000295053,0.04983134,0.0040398217],"genre_scores_gemma":[0.13976325,0.0004249897,0.8392771,0.00075810566,0.000120593606,0.00024186565,0.0020787066,0.012021869,0.0053134765],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978974,0.00038840374,0.00023886838,0.00048706334,0.0007349284,0.00025327865],"domain_scores_gemma":[0.99756783,0.0008661494,0.00021361861,0.000822754,0.0004193561,0.00011037813],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002231616,0.0010615775,0.00066445617,0.0008457107,0.00049907813,0.002591878,0.0031512834,0.0007924092,0.0031144577],"category_scores_gemma":[0.0043990538,0.00079186755,0.0013870035,0.0010296445,0.0015903626,0.0043864124,0.0027818335,0.0026843024,0.0012498628],"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":[0.0016213215,0.0008115554,0.009007652,0.0012111327,0.00026317514,0.0010224885,0.0022323618,0.09218536,0.09378499,0.15182602,0.054221448,0.5918125],"study_design_scores_gemma":[0.00025187194,0.0008690331,0.0019541671,0.00020262176,0.00025237637,0.0006655706,0.0004608051,0.5583472,0.21478032,0.09358828,0.12838736,0.00024042201],"about_ca_topic_score_codex":0.0018963595,"about_ca_topic_score_gemma":0.0020960923,"teacher_disagreement_score":0.0031512834,"about_ca_system_score_codex":0.0007810255,"about_ca_system_score_gemma":0.0014310934,"threshold_uncertainty_score":0.011802018},"labels":[],"label_agreement":null},{"id":"W2901398849","doi":"10.1109/edoc.2018.00025","title":"Real-Time Data Mining for Event Streams","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Workflow; Computer science; Process mining; Data stream mining; Event (particle physics); STREAMS; Data mining; Process (computing); Computation; Stream processing; Complex event processing; Real-time computing; Database; Distributed computing; Work in process; Business process management; Business process; Algorithm; Programming language; Engineering; Operating system","score_opus":0.04314160231087208,"score_gpt":0.3214480284631908,"score_spread":0.2783064261523187,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901398849","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":[0.039705057,0.0005256403,0.9439186,0.00030667422,0.00007081323,0.00016457222,0.0016918136,0.012778415,0.0008384634],"genre_scores_gemma":[0.36942777,0.0005879878,0.6235205,0.00009994985,0.00006652676,0.00023010062,0.004752785,0.00045676212,0.00085757405],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99743927,0.0004187989,0.0003763016,0.00055531994,0.0010805225,0.00012976865],"domain_scores_gemma":[0.9944332,0.0027414185,0.00062307017,0.00081439747,0.0010809369,0.00030704247],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003563066,0.0012929984,0.000901132,0.0034838861,0.00088692986,0.0022432106,0.0016352782,0.00068905344,0.0014505736],"category_scores_gemma":[0.012876129,0.0003990723,0.0009286551,0.0035188675,0.0005495329,0.00301557,0.0010348817,0.0010381503,0.0009167944],"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":[0.0017771192,0.00060994516,0.03850051,0.0011487729,0.00036559853,0.0015872776,0.0010365638,0.14365493,0.05324243,0.027436791,0.0133844605,0.7172557],"study_design_scores_gemma":[0.00006287448,0.00014084137,0.004406768,0.000048877817,0.000041979445,0.0005218235,0.0002343416,0.9185032,0.03773697,0.030227691,0.008028072,0.000046635447],"about_ca_topic_score_codex":0.002312855,"about_ca_topic_score_gemma":0.0024866231,"teacher_disagreement_score":0.003563066,"about_ca_system_score_codex":0.0007053491,"about_ca_system_score_gemma":0.0011258953,"threshold_uncertainty_score":0.018843472},"labels":[],"label_agreement":null},{"id":"W2904352995","doi":"10.1109/csci.2017.246","title":"Faster Querying for Database Integration and Virtualization with Distributed Semi-Joins","year":2017,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; Kelowna General Hospital; University of British Columbia","funders":"","keywords":"Computer science; Joins; Virtualization; Database; Distributed database; Operating system; Cloud computing; Programming language","score_opus":0.02522666362652493,"score_gpt":0.278368919391713,"score_spread":0.25314225576518806,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2904352995","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":[0.08165462,0.0011679475,0.8802631,0.00053774694,0.00035829013,0.00044852775,0.0005616862,0.027785823,0.0072222482],"genre_scores_gemma":[0.51300746,0.00032687254,0.47747943,0.00048682204,0.00021289047,0.00032875818,0.00237356,0.0014553156,0.004328915],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9916626,0.0016493619,0.0007107021,0.0013393068,0.0041046017,0.00053340395],"domain_scores_gemma":[0.9873963,0.002917719,0.00067792815,0.007155993,0.001321633,0.0005304731],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004487432,0.0010455741,0.0014519659,0.00096040824,0.0013679516,0.0056036874,0.0041851066,0.001159163,0.005789969],"category_scores_gemma":[0.008247042,0.00082032674,0.0011249444,0.0017007362,0.0011207546,0.006753566,0.005511597,0.0026138234,0.002915635],"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":[0.0057191253,0.002758655,0.014038782,0.0010523661,0.00052545016,0.00084333686,0.0020394481,0.028944645,0.27248222,0.067126945,0.038263988,0.5662051],"study_design_scores_gemma":[0.00096436974,0.001781916,0.007843527,0.00009495783,0.0002029892,0.0024839612,0.001045655,0.67828184,0.19402017,0.05332103,0.05971315,0.00024648232],"about_ca_topic_score_codex":0.0013435775,"about_ca_topic_score_gemma":0.0012932719,"teacher_disagreement_score":0.005789969,"about_ca_system_score_codex":0.000906197,"about_ca_system_score_gemma":0.0019632007,"threshold_uncertainty_score":0.023732066},"labels":[],"label_agreement":null},{"id":"W2909564896","doi":"10.14778/3352063.3352120","title":"Guided automated learning for query workload re-optimization","year":2019,"lang":"en","type":"preprint","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University; IBM (Canada); Ontario Tech University","funders":"","keywords":"Computer science; Query optimization; Sargable; Web query classification; Query expansion; Web search query; Query language; SQL; Query plan; Query by Example; Knowledge base; View; SPARQL; Online aggregation; Spatial query; Database; Information retrieval; RDF query language; Data mining; RDF; World Wide Web; Semantic Web; Search engine; Database design","score_opus":0.025071032492887956,"score_gpt":0.2745905191098624,"score_spread":0.24951948661697443,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2909564896","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":[0.060888655,0.0006808876,0.8891649,0.0009525241,0.00011522459,0.0005143054,0.0011826113,0.039802782,0.0066980165],"genre_scores_gemma":[0.38459757,0.0003330941,0.60272235,0.00089746574,0.00008069869,0.00048848614,0.005421785,0.0019080569,0.0035503905],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9970124,0.0007770991,0.00018579412,0.0009084373,0.00083663425,0.00027971284],"domain_scores_gemma":[0.99431723,0.0032043639,0.00027565,0.0011985949,0.0008680216,0.00013610715],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002188574,0.0018740873,0.0011049664,0.0013377927,0.0007155031,0.001853166,0.0031317305,0.0010703584,0.004231282],"category_scores_gemma":[0.012162262,0.0007716123,0.0012859427,0.0012874232,0.0010043235,0.002806869,0.0025869124,0.002703627,0.0015009714],"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":[0.00040504598,0.0008187586,0.0061067916,0.00050008204,0.00014122947,0.0002721044,0.00056614185,0.27552703,0.018884527,0.008675764,0.02764999,0.66045254],"study_design_scores_gemma":[0.000041353225,0.00005801568,0.00041346072,0.000020021405,0.00003158484,0.000033880224,0.0000897405,0.97793853,0.006699469,0.01037872,0.004280543,0.0000147755345],"about_ca_topic_score_codex":0.0076842145,"about_ca_topic_score_gemma":0.015693054,"teacher_disagreement_score":0.0076842145,"about_ca_system_score_codex":0.0020008544,"about_ca_system_score_gemma":0.0032929138,"threshold_uncertainty_score":0.015278935},"labels":[],"label_agreement":null},{"id":"W2909965602","doi":"10.1016/j.is.2019.01.004","title":"Introduction to the Special Issue on Integrating Process-oriented and Event-based Systems","year":2019,"lang":"en","type":"article","venue":"Information Systems","topic":"Advanced Database Systems and Queries","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 Toronto","funders":"","keywords":"Computer science; Process (computing); Event (particle physics); Software engineering; Process management; Data science; Programming language; Engineering","score_opus":0.005499075885879379,"score_gpt":0.2368060791239883,"score_spread":0.2313070032381089,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2909965602","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00026037774,0.07527029,0.025884151,0.03655845,0.83705693,0.00009747875,0.00030882252,0.00048716232,0.024076408],"genre_scores_gemma":[0.0016761415,0.052742664,0.007343385,0.01586143,0.8626463,0.00007159046,0.00061109225,0.0006709014,0.058376614],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99685186,0.0005398731,0.0004589109,0.00056480634,0.0013932821,0.00019125656],"domain_scores_gemma":[0.988361,0.0051561934,0.0005263451,0.00078268547,0.003963487,0.0012103248],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004865669,0.002203822,0.0027205131,0.004702881,0.0012674859,0.009072854,0.00260553,0.0046687266,0.051550347],"category_scores_gemma":[0.010338178,0.0009609167,0.0018823462,0.00473945,0.0017201115,0.0114531405,0.0031606876,0.008562414,0.024356522],"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":[0.000031176623,0.000053124946,0.00011896241,0.0006044568,0.00003490345,0.0000917425,0.000044351546,0.0002691822,0.00047885854,0.006735391,0.9163671,0.075170815],"study_design_scores_gemma":[0.000006993853,0.000035536214,0.00024460946,0.00028890092,0.000022576434,0.00018123203,0.000029127941,0.00047092655,0.00014979167,0.005582837,0.9929684,0.000019132505],"about_ca_topic_score_codex":0.001002918,"about_ca_topic_score_gemma":0.002028501,"teacher_disagreement_score":0.051550347,"about_ca_system_score_codex":0.0013960414,"about_ca_system_score_gemma":0.0017102136,"threshold_uncertainty_score":0.1724531},"labels":[],"label_agreement":null},{"id":"W2911715758","doi":"10.4018/978-1-59904-845-1.ch079","title":"A New Algorithm for Minimizing Tree Pattern Queries","year":2009,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg","funders":"","keywords":"XPath; XQuery; Computer science; Node (physics); XML; Tree (set theory); Theoretical computer science; Algorithm; Combinatorics; XML database; Mathematics; World Wide Web","score_opus":0.019751274423104006,"score_gpt":0.2521853222499345,"score_spread":0.2324340478268305,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2911715758","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":[0.0019255622,0.000227282,0.99225533,0.00026120708,0.00011473602,0.00019649557,0.0003340821,0.0020761185,0.0026091218],"genre_scores_gemma":[0.0147588495,0.00019398512,0.9775317,0.00022976888,0.00008984871,0.00032551086,0.0015369704,0.00065997534,0.0046734815],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9961624,0.00049916765,0.00035509607,0.0012622364,0.0014213158,0.0002997379],"domain_scores_gemma":[0.9976203,0.00090264704,0.00015240611,0.00053142785,0.00068787875,0.000105259096],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023117694,0.0023736784,0.0024636856,0.003449902,0.0013665038,0.004434041,0.005380741,0.0029854535,0.015158595],"category_scores_gemma":[0.008876971,0.0011814563,0.0022830584,0.0054778303,0.0012083718,0.0071758353,0.004083708,0.0031713,0.007722611],"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":[0.0002800298,0.00022964038,0.00080108887,0.00037749912,0.00008625258,0.000094323266,0.00018025145,0.046462953,0.0048686764,0.054326475,0.04241406,0.8498788],"study_design_scores_gemma":[0.00021106192,0.00022887583,0.0003341796,0.00010215392,0.00008713282,0.00042937632,0.00019453767,0.805019,0.0069775,0.14153318,0.044832155,0.000050885625],"about_ca_topic_score_codex":0.0040252684,"about_ca_topic_score_gemma":0.0060918164,"teacher_disagreement_score":0.015158595,"about_ca_system_score_codex":0.0019743058,"about_ca_system_score_gemma":0.0030755524,"threshold_uncertainty_score":0.05071056},"labels":[],"label_agreement":null},{"id":"W2913175468","doi":"","title":"Proceedings of the 23rd Brazilian symposium on Databases","year":2008,"lang":"en","type":"article","venue":"Brazilian Symposium on Databases","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Computer science; Database; Presentation (obstetrics); Latin Americans; Library science; World Wide Web; Political science; Geography","score_opus":0.025971609493490564,"score_gpt":0.259488498731684,"score_spread":0.23351688923819344,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2913175468","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0065170466,0.22860412,0.10386843,0.04863131,0.08629588,0.0012274263,0.013941383,0.0062442673,0.5046701],"genre_scores_gemma":[0.042736683,0.12772404,0.09946937,0.011455017,0.024342211,0.00080123596,0.03010294,0.003604544,0.659764],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99420184,0.0012718701,0.0008201405,0.00084477366,0.0024731096,0.00038825578],"domain_scores_gemma":[0.99193317,0.0013143151,0.00031619283,0.0017084894,0.0037037737,0.0010241433],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0059218467,0.0012762989,0.002202962,0.003627789,0.001738756,0.0105737755,0.0026282694,0.002280479,0.10755782],"category_scores_gemma":[0.01051654,0.000760025,0.0018190987,0.0040127835,0.0013101221,0.006617546,0.0044489307,0.0040263315,0.06425944],"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":[0.00014770842,0.00008846963,0.0011023604,0.0007848435,0.00009831586,0.00020582088,0.0003945282,0.0003624594,0.0026469028,0.032018945,0.7097315,0.25241804],"study_design_scores_gemma":[0.0000047579074,0.000014304199,0.0002529864,0.0001492795,0.00001372373,0.00012914852,0.000060534672,0.00025221915,0.00024956214,0.0022920358,0.9965731,0.000008286304],"about_ca_topic_score_codex":0.0060133664,"about_ca_topic_score_gemma":0.0051019792,"teacher_disagreement_score":0.10755782,"about_ca_system_score_codex":0.002656246,"about_ca_system_score_gemma":0.0049218494,"threshold_uncertainty_score":0.35981673},"labels":[],"label_agreement":null},{"id":"W2913546079","doi":"","title":"Proceedings of the Fourteenth International Database Engineering & Applications Symposium","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Concordia University","funders":"","keywords":"Government (linguistics); China; Work (physics); Database; Library science; Political science; Computer science; Engineering; Law","score_opus":0.004212166784780038,"score_gpt":0.20594507760260428,"score_spread":0.20173291081782424,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2913546079","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013779691,0.199343,0.1818413,0.09875019,0.17567223,0.0022273092,0.013137466,0.01265195,0.3025969],"genre_scores_gemma":[0.05808498,0.119506165,0.119531855,0.022649108,0.05633632,0.0015846781,0.053268716,0.0028995813,0.5661386],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99045664,0.0023476062,0.0012069924,0.0012160119,0.0042074188,0.0005653144],"domain_scores_gemma":[0.98465574,0.00312929,0.0005643306,0.002158752,0.0071043014,0.0023875707],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0104198335,0.0014702232,0.0023444202,0.0025658181,0.0015664846,0.009810683,0.0028022246,0.0026863855,0.08867497],"category_scores_gemma":[0.014096804,0.0006687243,0.0016246607,0.0021532737,0.001180639,0.007915353,0.0041875415,0.0047338856,0.058471378],"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":[0.00019673973,0.00017480497,0.00089049625,0.0006682605,0.00011756562,0.00018853162,0.00020522063,0.000255679,0.0022238398,0.009075563,0.7897171,0.19628622],"study_design_scores_gemma":[0.0000214804,0.00005694794,0.0006891184,0.0002554633,0.00004048467,0.00025544188,0.000104797946,0.0009213078,0.0007078501,0.0043594,0.992564,0.000023725264],"about_ca_topic_score_codex":0.0014166232,"about_ca_topic_score_gemma":0.0018633442,"teacher_disagreement_score":0.08867497,"about_ca_system_score_codex":0.0016093801,"about_ca_system_score_gemma":0.0043192687,"threshold_uncertainty_score":0.2966473},"labels":[],"label_agreement":null},{"id":"W2917127201","doi":"","title":"LogiQL and SQL","year":2015,"lang":"en","type":"book-chapter","venue":"Taylor & Francis Group eBooks","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Table (database); SQL; Relational database; Data definition language; Population; Computer science; Stored procedure; Key (lock); Null (SQL); Database; World Wide Web; Query by Example; Computer security; Sociology; Demography","score_opus":0.032028998254507994,"score_gpt":0.23611206060828274,"score_spread":0.20408306235377474,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2917127201","genre_codex":"methods","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":[0.0009833607,0.0023417484,0.7576236,0.0032486466,0.0006291311,0.001498103,0.029477155,0.11105591,0.093142286],"genre_scores_gemma":[0.02299275,0.008000982,0.75262773,0.0062702578,0.0011015907,0.0044307485,0.08506844,0.037901055,0.08160648],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9926916,0.0020388286,0.0011942241,0.00076171145,0.0028996505,0.00041400324],"domain_scores_gemma":[0.9915235,0.004610816,0.00037019528,0.001533251,0.0016804958,0.00028167188],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0064902618,0.0018137643,0.0012466,0.004274024,0.0010434426,0.009548534,0.0045541204,0.0014715189,0.09626322],"category_scores_gemma":[0.020173822,0.0013873951,0.001483065,0.0062786667,0.0013785168,0.011987003,0.0049808277,0.0045897923,0.07653321],"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":[0.00013692319,0.00011562131,0.00032623298,0.001673548,0.000023382747,0.0003472792,0.0005813251,0.0020506752,0.0014155761,0.20676412,0.5201045,0.26646078],"study_design_scores_gemma":[0.000041442858,0.00002339205,0.00018253773,0.0004995644,0.000008933233,0.00050563295,0.00016918308,0.0069596516,0.0015268959,0.07415666,0.9158683,0.00005773984],"about_ca_topic_score_codex":0.0029358505,"about_ca_topic_score_gemma":0.0014756283,"teacher_disagreement_score":0.09626322,"about_ca_system_score_codex":0.0023162917,"about_ca_system_score_gemma":0.003732075,"threshold_uncertainty_score":0.32203257},"labels":[],"label_agreement":null},{"id":"W2918321134","doi":"10.1007/978-3-319-77525-8_193","title":"Types of Stream Processing Algorithms","year":2019,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Big Data Technologies","topic":"Advanced Database Systems and Queries","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; Algorithm","score_opus":0.05150077375148996,"score_gpt":0.2637461768801143,"score_spread":0.21224540312862436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2918321134","genre_codex":"methods","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":[0.0024960274,0.013486892,0.8136028,0.0026987486,0.004977674,0.00058208784,0.0038981577,0.0056515946,0.15260601],"genre_scores_gemma":[0.042680603,0.02622514,0.69830203,0.0025376938,0.00812246,0.0010750961,0.012727238,0.003659135,0.20467052],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9977969,0.00024591145,0.0002785006,0.00050376233,0.0010278549,0.00014719431],"domain_scores_gemma":[0.9968929,0.00089822616,0.0001423025,0.0011289452,0.0008055291,0.00013210611],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016158165,0.0019100386,0.001208152,0.004539953,0.0011173269,0.006324389,0.0029646028,0.0021262954,0.04847937],"category_scores_gemma":[0.0070101223,0.00094277225,0.0023085568,0.00629611,0.0013229626,0.007390806,0.0022348196,0.0037153456,0.033284612],"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":[0.00017192731,0.00010786969,0.0003778104,0.00083255576,0.000054943335,0.0001397824,0.00010306082,0.0039380104,0.0019603416,0.45338833,0.11472154,0.42420375],"study_design_scores_gemma":[0.000053207597,0.0000691974,0.0003944823,0.00026763952,0.00005588054,0.00096459035,0.000045561632,0.027712854,0.0060748267,0.48548013,0.47882137,0.0000602525],"about_ca_topic_score_codex":0.0005488877,"about_ca_topic_score_gemma":0.0004856935,"teacher_disagreement_score":0.04847937,"about_ca_system_score_codex":0.0010462701,"about_ca_system_score_gemma":0.0013403223,"threshold_uncertainty_score":0.16217965},"labels":[],"label_agreement":null},{"id":"W2919943383","doi":"10.1007/978-0-387-39940-9_1302","title":"Uncertainty Management in Scientific Database Systems","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Database; Computer science; Data science","score_opus":0.017834447547742376,"score_gpt":0.24593657183652134,"score_spread":0.22810212428877896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2919943383","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":[0.007630922,0.07832519,0.8570441,0.006982892,0.0011267558,0.00011283694,0.00035126403,0.00064297917,0.04778309],"genre_scores_gemma":[0.4891858,0.09186845,0.34645098,0.0020089222,0.0074381507,0.00042310913,0.0014372573,0.00041575488,0.060771573],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9971169,0.0008596229,0.00021400808,0.00023191485,0.0014577955,0.00011977446],"domain_scores_gemma":[0.9955948,0.0031076348,0.00019476742,0.00047603727,0.00053381315,0.00009293016],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003097078,0.00056930527,0.0010677502,0.00112424,0.00083494344,0.0050657294,0.0016258423,0.001418849,0.0051188553],"category_scores_gemma":[0.0103444,0.00056793843,0.0006130747,0.0027702502,0.0015661996,0.0053094397,0.0017449154,0.0025024393,0.0014399731],"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":[0.000068936795,0.00006141842,0.00064638053,0.00055616954,0.00007500924,0.00021670641,0.00045574392,0.05349592,0.0010919408,0.5751488,0.0327859,0.33539703],"study_design_scores_gemma":[0.000011458451,0.00003045974,0.00030971487,0.00013913822,0.000027576825,0.00018225318,0.000103152124,0.118736595,0.00086019194,0.8131466,0.06642091,0.000032080963],"about_ca_topic_score_codex":0.0015998688,"about_ca_topic_score_gemma":0.0010075604,"teacher_disagreement_score":0.0051188553,"about_ca_system_score_codex":0.0013684364,"about_ca_system_score_gemma":0.001370007,"threshold_uncertainty_score":0.017124236},"labels":[],"label_agreement":null},{"id":"W2919957200","doi":"10.1007/978-0-387-39940-9_948","title":"Similarity and Ranking Operations","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Similarity (geometry); Ranking (information retrieval); Computer science; Artificial intelligence; Information retrieval; Pattern recognition (psychology); Image (mathematics)","score_opus":0.015273744867144126,"score_gpt":0.23762790827924443,"score_spread":0.2223541634121003,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2919957200","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":[0.010161056,0.024645632,0.7979047,0.0020076933,0.0021229242,0.00030681433,0.0015374762,0.0035958476,0.15771785],"genre_scores_gemma":[0.15185861,0.0208817,0.6176841,0.0013326441,0.0033484173,0.0004296377,0.006714015,0.0016550818,0.19609578],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99657506,0.00052475254,0.0003602802,0.0008930791,0.0014713632,0.0001753874],"domain_scores_gemma":[0.99820304,0.0004980093,0.0001243751,0.0006973456,0.00038847266,0.0000887748],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013260968,0.0011518241,0.0020459606,0.0046532457,0.0015119439,0.006002887,0.0022717523,0.0013748766,0.021323854],"category_scores_gemma":[0.0058256183,0.0005734726,0.0015003241,0.009737143,0.002505666,0.010647431,0.002572797,0.0024652749,0.014926394],"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":[0.000052996995,0.00007918391,0.00025513972,0.0003614838,0.000040659248,0.00008131466,0.00021694973,0.0017078208,0.0020545982,0.5324717,0.0397099,0.42296818],"study_design_scores_gemma":[0.00001618108,0.00009228767,0.0006556442,0.00011888401,0.000059142058,0.0012820398,0.00014336688,0.014944247,0.00482816,0.7431042,0.23469387,0.00006194383],"about_ca_topic_score_codex":0.0011760361,"about_ca_topic_score_gemma":0.0012975043,"teacher_disagreement_score":0.021323854,"about_ca_system_score_codex":0.0013287351,"about_ca_system_score_gemma":0.0011421117,"threshold_uncertainty_score":0.071335435},"labels":[],"label_agreement":null},{"id":"W2923407516","doi":"10.1145/3299869.3319861","title":"Designing Succinct Secondary Indexing Mechanism by Exploiting Column Correlations","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":50,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada)","funders":"","keywords":"Computer science; Search engine indexing; Overhead (engineering); Exploit; Online analytical processing; Outlier; Column (typography); Key (lock); Data mining; Access method; Data structure; Database; Information retrieval; Data warehouse; Computer network; Artificial intelligence","score_opus":0.00951753844807349,"score_gpt":0.2141737136724857,"score_spread":0.2046561752244122,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2923407516","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":[0.04966715,0.00059831305,0.9314129,0.00027816815,0.000103592945,0.00024302254,0.0010115458,0.014843646,0.001841741],"genre_scores_gemma":[0.3628564,0.0004842396,0.6281764,0.00034768207,0.00016302154,0.00030213714,0.0038423147,0.0010926592,0.0027352024],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99671125,0.0004129523,0.00045149255,0.00052997307,0.0015883355,0.0003059342],"domain_scores_gemma":[0.98932683,0.0018529021,0.0013795703,0.004162854,0.0028425516,0.00043530978],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024795942,0.0011470988,0.001423616,0.002832868,0.00094086863,0.0029828062,0.0029701965,0.00070649915,0.0030040487],"category_scores_gemma":[0.012064277,0.0008367881,0.00082165125,0.004762108,0.0010872284,0.006700736,0.0037176197,0.0014053074,0.0021156792],"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":[0.0017899636,0.00073770335,0.025887847,0.0007210317,0.00024734368,0.0007340232,0.0012604769,0.06241489,0.1698736,0.049095254,0.028657496,0.6585804],"study_design_scores_gemma":[0.00015603613,0.0008388713,0.0034528729,0.00007878996,0.00014870681,0.0010504738,0.00029784988,0.7878232,0.16013303,0.018279707,0.02754532,0.00019513578],"about_ca_topic_score_codex":0.0020405983,"about_ca_topic_score_gemma":0.0025090422,"teacher_disagreement_score":0.0030040487,"about_ca_system_score_codex":0.00093914144,"about_ca_system_score_gemma":0.0028728123,"threshold_uncertainty_score":0.013113499},"labels":[],"label_agreement":null},{"id":"W2934771417","doi":"10.5441/002/edbt.2019.26","title":"A Six-dimensional Analysis of In-memory Aggregation","year":2019,"lang":"en","type":"article","venue":"Movebank","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 New Brunswick","funders":"","keywords":"Computer science","score_opus":0.008031022054361662,"score_gpt":0.23317061521194016,"score_spread":0.2251395931575785,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2934771417","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":[0.31774664,0.0031104528,0.6397117,0.002252963,0.00048690898,0.00013703089,0.0023381107,0.0033659432,0.03085032],"genre_scores_gemma":[0.8703443,0.000971971,0.11478115,0.00024381789,0.00038317428,0.00012908959,0.0017649548,0.00039972004,0.010981891],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982343,0.00039475295,0.000099874254,0.00017548566,0.0007940319,0.00030155905],"domain_scores_gemma":[0.9957093,0.0015482964,0.00033154432,0.0010480054,0.0011248669,0.00023800413],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016436935,0.00073383155,0.00081703346,0.0025640079,0.0012914274,0.0037005926,0.0013116003,0.00057463336,0.008549834],"category_scores_gemma":[0.009414635,0.00030741817,0.0007673205,0.0033080915,0.00082955364,0.0035676584,0.0017572523,0.0015372026,0.0011937523],"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":[0.0011415387,0.0006628597,0.016080808,0.00028193896,0.00016484295,0.00050117227,0.00092258136,0.13280235,0.013973423,0.58235145,0.03218118,0.21893586],"study_design_scores_gemma":[0.00001702148,0.000071177485,0.004400935,0.000019531051,0.00004408347,0.00017295247,0.00021870226,0.8979283,0.0052832756,0.08511417,0.0066905757,0.000039239734],"about_ca_topic_score_codex":0.0028821526,"about_ca_topic_score_gemma":0.0016816877,"teacher_disagreement_score":0.008549834,"about_ca_system_score_codex":0.0011621735,"about_ca_system_score_gemma":0.0008263269,"threshold_uncertainty_score":0.028602064},"labels":[],"label_agreement":null},{"id":"W2941208251","doi":"10.1109/ispass.2019.00037","title":"An Improved Dynamic Vertical Partitioning Technique for Semi-Structured Data","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"JSON; Computer science; Database; Cache; Relational database; Heuristics; Workload; Data structure; Semi-structured data; Data mining; Tree traversal; Operating system; Algorithm","score_opus":0.015928630753779753,"score_gpt":0.29615741908141674,"score_spread":0.280228788327637,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2941208251","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":[0.052656878,0.0008644951,0.9342873,0.0002860031,0.00020228946,0.00022000592,0.0012447959,0.0070173154,0.003220803],"genre_scores_gemma":[0.21231201,0.00034977912,0.775066,0.0002243369,0.00007016669,0.00022418592,0.0057102,0.00113703,0.0049062436],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989355,0.000104008235,0.00012856857,0.00024315149,0.00044259836,0.00014603113],"domain_scores_gemma":[0.99848145,0.0002794553,0.00010996248,0.00059634406,0.00045739335,0.00007529675],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006552191,0.00075345766,0.0005557961,0.0017769684,0.0009239963,0.0012436575,0.0018431917,0.0005337282,0.0025575892],"category_scores_gemma":[0.0026752697,0.00047880545,0.00077985344,0.0024610653,0.00047623052,0.0023354616,0.001923223,0.00081103697,0.0012444977],"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":[0.00055539893,0.0002866425,0.005140972,0.0003664263,0.000093363386,0.00029093967,0.0010758708,0.039905038,0.12397709,0.015722198,0.027694674,0.7848914],"study_design_scores_gemma":[0.00022248564,0.0003973582,0.004683699,0.00011280379,0.00009963694,0.0011032403,0.00084236136,0.74913645,0.13174115,0.024235854,0.087285966,0.00013901421],"about_ca_topic_score_codex":0.005765782,"about_ca_topic_score_gemma":0.00959471,"teacher_disagreement_score":0.005765782,"about_ca_system_score_codex":0.0006238915,"about_ca_system_score_gemma":0.0012093921,"threshold_uncertainty_score":0.011464477},"labels":[],"label_agreement":null},{"id":"W2948074875","doi":"10.1109/cybermatics_2018.2018.00064","title":"MCEP: A Mobile Device Based Complex Event Processing System for Remote Healthcare","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Telus (Canada); Carleton University","funders":"","keywords":"Computer science; Health care; Event (particle physics); Complex event processing; Embedded system; Real-time computing; Operating system; Process (computing)","score_opus":0.048629806932160645,"score_gpt":0.33850390458339247,"score_spread":0.28987409765123184,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2948074875","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":[0.11822263,0.0031060555,0.7937078,0.0020989953,0.0009666835,0.002462316,0.0031669936,0.051265296,0.02500316],"genre_scores_gemma":[0.7327037,0.0012478925,0.24410918,0.0018563458,0.00046944345,0.00096986024,0.0033402774,0.00053973874,0.014763503],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995034,0.000066171895,0.000050135146,0.00011023891,0.00021696805,0.00005307572],"domain_scores_gemma":[0.99948514,0.00016746909,0.000042279866,0.00009686268,0.00013246531,0.00007573054],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039830286,0.00063985336,0.0006686963,0.0005295002,0.00029360366,0.0008785797,0.0016421049,0.0007157701,0.0077055143],"category_scores_gemma":[0.0015580597,0.00023718459,0.00024434834,0.00039216495,0.00019462171,0.0009133292,0.0011064411,0.00076858036,0.0020291053],"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":[0.0043374314,0.0010039785,0.007951594,0.0013598956,0.00027964875,0.0030264058,0.00055036414,0.018648248,0.15053014,0.015058602,0.099608935,0.69764477],"study_design_scores_gemma":[0.0009381592,0.0031416486,0.01718935,0.00025618693,0.00030404443,0.0062504117,0.00028108497,0.5927809,0.13040373,0.008292652,0.2398674,0.00029451077],"about_ca_topic_score_codex":0.00078191014,"about_ca_topic_score_gemma":0.0006264855,"teacher_disagreement_score":0.0077055143,"about_ca_system_score_codex":0.00025578393,"about_ca_system_score_gemma":0.00048096201,"threshold_uncertainty_score":0.025777519},"labels":[],"label_agreement":null},{"id":"W2949310134","doi":"10.1145/3328905.3332511","title":"Generating Reproducible Out-of-Order Data Streams","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Banting and Best Diabetes Centre, University of Toronto; Deutsche Forschungsgemeinschaft","keywords":"Tuple; Data stream mining; Computer science; STREAMS; Data stream; Generator (circuit theory); Stream processing; Data mining; Distributed computing; Mathematics; Computer network","score_opus":0.049356005342875924,"score_gpt":0.29804363025275454,"score_spread":0.2486876249098786,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2949310134","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":[0.29201555,0.00011909008,0.6948187,0.00019171386,0.00016393684,0.0006036564,0.0019998297,0.008793663,0.0012938385],"genre_scores_gemma":[0.7892317,0.00016551075,0.2050787,0.00009614932,0.000045385597,0.00063778536,0.002823331,0.0008451338,0.0010762931],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971608,0.00068283547,0.00025043715,0.00050469366,0.0012345249,0.00016676587],"domain_scores_gemma":[0.9847349,0.009467455,0.00079320016,0.0026484663,0.0020448288,0.0003111568],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032465484,0.0008111127,0.00068834465,0.0006707646,0.00029971518,0.0010407611,0.0016679268,0.0008449535,0.0013755634],"category_scores_gemma":[0.021877807,0.0004346794,0.0007013675,0.00079197704,0.00067948824,0.0011743652,0.0010021133,0.0010235967,0.00038153643],"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":[0.0015828965,0.00065738853,0.0211903,0.00046569834,0.0002721731,0.00094713253,0.0006144897,0.8031042,0.06706675,0.016691765,0.004324463,0.08308274],"study_design_scores_gemma":[0.00009470753,0.00016337408,0.00097163115,0.000010317803,0.000020216597,0.00012045552,0.00003139281,0.93889016,0.052243225,0.0062273024,0.0012007853,0.0000265317],"about_ca_topic_score_codex":0.0011003326,"about_ca_topic_score_gemma":0.0007185962,"teacher_disagreement_score":0.0032465484,"about_ca_system_score_codex":0.0006651918,"about_ca_system_score_gemma":0.0014415687,"threshold_uncertainty_score":0.017169595},"labels":[],"label_agreement":null},{"id":"W29501390","doi":"10.1007/978-3-642-16321-0_42","title":"Erratum to: Range Queries over Untangled Chains","year":2010,"lang":"en","type":"erratum","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Computer science; Range (aeronautics); Theoretical computer science; Information retrieval; Aerospace engineering; Engineering","score_opus":0.010543215280759622,"score_gpt":0.2600395636072869,"score_spread":0.24949634832652728,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W29501390","genre_codex":"editorial","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":[0.0014634265,0.0019133026,0.013405312,0.090513445,0.8716402,0.000091282294,0.002895332,0.0018356375,0.016242146],"genre_scores_gemma":[0.07846139,0.012937297,0.07140227,0.12683484,0.20078665,0.0004411559,0.01897079,0.0066937455,0.4834719],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99447745,0.0007747232,0.0008087761,0.00065976434,0.0029181505,0.00036118965],"domain_scores_gemma":[0.979924,0.0062558977,0.0008653135,0.0022137654,0.010063947,0.0006771096],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00283832,0.0022884596,0.0022399877,0.0030142372,0.003971804,0.0034134178,0.0028935736,0.005750797,0.07567743],"category_scores_gemma":[0.041038096,0.0012187446,0.0012669493,0.004301738,0.0022394827,0.0040159747,0.0022011371,0.0056280363,0.0302642],"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":[0.00013496623,0.00001905104,0.000102647915,0.00014126087,0.000015924055,0.00033459335,0.00003782355,0.0001898304,0.00025224968,0.0037987686,0.98402935,0.010943522],"study_design_scores_gemma":[0.00014336673,0.00011531877,0.00090387807,0.0003548831,0.00010333598,0.0015813556,0.00027227224,0.0031860443,0.0025755009,0.014823041,0.9758236,0.000117399366],"about_ca_topic_score_codex":0.006864539,"about_ca_topic_score_gemma":0.008857928,"teacher_disagreement_score":0.07567743,"about_ca_system_score_codex":0.0031830145,"about_ca_system_score_gemma":0.0029083109,"threshold_uncertainty_score":0.2531662},"labels":[],"label_agreement":null},{"id":"W2951321531","doi":"10.1145/342009.335419","title":"Efficient and extensible algorithms for multi query optimization","year":2000,"lang":"en","type":"preprint","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":226,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bell (Canada)","funders":"","keywords":"Query optimization; Computer science; Sargable; Extensibility; Web search query; Spatial query; Query language; Query expansion; Theoretical computer science; Optimization algorithm; Data mining; Web query classification; Algorithm; Information retrieval; Mathematical optimization; Search engine; Programming language; Mathematics","score_opus":0.04846750926809731,"score_gpt":0.3039473019634545,"score_spread":0.2554797926953572,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951321531","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":[0.0015860586,0.000781108,0.9914655,0.00019493984,0.00007073179,0.00012867496,0.0001512414,0.003493761,0.0021279503],"genre_scores_gemma":[0.04411578,0.00094972824,0.94942546,0.00027947238,0.00021790629,0.0004711824,0.00085529644,0.0009511703,0.0027338923],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9922023,0.0017418232,0.0008593425,0.0013784107,0.0031932453,0.000624965],"domain_scores_gemma":[0.99035305,0.0053863297,0.00047964838,0.0024753038,0.0011237595,0.00018184951],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005735974,0.0033783491,0.002555008,0.0029691095,0.001202984,0.0035644206,0.0061268653,0.0027770174,0.009051696],"category_scores_gemma":[0.020722676,0.001502114,0.0026303453,0.00528582,0.0019073352,0.006994413,0.0060990104,0.0062120953,0.005853545],"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":[0.00034677054,0.00045243287,0.0011381842,0.0005569362,0.00016329419,0.00018198551,0.00032961337,0.2066416,0.0042409673,0.10804107,0.025147157,0.65275997],"study_design_scores_gemma":[0.00014242146,0.0000875707,0.00021951408,0.00006280578,0.000056267923,0.0001843693,0.000079371755,0.8107862,0.0027266096,0.17142667,0.014183539,0.000044688404],"about_ca_topic_score_codex":0.003772647,"about_ca_topic_score_gemma":0.0047434005,"teacher_disagreement_score":0.009051696,"about_ca_system_score_codex":0.0017993716,"about_ca_system_score_gemma":0.002235399,"threshold_uncertainty_score":0.030335128},"labels":[],"label_agreement":null},{"id":"W2952776792","doi":"10.48550/arxiv.1208.0084","title":"Fundamentals of Order Dependencies","year":2012,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Lexicographical order; Functional dependency; Axiom; Tuple; Dependency theory (database theory); Computer science; Inference; Dependency (UML); Set (abstract data type); Query optimization; Theoretical computer science; Order (exchange); Rule of inference; Mathematics; Data mining; Discrete mathematics; Relational database; Artificial intelligence; Programming language; Combinatorics","score_opus":0.08898652615790204,"score_gpt":0.19788608524073503,"score_spread":0.108899559082833,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2952776792","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":[0.010980099,0.0076931086,0.88065684,0.005863913,0.0013040184,0.00025025132,0.0025512823,0.0010651593,0.089635335],"genre_scores_gemma":[0.30539703,0.016884066,0.6292729,0.004772836,0.0040767216,0.0010643697,0.003911382,0.0009817409,0.033638928],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9938584,0.0012989127,0.0008097386,0.0013967918,0.002116248,0.0005198359],"domain_scores_gemma":[0.989894,0.005880303,0.0005943284,0.0016537518,0.001736636,0.00024106722],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0050113327,0.0013109441,0.0010435022,0.003436585,0.003139299,0.004769359,0.0025243955,0.0024516012,0.009605069],"category_scores_gemma":[0.01150713,0.0014318172,0.0025422464,0.0042921677,0.008194344,0.013215937,0.0041409507,0.0060853646,0.0036924302],"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":[0.00001318822,0.000013865705,0.00020683075,0.00010733677,0.000011096849,0.00010089936,0.00023027408,0.0011892932,0.00042304452,0.98083454,0.0035219302,0.013347606],"study_design_scores_gemma":[0.000012650667,0.000014736205,0.00014069118,0.00005435344,0.000017457967,0.00024390602,0.000050706287,0.0029782902,0.00075116806,0.9292862,0.066427566,0.00002219372],"about_ca_topic_score_codex":0.006258833,"about_ca_topic_score_gemma":0.003521109,"teacher_disagreement_score":0.009605069,"about_ca_system_score_codex":0.003007604,"about_ca_system_score_gemma":0.002898157,"threshold_uncertainty_score":0.03213221},"labels":[],"label_agreement":null},{"id":"W2953181121","doi":"10.1145/3140587.3062348","title":"HoTTSQL: proving query rewrites with univalent SQL semantics","year":2017,"lang":"en","type":"article","venue":"ACM SIGPLAN Notices","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Defense Advanced Research Projects Agency; Alberta Innovates - Technology Futures; U.S. Department of Energy; National Science Foundation","keywords":"Computer science; SQL; Query optimization; Programming language; Query language; Conjunctive query; Query by Example; Sargable; Spatial query; Undecidable problem; Tuple; Null (SQL); Database; Theoretical computer science; Decidability; Relational database; Information retrieval; Web search query; Mathematics; Discrete mathematics","score_opus":0.025995750750134834,"score_gpt":0.26836799185769167,"score_spread":0.24237224110755684,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2953181121","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":[0.015869915,0.00017361491,0.96861935,0.00065236894,0.00013635785,0.0001757888,0.0006925925,0.0108924,0.0027875435],"genre_scores_gemma":[0.40247914,0.00047578264,0.5827797,0.0021044582,0.00045043146,0.0004763247,0.0036113488,0.0038422083,0.00378061],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98152614,0.0042418023,0.0019487395,0.002581471,0.007929556,0.0017722675],"domain_scores_gemma":[0.95953095,0.02600263,0.0018864196,0.006946812,0.005128226,0.0005049972],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009966806,0.0014973127,0.001394484,0.0020979973,0.0018740783,0.006338528,0.0053001675,0.0021876143,0.0066446685],"category_scores_gemma":[0.040175386,0.0019903139,0.005073568,0.0014844708,0.00589394,0.011226159,0.007248421,0.005280179,0.0014514087],"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":[0.0005283144,0.0005880921,0.011278648,0.0016154166,0.00062908407,0.0018267733,0.0023597977,0.08672984,0.034417734,0.7038888,0.02181356,0.13432392],"study_design_scores_gemma":[0.0002660011,0.0002702359,0.0015608361,0.00023524583,0.0004147802,0.0007677229,0.00069054816,0.45550725,0.08311863,0.4349579,0.022016725,0.0001941127],"about_ca_topic_score_codex":0.010397191,"about_ca_topic_score_gemma":0.008623196,"teacher_disagreement_score":0.010397191,"about_ca_system_score_codex":0.00287519,"about_ca_system_score_gemma":0.0059835194,"threshold_uncertainty_score":0.052710116},"labels":[],"label_agreement":null},{"id":"W2955898947","doi":"10.1145/3331184.3331395","title":"Information Retrieval Meets Scalable Text Analytics","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"SPARK (programming language); Scalability; Computer science; Analytics; Downstream (manufacturing); Pipeline transport; Range (aeronautics); Data science; Database; Programming language; Engineering","score_opus":0.008595608315333266,"score_gpt":0.22523293204248337,"score_spread":0.2166373237271501,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2955898947","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":[0.03692512,0.005466299,0.79768,0.025548577,0.0011558329,0.0012588948,0.014025035,0.049017597,0.06892262],"genre_scores_gemma":[0.3258457,0.00253514,0.62835443,0.002813006,0.0019665796,0.0009350695,0.020761458,0.0032025385,0.013586063],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.97675556,0.0049742153,0.002101403,0.004087281,0.010621829,0.0014597934],"domain_scores_gemma":[0.966705,0.01192175,0.0016602371,0.011344342,0.0070982073,0.0012704326],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00987419,0.0018057921,0.0023482018,0.0036645336,0.0018744986,0.010497582,0.003784814,0.003044633,0.0135353515],"category_scores_gemma":[0.05323259,0.0011878846,0.0015662988,0.007256145,0.0019959821,0.017800272,0.008170595,0.0032125989,0.020423086],"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":[0.0014667388,0.00067173684,0.0057444586,0.002299693,0.00037083265,0.0013126775,0.00092521665,0.0443364,0.027250094,0.15488063,0.29470578,0.46603578],"study_design_scores_gemma":[0.00033400557,0.00018277751,0.0016887961,0.0001465864,0.00010570161,0.0012490569,0.0008437259,0.41782585,0.019024264,0.44592604,0.11255073,0.00012249037],"about_ca_topic_score_codex":0.004040479,"about_ca_topic_score_gemma":0.0044890945,"teacher_disagreement_score":0.0135353515,"about_ca_system_score_codex":0.0016621083,"about_ca_system_score_gemma":0.004198554,"threshold_uncertainty_score":0.052220345},"labels":[],"label_agreement":null},{"id":"W2962712636","doi":"10.1109/iisa.2014.6878811","title":"Three-way joins on MapReduce: An experimental study","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Joins; Computer science; Join (topology); Traverse; Theoretical computer science; Programming paradigm; Node (physics); Computation; Data mining; Distributed computing; Parallel computing; Database; Algorithm; Programming language","score_opus":0.030378302954945074,"score_gpt":0.2955546399320789,"score_spread":0.26517633697713383,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2962712636","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":[0.92491335,0.0019044081,0.03528974,0.0010929621,0.0005821867,0.0012147033,0.005037332,0.0064473236,0.02351795],"genre_scores_gemma":[0.9061601,0.0010122943,0.07676724,0.00036545107,0.00017790172,0.0006192273,0.009519202,0.0006742842,0.004704168],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.98997635,0.0027488838,0.00074119243,0.0012841548,0.0043189996,0.00093044766],"domain_scores_gemma":[0.97246575,0.014175925,0.0012462531,0.006032242,0.0047357325,0.0013442017],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005905988,0.0015052238,0.0012007774,0.0012267658,0.001841197,0.0017301325,0.0026237122,0.0012330267,0.0037098497],"category_scores_gemma":[0.016709717,0.0004281862,0.00091094914,0.0028104458,0.0012578892,0.0032928665,0.0017326411,0.0013560317,0.0013688488],"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":[0.017895237,0.04583953,0.040127803,0.0063587436,0.001504704,0.0028540436,0.0034294785,0.166904,0.11517032,0.018069249,0.10633875,0.4755082],"study_design_scores_gemma":[0.004481253,0.026676202,0.054505225,0.00036841226,0.0008035357,0.0035802175,0.006737672,0.5857997,0.19976646,0.027439253,0.08932298,0.0005191305],"about_ca_topic_score_codex":0.004517579,"about_ca_topic_score_gemma":0.0037265935,"teacher_disagreement_score":0.005905988,"about_ca_system_score_codex":0.00093118515,"about_ca_system_score_gemma":0.0013784604,"threshold_uncertainty_score":0.031234205},"labels":[],"label_agreement":null},{"id":"W2964009285","doi":"","title":"InfoBot: Transfer and Exploration via the Information Bottleneck","year":2019,"lang":"en","type":"article","venue":"arXiv (Cornell University)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":35,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Université de Montréal","funders":"","keywords":"Bottleneck; Computer science; Embedded system","score_opus":0.0304719211964464,"score_gpt":0.15202580265193347,"score_spread":0.12155388145548707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2964009285","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":[0.0724465,0.0015918389,0.88303405,0.0026316666,0.00041669502,0.00017264513,0.0011225911,0.02700755,0.011576396],"genre_scores_gemma":[0.70558256,0.0006635585,0.27609366,0.00065747724,0.00030579453,0.00042929547,0.0019297241,0.0037228775,0.010615114],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99722916,0.0011917957,0.00013176649,0.0005420002,0.00057495135,0.00033037277],"domain_scores_gemma":[0.9856953,0.010342274,0.0003366475,0.0024000502,0.00059282087,0.00063290907],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0056829886,0.0013877922,0.00270269,0.0022086345,0.0019756877,0.0042127483,0.0042043813,0.0033880377,0.012159828],"category_scores_gemma":[0.027774932,0.0011767515,0.0012199758,0.0024949743,0.0026578244,0.012682354,0.008031782,0.0033395533,0.0034020888],"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":[0.004492924,0.0010467642,0.0039079413,0.0007458167,0.0002975846,0.0003511731,0.0011059624,0.24403264,0.0071205427,0.20015536,0.06793602,0.46880728],"study_design_scores_gemma":[0.00014398246,0.0001128772,0.00018944195,0.000028628749,0.000035581004,0.0000436535,0.00008091309,0.88292754,0.0035652334,0.109816045,0.0030288724,0.000027114747],"about_ca_topic_score_codex":0.004407311,"about_ca_topic_score_gemma":0.0038558817,"teacher_disagreement_score":0.012159828,"about_ca_system_score_codex":0.0017298135,"about_ca_system_score_gemma":0.0037791622,"threshold_uncertainty_score":0.04067868},"labels":[],"label_agreement":null},{"id":"W2965103467","doi":"10.1145/3335783.3335798","title":"Keep Your Host Language Object and Also Query it","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Relational database management system; Programming language; SQL; Query optimization; Relational database; Workflow; Interpreter; Language Integrated Query; Query language; Database; Query by Example; Information retrieval; Web search query; Search engine","score_opus":0.010048591963464224,"score_gpt":0.25545233049042276,"score_spread":0.24540373852695854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2965103467","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":[0.013565034,0.00168194,0.5042249,0.004362968,0.0037187964,0.0009547827,0.013841903,0.3269803,0.13066927],"genre_scores_gemma":[0.09791458,0.0028326167,0.22976184,0.009982528,0.0024847905,0.0016624073,0.039811723,0.31575245,0.29979712],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99728394,0.00035229753,0.00028889798,0.0005270288,0.0010672847,0.00048057846],"domain_scores_gemma":[0.9904923,0.0016374298,0.00045810523,0.005159571,0.0018859971,0.00036648996],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036468047,0.0020360772,0.0017415406,0.0014341596,0.0012972511,0.009543606,0.0046236482,0.0028974656,0.09835867],"category_scores_gemma":[0.013552775,0.0015093992,0.0014683924,0.0019611397,0.0015197066,0.015768686,0.010528217,0.0039733923,0.14503092],"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":[0.0015443454,0.00036513642,0.004511575,0.0010779947,0.00016174238,0.0010807385,0.0016545575,0.0016737431,0.01634823,0.05918646,0.64162797,0.27076754],"study_design_scores_gemma":[0.000110755,0.000095726136,0.000689035,0.00019031952,0.00005481348,0.0005515661,0.00026378385,0.0050074104,0.019652063,0.015218971,0.9580443,0.00012122056],"about_ca_topic_score_codex":0.0025090491,"about_ca_topic_score_gemma":0.0015534142,"teacher_disagreement_score":0.09835867,"about_ca_system_score_codex":0.0013938454,"about_ca_system_score_gemma":0.0016071581,"threshold_uncertainty_score":0.3290425},"labels":[],"label_agreement":null},{"id":"W2965906602","doi":"10.1145/3335783.3335800","title":"Improvement of SQL Recommendation on Scientific Database","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; SQL; Session (web analytics); Tuple; Information retrieval; Query by Example; Recommender system; Database; World Wide Web; Search engine; Web search query","score_opus":0.013738271643995461,"score_gpt":0.2502169216144368,"score_spread":0.23647864997044135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2965906602","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":[0.2980467,0.008255526,0.6341327,0.0014776703,0.00031930403,0.0007706618,0.010547304,0.037506066,0.008943969],"genre_scores_gemma":[0.43573624,0.002744093,0.5374417,0.0003884402,0.00016319954,0.00017080866,0.01745794,0.00045570813,0.0054418687],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9972186,0.0006790484,0.00030251613,0.0005269684,0.0011532913,0.00011958019],"domain_scores_gemma":[0.990694,0.0027851348,0.00050198624,0.0021760373,0.003590763,0.00025213952],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003957271,0.0010488844,0.0011105721,0.0024450864,0.0005104024,0.0015602836,0.0011243761,0.0008473413,0.0022216465],"category_scores_gemma":[0.014962581,0.00040509464,0.00084581866,0.0029371616,0.0001697372,0.0026770872,0.00065559294,0.0008374993,0.0018986135],"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":[0.0010645081,0.0007470963,0.036352053,0.0010246148,0.00038741034,0.00025208815,0.0005762744,0.029144049,0.03710531,0.0018872961,0.042642724,0.8488166],"study_design_scores_gemma":[0.00023985731,0.0012996239,0.035532936,0.0001055563,0.00042296026,0.0006964065,0.000733291,0.8663322,0.04472988,0.0037773557,0.045969747,0.00016018571],"about_ca_topic_score_codex":0.012413737,"about_ca_topic_score_gemma":0.022216426,"teacher_disagreement_score":0.012413737,"about_ca_system_score_codex":0.0005667504,"about_ca_system_score_gemma":0.0010206895,"threshold_uncertainty_score":0.024682939},"labels":[],"label_agreement":null},{"id":"W2970397632","doi":"10.14778/3352063.3352102","title":"Making an RDBMS data scientist friendly","year":2019,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Python (programming language); Relational database management system; Database; Implementation; Relational database; Programming language","score_opus":0.04182728214053458,"score_gpt":0.2994120196958087,"score_spread":0.2575847375552741,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2970397632","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":[0.022317387,0.0016695772,0.77621245,0.008700892,0.0027517017,0.0007398385,0.0034978327,0.14759688,0.036513466],"genre_scores_gemma":[0.102861024,0.0016623314,0.82311904,0.0043345424,0.000950229,0.00080234354,0.009538103,0.026387606,0.030344719],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9878499,0.0018939185,0.0008733616,0.0015880006,0.0069430633,0.00085178396],"domain_scores_gemma":[0.9801971,0.0024490952,0.00054049364,0.008741246,0.0060124015,0.002059558],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013656611,0.0011161115,0.0012308119,0.0013325169,0.0021274772,0.009221548,0.0075601884,0.00229433,0.012036926],"category_scores_gemma":[0.028268287,0.0017971222,0.0017406862,0.0016593159,0.002379476,0.016068272,0.015148168,0.0070228004,0.01124937],"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":[0.0019150074,0.0006693228,0.007908554,0.0012853859,0.00033915922,0.00090911984,0.0029965271,0.008192131,0.05679564,0.16183415,0.44369572,0.31345925],"study_design_scores_gemma":[0.00028678955,0.00010578054,0.0014404177,0.00020539972,0.000082314196,0.00041806983,0.00031082018,0.03402962,0.027532142,0.04586179,0.8895986,0.00012815984],"about_ca_topic_score_codex":0.0041517443,"about_ca_topic_score_gemma":0.0034376956,"teacher_disagreement_score":0.013656611,"about_ca_system_score_codex":0.0015734506,"about_ca_system_score_gemma":0.004530672,"threshold_uncertainty_score":0.07222396},"labels":[],"label_agreement":null},{"id":"W2971120804","doi":"10.14778/3352063.3352064","title":"GALO","year":2019,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University; IBM (Canada)","funders":"","keywords":"Computer science; SPARQL; Knowledge base; SQL; Query optimization; Process (computing); Query plan; Plan (archaeology); Information retrieval; Base (topology); RDF; Web query classification; Sargable; Database; Data mining; Web search query; World Wide Web; Search engine; Semantic Web; Programming language","score_opus":0.00448911751621578,"score_gpt":0.1879691187956926,"score_spread":0.18348000127947683,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2971120804","genre_codex":"software","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":[0.010525872,0.0019060544,0.21107273,0.0041572647,0.0013839058,0.0011346766,0.031998202,0.37604496,0.36177632],"genre_scores_gemma":[0.15662855,0.0026212423,0.29083353,0.007931165,0.0011530227,0.001276213,0.1750861,0.07154089,0.29292932],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99661726,0.00043733127,0.00017775806,0.000897536,0.0015097364,0.00036037245],"domain_scores_gemma":[0.9944537,0.0010831242,0.00019057078,0.0022193766,0.0015828061,0.0004703345],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003044591,0.0014822516,0.0009758264,0.0026689996,0.0009647626,0.005127639,0.0036481216,0.0015259404,0.11917507],"category_scores_gemma":[0.009577267,0.0008245737,0.0011715345,0.0019537152,0.00091060164,0.005481177,0.0048860894,0.0026337474,0.087329365],"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":[0.0010085172,0.0002805994,0.002508872,0.00065258617,0.00008520794,0.00024293318,0.0003575059,0.0025153717,0.009650969,0.0384119,0.6089027,0.33538282],"study_design_scores_gemma":[0.00017910646,0.00011190967,0.0013275428,0.000118732394,0.00003655697,0.0002629044,0.00012855064,0.017820202,0.0065975506,0.02193326,0.9514161,0.000067657485],"about_ca_topic_score_codex":0.003790809,"about_ca_topic_score_gemma":0.0035779031,"teacher_disagreement_score":0.11917507,"about_ca_system_score_codex":0.001738885,"about_ca_system_score_gemma":0.0022438779,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W2971769059","doi":"10.15488/5130","title":"Query Optimization Techniques For Scaling Up To Data Variety","year":2019,"lang":"en","type":"dissertation","venue":"Institutional Repository of Leibniz Universität Hannover (Leibniz Universität Hannover)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Variety (cybernetics); Query optimization; Computer science; Scaling; Information retrieval; Data science; Data mining; Artificial intelligence; Mathematics","score_opus":0.020967070605881228,"score_gpt":0.2596576127020602,"score_spread":0.238690542096179,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2971769059","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":[0.03556149,0.001137708,0.95026404,0.0006179936,0.00006096148,0.00053288706,0.00090074126,0.004848421,0.006075833],"genre_scores_gemma":[0.24092983,0.00081343733,0.7514423,0.00025587901,0.000060781018,0.00039119404,0.0023895192,0.0009571066,0.002760022],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99613523,0.00088222756,0.00034874532,0.0007019505,0.0015435542,0.00038821032],"domain_scores_gemma":[0.9957022,0.0020614748,0.00024806583,0.0011420543,0.00072761957,0.000118542535],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030622534,0.0011457691,0.00093900407,0.0014920045,0.0010787694,0.0021025816,0.0018410261,0.0007141512,0.0029070405],"category_scores_gemma":[0.009289,0.0005786173,0.0014349252,0.0034700704,0.0008555517,0.003645436,0.0022311597,0.001329983,0.00085636077],"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":[0.0008803823,0.00048681453,0.009139719,0.0012816477,0.00034930714,0.00066209486,0.0015908935,0.2159049,0.0637937,0.10036381,0.036135904,0.5694108],"study_design_scores_gemma":[0.00011311451,0.00018908535,0.0028941743,0.0000856969,0.00018578743,0.0004998544,0.0011809553,0.86812496,0.02786938,0.055383712,0.04340369,0.00006949178],"about_ca_topic_score_codex":0.010473779,"about_ca_topic_score_gemma":0.012997953,"teacher_disagreement_score":0.010473779,"about_ca_system_score_codex":0.0015101525,"about_ca_system_score_gemma":0.0022198723,"threshold_uncertainty_score":0.020825624},"labels":[],"label_agreement":null},{"id":"W2992750542","doi":"10.1007/978-3-030-26253-2_2","title":"Distributed and Parallel Database Design","year":2019,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Computer science; Conceptual schema; Fragmentation (computing); Schema (genetic algorithms); Database schema; Database; Conceptual design; Schema migration; Distributed database; Theoretical computer science; Distributed computing; Data mining; Database design; Programming language; Information retrieval; Semi-structured model; Gender schema theory; Human–computer interaction","score_opus":0.033937546950180975,"score_gpt":0.2365801642929061,"score_spread":0.20264261734272512,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2992750542","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":[0.0018558473,0.027717093,0.70316035,0.0029043092,0.0032468669,0.00018649358,0.0003945383,0.0024331748,0.2581014],"genre_scores_gemma":[0.039143413,0.028686766,0.2862896,0.0014749556,0.0020668444,0.00039159195,0.0010448708,0.001234486,0.63966745],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992761,0.00009790999,0.000041898653,0.00015680432,0.00038499534,0.000042215433],"domain_scores_gemma":[0.9995278,0.000117273376,0.000013114525,0.00016586338,0.00014113718,0.0000347113],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00087162806,0.00094393804,0.00071252615,0.0008666616,0.0007620401,0.003099797,0.0013743895,0.00080780184,0.028027322],"category_scores_gemma":[0.0016123864,0.0008593349,0.00048528184,0.0020423906,0.001149651,0.0035340975,0.0012408735,0.0018061555,0.015669193],"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":[0.000043749213,0.000055253997,0.00016295874,0.00039605377,0.000024676949,0.000060550123,0.00019829637,0.004107605,0.003618511,0.39143175,0.20338671,0.39651397],"study_design_scores_gemma":[0.000015256644,0.000034046803,0.00019501147,0.00011242192,0.000021237378,0.00025968434,0.000050297087,0.011282024,0.0014863206,0.21951057,0.7670182,0.00001498626],"about_ca_topic_score_codex":0.0010535126,"about_ca_topic_score_gemma":0.0015393354,"teacher_disagreement_score":0.028027322,"about_ca_system_score_codex":0.0012699406,"about_ca_system_score_gemma":0.0013027603,"threshold_uncertainty_score":0.09376073},"labels":[],"label_agreement":null},{"id":"W2994124935","doi":"10.1007/978-3-030-26253-2_7","title":"Database Integration—Multidatabase Systems","year":2019,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Database Systems and Queries","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":"Database; Computer science","score_opus":0.02582974097670323,"score_gpt":0.2440328993126684,"score_spread":0.21820315833596515,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2994124935","genre_codex":"methods","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":[0.0023524896,0.11367037,0.5127688,0.0037191545,0.0041709617,0.00023068552,0.0008251497,0.007598588,0.3546637],"genre_scores_gemma":[0.041813925,0.088704884,0.3109255,0.0048918505,0.0036917313,0.0003614057,0.004346779,0.0037047844,0.5415591],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.998847,0.00012747818,0.00008411389,0.00023207013,0.0006528604,0.00005654464],"domain_scores_gemma":[0.99935347,0.0001921055,0.000029879067,0.00018093224,0.00020373276,0.000039933755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009523328,0.0011661579,0.0011512043,0.0030801906,0.00080877234,0.006529041,0.0024264606,0.0012240374,0.03705016],"category_scores_gemma":[0.0015138261,0.0011904162,0.0007061334,0.007518277,0.0008221376,0.009307757,0.0031111802,0.00241817,0.030958513],"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":[0.000029550465,0.000076295466,0.00014733456,0.0006344307,0.00004030666,0.000108292414,0.00020712594,0.00097321445,0.0038053098,0.12580833,0.17297004,0.69519985],"study_design_scores_gemma":[0.0000068687173,0.00001966595,0.0002566689,0.00021142625,0.000024606925,0.00050068315,0.000063669024,0.0034337202,0.0022326305,0.060280662,0.93295044,0.000018907904],"about_ca_topic_score_codex":0.0011049791,"about_ca_topic_score_gemma":0.00093565724,"teacher_disagreement_score":0.03705016,"about_ca_system_score_codex":0.0010861332,"about_ca_system_score_gemma":0.00091764476,"threshold_uncertainty_score":0.12394512},"labels":[],"label_agreement":null},{"id":"W2997537198","doi":"","title":"Tightly-coupled spatial database features in the Odysseus/OpenGIS DBMS for high-performance","year":2010,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Database; Spatial database; Computer science; Spatial analysis; Geography; Remote sensing","score_opus":0.00860105876086701,"score_gpt":0.2387639600378736,"score_spread":0.2301629012770066,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2997537198","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":[0.028050512,0.00039977237,0.8839451,0.00081030035,0.00036937656,0.00021653606,0.0018572563,0.064144515,0.020206653],"genre_scores_gemma":[0.26025915,0.0003663355,0.7073294,0.001149812,0.00015732975,0.00027785756,0.004787835,0.006214598,0.019457785],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989936,0.000112737944,0.00010505697,0.00022581256,0.00046321534,0.00009960063],"domain_scores_gemma":[0.9990388,0.00012430166,0.0000591755,0.0005004997,0.00019730358,0.00007991874],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014675034,0.00044509387,0.00049359957,0.00060118927,0.000616015,0.0023395335,0.001717809,0.00055922434,0.0086253565],"category_scores_gemma":[0.002468686,0.0005611789,0.0004965949,0.0012884997,0.00067352393,0.002792922,0.0036408908,0.0013202332,0.0036738263],"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":[0.00087659946,0.00049397675,0.015474294,0.000615923,0.0003208827,0.00100098,0.0026986888,0.01820061,0.10143871,0.17521784,0.1202231,0.5634384],"study_design_scores_gemma":[0.00027721113,0.00025510672,0.0074586957,0.00022688598,0.00022033768,0.0013185868,0.0005654794,0.09147377,0.08456861,0.09276073,0.72066253,0.00021210998],"about_ca_topic_score_codex":0.0027627754,"about_ca_topic_score_gemma":0.0047957157,"teacher_disagreement_score":0.0086253565,"about_ca_system_score_codex":0.0003885816,"about_ca_system_score_gemma":0.0011448828,"threshold_uncertainty_score":0.028854728},"labels":[],"label_agreement":null},{"id":"W3007378362","doi":"10.1145/3377555.3377892","title":"Improving database query performance with automatic fusion","year":2020,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Compiler; Loop fusion; Query optimization; SQL; Sargable; Database; Fuse (electrical); Query language; Programming language; View; Loop unrolling; Search engine; Web search query; Information retrieval; Database design","score_opus":0.014408758794311758,"score_gpt":0.20802210057978401,"score_spread":0.19361334178547226,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3007378362","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":[0.28729248,0.00040704085,0.6488254,0.00031016354,0.00007066263,0.00018220389,0.00038595227,0.056826126,0.005700014],"genre_scores_gemma":[0.6964891,0.00015892362,0.29722205,0.00021067134,0.000034187295,0.00012579629,0.0011142644,0.0029640498,0.0016809767],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99728644,0.00039122452,0.000267221,0.00038886897,0.0012983438,0.000367927],"domain_scores_gemma":[0.9958055,0.0016284316,0.00028391942,0.0011251736,0.0010758709,0.000081086204],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018145819,0.0010385069,0.0008797575,0.0009824721,0.0006770803,0.0015522963,0.001740437,0.0006140536,0.0017796067],"category_scores_gemma":[0.0059501836,0.00059796823,0.0010267596,0.0019318167,0.0009067367,0.0023137124,0.0018196184,0.0012708658,0.000762158],"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":[0.00215725,0.00082153647,0.015886324,0.00037776213,0.00019807226,0.0004881379,0.0011833748,0.1629234,0.23665759,0.016175538,0.01655317,0.5465779],"study_design_scores_gemma":[0.00011969155,0.0002244086,0.0019616173,0.000015222298,0.00006696918,0.00017139726,0.00014274186,0.7989368,0.18841498,0.0046739806,0.0052104597,0.00006171337],"about_ca_topic_score_codex":0.0051114517,"about_ca_topic_score_gemma":0.0034453084,"teacher_disagreement_score":0.0051114517,"about_ca_system_score_codex":0.0009807906,"about_ca_system_score_gemma":0.0024701993,"threshold_uncertainty_score":0.010163426},"labels":[],"label_agreement":null},{"id":"W3008396432","doi":"10.1145/3318464.3380602","title":"Facilitating SQL Query Composition and Analysis","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Spatial query; Sargable; Query by Example; SQL; Query optimization; Web query classification; Class (philosophy); Query language; Query expansion; Web search query; Workload; Data mining; Database; Information retrieval; Artificial intelligence; Search engine; Operating system","score_opus":0.02791884469615542,"score_gpt":0.27682901176484265,"score_spread":0.24891016706868724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3008396432","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":[0.040496163,0.00030036859,0.86718535,0.0006472561,0.00010030947,0.0008405564,0.00068970496,0.08495108,0.00478922],"genre_scores_gemma":[0.39804313,0.0003467929,0.58159506,0.0005830858,0.00016259143,0.00046940098,0.0029914426,0.010788694,0.005019719],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9843701,0.0041051283,0.0014214544,0.002955079,0.005980781,0.0011675638],"domain_scores_gemma":[0.97100294,0.017151922,0.0011072202,0.0068531735,0.0032362177,0.0006485639],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008883543,0.0028840676,0.0021013871,0.0023835134,0.0015175765,0.0053582108,0.0030396436,0.0011369089,0.009341052],"category_scores_gemma":[0.037196096,0.0016835051,0.0019583614,0.0018653477,0.0015238321,0.0068948176,0.0044859713,0.0037673318,0.0046932152],"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":[0.001861348,0.001462597,0.022043409,0.00086119835,0.00034821784,0.00081784657,0.0019531229,0.05808022,0.12417265,0.038092297,0.027633114,0.72267395],"study_design_scores_gemma":[0.00012219495,0.00018752833,0.0038412563,0.0000825473,0.00011115646,0.0003822312,0.00059124734,0.82542276,0.09636519,0.04286282,0.029905194,0.00012588831],"about_ca_topic_score_codex":0.005056763,"about_ca_topic_score_gemma":0.006022865,"teacher_disagreement_score":0.009341052,"about_ca_system_score_codex":0.0017866606,"about_ca_system_score_gemma":0.0037925236,"threshold_uncertainty_score":0.046981275},"labels":[],"label_agreement":null},{"id":"W3011864725","doi":"","title":"DescribeX: A Framework for Exploring and Querying XML Web Collections","year":2008,"lang":"en","type":"preprint","venue":"TSpace","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"XPath; Computer science; Automatic summarization; XML; Information retrieval; Path expression; Scalability; XML database; Streaming XML; Database; Key (lock); Search engine indexing; World Wide Web","score_opus":0.13049253593178523,"score_gpt":0.345237154838614,"score_spread":0.21474461890682878,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3011864725","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":[0.00090277754,0.0005592706,0.96347314,0.00032875958,0.000056367422,0.00042884346,0.0020248285,0.030329129,0.0018969483],"genre_scores_gemma":[0.022914894,0.0021477754,0.94509083,0.0006835528,0.000110929504,0.0016011208,0.013794845,0.0071225422,0.0065335473],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99378514,0.0015520214,0.0010664379,0.00086433353,0.0023936266,0.0003384285],"domain_scores_gemma":[0.9958474,0.0018402305,0.00028051695,0.0012839005,0.00046136565,0.00028660783],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008835471,0.002160657,0.0027867917,0.004776319,0.002258785,0.009951605,0.009289435,0.0036951785,0.010673265],"category_scores_gemma":[0.012361131,0.0038744782,0.0052738916,0.005268756,0.0029324174,0.013822976,0.010739178,0.00466115,0.005025206],"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":[0.0008055465,0.00028758508,0.0056139785,0.0042648776,0.0007271938,0.0023520098,0.0038711554,0.05702611,0.0111288875,0.45824504,0.1350347,0.3206429],"study_design_scores_gemma":[0.00026938712,0.000121430974,0.0008171994,0.0007117197,0.00021544896,0.001642564,0.0008527797,0.2074191,0.011174703,0.18880975,0.5876501,0.00031593107],"about_ca_topic_score_codex":0.013877444,"about_ca_topic_score_gemma":0.016918665,"teacher_disagreement_score":0.013877444,"about_ca_system_score_codex":0.0025561836,"about_ca_system_score_gemma":0.0030130509,"threshold_uncertainty_score":0.046726942},"labels":[],"label_agreement":null},{"id":"W3012157188","doi":"10.1109/aiccsa47632.2019.9035283","title":"Quality Model for Evaluating and Choosing a Stream Processing Framework Architecture","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Computer science; Architecture; Quality (philosophy); Stream processing; Artificial intelligence; Distributed computing; Geography","score_opus":0.05353672395136307,"score_gpt":0.3744276585657075,"score_spread":0.3208909346143444,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3012157188","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":[0.086727485,0.0005980738,0.90062773,0.0018450251,0.000065720495,0.0009037762,0.0006142938,0.0015402485,0.007077526],"genre_scores_gemma":[0.51317346,0.00030947648,0.4833894,0.00021819696,0.000039008017,0.00050287327,0.00086105586,0.00019239349,0.0013140138],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9754499,0.00745469,0.0026401498,0.0016281856,0.0114322575,0.0013947756],"domain_scores_gemma":[0.94512916,0.022670692,0.00578168,0.0028423257,0.021549933,0.0020262129],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.025646389,0.0013461508,0.0009797992,0.0069065,0.0012962631,0.005368803,0.0020852378,0.0016928609,0.002092223],"category_scores_gemma":[0.070721924,0.0005880713,0.0013916893,0.0028127693,0.001370858,0.004886268,0.0019558745,0.0016637612,0.00040910486],"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":[0.0010845627,0.0009994091,0.06989607,0.0008746609,0.00043662198,0.00040851065,0.00143638,0.5296415,0.011165719,0.12090282,0.008062336,0.25509146],"study_design_scores_gemma":[0.0000554523,0.00040981555,0.0038474004,0.00015581999,0.0001375508,0.00011724282,0.00038414492,0.96073127,0.0037755077,0.02591061,0.0044077523,0.00006735443],"about_ca_topic_score_codex":0.014350777,"about_ca_topic_score_gemma":0.013211473,"teacher_disagreement_score":0.025646389,"about_ca_system_score_codex":0.006216501,"about_ca_system_score_gemma":0.0042748502,"threshold_uncertainty_score":0.1356327},"labels":[],"label_agreement":null},{"id":"W3022461306","doi":"","title":"Proceedings of the 9th annual ACM international workshop on Web information and data management","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Library science; China; Ninth; Computer science; Schedule; Metadata; Data management; World Wide Web; Database; Political science","score_opus":0.019290487378659796,"score_gpt":0.28119519557992245,"score_spread":0.26190470820126266,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3022461306","genre_codex":"methods","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":[0.023768736,0.100625,0.5008467,0.072561525,0.07925277,0.0024781753,0.0068274667,0.014640663,0.198999],"genre_scores_gemma":[0.05995985,0.06826276,0.22151811,0.010397827,0.01700582,0.0017534423,0.030000424,0.0054072808,0.5856945],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9952873,0.0016454917,0.0004510303,0.000589387,0.0016262094,0.00040058617],"domain_scores_gemma":[0.99169266,0.002299738,0.00026861788,0.0016967477,0.0023778102,0.0016644255],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0076097143,0.0018228325,0.0020238534,0.0025201223,0.0017043588,0.008504143,0.0028117972,0.0025547117,0.04970225],"category_scores_gemma":[0.0112802535,0.0010024871,0.001312612,0.002399011,0.0015760761,0.011624077,0.0044364054,0.0054820087,0.027261263],"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":[0.00021758117,0.0003927965,0.0011670814,0.00042409118,0.00009463087,0.0003071693,0.00088304194,0.0003904678,0.003965644,0.008974459,0.7045313,0.27865168],"study_design_scores_gemma":[0.000027394139,0.00007652326,0.0012058597,0.00033456655,0.00004417125,0.00035508734,0.00045715613,0.0025680698,0.001214797,0.008556421,0.98512286,0.000037096026],"about_ca_topic_score_codex":0.0033902489,"about_ca_topic_score_gemma":0.0054181535,"teacher_disagreement_score":0.04970225,"about_ca_system_score_codex":0.0011821481,"about_ca_system_score_gemma":0.002980752,"threshold_uncertainty_score":0.16627061},"labels":[],"label_agreement":null},{"id":"W3023331976","doi":"10.5555/3370272.3370301","title":"State of practices of Java native interface.","year":2019,"lang":"en","type":"article","venue":"PolyPublie (École Polytechnique de Montréal)","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":"Polytechnique Montréal","funders":"","keywords":"Java; Computer science; Interface (matter); State (computer science); Operating system; Programming language","score_opus":0.01260867590414676,"score_gpt":0.26610923757731814,"score_spread":0.25350056167317137,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3023331976","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":[0.02242759,0.06684585,0.52454853,0.01628177,0.0037001818,0.0007487803,0.0043145153,0.061760392,0.29937246],"genre_scores_gemma":[0.20371579,0.055176634,0.5142387,0.011287535,0.0021502494,0.0013045112,0.0141644515,0.023969933,0.17399219],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9886764,0.0017783424,0.0012304316,0.001872717,0.0052870996,0.0011549767],"domain_scores_gemma":[0.9694895,0.0065922034,0.0013546828,0.0104711335,0.01026952,0.0018228627],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015396762,0.0007957318,0.0005208597,0.0032630668,0.0011046228,0.009997766,0.0050876923,0.002271494,0.009515378],"category_scores_gemma":[0.021584876,0.0012066651,0.0006209201,0.0032233053,0.002716836,0.011615714,0.0028377168,0.0048102043,0.008372314],"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":[0.00058638747,0.00043804926,0.0034372471,0.0015751015,0.00005919612,0.00013731299,0.0017294876,0.00067846145,0.012874738,0.16273469,0.0949054,0.72084403],"study_design_scores_gemma":[0.000062290295,0.0001352376,0.0033312975,0.0012322188,0.00006339299,0.00035538193,0.00026996536,0.0033773761,0.013514981,0.015157643,0.9624132,0.000087042674],"about_ca_topic_score_codex":0.017214164,"about_ca_topic_score_gemma":0.011972616,"teacher_disagreement_score":0.017214164,"about_ca_system_score_codex":0.0025239391,"about_ca_system_score_gemma":0.007775336,"threshold_uncertainty_score":0.0814268},"labels":[],"label_agreement":null},{"id":"W3025940890","doi":"10.14778/3401960.3401966","title":"Approximate denial constraints","year":2020,"lang":"en","type":"preprint","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Overfitting; Computer science; Feature (linguistics); Focus (optics); Axiom; Mathematical optimization; Theoretical computer science; Algorithm; Mathematics; Artificial intelligence","score_opus":0.024586798940756546,"score_gpt":0.24463647034998354,"score_spread":0.220049671409227,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3025940890","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":[0.037859015,0.0014451302,0.948762,0.0021058891,0.00016518004,0.0002571396,0.002626486,0.0010510933,0.005728091],"genre_scores_gemma":[0.41623122,0.0011630188,0.5707599,0.0012708536,0.0003070173,0.00036941748,0.0054368353,0.00038580573,0.004075877],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9869435,0.0029191803,0.0013596063,0.0031609861,0.0047953213,0.0008215211],"domain_scores_gemma":[0.95969594,0.026939133,0.003004768,0.006488798,0.0033657728,0.0005056863],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0060097137,0.0011027172,0.0021454582,0.002379176,0.001463537,0.004509238,0.0038208754,0.0024173716,0.00639202],"category_scores_gemma":[0.055442676,0.0009390979,0.0020229619,0.0044105905,0.0021537018,0.009873597,0.0035561111,0.00368178,0.0011327782],"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":[0.0008479169,0.00022828774,0.022496592,0.0016673758,0.000497687,0.0012940944,0.0010134522,0.1923077,0.0065413895,0.34489587,0.023378069,0.40483156],"study_design_scores_gemma":[0.00006294383,0.00008681204,0.0026219708,0.00017903466,0.00010918128,0.002258302,0.0005325764,0.5511032,0.008584257,0.40894493,0.025447346,0.00006947845],"about_ca_topic_score_codex":0.003562211,"about_ca_topic_score_gemma":0.0033696732,"teacher_disagreement_score":0.00639202,"about_ca_system_score_codex":0.0014511807,"about_ca_system_score_gemma":0.0023593013,"threshold_uncertainty_score":0.031782806},"labels":[],"label_agreement":null},{"id":"W30283385","doi":"10.3389/fpsyg.2018.01740","title":"Computing data cubes without redundant aggregated nodes and single graph paths: the sequential MCG approach","year":2008,"lang":"en","type":"article","venue":"Brazilian Symposium on Databases","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research","keywords":"Cuboid; Cube (algebra); Data cube; Computer science; Computation; Tuple; Graph; Hypercube; Base (topology); Algorithm; Reduction (mathematics); Theoretical computer science; Combinatorics; Mathematics; Discrete mathematics; Data mining; Parallel computing","score_opus":0.07017860466193648,"score_gpt":0.282689483014899,"score_spread":0.2125108783529625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W30283385","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":[0.01434127,0.00039031805,0.98101586,0.00032852,0.000047148897,0.00021282308,0.000872975,0.00172272,0.0010683245],"genre_scores_gemma":[0.09193062,0.00029542943,0.9040697,0.00012522266,0.000061972045,0.0003284849,0.0020068728,0.0002686137,0.0009131523],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975963,0.0007857338,0.00020069392,0.00064755266,0.0005110662,0.0002585678],"domain_scores_gemma":[0.9899829,0.006064015,0.0007786609,0.0016439635,0.0011549775,0.00037548138],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030383493,0.0017399184,0.0023294673,0.004536993,0.0011854605,0.0028458526,0.0046791034,0.0013870635,0.0047800904],"category_scores_gemma":[0.016031343,0.0016224904,0.002963739,0.0067525846,0.0018975602,0.004383706,0.0046028644,0.001737055,0.0009806836],"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":[0.00067787396,0.0002832531,0.011384486,0.001071194,0.0006102443,0.0006305142,0.0008497443,0.55305505,0.004188432,0.04875606,0.007961215,0.370532],"study_design_scores_gemma":[0.000057487818,0.00009457661,0.0008800579,0.000048284972,0.000079445395,0.00009165892,0.00022781175,0.9281982,0.00081589917,0.06596818,0.0035112977,0.000027096989],"about_ca_topic_score_codex":0.027274929,"about_ca_topic_score_gemma":0.045972954,"teacher_disagreement_score":0.027274929,"about_ca_system_score_codex":0.001459453,"about_ca_system_score_gemma":0.0031243984,"threshold_uncertainty_score":0.05423236},"labels":[],"label_agreement":null},{"id":"W3037245005","doi":"10.3166/isi.11.6.11-31","title":"Cubes convexes","year":2006,"lang":"fr","type":"article","venue":"Ingénierie des systèmes d information","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Data cube; Online analytical processing; Cube (algebra); Computer science; Tuple; Regular polygon; Polyhedron; Data structure; Algorithm; Mathematics; Data warehouse; Combinatorics; Discrete mathematics; Data mining","score_opus":0.015685722282688948,"score_gpt":0.23064698592873858,"score_spread":0.21496126364604964,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3037245005","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":[0.021161776,0.0028345287,0.89197224,0.0012025465,0.00051207264,0.0002519379,0.002773013,0.00049206906,0.078799784],"genre_scores_gemma":[0.37917647,0.008470493,0.5387888,0.0016268017,0.0010892549,0.0010891653,0.009880351,0.00089536357,0.05898327],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99727976,0.00045798183,0.00022677844,0.00073460874,0.0010626727,0.00023801741],"domain_scores_gemma":[0.99733967,0.0007656733,0.00028694147,0.00045684635,0.0010113468,0.00013957976],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011770694,0.001409406,0.00088014576,0.0019043465,0.0014503662,0.0046816426,0.0013823865,0.00079089514,0.012565102],"category_scores_gemma":[0.004635831,0.0005695563,0.0014087228,0.0033243438,0.0028274877,0.006493589,0.0039562527,0.0028532017,0.0039133755],"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":[0.00006021118,0.000012967648,0.0003373226,0.00013346158,0.000024624916,0.00013923,0.0002048548,0.009554374,0.0013454035,0.934387,0.0076943072,0.046106186],"study_design_scores_gemma":[0.000016602446,0.00006383613,0.0003197775,0.00008615835,0.000023808727,0.0005964444,0.00028768383,0.04656263,0.0031329277,0.78324294,0.16562109,0.00004603775],"about_ca_topic_score_codex":0.0030356725,"about_ca_topic_score_gemma":0.001981404,"teacher_disagreement_score":0.012565102,"about_ca_system_score_codex":0.001657856,"about_ca_system_score_gemma":0.00088188803,"threshold_uncertainty_score":0.042034447},"labels":[],"label_agreement":null},{"id":"W3040097605","doi":"10.1017/s1471068420000101","title":"Restricted Chase Termination for Existential Rules: A Hierarchical Approach and Experimentation","year":2020,"lang":"en","type":"article","venue":"Theory and Practice of Logic Programming","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Chase; Computer science; Decidability; Parameterized complexity; Hierarchy; Class (philosophy); Bounded function; Conjunctive query; Existentialism; Theoretical computer science; Programming language; Algorithm; Artificial intelligence; Database; Mathematics; Relational database","score_opus":0.05125413606843647,"score_gpt":0.3375370963073417,"score_spread":0.2862829602389052,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3040097605","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":[0.4597731,0.00041740775,0.52100575,0.00026367462,0.000036651873,0.0008494305,0.0005206339,0.0034679642,0.013665373],"genre_scores_gemma":[0.7032385,0.00019116983,0.29298946,0.000096547374,0.000012347732,0.00026710925,0.00087202294,0.00050889736,0.0018238424],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9942696,0.0026964291,0.00032483993,0.00069374096,0.0016382525,0.00037709842],"domain_scores_gemma":[0.9727745,0.019739576,0.00052305585,0.003867066,0.0026521836,0.00044358798],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00568065,0.0004813427,0.0006831257,0.0016226835,0.0010914837,0.0012611318,0.0021108326,0.0010508337,0.0038660876],"category_scores_gemma":[0.027921157,0.00037781367,0.0010680335,0.0012049135,0.0018121016,0.003142452,0.0019583008,0.0019233841,0.0006116002],"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":[0.002127497,0.0058831074,0.024405433,0.0017229528,0.0002891295,0.0011865336,0.008006987,0.30422926,0.102204286,0.141886,0.0068996106,0.40115908],"study_design_scores_gemma":[0.00015287419,0.00070587854,0.0031758025,0.000108716165,0.00007946096,0.00021759838,0.0010324082,0.9007604,0.047499336,0.038592685,0.0076071913,0.00006771637],"about_ca_topic_score_codex":0.005986583,"about_ca_topic_score_gemma":0.006649495,"teacher_disagreement_score":0.005986583,"about_ca_system_score_codex":0.0014741318,"about_ca_system_score_gemma":0.0011854735,"threshold_uncertainty_score":0.03004253},"labels":[],"label_agreement":null},{"id":"W3041355115","doi":"10.1145/3385191","title":"Interval-based Queries over Lossy IoT Event Streams","year":2020,"lang":"en","type":"article","venue":"ACM/IMS Transactions on Data Science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Deutsche Forschungsgemeinschaft; Alexander von Humboldt-Stiftung","keywords":"Computer science; Event (particle physics); Timestamp; Probabilistic logic; Interval (graph theory); Sequence (biology); Data mining; Theoretical computer science; Real-time computing; Artificial intelligence; Mathematics","score_opus":0.06056157224516586,"score_gpt":0.318393266819087,"score_spread":0.25783169457392113,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3041355115","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":[0.08135834,0.00042199506,0.91102934,0.00034746813,0.000054933887,0.00023937911,0.0015045169,0.0034238482,0.0016202632],"genre_scores_gemma":[0.75749254,0.0003050052,0.23782955,0.00014429895,0.00010876094,0.00021501299,0.0025831352,0.00031963203,0.001002144],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99435437,0.0011046131,0.00059791066,0.0009768705,0.0026898705,0.00027638234],"domain_scores_gemma":[0.98772556,0.008600642,0.0010512929,0.00094936,0.001289405,0.00038374757],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031908748,0.0010695832,0.0012645797,0.0017898951,0.00063155603,0.0027949682,0.0022181314,0.00095087674,0.0020644541],"category_scores_gemma":[0.021865811,0.0005214424,0.00096558343,0.0020905798,0.00075055746,0.004255876,0.0022058568,0.001213748,0.00043420543],"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":[0.0012413841,0.00028361107,0.010980384,0.00041133663,0.00021598967,0.0007507073,0.00066925195,0.76868516,0.009431635,0.038255177,0.0056197937,0.16345559],"study_design_scores_gemma":[0.00001651553,0.000028854462,0.0003067041,0.000008586156,0.000008382253,0.000075823125,0.000068165464,0.98041534,0.0018553529,0.016437588,0.0007707669,0.000007852275],"about_ca_topic_score_codex":0.0037139636,"about_ca_topic_score_gemma":0.0035147353,"teacher_disagreement_score":0.0037139636,"about_ca_system_score_codex":0.0012801363,"about_ca_system_score_gemma":0.0010867774,"threshold_uncertainty_score":0.016875148},"labels":[],"label_agreement":null},{"id":"W3043649939","doi":"10.1145/3401025.3401732","title":"Leaving stragglers at the window","year":2020,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Latency (audio); Real-time computing; Window (computing); Timeline; Operating system; Statistics; Telecommunications","score_opus":0.026346102285606156,"score_gpt":0.2227994991551019,"score_spread":0.19645339686949573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3043649939","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":[0.26419023,0.0010100674,0.71513265,0.00077511685,0.00031196198,0.0002444199,0.00055271725,0.012993416,0.0047895317],"genre_scores_gemma":[0.7338116,0.0004198305,0.25496468,0.0006293444,0.00012468848,0.00015113069,0.0012732022,0.0012706597,0.007354874],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99766076,0.0002668277,0.00020369828,0.00063521054,0.0009324452,0.0003010227],"domain_scores_gemma":[0.9929866,0.002528785,0.00079906004,0.0022581392,0.0010566853,0.00037067683],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017221735,0.0010430709,0.0012532169,0.0007497721,0.000937914,0.0024646935,0.0016948791,0.0008536767,0.0029633965],"category_scores_gemma":[0.011289926,0.0006760126,0.0007281774,0.0009540688,0.00085234613,0.0034921481,0.0021313548,0.0011516656,0.0013872102],"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":[0.0054294094,0.0004552579,0.047201645,0.0006306847,0.00027943356,0.0011101465,0.0025315816,0.112838045,0.13791916,0.0290955,0.02268338,0.6398257],"study_design_scores_gemma":[0.00017668106,0.0007723075,0.004830224,0.00010161045,0.00013495107,0.0005533774,0.000754112,0.80167526,0.12909639,0.03439259,0.027418947,0.00009352566],"about_ca_topic_score_codex":0.0045084953,"about_ca_topic_score_gemma":0.00478048,"teacher_disagreement_score":0.0045084953,"about_ca_system_score_codex":0.00091268413,"about_ca_system_score_gemma":0.0028246765,"threshold_uncertainty_score":0.009913564},"labels":[],"label_agreement":null},{"id":"W3046132349","doi":"10.1007/978-3-030-47992-3_4","title":"Compilations: Designing and Using Archaeological Databases","year":2020,"lang":"en","type":"book-chapter","venue":"Interdisciplinary Contributions to Archaeology/Interdisciplinary contributions to archaeology","topic":"Advanced Database Systems and Queries","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 Toronto","funders":"","keywords":"Database; Computer science; Metadata; Relational database; Database design; Redundancy (engineering); Database model; Data redundancy; View; Information retrieval; World Wide Web","score_opus":0.03578809629777251,"score_gpt":0.3499177429721882,"score_spread":0.3141296466744157,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3046132349","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":[0.008258088,0.0012922116,0.9439803,0.00065082684,0.00022574847,0.00036359573,0.0024790466,0.025098264,0.017651862],"genre_scores_gemma":[0.055336066,0.0019461036,0.90294254,0.00035523408,0.00014334274,0.00041831002,0.0073371073,0.00982494,0.021696331],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9966568,0.0008949957,0.00045211677,0.0006376151,0.0012296021,0.00012895369],"domain_scores_gemma":[0.9921163,0.0045904787,0.0003674064,0.0018835963,0.0008014416,0.00024075324],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0042502317,0.0010571565,0.0010188551,0.004954371,0.0013986515,0.009235237,0.003133328,0.0008611714,0.010364424],"category_scores_gemma":[0.016155094,0.0022146062,0.0011478247,0.0056688115,0.0023690194,0.010693111,0.0052634603,0.0015248989,0.0040805927],"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":[0.00011958099,0.00009953768,0.0035092097,0.0016888262,0.00013589927,0.00064160884,0.011541638,0.0054964777,0.0071791066,0.14466627,0.07645102,0.74847084],"study_design_scores_gemma":[0.00006234259,0.000058939902,0.0022296943,0.0006572334,0.00021512617,0.0009065151,0.0054926034,0.03563512,0.024381744,0.15656313,0.7736888,0.000108733846],"about_ca_topic_score_codex":0.0037978424,"about_ca_topic_score_gemma":0.006192547,"teacher_disagreement_score":0.010364424,"about_ca_system_score_codex":0.00082968606,"about_ca_system_score_gemma":0.0022432138,"threshold_uncertainty_score":0.03467244},"labels":[],"label_agreement":null},{"id":"W3084942588","doi":"10.1007/978-3-030-26253-2_13","title":"Correction to: Principles of Distributed Database Systems","year":2020,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Database Systems and Queries","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":"University of Waterloo","funders":"","keywords":"Computer science; Information retrieval; Database; Library science; History; World Wide Web","score_opus":0.03557865884990563,"score_gpt":0.2446002381222725,"score_spread":0.20902157927236686,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3084942588","genre_codex":"editorial","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":[0.000076815486,0.0020725376,0.0021588868,0.098445214,0.8731207,0.000037410715,0.0010128366,0.00088627706,0.022189312],"genre_scores_gemma":[0.0044285487,0.0051800148,0.004788209,0.090630345,0.22555336,0.00015436854,0.0014708556,0.0018321222,0.6659621],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9952361,0.0005978949,0.0005589802,0.00066680595,0.0025922088,0.00034799782],"domain_scores_gemma":[0.9638422,0.00552078,0.0009456915,0.003023857,0.025272787,0.0013945339],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035551756,0.0016000614,0.0018909421,0.004603852,0.004043378,0.0075985123,0.003653738,0.007298403,0.1037403],"category_scores_gemma":[0.043340366,0.0010073847,0.0012775937,0.004631639,0.0033559466,0.005208256,0.0022082028,0.012522282,0.099182375],"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":[0.000005996068,0.0000023119728,0.000011936553,0.00003489748,0.0000016831816,0.000014902447,0.00000947184,0.00001930743,0.000010976728,0.0016288215,0.99476093,0.003498722],"study_design_scores_gemma":[0.00000811488,0.0000039897905,0.00012654046,0.00007249585,0.0000049849937,0.00006081682,0.000023840319,0.000090799236,0.00005489361,0.0019946767,0.99755055,0.000008397456],"about_ca_topic_score_codex":0.021851746,"about_ca_topic_score_gemma":0.029696075,"teacher_disagreement_score":0.1037403,"about_ca_system_score_codex":0.004834516,"about_ca_system_score_gemma":0.0059349365,"threshold_uncertainty_score":0.3470459},"labels":[],"label_agreement":null},{"id":"W3088315510","doi":"10.1109/ibdap50342.2020.9245462","title":"Towards a Natural Language Query Processing System","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; RDF query language; Query language; Query expansion; View; Query optimization; Natural language user interface; Web search query; Query by Example; Sargable; Web query classification; Information retrieval; Data control language; Semantic query; Database; Natural language; Database design; Natural language processing; Search engine","score_opus":0.01797519539715849,"score_gpt":0.27408284097476837,"score_spread":0.2561076455776099,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3088315510","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":[0.0051034084,0.00025907173,0.9420761,0.0011895606,0.00009880895,0.00053925306,0.0012396523,0.04759095,0.0019032953],"genre_scores_gemma":[0.037344437,0.00029945915,0.94897825,0.0010796246,0.00009949369,0.00052060664,0.006153141,0.001889878,0.003635247],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9914038,0.0022174984,0.0014317553,0.0017990537,0.0027466035,0.0004011365],"domain_scores_gemma":[0.9909485,0.003061078,0.0004314334,0.0017602189,0.0034335651,0.0003651767],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010356436,0.0012688066,0.0015964166,0.0031784307,0.0013640007,0.0076465756,0.004719122,0.0026861888,0.005792813],"category_scores_gemma":[0.0149905225,0.00132075,0.0021757507,0.0027545043,0.0022620102,0.0098402575,0.0051485184,0.0047588097,0.006368903],"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":[0.0022560565,0.0011274846,0.0047333166,0.00215542,0.00036228215,0.0019046963,0.0050495695,0.031351537,0.12657504,0.19806632,0.12511247,0.5013058],"study_design_scores_gemma":[0.00038096088,0.00045084997,0.0010271118,0.0002464087,0.00023526701,0.0008891197,0.0012781534,0.6136319,0.07648203,0.12681812,0.17829028,0.0002698348],"about_ca_topic_score_codex":0.01248613,"about_ca_topic_score_gemma":0.0071566836,"teacher_disagreement_score":0.01248613,"about_ca_system_score_codex":0.002236415,"about_ca_system_score_gemma":0.00351686,"threshold_uncertainty_score":0.054770768},"labels":[],"label_agreement":null},{"id":"W3093060337","doi":"10.1145/640128.604132","title":"The essence of XML","year":2003,"lang":"en","type":"article","venue":"ACM SIGPLAN Notices","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bell (Canada)","funders":"","keywords":"XPath; Computer science; XML Schema Editor; Document Structure Description; XQuery; XML validation; XML Schema (W3C); Programming language; Streaming XML; Efficient XML Interchange; Information retrieval; RELAX NG; XML; Document type definition; World Wide Web","score_opus":0.015706351964519357,"score_gpt":0.2509543156734476,"score_spread":0.23524796370892825,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3093060337","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":[0.0059891646,0.03232485,0.5945636,0.039944496,0.0052023306,0.00047701198,0.0037837478,0.0035881072,0.3141267],"genre_scores_gemma":[0.15954173,0.046536252,0.567459,0.029401686,0.0068014716,0.0012807887,0.007657138,0.0025535226,0.17876837],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9942154,0.0018791696,0.00057417346,0.0008765091,0.0021772673,0.00027739516],"domain_scores_gemma":[0.9937789,0.002554307,0.00046873602,0.0020633906,0.0008595629,0.0002750705],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0042340094,0.00080585893,0.000784306,0.0027057417,0.002179882,0.009970904,0.0023175494,0.0032814308,0.012111209],"category_scores_gemma":[0.012109253,0.00059429044,0.00092480704,0.0045194556,0.0074348194,0.014780734,0.0056431876,0.0047640745,0.0069203386],"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":[0.000016782047,0.000011784179,0.00021323065,0.00023085409,0.000016607615,0.000116877745,0.0010227036,0.00045310298,0.00058255,0.92537147,0.020034334,0.05192962],"study_design_scores_gemma":[0.000006259376,0.000016182394,0.00014567337,0.0002799038,0.000009625726,0.00033778092,0.00029309993,0.00054443144,0.00042352354,0.25013986,0.7477864,0.000017273629],"about_ca_topic_score_codex":0.0026607532,"about_ca_topic_score_gemma":0.0014622583,"teacher_disagreement_score":0.012111209,"about_ca_system_score_codex":0.0015222498,"about_ca_system_score_gemma":0.00289554,"threshold_uncertainty_score":0.04051608},"labels":[],"label_agreement":null},{"id":"W3096138397","doi":"10.3390/sym12111799","title":"DSP: Schema Design for Non-Relational Applications","year":2020,"lang":"en","type":"article","venue":"Symmetry","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"NoSQL; Computer science; Relational database; Schema (genetic algorithms); Semi-structured model; Database schema; SQL; Database; Star schema; Conceptual schema; Big data; Data mining; Database design; Information retrieval","score_opus":0.05050892290811986,"score_gpt":0.2765926388141499,"score_spread":0.22608371590603005,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3096138397","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":[0.0042424602,0.00023027416,0.98958695,0.00028577406,0.000046078203,0.00033735286,0.0003299135,0.0027859947,0.0021551228],"genre_scores_gemma":[0.06911988,0.00059554353,0.9247402,0.00025679407,0.00003773277,0.00043523984,0.0018604427,0.0008122496,0.0021418424],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9959019,0.0012684651,0.00079006713,0.000497522,0.0013833565,0.00015874143],"domain_scores_gemma":[0.9950165,0.0012868992,0.00043942788,0.001946696,0.0010984325,0.00021211614],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00608891,0.00063356303,0.00037492532,0.00075640006,0.0005168341,0.0032862378,0.0028976211,0.00097336515,0.003562675],"category_scores_gemma":[0.011332865,0.00082937547,0.0011519563,0.0012073013,0.0009396757,0.005374342,0.0023948026,0.0017522449,0.0017019316],"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":[0.00044392637,0.00036866372,0.0041626,0.0018222231,0.0001577617,0.0006451577,0.0020498906,0.06160916,0.049359415,0.5273613,0.025418205,0.3266017],"study_design_scores_gemma":[0.00016815335,0.00046047222,0.0011125223,0.00045640624,0.00010885706,0.0013871818,0.00061233004,0.4612148,0.052092012,0.12710534,0.35518953,0.00009235654],"about_ca_topic_score_codex":0.0011343191,"about_ca_topic_score_gemma":0.0010320718,"teacher_disagreement_score":0.00608891,"about_ca_system_score_codex":0.00093265285,"about_ca_system_score_gemma":0.0020289517,"threshold_uncertainty_score":0.032201648},"labels":[],"label_agreement":null},{"id":"W3099617739","doi":"10.1109/wimob50308.2020.9253426","title":"Data Stream Query Processing on Mobile Devices","year":2020,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Computer science; Stream processing; Query optimization; Database; Distributed computing","score_opus":0.06759799372661951,"score_gpt":0.30708726287702315,"score_spread":0.23948926915040364,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3099617739","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":[0.1035249,0.0020681955,0.87003446,0.00082822854,0.00022564968,0.00046967313,0.0010166203,0.009746316,0.012085959],"genre_scores_gemma":[0.6854853,0.0011174044,0.3030311,0.00034482792,0.0001564486,0.00026899992,0.0013606529,0.00033075726,0.007904434],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991246,0.00017104948,0.00008838592,0.00015906144,0.0003448309,0.000112094],"domain_scores_gemma":[0.9992681,0.00023827418,0.000042522177,0.00015992121,0.00022984859,0.00006128732],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007710081,0.00051699026,0.00088086637,0.0008234442,0.0006578283,0.0020143152,0.0010637525,0.00077587477,0.002835211],"category_scores_gemma":[0.0021014311,0.0002470903,0.0005049449,0.0010918867,0.00034632938,0.0015105846,0.00096973946,0.0005532024,0.0009065394],"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":[0.0032200657,0.00040558062,0.008888233,0.00093718106,0.0002977448,0.0036543394,0.00213657,0.06994397,0.16160415,0.09409214,0.056531947,0.59828806],"study_design_scores_gemma":[0.00022457102,0.0003161461,0.0033136962,0.00012337156,0.000113183385,0.0010450073,0.0009849715,0.8144043,0.06682026,0.027729942,0.08484595,0.000078517616],"about_ca_topic_score_codex":0.0039486275,"about_ca_topic_score_gemma":0.0031487066,"teacher_disagreement_score":0.0039486275,"about_ca_system_score_codex":0.00071684696,"about_ca_system_score_gemma":0.00051691564,"threshold_uncertainty_score":0.009484708},"labels":[],"label_agreement":null},{"id":"W3099789104","doi":"10.5220/0010132201890196","title":"Intensional Model for Data Integration System in Open Environment","year":2020,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","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":"Western University","funders":"","keywords":"Computer science; Data modeling; Data integration; Data model (GIS); Database; Software engineering; Artificial intelligence","score_opus":0.17241378053867934,"score_gpt":0.3084980254220243,"score_spread":0.13608424488334497,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3099789104","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":[0.02045858,0.00049311575,0.9522772,0.001074775,0.0001989161,0.00017921162,0.0005910147,0.0035073366,0.02121995],"genre_scores_gemma":[0.48228124,0.0007245399,0.48064122,0.001056609,0.00043359256,0.00049114745,0.0017731359,0.00083240954,0.03176616],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99745196,0.0005211278,0.00026809477,0.0005607746,0.0008919085,0.00030603312],"domain_scores_gemma":[0.9985821,0.00025946932,0.000093417235,0.00053529744,0.00043749617,0.00009216368],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026916463,0.00050933636,0.00053455326,0.0014685036,0.0011102564,0.0042784074,0.0023988388,0.0011815486,0.008079017],"category_scores_gemma":[0.0031497783,0.00043389408,0.001213863,0.0014003096,0.0014027322,0.008994427,0.002430685,0.0018706546,0.0016183571],"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":[0.00017640532,0.00013965834,0.0014798464,0.00019473402,0.000054133783,0.00037044828,0.00075838255,0.011494453,0.0056713377,0.92140555,0.007498825,0.050756223],"study_design_scores_gemma":[0.000077189834,0.00014381022,0.00080940436,0.00011780555,0.00020736142,0.00067499274,0.00028429448,0.2998747,0.00911328,0.61742634,0.07119386,0.00007693643],"about_ca_topic_score_codex":0.0026920086,"about_ca_topic_score_gemma":0.0023840407,"teacher_disagreement_score":0.008079017,"about_ca_system_score_codex":0.0011971644,"about_ca_system_score_gemma":0.0013957974,"threshold_uncertainty_score":0.02702701},"labels":[],"label_agreement":null},{"id":"W3105928468","doi":"","title":"Research Guides: Graduate Specialist Program (New Brunswick Libraries): SQL","year":2018,"lang":"en","type":"libguides","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"SQL; Computer science; Library science; World Wide Web; Database","score_opus":0.14997199755354926,"score_gpt":0.3858253569506713,"score_spread":0.23585335939712207,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3105928468","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014248203,0.0015464361,0.029540526,0.01209508,0.0017607822,0.0008010041,0.04323099,0.044877768,0.86472255],"genre_scores_gemma":[0.0035825346,0.0015334473,0.010391019,0.000904564,0.00038620573,0.00019896669,0.017181184,0.0090502305,0.9567719],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99543285,0.00060449535,0.0004266627,0.0009638431,0.002348882,0.0002232903],"domain_scores_gemma":[0.96320087,0.006069266,0.0009787893,0.004713688,0.021910302,0.003127098],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.007015073,0.0020055186,0.0016825444,0.008020206,0.0020600078,0.010020342,0.0031244059,0.0016569085,0.7543109],"category_scores_gemma":[0.038354065,0.0015933028,0.00062574074,0.012597689,0.0013062714,0.008818842,0.0029628936,0.0024620607,0.7211983],"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":[0.000025924392,0.00003534679,0.00021049094,0.00016775384,0.0000019140793,0.00001364034,0.00009382377,0.00006402833,0.00034947303,0.006123942,0.8980451,0.09486862],"study_design_scores_gemma":[0.00002233031,0.000023882923,0.0005472956,0.00022240782,0.0000076154524,0.000050476898,0.00014661085,0.00044935817,0.0012036279,0.002337423,0.9949759,0.00001312183],"about_ca_topic_score_codex":0.033391442,"about_ca_topic_score_gemma":0.041386705,"teacher_disagreement_score":0.7543109,"about_ca_system_score_codex":0.0049333926,"about_ca_system_score_gemma":0.012618217,"threshold_uncertainty_score":0.35044563},"labels":[],"label_agreement":null},{"id":"W3111141572","doi":"10.14778/3461535.3461552","title":"Are we ready for learned cardinality estimation?","year":2021,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":94,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Cardinality (data modeling); Inference; Focus (optics); Ask price; Domain (mathematical analysis); Workload; Data modeling","score_opus":0.07254020723674541,"score_gpt":0.3182425928154698,"score_spread":0.24570238557872437,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111141572","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":[0.0552291,0.0022674068,0.9302608,0.005571324,0.00022214995,0.00013366235,0.00066064514,0.0037181743,0.0019368448],"genre_scores_gemma":[0.51565546,0.0012035336,0.47727126,0.0015539164,0.00032224803,0.00019644896,0.0017512414,0.0007182777,0.0013276407],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99075186,0.004175003,0.0005388198,0.001923136,0.0020291833,0.0005819459],"domain_scores_gemma":[0.95412374,0.024429204,0.0030440444,0.013396651,0.003982592,0.0010237575],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010296117,0.0014130857,0.002231424,0.0009575972,0.00067134085,0.0040491675,0.0044897636,0.0021815235,0.0019685868],"category_scores_gemma":[0.070840836,0.0012063334,0.0011529257,0.0016133662,0.0020303146,0.017070213,0.0033729798,0.0052531376,0.0012415331],"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":[0.0006511849,0.00044301245,0.025706664,0.0006423184,0.0003528586,0.00017248809,0.0006470481,0.5115672,0.0056395573,0.039612167,0.019975323,0.39459026],"study_design_scores_gemma":[0.00003348662,0.0000715236,0.001021306,0.00005750674,0.000031941756,0.00008474244,0.0001983291,0.9613079,0.002418015,0.03167138,0.0030735321,0.000030409592],"about_ca_topic_score_codex":0.0053753257,"about_ca_topic_score_gemma":0.0068178466,"teacher_disagreement_score":0.010296117,"about_ca_system_score_codex":0.002344457,"about_ca_system_score_gemma":0.0031298331,"threshold_uncertainty_score":0.054451764},"labels":[],"label_agreement":null},{"id":"W3111316923","doi":"10.1145/376284.375749","title":"Exploiting constraint-like data characterizations in query optimization","year":2001,"lang":"en","type":"article","venue":"ACM SIGMOD Record","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada); York University","funders":"","keywords":"Computer science; Query optimization; Constraint (computer-aided design); Data integrity; Binary constraint; Exploit; Constraint programming; USable; Data mining; Database; Constraint satisfaction; Constraint logic programming; Mathematical optimization; Probabilistic logic; Artificial intelligence","score_opus":0.0655448349157439,"score_gpt":0.28878375790549454,"score_spread":0.22323892298975065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111316923","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":[0.013516058,0.00053514296,0.97772753,0.0012988885,0.00007417897,0.00022288981,0.0016169639,0.0016996318,0.0033087023],"genre_scores_gemma":[0.25153238,0.00085434155,0.7365792,0.0010510901,0.00026094675,0.00076257816,0.00386407,0.0019154547,0.0031799872],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.97685224,0.0062505715,0.0032154787,0.002623151,0.009821761,0.001236855],"domain_scores_gemma":[0.94747037,0.032541674,0.0049756127,0.009590062,0.0048651593,0.0005569927],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012322414,0.0018573639,0.0020265568,0.0038236992,0.0014397112,0.008370128,0.003457537,0.0017059271,0.0039816382],"category_scores_gemma":[0.052416146,0.0016825604,0.0028108,0.008371071,0.0035572944,0.016683936,0.0044934647,0.005209405,0.0010982346],"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":[0.0006956754,0.00028262933,0.0076555107,0.0010914839,0.00032882366,0.0005723924,0.0016873954,0.30866703,0.012508991,0.47679797,0.012657132,0.17705506],"study_design_scores_gemma":[0.000054396474,0.00009577501,0.0007337798,0.000120030636,0.00007058344,0.0002334465,0.0003703543,0.6821553,0.009037998,0.28916076,0.017853035,0.000114547904],"about_ca_topic_score_codex":0.008247627,"about_ca_topic_score_gemma":0.010639227,"teacher_disagreement_score":0.012322414,"about_ca_system_score_codex":0.003131245,"about_ca_system_score_gemma":0.003382669,"threshold_uncertainty_score":0.065167904},"labels":[],"label_agreement":null},{"id":"W3115554056","doi":"10.1145/3252255","title":"Session details: Session on Data and Knowledge Discovery for Simulation","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Northern British Columbia","funders":"","keywords":"Session (web analytics); Computer science; World Wide Web","score_opus":0.060015078901408656,"score_gpt":0.3456871962788432,"score_spread":0.28567211737743453,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3115554056","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0040250686,0.0054472447,0.053532436,0.04517121,0.050264258,0.0038155897,0.08437368,0.024009341,0.7293611],"genre_scores_gemma":[0.026275592,0.0040859384,0.014670858,0.0041971533,0.013191307,0.0016198566,0.04396861,0.004499149,0.8874915],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989772,0.00027726003,0.0000564974,0.00023290771,0.00031701857,0.0001392486],"domain_scores_gemma":[0.99436486,0.001881735,0.00009427024,0.0010673373,0.0010257623,0.0015660814],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0031153741,0.0014741773,0.0027077624,0.0008328294,0.0018148818,0.006013441,0.0017969086,0.003322619,0.8255565],"category_scores_gemma":[0.007365295,0.00045385514,0.0019529874,0.0012022502,0.00047769945,0.0032080195,0.003868996,0.0027034355,0.6197539],"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":[0.00036033435,0.000113246344,0.00012824136,0.00015515505,0.000018765695,0.000036630612,0.000024968285,0.0001653956,0.00092746457,0.0017997691,0.9654363,0.03083375],"study_design_scores_gemma":[0.00021175291,0.00013819952,0.00072797877,0.00009749513,0.000025084064,0.00007007546,0.00005236016,0.0019410001,0.0011247629,0.005105504,0.99047196,0.00003395946],"about_ca_topic_score_codex":0.001645488,"about_ca_topic_score_gemma":0.0028125606,"teacher_disagreement_score":0.17444348,"about_ca_system_score_codex":0.0009715141,"about_ca_system_score_gemma":0.002127706,"threshold_uncertainty_score":0.24882239},"labels":[],"label_agreement":null},{"id":"W3116324870","doi":"10.1109/iemcon51383.2020.9284904","title":"A Streaming Stock Market Application Adapted to a Mobile Device","year":2020,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Computer science; Stream processing; Data stream mining; Data stream; Mobile device; Mobile computing; Computer network; Database; Mobile telephony; Server; Real-time computing; Distributed computing; Operating system; Telecommunications; Mobile radio; Data mining","score_opus":0.01936156703054924,"score_gpt":0.2602897676912517,"score_spread":0.24092820066070247,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3116324870","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":[0.07759785,0.00086556555,0.8362248,0.0006699856,0.00037600225,0.0018742166,0.0012619591,0.051001593,0.030128084],"genre_scores_gemma":[0.46417627,0.001146892,0.48203975,0.001079819,0.00037066903,0.00091078243,0.0026689724,0.0022278056,0.045379024],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99971586,0.000037809754,0.000027823733,0.000056971643,0.00012527303,0.000036354908],"domain_scores_gemma":[0.99954164,0.00013816329,0.000027262427,0.00006167353,0.00015786735,0.000073326206],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039521448,0.0005714668,0.00045866234,0.00064870116,0.0003041748,0.0009071468,0.0011107144,0.0006953199,0.010072669],"category_scores_gemma":[0.0011240869,0.00031100103,0.0003299394,0.0004535684,0.00018168364,0.0010065766,0.0006422658,0.0005773239,0.0030831527],"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":[0.002209183,0.00079370977,0.0070715873,0.0011290594,0.00018687765,0.0034303225,0.0011069922,0.010145035,0.27888456,0.017126793,0.06368769,0.61422825],"study_design_scores_gemma":[0.00081325095,0.0012454024,0.0115366625,0.00024137169,0.00038978513,0.004249952,0.00033105712,0.50865096,0.13231407,0.0073336693,0.33264655,0.0002471785],"about_ca_topic_score_codex":0.0010670339,"about_ca_topic_score_gemma":0.0009901102,"teacher_disagreement_score":0.010072669,"about_ca_system_score_codex":0.00023087383,"about_ca_system_score_gemma":0.00033270894,"threshold_uncertainty_score":0.033696473},"labels":[],"label_agreement":null},{"id":"W3124893432","doi":"10.1504/ijdmmm.2021.10035065","title":"A formal theoretical framework for a flexible classification process","year":2021,"lang":"en","type":"article","venue":"International Journal of Data Mining Modelling and Management","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Computer science; Flexibility (engineering); Process (computing); Formal language; Adaptation (eye); Software engineering; Artificial intelligence; Data science; Knowledge management; Natural language processing; Programming language","score_opus":0.09862009684106916,"score_gpt":0.36801733138853854,"score_spread":0.2693972345474694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3124893432","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":[0.0034985233,0.0003692623,0.9793058,0.0030720297,0.0001421122,0.000129729,0.00018624833,0.000192122,0.013104158],"genre_scores_gemma":[0.19347256,0.00075575634,0.78996587,0.0012051399,0.0006366389,0.0009383504,0.0006395029,0.0001893723,0.012196755],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98854625,0.0043033008,0.0013160191,0.002034901,0.0029364298,0.0008630948],"domain_scores_gemma":[0.98169553,0.011888697,0.0014591056,0.0021325883,0.002161535,0.0006625657],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.016653791,0.00083138875,0.00084729923,0.005144597,0.0038927956,0.009163524,0.0041773296,0.0043957327,0.009953889],"category_scores_gemma":[0.021444624,0.0008912974,0.0032942772,0.004024043,0.014691632,0.018013148,0.0049868645,0.005089126,0.0028000548],"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":[0.0000029095588,0.000008191856,0.00006387608,0.000017018137,0.000003060466,0.000031088464,0.00014417668,0.0006215043,0.00007656705,0.99692625,0.00029574416,0.0018095124],"study_design_scores_gemma":[0.000014324699,0.000012503427,0.00004709294,0.00003054831,0.000008058589,0.000080287755,0.00007805638,0.010758874,0.00019331597,0.9790259,0.009739905,0.000011159482],"about_ca_topic_score_codex":0.0038097298,"about_ca_topic_score_gemma":0.0019569173,"teacher_disagreement_score":0.016653791,"about_ca_system_score_codex":0.0050987587,"about_ca_system_score_gemma":0.003947707,"threshold_uncertainty_score":0.088074744},"labels":[],"label_agreement":null},{"id":"W3126368050","doi":"","title":"R3V3RS3: Querying for Syntactical Patterns of Conditional Compilation Usage","year":2009,"lang":"en","type":"article","venue":"VUBIR (Vrije Universiteit Brussel)","topic":"Advanced Database Systems and Queries","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":"Queen's University","funders":"","keywords":"Computer science; Natural language processing; Information retrieval","score_opus":0.013582532987215002,"score_gpt":0.24479498482330037,"score_spread":0.23121245183608535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3126368050","genre_codex":"software","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":[0.03813724,0.00034662793,0.23928359,0.00036566486,0.00011889936,0.00021374982,0.023425719,0.6914306,0.0066778893],"genre_scores_gemma":[0.49902463,0.0004603141,0.21598536,0.0006969077,0.00017331407,0.0006706824,0.095629066,0.17700215,0.010357705],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99554646,0.0007378799,0.00047930537,0.0012388638,0.0014699175,0.00052749796],"domain_scores_gemma":[0.9926484,0.0033352799,0.00049287255,0.002591133,0.0007092152,0.00022312402],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002835761,0.002818321,0.0018231068,0.0033470308,0.0009531085,0.0037925404,0.00448588,0.0022067954,0.023341473],"category_scores_gemma":[0.01163528,0.0020850978,0.0031335037,0.0034823336,0.0015306569,0.0060350066,0.0044612545,0.0017286933,0.007309771],"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":[0.004982088,0.00046536315,0.0380302,0.00290517,0.000757178,0.0017249543,0.003926212,0.019864867,0.073055744,0.050010666,0.4119459,0.39233166],"study_design_scores_gemma":[0.0012520215,0.00056629756,0.01978505,0.00054922106,0.0006250303,0.0021152652,0.0013579578,0.37004238,0.21244332,0.06400601,0.3262607,0.0009967189],"about_ca_topic_score_codex":0.013590944,"about_ca_topic_score_gemma":0.014119826,"teacher_disagreement_score":0.023341473,"about_ca_system_score_codex":0.0018365294,"about_ca_system_score_gemma":0.0021161735,"threshold_uncertainty_score":0.078085005},"labels":[],"label_agreement":null},{"id":"W3136198913","doi":"10.1145/3261861","title":"Session details: Database principle","year":2006,"lang":"en","type":"article","venue":"ACM SIGMOD Record","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Session (web analytics); Database; Information retrieval; Programming language; World Wide Web","score_opus":0.020976961408618672,"score_gpt":0.2764887543090294,"score_spread":0.25551179290041076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3136198913","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010556744,0.009137281,0.017437464,0.028591411,0.015303446,0.00047521113,0.014675155,0.0033484807,0.9099759],"genre_scores_gemma":[0.02340777,0.0066188565,0.0054102065,0.004402653,0.009811939,0.0002849167,0.008401434,0.0010711061,0.9405912],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9981817,0.00041448427,0.00010118701,0.00049650914,0.0006401483,0.00016595008],"domain_scores_gemma":[0.9963882,0.0011610233,0.000121307996,0.001080489,0.0006243886,0.00062465714],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0025432429,0.0010684233,0.002055082,0.0013379406,0.003033555,0.008892196,0.0022716983,0.0039307293,0.7449129],"category_scores_gemma":[0.007563874,0.0008691293,0.0012786089,0.0030365817,0.0013556508,0.005613128,0.00378286,0.0046311095,0.63862675],"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":[0.00015374333,0.000058575402,0.00012637179,0.00023346764,0.000015806214,0.000042888045,0.00004426866,0.00007450191,0.0010381818,0.038155094,0.9222961,0.037760913],"study_design_scores_gemma":[0.00006828202,0.00002727544,0.00026549867,0.00006151946,0.000012773444,0.0001241126,0.000032963744,0.00024950146,0.00056436367,0.012964362,0.98561674,0.0000124860935],"about_ca_topic_score_codex":0.00095629215,"about_ca_topic_score_gemma":0.0011247194,"teacher_disagreement_score":0.7449129,"about_ca_system_score_codex":0.0020604725,"about_ca_system_score_gemma":0.001719207,"threshold_uncertainty_score":0.3638507},"labels":[],"label_agreement":null},{"id":"W3141776985","doi":"10.1109/wsc.2011.6147976","title":"RMSim: A java library for simulating revenue management systems","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Java; Computer science; Flexibility (engineering); Revenue; Process (computing); Extensibility; Control (management); Revenue management; Event (particle physics); Software engineering; Distributed computing; Operations research; Programming language; Finance; Engineering; Business; Artificial intelligence","score_opus":0.039854819642362434,"score_gpt":0.24228386971284185,"score_spread":0.20242905007047943,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3141776985","genre_codex":"methods","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010579283,0.00014421302,0.8916641,0.00016043875,0.00011780991,0.00031077786,0.0030158316,0.08828852,0.005719087],"genre_scores_gemma":[0.19246148,0.00089621847,0.7557746,0.00052127085,0.00012126453,0.002093335,0.011171173,0.026091723,0.010868907],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99930954,0.0001618652,0.00008470246,0.00009890413,0.00026154314,0.00008348873],"domain_scores_gemma":[0.99803823,0.0011187755,0.00017145308,0.00027293625,0.00027684783,0.000121756544],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016364137,0.001069675,0.000891173,0.0008596227,0.00045938627,0.0013459572,0.004236994,0.0013932077,0.010041963],"category_scores_gemma":[0.0042915074,0.000968546,0.0013008113,0.00067282334,0.0005825651,0.0015657777,0.0012935465,0.0019926557,0.0025210609],"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":[0.00069518894,0.0007694762,0.008718825,0.0015749299,0.00039794954,0.0006285185,0.0006212367,0.7196051,0.020996938,0.039536834,0.061234362,0.14522064],"study_design_scores_gemma":[0.00018332664,0.0000677995,0.0008035212,0.000051753905,0.000050793908,0.00012544522,0.000026465192,0.94416916,0.008863744,0.0066604945,0.03894417,0.00005322968],"about_ca_topic_score_codex":0.0059790886,"about_ca_topic_score_gemma":0.0058743986,"teacher_disagreement_score":0.010041963,"about_ca_system_score_codex":0.0007146431,"about_ca_system_score_gemma":0.0012513866,"threshold_uncertainty_score":0.033593655},"labels":[],"label_agreement":null},{"id":"W3143785297","doi":"10.1007/978-3-030-68514-0_5","title":"Sequential and Parallel Models","year":2021,"lang":"en","type":"book-chapter","venue":"SpringerBriefs in optimization","topic":"Advanced Database Systems and Queries","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":"Wilfrid Laurier University","funders":"","keywords":"Computer science; Portfolio; Computation; Parallel processing; Resource (disambiguation); Parallel computing; Resource allocation; Unit (ring theory); Theoretical computer science; Algorithm; Mathematics; Finance","score_opus":0.026037008159622513,"score_gpt":0.23202201917265639,"score_spread":0.20598501101303388,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3143785297","genre_codex":"other","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":[0.011785864,0.008611345,0.4741997,0.009017308,0.0015726996,0.000093939154,0.0009740884,0.0007838338,0.49296123],"genre_scores_gemma":[0.41729397,0.010104501,0.07733996,0.0020255346,0.0028424868,0.00039193206,0.0014951602,0.001053584,0.48745283],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9992034,0.00020987676,0.000029338134,0.00017534255,0.00028918084,0.00009285944],"domain_scores_gemma":[0.9989961,0.00042502492,0.000061486746,0.00030607544,0.0001361345,0.0000751989],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00085481384,0.0011634579,0.0009283517,0.0007099112,0.0008700039,0.0031590024,0.0014135857,0.0014287852,0.03852303],"category_scores_gemma":[0.0038511867,0.00063399004,0.0008758094,0.0016548542,0.001943198,0.0062353704,0.0015636926,0.0023337833,0.006188071],"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":[0.00001609457,0.000022100905,0.000082238024,0.000036238034,0.00000837159,0.000029601422,0.000042447926,0.007953471,0.00011116653,0.96505564,0.01545173,0.011190922],"study_design_scores_gemma":[0.000006964283,0.000007966958,0.000055333094,0.000009421343,0.000006103925,0.00003370379,0.000020377192,0.021891506,0.000061621766,0.95626545,0.021637809,0.000003727058],"about_ca_topic_score_codex":0.003502598,"about_ca_topic_score_gemma":0.0026445831,"teacher_disagreement_score":0.03852303,"about_ca_system_score_codex":0.001313558,"about_ca_system_score_gemma":0.0012706872,"threshold_uncertainty_score":0.12887233},"labels":[],"label_agreement":null},{"id":"W3147966060","doi":"10.1109/ideas.2007.4318084","title":"Adaptive Execution of Stream Window Joins in a Limited Memory Environment","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Joins; Data stream mining; Sliding window protocol; Data stream; Window (computing); Parallel computing; Distributed computing; Volume (thermodynamics); Real-time computing; Algorithm; Data mining; Operating system","score_opus":0.015469293834898645,"score_gpt":0.2254680909238218,"score_spread":0.20999879708892316,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3147966060","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":[0.39418224,0.00044755996,0.6002518,0.000097030716,0.0000648843,0.000111994814,0.000092018534,0.002850499,0.0019019274],"genre_scores_gemma":[0.7895462,0.0001815425,0.20820814,0.000033581924,0.000045523608,0.00009556642,0.0002660424,0.0001633162,0.0014600148],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999111,0.00020050086,0.00008627021,0.0002112507,0.00030467514,0.000086359854],"domain_scores_gemma":[0.9980909,0.000867418,0.00016693464,0.00046277913,0.00024221557,0.00016968042],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014368014,0.000412069,0.0005585364,0.00039371048,0.00053091475,0.0009118984,0.0011864891,0.00037725127,0.00087585277],"category_scores_gemma":[0.003986547,0.00030910125,0.0002971106,0.00052186084,0.0004098266,0.0012584853,0.0011784425,0.00045142832,0.00022656328],"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":[0.006147852,0.00067548954,0.016602296,0.00032425308,0.00023306701,0.001172303,0.0011931546,0.23463127,0.25079265,0.024624333,0.0039342474,0.45966908],"study_design_scores_gemma":[0.0001242745,0.00022357405,0.0010115537,0.0000073032315,0.000030701223,0.00015072191,0.00006627746,0.94754934,0.04371355,0.004684108,0.0024231616,0.00001542224],"about_ca_topic_score_codex":0.0007158455,"about_ca_topic_score_gemma":0.00084724283,"teacher_disagreement_score":0.0014368014,"about_ca_system_score_codex":0.00027665388,"about_ca_system_score_gemma":0.00047374345,"threshold_uncertainty_score":0.0075986385},"labels":[],"label_agreement":null},{"id":"W3150796452","doi":"10.1109/ideas.2007.4318113","title":"A Generalized Model for Mediator Based Information Integration","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Schema (genetic algorithms); Information integration; Theoretical computer science; Data integration; Metadata; Dimension (graph theory); Semi-structured model; Relational database; Data mining; Information retrieval; Mathematics; Database model; Pure mathematics","score_opus":0.020337774383326027,"score_gpt":0.2707657912745673,"score_spread":0.2504280168912413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3150796452","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":[0.0043927734,0.0005745222,0.96664166,0.002443768,0.00012020644,0.00027040465,0.00017787839,0.0007607547,0.024617959],"genre_scores_gemma":[0.26406914,0.0016821042,0.7079439,0.0018089085,0.000292551,0.0018187623,0.00079729175,0.0002590845,0.021328278],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9960414,0.001453975,0.0003533378,0.0006651109,0.0011385377,0.00034761743],"domain_scores_gemma":[0.99856585,0.00044309115,0.00010508391,0.00045803792,0.00030849202,0.000119396915],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0041066557,0.000830447,0.0010093166,0.001577806,0.0019393953,0.007837394,0.0035308914,0.0042926753,0.0064701587],"category_scores_gemma":[0.004618332,0.0007318175,0.0021423448,0.0031317705,0.0031223882,0.009064416,0.0056188935,0.0032841708,0.0024740195],"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":[0.000025819276,0.00002144461,0.00012517867,0.000051081035,0.000028205619,0.00034425766,0.00046063648,0.008447858,0.0010961258,0.980547,0.001834973,0.007017527],"study_design_scores_gemma":[0.00006838045,0.000048793678,0.00008600912,0.000066799344,0.00005514209,0.000426852,0.0002336791,0.0958119,0.0013367402,0.849319,0.052508537,0.000038175775],"about_ca_topic_score_codex":0.0038719573,"about_ca_topic_score_gemma":0.0022051097,"teacher_disagreement_score":0.007837394,"about_ca_system_score_codex":0.002489074,"about_ca_system_score_gemma":0.002557498,"threshold_uncertainty_score":0.021718323},"labels":[],"label_agreement":null},{"id":"W3161742868","doi":"10.14778/3529337.3529339","title":"Accurate summary-based cardinality estimation through the lens of cardinality estimation graphs","year":2022,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Estimator; Cardinality (data modeling); Graph; Mathematics; Computer science; Joins; Statistics; Mathematical optimization; Theoretical computer science; Data mining","score_opus":0.026187567913794885,"score_gpt":0.2648038244692834,"score_spread":0.23861625655548852,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3161742868","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":[0.0807599,0.0007284549,0.9125609,0.00065085833,0.000045080866,0.00008170006,0.00074326526,0.002106981,0.0023230275],"genre_scores_gemma":[0.710801,0.00036996137,0.28605378,0.00019785731,0.0000614448,0.00011692689,0.0011065239,0.00041577418,0.00087675446],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99035686,0.0039434135,0.000497622,0.0015554182,0.0031821865,0.0004645324],"domain_scores_gemma":[0.940362,0.03990454,0.0053742784,0.009975044,0.0036669183,0.0007172966],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009508972,0.0010286944,0.0013238619,0.002468712,0.00079796574,0.0041590454,0.002165312,0.0012417766,0.0017193026],"category_scores_gemma":[0.079818256,0.00074499525,0.00052172085,0.0028824336,0.0013712967,0.01021967,0.003056455,0.0023052283,0.000407356],"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":[0.0011342502,0.00019719865,0.022120662,0.00041682826,0.00020069472,0.00027267006,0.0015025572,0.47150725,0.014263001,0.26878235,0.0066028177,0.2129997],"study_design_scores_gemma":[0.000021532742,0.000075542746,0.001365363,0.000028428314,0.000028956272,0.00010516948,0.0001985632,0.91141003,0.006171082,0.077845745,0.002715219,0.000034351648],"about_ca_topic_score_codex":0.0031630443,"about_ca_topic_score_gemma":0.0021242576,"teacher_disagreement_score":0.009508972,"about_ca_system_score_codex":0.0022029171,"about_ca_system_score_gemma":0.0017766461,"threshold_uncertainty_score":0.050288856},"labels":[],"label_agreement":null},{"id":"W3170003207","doi":"10.1007/978-3-030-78230-6_16","title":"On the Usefulness of Linear Modular Arithmetic in Constraint Programming","year":2021,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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":"Polytechnique Montréal","funders":"","keywords":"Computer science; Modular design; Hash function; Theoretical computer science; Checksum; Linear programming; Mathematical optimization; Algorithm; Programming language; Mathematics","score_opus":0.02747435905450191,"score_gpt":0.2477633709259295,"score_spread":0.2202890118714276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3170003207","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":[0.020187324,0.013213184,0.70054007,0.008088967,0.0009954055,0.00006856001,0.00022401997,0.0006032712,0.25607914],"genre_scores_gemma":[0.454798,0.014226978,0.48285654,0.0030707156,0.004419428,0.00022777397,0.00038710292,0.0007393867,0.03927407],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9983987,0.00074448076,0.00008410077,0.00021099726,0.0004302185,0.00013138102],"domain_scores_gemma":[0.9855032,0.012923918,0.00025422842,0.00081355346,0.00038651878,0.00011861502],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034192365,0.0012721355,0.0008887898,0.0016295803,0.0012835187,0.0029885776,0.0020048278,0.0010224369,0.010710968],"category_scores_gemma":[0.014862763,0.0009920874,0.0011915609,0.004188528,0.007824753,0.010168338,0.0029450285,0.0055033835,0.0017398049],"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":[0.000032068885,0.000017535069,0.000085461914,0.000098208584,0.000008821459,0.000038512,0.00011420755,0.004846906,0.0002474371,0.95581293,0.0045843106,0.034113523],"study_design_scores_gemma":[0.000012013123,0.000012647057,0.00005840761,0.00004665796,0.000009930028,0.000030666783,0.000018906956,0.012728788,0.00021784416,0.9807123,0.0061410805,0.000010720262],"about_ca_topic_score_codex":0.0019869609,"about_ca_topic_score_gemma":0.0019483921,"teacher_disagreement_score":0.010710968,"about_ca_system_score_codex":0.0018818814,"about_ca_system_score_gemma":0.0007954134,"threshold_uncertainty_score":0.03583169},"labels":[],"label_agreement":null},{"id":"W3174680429","doi":"10.1145/3448016.3452794","title":"Klink: Progress-Aware Scheduling for Streaming Data Systems","year":2021,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Sapienza Università di Roma","keywords":"Computer science; Timestamp; Scheduling (production processes); Leverage (statistics); Real-time computing; Stream processing; Latency (audio); Distributed computing; Query plan; Sliding window protocol; Data stream; Window (computing); Operating system; Artificial intelligence; Sargable; Telecommunications; Search engine","score_opus":0.06721397898214153,"score_gpt":0.32477836417866396,"score_spread":0.2575643851965224,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3174680429","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":[0.055746045,0.0019569849,0.7923731,0.00070170674,0.0006217183,0.00064885936,0.002298106,0.13678196,0.008871529],"genre_scores_gemma":[0.53818506,0.00094772375,0.44649202,0.00037309944,0.0001986428,0.00040070235,0.0040313844,0.004240549,0.005130886],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99842983,0.0002405285,0.00020337645,0.00035650813,0.0005715824,0.00019817174],"domain_scores_gemma":[0.9966438,0.00097615353,0.0003812445,0.0009299268,0.0006786395,0.0003902423],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025306214,0.0013449994,0.0006656446,0.0010220824,0.0006548086,0.0017130637,0.002580806,0.0005159282,0.0038893025],"category_scores_gemma":[0.009431535,0.00070300134,0.00044912487,0.00085240544,0.00075025426,0.0031788899,0.0018389961,0.0016281294,0.0018170651],"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":[0.0034716947,0.0006270832,0.010937078,0.0014488375,0.0002164382,0.00036210354,0.0007386016,0.27341014,0.08141407,0.030756807,0.087401405,0.5092157],"study_design_scores_gemma":[0.00029311999,0.00031845408,0.001495806,0.00005544002,0.000051276766,0.00014388512,0.00010597318,0.92764926,0.029582784,0.014019585,0.026191011,0.000093407805],"about_ca_topic_score_codex":0.0050492,"about_ca_topic_score_gemma":0.0074940207,"teacher_disagreement_score":0.0050492,"about_ca_system_score_codex":0.0015026983,"about_ca_system_score_gemma":0.0035227523,"threshold_uncertainty_score":0.013383329},"labels":[],"label_agreement":null},{"id":"W3174728063","doi":"10.1109/icde51399.2021.00271","title":"Exploratory Data Analysis in SAP IQ Using Query-Time Sampling","year":2021,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Systems, Applications & Products in Data Processing (Canada)","funders":"","keywords":"Computer science; Online analytical processing; Relational database; Relational database management system; Data mining; Query optimization; Data warehouse; Database; Sampling (signal processing); Exploratory analysis; Information retrieval; Data science","score_opus":0.12808131751512034,"score_gpt":0.3384740585306235,"score_spread":0.21039274101550318,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3174728063","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":[0.032156453,0.00015133158,0.95389783,0.00017301459,0.000026438734,0.0001935708,0.00032470567,0.011685298,0.0013915099],"genre_scores_gemma":[0.30160373,0.00013533267,0.69529825,0.0001790898,0.00004725126,0.0002887898,0.0010219187,0.0005275733,0.00089806935],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99583566,0.0009859477,0.0003853414,0.00067789725,0.0018714193,0.0002437103],"domain_scores_gemma":[0.9888896,0.004114116,0.00045831804,0.0046058074,0.0016271403,0.00030499382],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0058225677,0.00072640064,0.0007633905,0.0012426339,0.00075227063,0.0026361924,0.0021471106,0.0006401516,0.0019985265],"category_scores_gemma":[0.017124984,0.00055209384,0.0007275701,0.0030396741,0.0011607546,0.0032367231,0.0020873672,0.0013227226,0.0006770345],"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":[0.0017155563,0.0004958176,0.025986547,0.00035304305,0.0002271749,0.00049571955,0.0021996396,0.10978874,0.046599668,0.07680657,0.013626008,0.72170544],"study_design_scores_gemma":[0.000084279985,0.00021144304,0.00178161,0.00001632792,0.000031131087,0.00025158832,0.00022323338,0.9514902,0.016145123,0.021806037,0.007925459,0.000033573662],"about_ca_topic_score_codex":0.006709168,"about_ca_topic_score_gemma":0.005306471,"teacher_disagreement_score":0.006709168,"about_ca_system_score_codex":0.0009095987,"about_ca_system_score_gemma":0.0027825453,"threshold_uncertainty_score":0.03079307},"labels":[],"label_agreement":null},{"id":"W3175773231","doi":"","title":"Systemic Behavior of Cooperative Search Algorithms","year":2002,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal; Université du Québec à Montréal; University of Manitoba","funders":"","keywords":"Computer science; Relevance (law); Representation (politics); Space (punctuation); Theoretical computer science; Information exchange; Mechanism (biology); Mathematical optimization; Algorithm; Mathematics","score_opus":0.01916340061527134,"score_gpt":0.263740366344034,"score_spread":0.2445769657287627,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3175773231","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":[0.35647193,0.00047461537,0.61335427,0.0014658936,0.0000311308,0.00016526562,0.00006743216,0.00041195992,0.027557548],"genre_scores_gemma":[0.9605222,0.00016668138,0.035749234,0.000121831734,0.000015747915,0.00017441974,0.000043786742,0.000037641243,0.003168473],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979528,0.0011231166,0.00006754012,0.0002816056,0.00040906298,0.00016576968],"domain_scores_gemma":[0.9936365,0.004456948,0.0005618593,0.0005708224,0.0004962854,0.0002776522],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027445627,0.0003878858,0.0005741075,0.0006907604,0.00082082953,0.0017058363,0.0008593091,0.0014057391,0.002881577],"category_scores_gemma":[0.016307365,0.00034114002,0.00048529782,0.0005070785,0.0020908415,0.002172085,0.0017827317,0.0009994855,0.0003305483],"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":[0.000119455966,0.00013352267,0.0051356507,0.00016758456,0.0001245088,0.00032696011,0.0013265584,0.32547438,0.008247236,0.62262106,0.001945146,0.03437792],"study_design_scores_gemma":[0.000062306215,0.00009548733,0.00088026794,0.000020783806,0.000029944697,0.000097278666,0.00019176224,0.7767606,0.001101803,0.21874242,0.0019978504,0.000019463769],"about_ca_topic_score_codex":0.001403802,"about_ca_topic_score_gemma":0.0010735758,"teacher_disagreement_score":0.002881577,"about_ca_system_score_codex":0.0012000884,"about_ca_system_score_gemma":0.0012870658,"threshold_uncertainty_score":0.014514744},"labels":[],"label_agreement":null},{"id":"W31861015","doi":"10.1097/md.0000000000018442","title":"Distributed XML Query Processing - (Extended Abstract).","year":2010,"lang":"en","type":"article","venue":"International XML Database Symposium","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Streaming XML; XML database; Query optimization; XML; Information retrieval; Database; World Wide Web","score_opus":0.009602102889350417,"score_gpt":0.26632898260433896,"score_spread":0.25672687971498853,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W31861015","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":[0.0032280232,0.00094098505,0.48516753,0.0020782407,0.00090646616,0.0012264954,0.055188823,0.40866143,0.042601984],"genre_scores_gemma":[0.10684587,0.0018119483,0.36451706,0.0044451943,0.00075045205,0.0023395058,0.28100458,0.0688073,0.1694781],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9971969,0.00065541774,0.00044378897,0.0005476081,0.000930273,0.0002259195],"domain_scores_gemma":[0.9962979,0.0009681959,0.00015749555,0.0014917261,0.00080448884,0.00028019244],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0042104586,0.0019716974,0.0013886893,0.002031653,0.0009859218,0.004808041,0.00368514,0.0022536328,0.22242709],"category_scores_gemma":[0.009308575,0.0013102213,0.001142146,0.0025591871,0.0006922745,0.004801039,0.0051196082,0.0018039646,0.1755797],"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":[0.0012762926,0.00023560971,0.0018463833,0.0009407673,0.00019008789,0.00047215464,0.0006271515,0.0021163116,0.010586525,0.019374864,0.6500473,0.3122866],"study_design_scores_gemma":[0.0006041462,0.00023877759,0.0025511836,0.00033854644,0.000078958255,0.00085402944,0.00030249805,0.05458881,0.018789247,0.034354772,0.8871357,0.00016334295],"about_ca_topic_score_codex":0.0037913749,"about_ca_topic_score_gemma":0.0031091592,"teacher_disagreement_score":0.22242709,"about_ca_system_score_codex":0.0012287707,"about_ca_system_score_gemma":0.0011995599,"threshold_uncertainty_score":0.7440927},"labels":[],"label_agreement":null},{"id":"W3188393868","doi":"10.1016/j.is.2022.102156","title":"Extending sticky-Datalog<mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"inline\" id=\"d1e182\" altimg=\"si10.svg\"><mml:msup><mml:mrow/><mml:mrow><mml:mo>±</mml:mo></mml:mrow></mml:msup></mml:math>via finite-position selection functions: Tractability, algorithms, and optimization","year":2022,"lang":"lv","type":"article","venue":"Information Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Agencia Nacional de Investigación y Desarrollo","keywords":"Datalog; Computer science; Oracle; MAGIC (telescope); Modulo; Predicate (mathematical logic); Class (philosophy); Function (biology); Selection (genetic algorithm); Algorithm; Theoretical computer science; Discrete mathematics; Programming language; Mathematics; Artificial intelligence","score_opus":0.016549941385575848,"score_gpt":0.23897838599432242,"score_spread":0.22242844460874656,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3188393868","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":[0.0048492737,0.00031607278,0.9590866,0.0011448408,0.00029580537,0.00013109494,0.003998435,0.011546619,0.018631248],"genre_scores_gemma":[0.18909284,0.0013728858,0.74712247,0.0028485092,0.00052508974,0.0005708287,0.014997976,0.009751908,0.033717476],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99792236,0.0004842858,0.00027986217,0.00035921446,0.0007831821,0.00017111287],"domain_scores_gemma":[0.99451596,0.0024860417,0.00019173486,0.0017231816,0.00093812164,0.00014502184],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028735935,0.00078237866,0.0007049832,0.0013879997,0.00073085463,0.0025634773,0.0018853634,0.00071223185,0.022505974],"category_scores_gemma":[0.012437459,0.0007211524,0.0017637333,0.0019596498,0.0011915165,0.0069295033,0.0038899619,0.0028948616,0.00905147],"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":[0.00033928538,0.00016176548,0.0015670111,0.0009707687,0.00008875876,0.00025251208,0.0004386979,0.026882535,0.004272291,0.5664743,0.08643914,0.31211296],"study_design_scores_gemma":[0.00008410302,0.00008475748,0.00045603668,0.00019146352,0.00005108053,0.0002001679,0.00008636614,0.15337509,0.010425676,0.62218064,0.21280801,0.000056567416],"about_ca_topic_score_codex":0.0063300077,"about_ca_topic_score_gemma":0.0075827367,"teacher_disagreement_score":0.022505974,"about_ca_system_score_codex":0.0014301471,"about_ca_system_score_gemma":0.0022978648,"threshold_uncertainty_score":0.075289965},"labels":[],"label_agreement":null},{"id":"W3193434541","doi":"10.3929/ethz-b-000504426","title":"The Future is Big Graphs! A Community View on Graph Processing Systems","year":2020,"lang":"en","type":"article","venue":"Repository for Publications and Research Data (ETH Zurich)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of Waterloo","funders":"","keywords":"Computer science; Big data; Graph algorithms; Graph database; Graph; SQL; Relational database management system; Data science; Theoretical computer science; Database; Distributed computing; World Wide Web; Relational database; Operating system","score_opus":0.19875032630526912,"score_gpt":0.38581119775139905,"score_spread":0.18706087144612993,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3193434541","genre_codex":"commentary","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":[0.005072492,0.13258745,0.095363885,0.70791376,0.0091948295,0.00005952084,0.000699467,0.0011789512,0.047929663],"genre_scores_gemma":[0.2434285,0.38070866,0.12902252,0.15478845,0.052528344,0.0004482788,0.0018583473,0.0022847343,0.034932155],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.9955604,0.0016687616,0.00018022624,0.00072889373,0.0015732818,0.0002884485],"domain_scores_gemma":[0.96589035,0.01956432,0.00070576125,0.0043106214,0.005926398,0.0036025795],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012873687,0.00077243923,0.0010606893,0.0060992585,0.003273317,0.013794924,0.0028896292,0.005949687,0.009497875],"category_scores_gemma":[0.020734964,0.00066317286,0.0010126088,0.008453229,0.013771841,0.053194936,0.006042399,0.0101430565,0.0018909934],"study_design_candidate":"qualitative","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":[0.000034265035,0.000036170106,0.0005021775,0.00038864583,0.000022107055,0.000048966536,0.00089502876,0.0011883508,0.00021613746,0.80104077,0.1370097,0.058617614],"study_design_scores_gemma":[0.000012039361,0.000017932403,0.0002092738,0.0003755443,0.000009523283,0.00008518135,0.00089118606,0.0024073236,0.00011990097,0.57846016,0.41738236,0.000029657596],"about_ca_topic_score_codex":0.005008668,"about_ca_topic_score_gemma":0.0045329654,"teacher_disagreement_score":0.013794924,"about_ca_system_score_codex":0.003934299,"about_ca_system_score_gemma":0.0047363825,"threshold_uncertainty_score":0.068083405},"labels":[],"label_agreement":null},{"id":"W3193493045","doi":"10.14778/3510397.3510400","title":"Making RDBMSs efficient on graph workloads through predefined joins","year":2022,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Joins; Computer science; Relational database management system; Hash function; Tuple; Graph; Theoretical computer science; Database; Relational database; Parallel computing; Data mining; Programming language","score_opus":0.03152427770464434,"score_gpt":0.2577984677144628,"score_spread":0.22627419000981847,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3193493045","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":[0.6496421,0.0011598717,0.22561274,0.0012091051,0.00041561207,0.00069521787,0.002601195,0.0986813,0.019982908],"genre_scores_gemma":[0.7708418,0.00045524418,0.21415041,0.0003272854,0.00007800486,0.00027172855,0.0055374,0.0038939845,0.004444053],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99475116,0.0009704587,0.00045604454,0.00088638737,0.0021527787,0.000783181],"domain_scores_gemma":[0.9899132,0.0025596942,0.00042821481,0.004997568,0.0016709261,0.00043027243],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031008462,0.0012528289,0.0009567195,0.0012709784,0.0014835056,0.00379584,0.0041403924,0.0008514978,0.0033136997],"category_scores_gemma":[0.011128209,0.00093932654,0.000662365,0.0027056038,0.0012365244,0.0066332123,0.003033125,0.0011939723,0.002009158],"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":[0.004318158,0.0011898798,0.019197846,0.0011627675,0.00026912795,0.00078556,0.0014466778,0.17839316,0.16436715,0.026714059,0.07959966,0.52255607],"study_design_scores_gemma":[0.00058898004,0.0004928954,0.0072221407,0.000073332645,0.00012441952,0.00029230796,0.0009948546,0.77549404,0.15052573,0.02160552,0.042447466,0.00013834314],"about_ca_topic_score_codex":0.011502222,"about_ca_topic_score_gemma":0.01252631,"teacher_disagreement_score":0.011502222,"about_ca_system_score_codex":0.0019002199,"about_ca_system_score_gemma":0.0031587682,"threshold_uncertainty_score":0.0228706},"labels":[],"label_agreement":null},{"id":"W3199929767","doi":"10.22215/etd/2017-11784","title":"Priority-Based Scheduling Techniques for a Multitenant Stream Processing Platform","year":2017,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Network topology; Computer science; Scheduling (production processes); Distributed computing; Multitenancy; Stream processing; Temporal isolation among virtual machines; Key (lock); Computer network; Engineering; Operating system; Virtualization; Cloud computing","score_opus":0.02735217984353017,"score_gpt":0.32777008695079624,"score_spread":0.30041790710726607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3199929767","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":[0.024892623,0.00067067967,0.96785486,0.00032447666,0.000398546,0.00017407781,0.00009317395,0.0017893467,0.003802153],"genre_scores_gemma":[0.46321833,0.00067852944,0.5281303,0.00018980629,0.00038070913,0.00017687454,0.00034620846,0.0005772648,0.0063019944],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99892884,0.00017947548,0.000093362294,0.00017354549,0.00043243504,0.00019240627],"domain_scores_gemma":[0.9976386,0.00074360217,0.00014929836,0.0003975371,0.00078684284,0.00028421945],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020702376,0.000669688,0.00067540084,0.00080510025,0.0013056241,0.0014305387,0.0023035049,0.00047184408,0.0033095777],"category_scores_gemma":[0.0038413138,0.00046167208,0.0005710492,0.0010285254,0.0004052422,0.0015612816,0.0011709231,0.0013525416,0.0008192397],"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":[0.0016411183,0.0006563018,0.0023518677,0.00046966577,0.00016758878,0.00045262216,0.0006658834,0.37132367,0.06760103,0.10050611,0.02730096,0.42686325],"study_design_scores_gemma":[0.00008620513,0.00013400568,0.00029119966,0.000013620159,0.000042204498,0.000080582075,0.00006898693,0.9659344,0.0066334684,0.019635232,0.007056962,0.000023090719],"about_ca_topic_score_codex":0.006275898,"about_ca_topic_score_gemma":0.008064887,"teacher_disagreement_score":0.006275898,"about_ca_system_score_codex":0.0012363861,"about_ca_system_score_gemma":0.0023935805,"threshold_uncertainty_score":0.012478709},"labels":[],"label_agreement":null},{"id":"W3209412140","doi":"10.1145/3459637.3481947","title":"Scalable Learning to Troubleshoot Query Performance Problems","year":2021,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University; IBM (Canada); Ontario Tech University","funders":"","keywords":"Computer science; Troubleshooting; Scalability; Query plan; SPARK (programming language); Query optimization; IBM; Pruning; Benchmark (surveying); Database; Distributed computing; Knowledge base; Data mining; Web search query; Information retrieval; Sargable; Artificial intelligence; Search engine; Operating system; Programming language","score_opus":0.01561689336379097,"score_gpt":0.23061728307697615,"score_spread":0.2150003897131852,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3209412140","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":[0.108038634,0.0009581178,0.8754286,0.0011142435,0.00009355779,0.00024589256,0.00037725372,0.00969279,0.0040509254],"genre_scores_gemma":[0.59437656,0.00030422275,0.40125996,0.00037318456,0.0001668804,0.0001952876,0.0010842128,0.00057103037,0.0016686758],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979685,0.0004581675,0.00012600773,0.00060156756,0.00060129113,0.0002445017],"domain_scores_gemma":[0.9928308,0.0044316254,0.00043720476,0.0012739623,0.0007964509,0.00022998656],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031664378,0.0018071196,0.0016576737,0.0009788545,0.00082325155,0.0013113774,0.0030957386,0.0011477252,0.0022745188],"category_scores_gemma":[0.011593057,0.0006810442,0.0009477035,0.0013409173,0.0010672259,0.0026280982,0.0020715117,0.0024946823,0.00068426004],"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":[0.00029963147,0.00060134084,0.0055570533,0.00021989191,0.00011658363,0.000113391936,0.00021407174,0.70337343,0.0068540205,0.00404911,0.008197851,0.2704036],"study_design_scores_gemma":[0.000031883053,0.000047159934,0.00020438411,0.000004316997,0.000012262964,0.000022597027,0.000048139314,0.99351776,0.0013359267,0.0043320907,0.00043961118,0.000004022311],"about_ca_topic_score_codex":0.007188062,"about_ca_topic_score_gemma":0.014680124,"teacher_disagreement_score":0.007188062,"about_ca_system_score_codex":0.0013455785,"about_ca_system_score_gemma":0.002719918,"threshold_uncertainty_score":0.016745925},"labels":[],"label_agreement":null},{"id":"W3210216704","doi":"10.1109/dsaa53316.2021.9564218","title":"DaskDB: Scalable Data Science with Unified Data Analytics and In Situ Query Processing","year":2021,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; Python (programming language); Scalability; SQL; Relational database management system; Analytics; Database; Relational database; Benchmark (surveying); Data analysis; Usability; Data mining; Programming language; Operating system","score_opus":0.07135703472201405,"score_gpt":0.3065453377071228,"score_spread":0.23518830298510873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3210216704","genre_codex":"software","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":[0.014882361,0.0008578861,0.43274745,0.0010256537,0.00041982735,0.0009097926,0.016135506,0.52411336,0.008908153],"genre_scores_gemma":[0.19248323,0.0010737575,0.6643775,0.0019085227,0.00026186326,0.0020481944,0.09872739,0.03017838,0.008941224],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9912527,0.001104639,0.00086529646,0.0015535853,0.0045397845,0.00068393484],"domain_scores_gemma":[0.9927699,0.0013363177,0.0004101728,0.003183227,0.0013025093,0.0009978389],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0063241827,0.002081731,0.002072268,0.0029318419,0.0017681356,0.0061424803,0.008246605,0.0010643688,0.008697551],"category_scores_gemma":[0.013859438,0.0019278673,0.0023007002,0.0052335714,0.0022965753,0.009034997,0.01280795,0.0043667066,0.006476612],"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":[0.0031689177,0.0011411259,0.014808665,0.0021641653,0.0010930967,0.0008844189,0.0013159378,0.024970287,0.035908654,0.038542885,0.5444242,0.33157766],"study_design_scores_gemma":[0.002234752,0.0005220842,0.009035778,0.00021768625,0.00024654737,0.0010856648,0.00060698413,0.5332979,0.07196388,0.08404848,0.29606214,0.0006780684],"about_ca_topic_score_codex":0.010687111,"about_ca_topic_score_gemma":0.007963886,"teacher_disagreement_score":0.010687111,"about_ca_system_score_codex":0.0022183827,"about_ca_system_score_gemma":0.0064932196,"threshold_uncertainty_score":0.033445895},"labels":[],"label_agreement":null},{"id":"W3210720616","doi":"","title":"Scallop: From Probabilistic Deductive Databases to Scalable Differentiable Reasoning","year":2021,"lang":"en","type":"article","venue":"Neural Information Processing Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Probabilistic logic; Scalability; Deductive reasoning; Deductive database; Database; Programming language; Natural language processing; Artificial intelligence; Data mining; Information retrieval","score_opus":0.021531567657527787,"score_gpt":0.2609899767663771,"score_spread":0.2394584091088493,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3210720616","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":[0.0068768593,0.00047848668,0.95754135,0.0005356405,0.00012787827,0.00011316234,0.0015471524,0.028855657,0.0039237235],"genre_scores_gemma":[0.19588299,0.00066622486,0.78922695,0.0006355368,0.00014536231,0.0002376572,0.0043212627,0.003182869,0.005701165],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99851686,0.00025529307,0.00013262378,0.00032386204,0.00066794705,0.00010349061],"domain_scores_gemma":[0.99525815,0.0021822557,0.00015836582,0.0018066862,0.00048391524,0.00011061622],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018233854,0.0009863193,0.0010539417,0.0010998275,0.00058820634,0.002965106,0.004321215,0.0009789407,0.016831636],"category_scores_gemma":[0.012820658,0.0010957692,0.001581509,0.0015300928,0.0014044718,0.0059788222,0.0050298455,0.0032285322,0.003979304],"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":[0.0006470546,0.00026088313,0.0016370559,0.00080509624,0.00025257297,0.00027907756,0.00024447826,0.11358797,0.0051657604,0.1392672,0.060622282,0.67723054],"study_design_scores_gemma":[0.000085708256,0.0000346555,0.00023711368,0.00005039542,0.00006174235,0.00006539477,0.00004052755,0.7682598,0.0056352937,0.21295343,0.012552701,0.000023277586],"about_ca_topic_score_codex":0.005939442,"about_ca_topic_score_gemma":0.010886461,"teacher_disagreement_score":0.016831636,"about_ca_system_score_codex":0.001184913,"about_ca_system_score_gemma":0.0018383879,"threshold_uncertainty_score":0.056307435},"labels":[],"label_agreement":null},{"id":"W32460722","doi":"10.1186/s12885-020-06943-w","title":"Performance Improvement of Distributed Database Management Systems.","year":2003,"lang":"en","type":"article","venue":"International Conference on Enterprise Information Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research","keywords":"Computer science; Distributed database; Database","score_opus":0.019209172892256213,"score_gpt":0.2540870962401589,"score_spread":0.2348779233479027,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W32460722","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":[0.4522779,0.028376026,0.3755519,0.01294112,0.0027101287,0.0013874489,0.0053737396,0.03903103,0.082350716],"genre_scores_gemma":[0.9166233,0.0018529712,0.07041774,0.0003289203,0.00038033826,0.00018848464,0.0039530373,0.0004011354,0.0058540786],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9908602,0.0031911696,0.00062303315,0.001023294,0.003467649,0.00083460234],"domain_scores_gemma":[0.98402494,0.0047058132,0.0009193755,0.0042894934,0.005027498,0.0010329189],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010988036,0.0010327249,0.0006622523,0.0014296215,0.0008510282,0.0024618392,0.0018203019,0.000639497,0.0053942394],"category_scores_gemma":[0.025364993,0.00031776525,0.0004114653,0.0018076993,0.00040170155,0.0023725834,0.0016278668,0.00079787144,0.0024604134],"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":[0.0017209111,0.0006121293,0.023966178,0.00046637474,0.00015056678,0.00010431684,0.00036652666,0.02783404,0.0073291534,0.007690609,0.051691618,0.8780675],"study_design_scores_gemma":[0.0009651861,0.0035381017,0.05693126,0.00030060927,0.0005331093,0.00075097405,0.0009186011,0.74253696,0.03722693,0.031311125,0.124856114,0.00013098787],"about_ca_topic_score_codex":0.0033207831,"about_ca_topic_score_gemma":0.0022761512,"teacher_disagreement_score":0.010988036,"about_ca_system_score_codex":0.0011963447,"about_ca_system_score_gemma":0.0019390916,"threshold_uncertainty_score":0.058111012},"labels":[],"label_agreement":null},{"id":"W32689398","doi":"10.1071/fp07118","title":"Towards workload-aware dbmss: identifying workload type and predicting its change","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Workload; Computer science; Online transaction processing; Database; Overhead (engineering); Online analytical processing; Architecture; Decision support system; Database transaction; Operating system; Transaction processing; Data mining; Data warehouse","score_opus":0.07094808763007728,"score_gpt":0.2987936270965784,"score_spread":0.22784553946650116,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W32689398","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":[0.9481325,0.00035325286,0.047640093,0.0001322473,0.000021891577,0.00007210617,0.0010784537,0.001833234,0.0007361906],"genre_scores_gemma":[0.96201974,0.0001420301,0.035743702,0.000022956687,0.000020248583,0.000037032325,0.0016836118,0.00003313515,0.00029764895],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996357,0.00006418102,0.00005021739,0.00010045571,0.0001087788,0.00004066744],"domain_scores_gemma":[0.99818844,0.0005066101,0.0004046944,0.00019842107,0.0005240317,0.00017776343],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00071124424,0.0006170186,0.0005542427,0.001421665,0.0002403858,0.00087267015,0.0005520273,0.0004677035,0.00025805118],"category_scores_gemma":[0.0026389216,0.00026944524,0.00023788646,0.0011834787,0.00012859948,0.0013298609,0.0002769587,0.00034295864,0.0003137169],"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":[0.00074997154,0.00057195546,0.52535695,0.0002514735,0.00014749772,0.00023411312,0.0003293351,0.043472447,0.16941223,0.0006096175,0.0022686303,0.25659576],"study_design_scores_gemma":[0.000025105724,0.00040811108,0.21341042,0.000017336972,0.00006206158,0.00044181696,0.00027165236,0.747875,0.0344453,0.0014582707,0.0015509818,0.00003388269],"about_ca_topic_score_codex":0.003105797,"about_ca_topic_score_gemma":0.0053439583,"teacher_disagreement_score":0.003105797,"about_ca_system_score_codex":0.0002913898,"about_ca_system_score_gemma":0.00040276634,"threshold_uncertainty_score":0.006175399},"labels":[],"label_agreement":null},{"id":"W3347319","doi":"","title":"Supporting Uncertainty in Standard Database Management Systems","year":2012,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Concordia University","keywords":"Computer science; SQL; Database; Uncertain data; Relational database management system; Probabilistic logic; Relational database; Benchmark (surveying); Query optimization; Class (philosophy); Data management; Formalism (music); Data mining; Artificial intelligence","score_opus":0.016397621060299877,"score_gpt":0.3069281358977834,"score_spread":0.2905305148374835,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3347319","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":[0.055577375,0.00092139887,0.9352866,0.000557788,0.000064135675,0.00021303784,0.0003770216,0.004201278,0.002801259],"genre_scores_gemma":[0.523258,0.0013957031,0.47151276,0.00030896146,0.00019753366,0.00030621394,0.001280579,0.0003221607,0.0014180426],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9802684,0.004135328,0.002526535,0.001807193,0.010446441,0.00081606756],"domain_scores_gemma":[0.9759127,0.010122913,0.0018694897,0.008149791,0.0035979794,0.00034713556],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012538536,0.0008282512,0.0012950222,0.0017327525,0.0014507482,0.0071643554,0.0037407281,0.0014313904,0.0014693771],"category_scores_gemma":[0.037417695,0.00090046163,0.00095884065,0.004034959,0.0016251218,0.011608605,0.0051630535,0.0018741178,0.00055250863],"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":[0.001157902,0.0005885884,0.010633387,0.001139691,0.0003703461,0.00085509114,0.00211058,0.20915474,0.029864578,0.32512936,0.009762404,0.40923333],"study_design_scores_gemma":[0.00011020618,0.00021450629,0.0014294044,0.00010943325,0.00013537247,0.00039433842,0.0003676194,0.76315767,0.03717325,0.17018294,0.026631799,0.00009333447],"about_ca_topic_score_codex":0.0022338128,"about_ca_topic_score_gemma":0.0018145589,"teacher_disagreement_score":0.012538536,"about_ca_system_score_codex":0.0014013354,"about_ca_system_score_gemma":0.0023198372,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W35014963","doi":"10.2196/27631","title":"Using Design Guidelines to Improve Data Warehouse Logical Design.","year":2003,"lang":"en","type":"article","venue":"JMIR Human Factors","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Logical data model; Data warehouse; Schema (genetic algorithms); Conceptual schema; Dimensional modeling; Software versioning; Logical conjunction; Software engineering; Data modeling; Database; Data science; Data mining; Information retrieval; Programming language; Software","score_opus":0.4361212398271037,"score_gpt":0.4194635940573503,"score_spread":0.016657645769753426,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W35014963","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":[0.0023715836,0.00043360377,0.9796826,0.001507376,0.00015504264,0.002527432,0.0012243818,0.009761827,0.0023360215],"genre_scores_gemma":[0.009146878,0.00020078965,0.9855369,0.00033788919,0.000030377734,0.0012090442,0.0018102988,0.0009318669,0.00079593237],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.91082567,0.05626176,0.013750012,0.0031558955,0.0146931335,0.0013135879],"domain_scores_gemma":[0.8012142,0.10603491,0.0086910445,0.03230037,0.0493841,0.0023754034],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.09641461,0.0022224595,0.0010919647,0.0044235936,0.002026416,0.011431296,0.004943182,0.0023090227,0.006030626],"category_scores_gemma":[0.19040786,0.0038440481,0.0035137483,0.003764754,0.0021711767,0.010500143,0.0045962348,0.0043745707,0.003722745],"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":[0.0010106623,0.00077788485,0.008051193,0.005580836,0.0010523492,0.0010531489,0.008981588,0.0350227,0.0117721325,0.13577391,0.144309,0.6466146],"study_design_scores_gemma":[0.0012977853,0.0008819752,0.0024854166,0.004183662,0.00135413,0.0012269361,0.0035816086,0.22998367,0.025426358,0.20368947,0.5254703,0.00041861052],"about_ca_topic_score_codex":0.0077200057,"about_ca_topic_score_gemma":0.012670347,"teacher_disagreement_score":0.09641461,"about_ca_system_score_codex":0.0021377972,"about_ca_system_score_gemma":0.010454242,"threshold_uncertainty_score":0.5098953},"labels":[],"label_agreement":null},{"id":"W36570737","doi":"10.1093/conphys/coac071","title":"Evaluation Methodology for Rule Scheduling in Active Database Systems.","year":2004,"lang":"en","type":"article","venue":"International Conference on Computational Intelligence","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Active database; Database; Scheduling (production processes); Data mining; Mathematical optimization; Mathematics","score_opus":0.28275152046420693,"score_gpt":0.4406739859647228,"score_spread":0.15792246550051586,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W36570737","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":[0.0048605753,0.00041863273,0.9837918,0.00021202026,0.00012966027,0.00066051574,0.0009035518,0.0068574,0.0021659234],"genre_scores_gemma":[0.147043,0.00032086275,0.845729,0.00020743461,0.000121242614,0.0012578071,0.0029862965,0.0006823784,0.0016520679],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98468125,0.006241037,0.0020225367,0.0018439587,0.004511803,0.00069937535],"domain_scores_gemma":[0.9651967,0.022190034,0.0014677886,0.0044710045,0.0059097637,0.000764611],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.018585455,0.0019558726,0.0015740994,0.002787876,0.00089608,0.0044815657,0.004283723,0.0013847102,0.012700697],"category_scores_gemma":[0.05672211,0.0009861985,0.0019060115,0.0022013865,0.0009232136,0.005607866,0.0025003762,0.001746565,0.0028608236],"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":[0.0011038963,0.00047517935,0.0044546435,0.0012888622,0.00037599212,0.00021879407,0.00029897992,0.1917147,0.0035918793,0.05671976,0.018100804,0.7216565],"study_design_scores_gemma":[0.00011702865,0.00018167979,0.00036126858,0.00010213827,0.000064757936,0.00009450904,0.00008597182,0.94989693,0.0024287887,0.04081267,0.0058343345,0.00001994642],"about_ca_topic_score_codex":0.0041658506,"about_ca_topic_score_gemma":0.0039526224,"teacher_disagreement_score":0.018585455,"about_ca_system_score_codex":0.0017046414,"about_ca_system_score_gemma":0.0038604175,"threshold_uncertainty_score":0.0982905},"labels":[],"label_agreement":null},{"id":"W41713151","doi":"10.1007/978-1-4471-5073-2_1","title":"Introduction to Engineering Informatics","year":2013,"lang":"en","type":"book-chapter","venue":"Springer series in advanced manufacturing","topic":"Advanced Database Systems and Queries","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 Alberta","funders":"","keywords":"Informatics; Computer science; Engineering; Electrical engineering","score_opus":0.005909843499621045,"score_gpt":0.19512748098660243,"score_spread":0.1892176374869814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W41713151","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00046433683,0.059240934,0.049338236,0.006453039,0.0068103713,0.00007496025,0.00058441516,0.0008909611,0.8761428],"genre_scores_gemma":[0.0066851084,0.04228429,0.018005345,0.002734199,0.0042290105,0.00012097711,0.0006159579,0.0005593701,0.9247657],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9994677,0.000085581974,0.000029901697,0.000105355604,0.00027292367,0.00003849375],"domain_scores_gemma":[0.99955624,0.00018405051,0.000015726475,0.00007535969,0.00012262957,0.000045936773],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005466114,0.0015256192,0.0010485252,0.00329131,0.0010524847,0.004032859,0.00096628466,0.0010910768,0.110026695],"category_scores_gemma":[0.0014533777,0.0005244496,0.00058009446,0.0037952524,0.0016736957,0.0044420534,0.001963807,0.0029655134,0.066877134],"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":[0.000008322954,0.000035679666,0.00008763759,0.00037345977,0.0000066511034,0.00005884545,0.000322544,0.0005765687,0.00041102912,0.22860566,0.4637159,0.3057978],"study_design_scores_gemma":[0.0000012626695,0.000005085017,0.0000716551,0.00013247588,0.0000017566462,0.000053426924,0.000037345664,0.00015746085,0.000059440154,0.045991536,0.9534851,0.0000034718496],"about_ca_topic_score_codex":0.00084882166,"about_ca_topic_score_gemma":0.0020608655,"teacher_disagreement_score":0.110026695,"about_ca_system_score_codex":0.0013031692,"about_ca_system_score_gemma":0.0015284648,"threshold_uncertainty_score":0.36807597},"labels":[],"label_agreement":null},{"id":"W4200539811","doi":"10.5753/sbbd.2021.17877","title":"Stream and Historical Data Integration using SQL as Standard Language","year":2021,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Computer science; SQL; Data integration; Streaming data; Process (computing); Data definition language; Relational database; Contextualization; Database; Point (geometry); Information retrieval; Data mining; Programming language","score_opus":0.05652361904121651,"score_gpt":0.31531933282660796,"score_spread":0.25879571378539146,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200539811","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":[0.0034978304,0.00019798234,0.9840934,0.0002656175,0.00007633409,0.0002016586,0.001253481,0.0077116066,0.0027021407],"genre_scores_gemma":[0.0899982,0.00079135736,0.8911891,0.0006859985,0.00021711404,0.00057379605,0.009203578,0.0024228783,0.0049179154],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99108666,0.0018980613,0.0022537478,0.0011773047,0.0033028512,0.0002813207],"domain_scores_gemma":[0.99392784,0.0018760549,0.000566549,0.0017300764,0.001685384,0.00021410339],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008214831,0.0009550724,0.001056407,0.0029107595,0.00067026133,0.005559196,0.0018733364,0.00080323697,0.0037294712],"category_scores_gemma":[0.009737525,0.00074769236,0.0016626985,0.003288766,0.0011300719,0.0073999735,0.003993831,0.0019561034,0.0019330224],"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":[0.0011718655,0.00047252618,0.01061059,0.0017239605,0.0006207933,0.0022206416,0.005865964,0.018131299,0.04887539,0.4488456,0.039370168,0.42209125],"study_design_scores_gemma":[0.00018298665,0.00043488163,0.004101542,0.0005427178,0.00034619236,0.0021486187,0.0020861172,0.1866542,0.08172996,0.22546841,0.4960023,0.0003020566],"about_ca_topic_score_codex":0.002279082,"about_ca_topic_score_gemma":0.0014014596,"teacher_disagreement_score":0.008214831,"about_ca_system_score_codex":0.0006507235,"about_ca_system_score_gemma":0.0020226855,"threshold_uncertainty_score":0.043444693},"labels":[],"label_agreement":null},{"id":"W4206074731","doi":"10.1007/978-1-4419-8834-8_4","title":"Database Integration","year":2011,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Database; Computer science","score_opus":0.041281845522897695,"score_gpt":0.24000807620557668,"score_spread":0.19872623068267897,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206074731","genre_codex":"methods","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":[0.0044429936,0.009555783,0.5516399,0.0020009025,0.0015822602,0.00084462325,0.0028011627,0.016446479,0.41068587],"genre_scores_gemma":[0.06712327,0.014375435,0.4805434,0.0034736607,0.001014922,0.00062664866,0.018140048,0.003864041,0.41083854],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99805284,0.00018968162,0.00015596938,0.00043956382,0.0010566865,0.00010527813],"domain_scores_gemma":[0.998681,0.00021610051,0.000035976413,0.0005374503,0.00047125528,0.000058232537],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015701035,0.0011290895,0.0011854781,0.0029950223,0.0010735731,0.005811925,0.002705129,0.0010792566,0.05504548],"category_scores_gemma":[0.0037502649,0.0008620404,0.0010827343,0.0046936963,0.0006260086,0.0057692765,0.0038295938,0.0018944562,0.04677326],"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":[0.00008033042,0.00012862463,0.0004330415,0.0006153508,0.00005007523,0.00016125159,0.00028850543,0.0007194831,0.006594014,0.09326973,0.13985908,0.75780064],"study_design_scores_gemma":[0.000022472037,0.00004718958,0.0005082928,0.00023939926,0.00007192601,0.00084815256,0.00014171186,0.005907841,0.009844453,0.06384059,0.91849625,0.000031769872],"about_ca_topic_score_codex":0.001419293,"about_ca_topic_score_gemma":0.0012283284,"teacher_disagreement_score":0.05504548,"about_ca_system_score_codex":0.0007985027,"about_ca_system_score_gemma":0.0014249797,"threshold_uncertainty_score":0.18414551},"labels":[],"label_agreement":null},{"id":"W4206223073","doi":"10.1145/872797.872798","title":"Mapping data in peer-to-peer systems","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Semantic mapping; Data mapping; Semantics (computer science); Peer-to-peer; Information retrieval; Listing (finance); Data sharing; Theoretical computer science; Data exchange; Data mining; Database; Programming language; World Wide Web","score_opus":0.05434415495395329,"score_gpt":0.2929551774574246,"score_spread":0.23861102250347133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206223073","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":[0.017247897,0.0015090316,0.97447985,0.0015891022,0.00018389351,0.00038641802,0.00038590224,0.00088890124,0.0033290004],"genre_scores_gemma":[0.22887805,0.0024035193,0.76279634,0.00034404043,0.00021163258,0.00047558377,0.0010252487,0.00021377893,0.0036517796],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9888594,0.0042173867,0.0012609477,0.0016439882,0.0034856128,0.0005326522],"domain_scores_gemma":[0.98194677,0.011319977,0.0011632752,0.0036005243,0.0013630312,0.00060639804],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009605664,0.0010042465,0.0023708032,0.0028183681,0.00440413,0.008070114,0.004794102,0.004111997,0.0036499298],"category_scores_gemma":[0.032275558,0.0014913687,0.0013665564,0.0077426303,0.0032770047,0.019067993,0.007495873,0.0029056284,0.0011965589],"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":[0.00027108763,0.00015722225,0.0028599035,0.0010529358,0.00020972986,0.0018751358,0.0024358945,0.21385634,0.0033998424,0.6240019,0.009093298,0.14078663],"study_design_scores_gemma":[0.00007559145,0.000083088606,0.00032103315,0.00011411868,0.00009275465,0.00067417376,0.0010283393,0.2811044,0.005044029,0.6527612,0.058613036,0.0000882561],"about_ca_topic_score_codex":0.004178782,"about_ca_topic_score_gemma":0.0026682522,"teacher_disagreement_score":0.009605664,"about_ca_system_score_codex":0.0017701406,"about_ca_system_score_gemma":0.0025579433,"threshold_uncertainty_score":0.050800204},"labels":[],"label_agreement":null},{"id":"W4206769521","doi":"10.1109/ideas.2007.4318107","title":"Stream Processing in a Relational Database: a Case Study","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Computer science; Database; Stream processing; Relational database; Relational database management system; Point (geometry); Distributed computing","score_opus":0.0365202686735736,"score_gpt":0.3175671496795327,"score_spread":0.2810468810059591,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206769521","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":[0.77259266,0.008251135,0.15273045,0.012928295,0.00032600618,0.0007053159,0.0017191127,0.0023372842,0.048409708],"genre_scores_gemma":[0.8732687,0.0049328855,0.11189847,0.0008181984,0.00027138143,0.00015231264,0.00088424946,0.00040934482,0.0073645087],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9947566,0.002063505,0.0004337188,0.0004364638,0.0020093147,0.00030050045],"domain_scores_gemma":[0.98831815,0.008096701,0.0004193291,0.0011529977,0.0013147634,0.00069809915],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0053553246,0.00034543872,0.000536002,0.0009693437,0.0019018694,0.0040729837,0.0020495513,0.0026664357,0.0025671355],"category_scores_gemma":[0.014820567,0.00037028547,0.0007580384,0.003474575,0.0014926618,0.0040763356,0.0016016877,0.0017424404,0.00087752054],"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":[0.0028634914,0.003938007,0.075910725,0.0029872875,0.00039212103,0.09727299,0.034872618,0.07605739,0.025319932,0.19664685,0.0676542,0.4160845],"study_design_scores_gemma":[0.0008565775,0.0030085496,0.035076465,0.00078130665,0.0004012987,0.0571691,0.031103676,0.31786457,0.05309809,0.07384629,0.42643443,0.00035969712],"about_ca_topic_score_codex":0.008325859,"about_ca_topic_score_gemma":0.0066635134,"teacher_disagreement_score":0.008325859,"about_ca_system_score_codex":0.0014464023,"about_ca_system_score_gemma":0.0010464978,"threshold_uncertainty_score":0.028322041},"labels":[],"label_agreement":null},{"id":"W4210351797","doi":"10.1109/rasse53195.2021.9686815","title":"A Survey of Natural Language Processing Implementation for Data Query Systems","year":2021,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Okanagan College; Langara College","funders":"Natural Sciences and Engineering Research Council of Canada; Harris","keywords":"Computer science; Online analytical processing; SQL; Data warehouse; Online transaction processing; Database; Big data; Implementation; Information retrieval; Query by Example; Data mining; Transaction processing; Web search query; Programming language; Search engine","score_opus":0.06996851954237338,"score_gpt":0.3820479352539826,"score_spread":0.31207941571160924,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210351797","genre_codex":"methods","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008510764,0.05518402,0.8789044,0.002555319,0.00041087068,0.001056424,0.0032607252,0.019612525,0.030504975],"genre_scores_gemma":[0.029752493,0.05687724,0.8803891,0.0022257364,0.0002308473,0.0011965841,0.011607677,0.005581367,0.01213902],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9894944,0.0018995461,0.001746641,0.0011039643,0.0053186524,0.00043680143],"domain_scores_gemma":[0.98751706,0.0065605943,0.00042409127,0.0016209523,0.003732993,0.00014424988],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0070737284,0.0016683476,0.0013552402,0.005275778,0.00091007166,0.0053342995,0.0065680034,0.0021933862,0.014700512],"category_scores_gemma":[0.0184815,0.002267553,0.002097078,0.009324894,0.001194866,0.00860263,0.0018125431,0.0036333655,0.009130969],"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":[0.00028573562,0.0002986648,0.0015522139,0.008044486,0.00013134185,0.000349648,0.0009729871,0.0058330526,0.014236779,0.056854494,0.046537507,0.86490303],"study_design_scores_gemma":[0.00014495382,0.00035028395,0.0025428142,0.0037061702,0.00016013862,0.0019937018,0.0006489317,0.06085144,0.031169858,0.0315578,0.8666162,0.00025772172],"about_ca_topic_score_codex":0.005017397,"about_ca_topic_score_gemma":0.0024906618,"teacher_disagreement_score":0.014700512,"about_ca_system_score_codex":0.0025475759,"about_ca_system_score_gemma":0.0042725955,"threshold_uncertainty_score":0.049178064},"labels":[],"label_agreement":null},{"id":"W4214690579","doi":"10.1109/wi.2004.10048","title":"A Fast Tree Pattern Matching Algorithm for XML Query","year":2005,"lang":"en","type":"article","venue":"IEEE/WIC/ACM International Conference on Web Intelligence (WI'04)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":14,"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 Regina","funders":"","keywords":"Pattern matching; Computer science; XML; Matching (statistics); Tree (set theory); Tree decomposition; Algorithm; Theoretical computer science; Mathematics; Artificial intelligence; Combinatorics","score_opus":0.05704593411194284,"score_gpt":0.3251700530208864,"score_spread":0.26812411890894355,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4214690579","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":[0.0030263637,0.00029625787,0.9909958,0.00012208149,0.000047936224,0.00016180868,0.00032535545,0.0036046153,0.0014198438],"genre_scores_gemma":[0.03336503,0.00030048462,0.96104443,0.00012930957,0.000036362228,0.0002705054,0.0016981065,0.00033848683,0.0028173255],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99859124,0.00017948603,0.0001732494,0.0003221331,0.0006227107,0.000111186484],"domain_scores_gemma":[0.9992712,0.00019618118,0.000054658176,0.00015959033,0.0002893285,0.000029011691],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009786106,0.00080467795,0.00085546076,0.0019933006,0.0010916126,0.0014067441,0.0016861751,0.0011799228,0.006676963],"category_scores_gemma":[0.0025148918,0.00048885145,0.00095346314,0.0032204124,0.0005185572,0.0039114873,0.0019516997,0.0012043042,0.0032556404],"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":[0.0003973619,0.00013785945,0.0010287095,0.00036475004,0.00008058743,0.00022037652,0.00028725225,0.017516492,0.034934424,0.05269085,0.030929592,0.8614118],"study_design_scores_gemma":[0.0002908346,0.0003663883,0.00094975904,0.00007586823,0.0000942274,0.0013813602,0.00025190468,0.7307529,0.054112438,0.10357434,0.10801687,0.00013311404],"about_ca_topic_score_codex":0.0030178588,"about_ca_topic_score_gemma":0.0030478379,"teacher_disagreement_score":0.006676963,"about_ca_system_score_codex":0.0008773187,"about_ca_system_score_gemma":0.0015969839,"threshold_uncertainty_score":0.022336721},"labels":[],"label_agreement":null},{"id":"W4221075496","doi":"10.1145/3503646.3524295","title":"TONE","year":2022,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Latency (audio); Adaptability; Memory footprint; Popularity; Search engine indexing; Low latency (capital markets); Overhead (engineering); Embedded system; Operating system; Computer network; Telecommunications; Artificial intelligence","score_opus":0.011703694918344856,"score_gpt":0.25909243501005674,"score_spread":0.24738874009171188,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4221075496","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005976225,0.002095021,0.014986585,0.006668843,0.0066130282,0.0002824303,0.003846035,0.0026181834,0.9569136],"genre_scores_gemma":[0.06853965,0.0024226452,0.009424663,0.0052926894,0.001497373,0.0002856037,0.0056115757,0.0010364277,0.9058893],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990501,0.000099428034,0.00005452739,0.00020100536,0.00044149646,0.00015341432],"domain_scores_gemma":[0.99849236,0.00015122157,0.000079749356,0.00028081093,0.0007476175,0.00024818326],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006756042,0.00060843653,0.00039959385,0.000974488,0.0015334988,0.0039191046,0.0012629307,0.0015654624,0.3972993],"category_scores_gemma":[0.0037677668,0.00024815768,0.00038051754,0.0008818885,0.00055615115,0.0026039283,0.0026860023,0.0012004337,0.2557058],"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":[0.00038940564,0.00010651674,0.0014986397,0.0005976031,0.000019013985,0.0005742751,0.00050260057,0.00037491962,0.0097395275,0.07352528,0.4864532,0.426219],"study_design_scores_gemma":[0.000016299504,0.00004187438,0.00066021463,0.00008209168,0.0000069228113,0.00033372195,0.00015314412,0.0002410318,0.0019624857,0.0070213326,0.9894692,0.000011764222],"about_ca_topic_score_codex":0.0013959351,"about_ca_topic_score_gemma":0.0018443229,"teacher_disagreement_score":0.6027007,"about_ca_system_score_codex":0.000909497,"about_ca_system_score_gemma":0.0014188517,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W4229492659","doi":"10.1145/543621.543625","title":"A normal form for XML documents","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Information retrieval; XML; Document Structure Description; Programming language; World Wide Web","score_opus":0.021205348079384144,"score_gpt":0.24944127376469227,"score_spread":0.22823592568530812,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4229492659","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":[0.0033170797,0.00031417955,0.9851757,0.0009183849,0.00033476597,0.00019402374,0.0008119053,0.0017713958,0.0071625523],"genre_scores_gemma":[0.06718381,0.00084899215,0.91572404,0.0005434868,0.00030823605,0.0005993949,0.002426693,0.0007680109,0.01159736],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9945157,0.001107091,0.0011184535,0.0011777104,0.0018439002,0.00023711655],"domain_scores_gemma":[0.9949051,0.0016529686,0.00041302762,0.001189089,0.0016921838,0.00014766077],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004093618,0.0008655788,0.0006466845,0.0021048689,0.0010105382,0.0038614206,0.0011523827,0.0013028625,0.004841856],"category_scores_gemma":[0.010708791,0.0006018454,0.00087048433,0.0021399183,0.0028749462,0.008568776,0.0019390696,0.0030245576,0.0027522983],"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":[0.00005362886,0.000027152499,0.00030770025,0.0001494295,0.000010682265,0.0001291245,0.0005238732,0.0026602116,0.002926194,0.89778745,0.009543563,0.085881025],"study_design_scores_gemma":[0.000033725075,0.000069607864,0.00015781945,0.0001271125,0.00001961273,0.0007786298,0.00020250527,0.0275851,0.0065082433,0.66777253,0.29669556,0.00004952624],"about_ca_topic_score_codex":0.002133047,"about_ca_topic_score_gemma":0.0015719464,"teacher_disagreement_score":0.004841856,"about_ca_system_score_codex":0.0018367664,"about_ca_system_score_gemma":0.0018657517,"threshold_uncertainty_score":0.02164936},"labels":[],"label_agreement":null},{"id":"W4229594032","doi":"10.1007/978-1-4939-7131-2_100935","title":"Query Expansion","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Database Systems and Queries","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 Calgary","funders":"","keywords":"Computer science","score_opus":0.02078151773850711,"score_gpt":0.23532764344096277,"score_spread":0.21454612570245565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4229594032","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":[0.0069800215,0.0104430085,0.5527975,0.0037380182,0.0018374803,0.0010426269,0.0045997263,0.015819902,0.40274176],"genre_scores_gemma":[0.103573576,0.016926048,0.43424973,0.004327568,0.0024384009,0.00083855295,0.020333549,0.004318055,0.41299456],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983342,0.00023588561,0.00009397209,0.00037414022,0.00084114866,0.00012057675],"domain_scores_gemma":[0.99852544,0.00042114724,0.000038026385,0.00046251857,0.00050311646,0.000049789247],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014230494,0.0013670432,0.0009788414,0.0023238112,0.0007680181,0.0024389569,0.0020050996,0.00069973985,0.062121566],"category_scores_gemma":[0.0042587747,0.0004951587,0.0009454577,0.0030761913,0.00075760944,0.0056501646,0.002264919,0.0024376288,0.03628528],"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":[0.00015368852,0.00011652133,0.00022799459,0.00070599094,0.00002959813,0.000098451026,0.00016828206,0.0022759128,0.011320761,0.11844569,0.22888783,0.63756925],"study_design_scores_gemma":[0.00004214762,0.00006610856,0.0005066078,0.00023826143,0.000086449065,0.0007953075,0.00014126649,0.02994403,0.01760073,0.07696545,0.8735591,0.000054529813],"about_ca_topic_score_codex":0.0022781356,"about_ca_topic_score_gemma":0.0018056364,"teacher_disagreement_score":0.062121566,"about_ca_system_score_codex":0.0010945471,"about_ca_system_score_gemma":0.0011848876,"threshold_uncertainty_score":0.20781738},"labels":[],"label_agreement":null},{"id":"W4229738128","doi":"10.1515/iupac.83.0538","title":"Extensions to Enumeration Lists for Speciation and Complex Equilibria","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Enumeration; Schema (genetic algorithms); Computer science; XML; Data exchange; Genetic algorithm; Theoretical computer science; Information retrieval; Data mining; Database; Mathematics; Combinatorics; Biology; World Wide Web; Ecology","score_opus":0.029494771668749597,"score_gpt":0.4172921133608124,"score_spread":0.3877973416920628,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4229738128","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00019036629,0.00008220342,0.0003600627,0.000054585864,0.000016737997,0.000028861177,0.9977912,0.0008746074,0.0006013144],"genre_scores_gemma":[0.00041967264,0.000079499456,0.0014245592,0.000060786748,0.000006187129,0.00019163049,0.9973055,0.00012620087,0.000386018],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978346,0.00031363431,0.0004530449,0.00063852966,0.0005211079,0.00023905093],"domain_scores_gemma":[0.9959543,0.0012918081,0.0004291594,0.0011430552,0.0009361384,0.00024549433],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022519084,0.0026997237,0.0017972685,0.006203429,0.0011712746,0.0030729368,0.004153598,0.002325727,0.0829845],"category_scores_gemma":[0.010764147,0.0010416434,0.0026180956,0.008448355,0.00045512867,0.00346278,0.0031355317,0.0025906358,0.061978534],"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":[0.00032514255,0.000069262634,0.0023599914,0.0026945446,0.00008293147,0.00007674414,0.000082482824,0.0012166692,0.00063791726,0.0029231186,0.9781003,0.011430968],"study_design_scores_gemma":[0.00044048496,0.000025973623,0.0034717245,0.00051034085,0.000051086623,0.00012994456,0.0000823461,0.0013853201,0.001144743,0.0057189325,0.986979,0.00006011066],"about_ca_topic_score_codex":0.017543336,"about_ca_topic_score_gemma":0.029347409,"teacher_disagreement_score":0.0829845,"about_ca_system_score_codex":0.002210161,"about_ca_system_score_gemma":0.004012825,"threshold_uncertainty_score":0.27761084},"labels":[],"label_agreement":null},{"id":"W4230144441","doi":"10.1145/872830.872832","title":"A comprehensive XQuery to SQL translation using dynamic interval encoding","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"XQuery; Computer science; SQL; Query language; XML; Information retrieval; Relational database; Programming language; Database; Theoretical computer science; XML database; World Wide Web","score_opus":0.05424338726814418,"score_gpt":0.30973911347114114,"score_spread":0.255495726202997,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4230144441","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":[0.0063964073,0.00019393384,0.96804285,0.00029088967,0.00007708729,0.00023977846,0.0007604448,0.016642688,0.0073558963],"genre_scores_gemma":[0.1014842,0.0008950664,0.8726176,0.00050781574,0.00011019689,0.00045621055,0.004893811,0.0051708147,0.013864275],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998221,0.00028663606,0.00022216706,0.00026937417,0.00085259683,0.00014826017],"domain_scores_gemma":[0.99908817,0.00021245667,0.00006178645,0.0002636414,0.00032027817,0.000053677104],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016597228,0.00065730995,0.00046604307,0.00066149945,0.000506429,0.0019008216,0.0012101555,0.0006155983,0.005636486],"category_scores_gemma":[0.0028556895,0.00059552345,0.0006571869,0.0009876536,0.0007493832,0.0021668496,0.0018622642,0.0015592893,0.003206815],"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":[0.00095223467,0.00046676927,0.001525507,0.00076754723,0.000098856755,0.0011238958,0.0020398786,0.015028325,0.10464841,0.25889102,0.08382721,0.5306304],"study_design_scores_gemma":[0.00051376416,0.00065622514,0.0017397383,0.0004028353,0.00014030389,0.0023258878,0.0010390345,0.21202883,0.19120386,0.11748923,0.47217137,0.00028892045],"about_ca_topic_score_codex":0.0019003049,"about_ca_topic_score_gemma":0.0010880874,"teacher_disagreement_score":0.005636486,"about_ca_system_score_codex":0.00043893902,"about_ca_system_score_gemma":0.001128266,"threshold_uncertainty_score":0.01885593},"labels":[],"label_agreement":null},{"id":"W4230262470","doi":"10.4018/978-1-60566-717-1.ch006","title":"RCUBE","year":2010,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; Concordia University; Carleton University","funders":"","keywords":"Online analytical processing; Computer science; Scalability; Search engine indexing; Scheme (mathematics); Multidimensional data; Volume (thermodynamics); Index (typography); Materialized view; Data cube; Distributed computing; Theoretical computer science; Data mining; Database; Data warehouse; Information retrieval; View; Mathematics; Database design; World Wide Web","score_opus":0.014910870572510752,"score_gpt":0.24078917534784652,"score_spread":0.22587830477533577,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4230262470","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0039731488,0.011559794,0.2500772,0.0019862857,0.003142393,0.0005914808,0.007920084,0.030402444,0.69034725],"genre_scores_gemma":[0.029853435,0.01656733,0.2674932,0.0022919984,0.0011356975,0.0008123553,0.027854767,0.012590346,0.64140093],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984457,0.00012166102,0.00010140217,0.0002602154,0.0009358499,0.00013520876],"domain_scores_gemma":[0.99851865,0.00024333646,0.00004805738,0.00054576376,0.00054015673,0.00010404816],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006276461,0.0010766648,0.0010906165,0.0025478823,0.0014883336,0.0052802744,0.0036681513,0.0015204629,0.14270377],"category_scores_gemma":[0.0027613214,0.00058815477,0.0009054608,0.0058553293,0.0005928614,0.005759799,0.0037232633,0.0019649607,0.13060588],"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":[0.00008772356,0.00006343844,0.0002194111,0.00067492167,0.000017119568,0.00018800938,0.00020449099,0.0017907197,0.0036929494,0.08805208,0.3587063,0.54630286],"study_design_scores_gemma":[0.0000058768824,0.000016151127,0.000084690364,0.000056156674,0.0000040921236,0.00033326415,0.00003592105,0.0019780945,0.0012415026,0.0069261496,0.98930407,0.000013889735],"about_ca_topic_score_codex":0.0032074875,"about_ca_topic_score_gemma":0.004324879,"teacher_disagreement_score":0.14270377,"about_ca_system_score_codex":0.0015915124,"about_ca_system_score_gemma":0.0017256548,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W4230504145","doi":"10.1145/2488222","title":"Proceedings of the 7th ACM international conference on Distributed event-based systems","year":2013,"lang":"en","type":"paratext","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Complex event processing; Event (particle physics); World Wide Web; Publication; Middleware (distributed applications); Cloud computing; The Internet; Variety (cybernetics); Data science; Stream processing; Process (computing); Database","score_opus":0.030477892724154708,"score_gpt":0.27829935553437807,"score_spread":0.24782146281022335,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4230504145","genre_codex":"methods","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":[0.010603669,0.054034192,0.5803946,0.020330822,0.091354735,0.0021459819,0.0036140422,0.0116088595,0.22591306],"genre_scores_gemma":[0.13330466,0.057692483,0.25745082,0.011071931,0.02526481,0.0023268498,0.021901727,0.003220386,0.48776639],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9967219,0.00082176866,0.00043080005,0.0005298987,0.0012606853,0.00023492055],"domain_scores_gemma":[0.99504733,0.0016093528,0.00017205667,0.001044715,0.001497506,0.0006291063],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0044098203,0.0018697619,0.0022012198,0.0010189925,0.0008736315,0.0066152266,0.002870402,0.002463586,0.08974504],"category_scores_gemma":[0.008854232,0.0006135073,0.0013287776,0.0011197029,0.001272627,0.00478907,0.003172494,0.004207585,0.037457224],"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":[0.00050013495,0.00040308514,0.0013586186,0.0009444957,0.0002761594,0.00073726976,0.00038303327,0.0042569325,0.0060061803,0.030838251,0.5674533,0.38684258],"study_design_scores_gemma":[0.000087218774,0.0001337276,0.00060388877,0.00027174514,0.00006471864,0.00046414783,0.00013253503,0.012388429,0.0011705438,0.015274947,0.969369,0.00003915446],"about_ca_topic_score_codex":0.0019376185,"about_ca_topic_score_gemma":0.0014840666,"teacher_disagreement_score":0.91025496,"about_ca_system_score_codex":0.0007387192,"about_ca_system_score_gemma":0.0020817055,"threshold_uncertainty_score":0.3002271},"labels":[],"label_agreement":null},{"id":"W4230614195","doi":"10.1145/944877.944879","title":"Scenario-based and model-driven information development with XML DITA","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada)","funders":"","keywords":"Computer science; XML; Process (computing); World Wide Web; Information model; Software engineering","score_opus":0.008794466694148807,"score_gpt":0.19594950260967414,"score_spread":0.18715503591552535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4230614195","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":[0.0063947877,0.000112264504,0.97200316,0.00064857356,0.000059424656,0.00057628803,0.0003312539,0.0023336394,0.017540568],"genre_scores_gemma":[0.08060895,0.0002579001,0.9089343,0.0002016597,0.000018418172,0.00083891,0.0010761786,0.00046736567,0.007596396],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99205595,0.005120674,0.00050951634,0.0004587779,0.0016520944,0.00020298708],"domain_scores_gemma":[0.9875874,0.0077621546,0.00043723956,0.0020473208,0.001738893,0.00042700418],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008248411,0.0009261399,0.0003930898,0.0016276063,0.0011196667,0.0051995274,0.0024497653,0.0018629016,0.009077652],"category_scores_gemma":[0.018467598,0.0010126599,0.0011174403,0.0012255657,0.0012390581,0.004878243,0.0037154586,0.0021689455,0.0026998753],"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":[0.00038214045,0.00070560776,0.0036787468,0.0012943676,0.00017340393,0.0022427237,0.010154569,0.16715255,0.013496577,0.4707986,0.025197975,0.30472273],"study_design_scores_gemma":[0.00016188594,0.00033682477,0.00092298305,0.0007238679,0.00008760669,0.0013668138,0.0026549608,0.4853514,0.020851508,0.14897265,0.33836222,0.00020734456],"about_ca_topic_score_codex":0.0031514391,"about_ca_topic_score_gemma":0.004087427,"teacher_disagreement_score":0.009077652,"about_ca_system_score_codex":0.0017068572,"about_ca_system_score_gemma":0.0020582322,"threshold_uncertainty_score":0.043622255},"labels":[],"label_agreement":null},{"id":"W4230628416","doi":"10.1007/978-1-4614-8265-9_321","title":"Scheduling Strategies for Data Stream Processing","year":2018,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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 Toronto","funders":"","keywords":"Computer science; Stream processing; Scheduling (production processes); Distributed computing; Engineering; Operations management","score_opus":0.046833335357245105,"score_gpt":0.29341103455515116,"score_spread":0.24657769919790606,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4230628416","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":[0.0068633235,0.0047908463,0.9705677,0.0005084688,0.00054983457,0.00014258,0.00014923599,0.0010766481,0.015351294],"genre_scores_gemma":[0.2941779,0.0090884175,0.65855724,0.0005061456,0.0014723034,0.00041541233,0.0008323922,0.0010850334,0.03386518],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9993962,0.00013356764,0.000055471985,0.000087417284,0.0002540217,0.00007329232],"domain_scores_gemma":[0.9990717,0.000423089,0.000049590715,0.00014967947,0.00024085214,0.000065073225],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011007236,0.0013062578,0.00091056916,0.00079596613,0.0006829977,0.0021528476,0.0018947213,0.0005919506,0.008034461],"category_scores_gemma":[0.0033036328,0.00045376862,0.0004950249,0.001765088,0.00054563564,0.0018090423,0.0010426338,0.0013842606,0.0024018758],"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":[0.0005653107,0.00026662773,0.0003682657,0.00048095876,0.00008238674,0.00013987896,0.00023265665,0.13360843,0.0148257725,0.25641173,0.03965364,0.55336434],"study_design_scores_gemma":[0.0000655477,0.00007945164,0.00014523652,0.000056309458,0.000043349137,0.00009427542,0.000084036896,0.7717628,0.0060301176,0.19454585,0.027070016,0.000023027998],"about_ca_topic_score_codex":0.0023367105,"about_ca_topic_score_gemma":0.0022950089,"teacher_disagreement_score":0.008034461,"about_ca_system_score_codex":0.0011855684,"about_ca_system_score_gemma":0.0013265654,"threshold_uncertainty_score":0.026878},"labels":[],"label_agreement":null},{"id":"W4230811822","doi":"10.1007/978-0-387-39940-9_3372","title":"Query by Example","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Computer science; Information retrieval","score_opus":0.015607465469600207,"score_gpt":0.22605913520893345,"score_spread":0.21045166973933324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4230811822","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0069234692,0.0043390407,0.31229252,0.00747995,0.0019405538,0.0014886726,0.03354141,0.04096274,0.59103155],"genre_scores_gemma":[0.123578906,0.008715971,0.23991425,0.0067066713,0.0013829978,0.0016208708,0.061517525,0.015950792,0.5406119],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984999,0.00024297686,0.00010359945,0.00028003348,0.000712247,0.00016125721],"domain_scores_gemma":[0.99899346,0.00041894373,0.0000346129,0.00026626332,0.00023535894,0.00005141739],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006943243,0.0012920665,0.0013492968,0.0017920989,0.0008140784,0.004171528,0.0015005734,0.0015633308,0.17914148],"category_scores_gemma":[0.0048074047,0.00044503555,0.0009985471,0.002337283,0.0005886307,0.006039688,0.0025291222,0.0012105774,0.09561847],"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":[0.00024251066,0.00007917329,0.00036147112,0.0008097369,0.00004169096,0.00033248065,0.00027978898,0.0011127619,0.0027315253,0.10761828,0.7060628,0.18032776],"study_design_scores_gemma":[0.00004957219,0.000021638238,0.0001809905,0.00012103176,0.000023656981,0.0003827354,0.00010356938,0.0040129474,0.0018801906,0.030384716,0.96281326,0.000025786454],"about_ca_topic_score_codex":0.0029653287,"about_ca_topic_score_gemma":0.003496311,"teacher_disagreement_score":0.17914148,"about_ca_system_score_codex":0.00096285634,"about_ca_system_score_gemma":0.00072164735,"threshold_uncertainty_score":0.5992879},"labels":[],"label_agreement":null},{"id":"W4231265779","doi":"10.1007/978-0-387-39940-9_4064","title":"XML Algebra","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Computer science; Algebra over a field; XML; Programming language; Mathematics; Pure mathematics; World Wide Web","score_opus":0.013363270126731112,"score_gpt":0.2297912186363211,"score_spread":0.21642794850959,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4231265779","genre_codex":"other","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":[0.0015240073,0.006692159,0.3899494,0.0026655083,0.0012476394,0.00020797054,0.0040968666,0.009272659,0.58434385],"genre_scores_gemma":[0.04287431,0.012208332,0.25514883,0.0027531206,0.0014255309,0.0004116314,0.015535303,0.0041093617,0.6655336],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9991941,0.00012785077,0.00009058657,0.00018915186,0.00035296186,0.000045299184],"domain_scores_gemma":[0.9995338,0.00010905541,0.000021433978,0.0001785258,0.00012903447,0.000028172444],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007685646,0.0009800512,0.000843348,0.0023996218,0.0011135034,0.0047696778,0.0015673641,0.0008883097,0.08790729],"category_scores_gemma":[0.0016752685,0.0007544901,0.0010664115,0.0031848382,0.0013930671,0.008096169,0.0020554047,0.0024579193,0.06439284],"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":[0.000023558512,0.000038151014,0.000097597695,0.00023481005,0.000013621832,0.000068896625,0.00020490342,0.00037834723,0.0013048517,0.71299154,0.12927563,0.15536802],"study_design_scores_gemma":[0.00000891161,0.000008131279,0.00009716514,0.00007944786,0.000010905423,0.000258854,0.00004213067,0.001125089,0.0013260468,0.24695575,0.75007415,0.000013412888],"about_ca_topic_score_codex":0.0015995031,"about_ca_topic_score_gemma":0.0017458476,"teacher_disagreement_score":0.08790729,"about_ca_system_score_codex":0.0010679105,"about_ca_system_score_gemma":0.0009870445,"threshold_uncertainty_score":0.29407918},"labels":[],"label_agreement":null},{"id":"W4231701252","doi":"10.1007/978-1-4939-7131-2_100934","title":"Query Auto-Completion","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Database Systems and Queries","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 Calgary","funders":"","keywords":"Computer science; Completion (oil and gas wells); Information retrieval; Engineering; Mechanical engineering","score_opus":0.02395121053661155,"score_gpt":0.23720841819948457,"score_spread":0.213257207662873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4231701252","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":[0.0033785112,0.0027075275,0.93972844,0.00066441804,0.00061257585,0.0002242536,0.0012531037,0.015030354,0.036400806],"genre_scores_gemma":[0.07880777,0.0034418502,0.77546436,0.0009786659,0.000863738,0.0002869898,0.010518264,0.004251167,0.12538716],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9969324,0.00034698495,0.00016602366,0.0008032343,0.0015551336,0.00019611194],"domain_scores_gemma":[0.9972548,0.00051203405,0.00006247734,0.0013389966,0.0007587635,0.00007293712],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018929706,0.0016417768,0.0016708862,0.0016817614,0.0008509102,0.0023238268,0.0023403629,0.00085278647,0.032933954],"category_scores_gemma":[0.0048554773,0.00089764514,0.0014414783,0.0023675303,0.0010196937,0.0038554624,0.0028640619,0.0030111636,0.024720423],"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":[0.00019284108,0.00014749319,0.0002636645,0.0005660115,0.0000690024,0.000074434836,0.00016137604,0.006263746,0.008360905,0.060886886,0.15351498,0.76949865],"study_design_scores_gemma":[0.00006838059,0.00014165102,0.000918964,0.00018771758,0.00013902666,0.0012003509,0.00019461157,0.21141672,0.053782158,0.17024034,0.5615959,0.00011416134],"about_ca_topic_score_codex":0.0028632027,"about_ca_topic_score_gemma":0.0028216424,"teacher_disagreement_score":0.032933954,"about_ca_system_score_codex":0.00088533957,"about_ca_system_score_gemma":0.0016428666,"threshold_uncertainty_score":0.11017501},"labels":[],"label_agreement":null},{"id":"W4231828660","doi":"10.22215/etd/2014-10052","title":"Parallel Real-Time OLAP On Cloud Platforms","year":2014,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Online analytical processing; Computer science; Scalability; Cloud computing; Database; Skyline; Tuple; Distributed computing; Business intelligence; NoSQL; Data warehouse; Data mining; Operating system","score_opus":0.010781990047406018,"score_gpt":0.25611350619544127,"score_spread":0.24533151614803525,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4231828660","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":[0.2569613,0.002186924,0.69156927,0.0019186224,0.0004531485,0.00063032826,0.0013443001,0.015956616,0.028979529],"genre_scores_gemma":[0.59794694,0.0011966866,0.38864768,0.0002251327,0.00015081605,0.0002637616,0.0019326651,0.00069247675,0.008943822],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99843794,0.00017407334,0.00009669331,0.000288039,0.0007682579,0.00023501505],"domain_scores_gemma":[0.9979463,0.00036833325,0.00012798712,0.00075224444,0.0006440997,0.0001609887],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010607389,0.00073080906,0.0005021694,0.0005501298,0.0010264546,0.0020357294,0.0015033337,0.00040996532,0.0023464686],"category_scores_gemma":[0.0025807251,0.00045256794,0.00061476516,0.0015380481,0.00047385684,0.0024961482,0.001155996,0.0009573614,0.0014110109],"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":[0.0017550305,0.00058300764,0.0075619216,0.00053271494,0.00020344608,0.0010480362,0.0008762479,0.2964055,0.113587506,0.050580636,0.05391059,0.47295538],"study_design_scores_gemma":[0.00016642117,0.0001826758,0.0022949274,0.000033207823,0.000056225104,0.00023623167,0.00039747744,0.9069114,0.04041623,0.021087978,0.028170956,0.000046365836],"about_ca_topic_score_codex":0.0096553955,"about_ca_topic_score_gemma":0.010338047,"teacher_disagreement_score":0.0096553955,"about_ca_system_score_codex":0.0011552535,"about_ca_system_score_gemma":0.0024086253,"threshold_uncertainty_score":0.019198358},"labels":[],"label_agreement":null},{"id":"W4232301754","doi":"10.1007/978-0-387-39940-9_2775","title":"Homogeneous Distributed Database Systems","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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":"Homogeneous; Database; Computer science; Distributed database; Distributed computing; Physics; Statistical physics","score_opus":0.014708082373952805,"score_gpt":0.2309667022704371,"score_spread":0.21625861989648432,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4232301754","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":[0.010304636,0.011791737,0.73382914,0.0014168976,0.0013016874,0.0004206521,0.0014467158,0.013745988,0.22574247],"genre_scores_gemma":[0.22043638,0.015904553,0.32859662,0.001023324,0.0018826108,0.00044544184,0.006187247,0.0020970819,0.42342675],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99913186,0.00010796247,0.000068182504,0.00019701303,0.0004097174,0.000085302774],"domain_scores_gemma":[0.9989555,0.00014588192,0.000041435942,0.0005578568,0.00022117438,0.00007818899],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00080012856,0.0006725653,0.0008895437,0.001130716,0.0008877089,0.0033682259,0.0018098319,0.0005092461,0.027413175],"category_scores_gemma":[0.0018863704,0.00069220684,0.00043828366,0.0025161183,0.0008450215,0.0031426344,0.0019439611,0.00094241434,0.014953061],"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":[0.00018992159,0.0001389657,0.00068816997,0.000625994,0.00007204161,0.0002762879,0.0004489009,0.0040925434,0.008981268,0.36082128,0.14039196,0.48327264],"study_design_scores_gemma":[0.00006863444,0.000105244435,0.0011082374,0.0001152406,0.00009492007,0.0007291429,0.00012839182,0.020895587,0.010184535,0.19708005,0.76945645,0.000033582437],"about_ca_topic_score_codex":0.00096287695,"about_ca_topic_score_gemma":0.0012099347,"teacher_disagreement_score":0.027413175,"about_ca_system_score_codex":0.0008148444,"about_ca_system_score_gemma":0.00120505,"threshold_uncertainty_score":0.09170616},"labels":[],"label_agreement":null},{"id":"W4232517555","doi":"10.1007/978-1-4939-7131-2_100489","title":"Incremental Computation","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Database Systems and Queries","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 Calgary","funders":"","keywords":"Computer science","score_opus":0.02435688631042499,"score_gpt":0.2546877465954034,"score_spread":0.2303308602849784,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4232517555","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":[0.0038895505,0.0062462287,0.58607626,0.0018639616,0.0015134099,0.00016889692,0.0010173643,0.004321908,0.39490244],"genre_scores_gemma":[0.15602212,0.0095107965,0.47860295,0.0009501408,0.0019328372,0.0003556917,0.0050490554,0.0029663516,0.34461007],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99944323,0.000057175428,0.000026118418,0.00016139848,0.00026603817,0.000046039993],"domain_scores_gemma":[0.9992551,0.00020059462,0.000016794747,0.00032425547,0.0001722694,0.000031019717],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040991785,0.00085903733,0.00064051105,0.0010450443,0.0007565186,0.002280169,0.0015580041,0.0005895863,0.040729247],"category_scores_gemma":[0.00266346,0.00044001002,0.0007055051,0.0018846052,0.0009424364,0.003562448,0.0014970376,0.0019054508,0.015583121],"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":[0.000058429338,0.000034036442,0.00012601193,0.00026820024,0.000019806797,0.00003275901,0.00008432404,0.0040163007,0.001816498,0.41743475,0.1146488,0.46146014],"study_design_scores_gemma":[0.00002313212,0.000025363755,0.00033601085,0.000119546654,0.000037491278,0.00021762396,0.00004288181,0.03336067,0.0047457395,0.48899674,0.47206786,0.000026893033],"about_ca_topic_score_codex":0.0015278689,"about_ca_topic_score_gemma":0.0020462302,"teacher_disagreement_score":0.040729247,"about_ca_system_score_codex":0.0010566446,"about_ca_system_score_gemma":0.0010147798,"threshold_uncertainty_score":0.13625294},"labels":[],"label_agreement":null},{"id":"W4232759479","doi":"10.1007/978-1-4614-8265-9_1253","title":"Conditional Tables","year":2018,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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":"Concordia University","funders":"","keywords":"Mathematics","score_opus":0.01585190145949603,"score_gpt":0.23721063138214465,"score_spread":0.22135872992264863,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4232759479","genre_codex":"methods","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":[0.0035647566,0.0024997748,0.52419055,0.0029563203,0.0019302253,0.0004589083,0.04049754,0.035704132,0.38819784],"genre_scores_gemma":[0.08257389,0.005548996,0.3132433,0.0027848883,0.0015415553,0.00063152786,0.09177849,0.0126235075,0.48927385],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988986,0.00015890083,0.0000887414,0.00032528062,0.00043871588,0.000089767935],"domain_scores_gemma":[0.99788034,0.0007487421,0.00008381863,0.0007272351,0.000466032,0.00009380655],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010397888,0.0010706552,0.00069574383,0.0021144594,0.0010077971,0.0041063516,0.002054209,0.00074108416,0.21525562],"category_scores_gemma":[0.0061308797,0.0008396779,0.0009933496,0.0030103433,0.00082772924,0.0074852803,0.0022874353,0.0019802472,0.103904754],"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":[0.00011651549,0.000054844313,0.00037174218,0.00036951047,0.000021907106,0.00009907071,0.00015696476,0.0012096812,0.001718361,0.3370044,0.40498334,0.25389376],"study_design_scores_gemma":[0.000018243532,0.000018667708,0.0002058763,0.00011886978,0.000024695553,0.00025039387,0.00004084801,0.00304247,0.0028214415,0.15355353,0.8398752,0.000029795287],"about_ca_topic_score_codex":0.0015665472,"about_ca_topic_score_gemma":0.0019248421,"teacher_disagreement_score":0.21525562,"about_ca_system_score_codex":0.00089105417,"about_ca_system_score_gemma":0.0016348992,"threshold_uncertainty_score":0.7201018},"labels":[],"label_agreement":null},{"id":"W4233461207","doi":"10.1007/978-0-387-39940-9_3453","title":"Relational Query Processor","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Computer science; Query optimization; Sargable; Information retrieval; Database; Web search query; Search engine","score_opus":0.023405504392865047,"score_gpt":0.23585986255759847,"score_spread":0.21245435816473343,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4233461207","genre_codex":"methods","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":[0.0044050794,0.003462987,0.6855683,0.0012054406,0.0005279606,0.0007325842,0.017119799,0.12114383,0.16583395],"genre_scores_gemma":[0.04904797,0.004860452,0.5709943,0.0018855699,0.00045269946,0.00056403904,0.06497641,0.01145775,0.29576084],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99906033,0.000071435985,0.000075843964,0.0002350705,0.00047766196,0.000079623234],"domain_scores_gemma":[0.9992536,0.00015593247,0.000027257794,0.00024261269,0.00027983784,0.000040764713],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00078105787,0.0012684985,0.0012674719,0.0020126002,0.0007804233,0.0040184935,0.002459137,0.0007992012,0.10301222],"category_scores_gemma":[0.0021300835,0.00077138067,0.0008158583,0.0031237926,0.0005095743,0.004361038,0.0018838592,0.001579106,0.10504505],"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":[0.00026351548,0.00013332414,0.00037737202,0.00059504516,0.000044856857,0.00014996098,0.00018110896,0.0013263477,0.013752982,0.065085866,0.3339455,0.58414406],"study_design_scores_gemma":[0.00009368039,0.00010178157,0.00053340005,0.00013770034,0.000091580136,0.0007345107,0.00013700557,0.015544336,0.039361384,0.042888153,0.9003102,0.00006624702],"about_ca_topic_score_codex":0.0022358499,"about_ca_topic_score_gemma":0.0022074527,"teacher_disagreement_score":0.10301222,"about_ca_system_score_codex":0.0007624635,"about_ca_system_score_gemma":0.0015334717,"threshold_uncertainty_score":0.3446102},"labels":[],"label_agreement":null},{"id":"W4233925792","doi":"10.1145/956718.956721","title":"Partial answers in information integration systems","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Concordia University","funders":"","keywords":"Citation; World Wide Web; Library science; Computer science","score_opus":0.010095854802269493,"score_gpt":0.22456011690282532,"score_spread":0.21446426210055583,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4233925792","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":[0.018912563,0.06416638,0.45552185,0.08770367,0.0047970936,0.00047161142,0.001761763,0.0032631308,0.36340186],"genre_scores_gemma":[0.51312196,0.049525075,0.20521544,0.011953561,0.008088477,0.0011760693,0.006034596,0.0017091328,0.2031757],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9855692,0.007300946,0.0012381491,0.001517946,0.0036417418,0.0007320981],"domain_scores_gemma":[0.98084337,0.01097251,0.0006696208,0.0040156604,0.0028000495,0.0006987674],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010353778,0.00092183717,0.0013584037,0.0043191686,0.004179969,0.013677952,0.0017206618,0.0044552837,0.03697913],"category_scores_gemma":[0.034950398,0.0010516439,0.0013209821,0.008488858,0.008562572,0.043885987,0.009882034,0.0036415674,0.008736262],"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":[0.000042612017,0.000029903857,0.00046005973,0.0003993136,0.000024721425,0.00015603782,0.0017073074,0.0009735458,0.00017867763,0.8643534,0.041978575,0.08969582],"study_design_scores_gemma":[0.000017002369,0.000023285582,0.00015272449,0.00023186233,0.0000181321,0.00018277718,0.00052008894,0.0021621573,0.00024637097,0.7794137,0.21701291,0.000018962104],"about_ca_topic_score_codex":0.002921974,"about_ca_topic_score_gemma":0.0023563525,"teacher_disagreement_score":0.03697913,"about_ca_system_score_codex":0.0035141506,"about_ca_system_score_gemma":0.0032036128,"threshold_uncertainty_score":0.12370753},"labels":[],"label_agreement":null},{"id":"W4235025869","doi":"10.1007/978-1-4614-6170-8_100621","title":"Data Integration","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Database Systems and Queries","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 Calgary","funders":"","keywords":"Computer science","score_opus":0.060285155772828676,"score_gpt":0.2734954247683652,"score_spread":0.21321026899553652,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4235025869","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":[0.00434818,0.0076881098,0.6259648,0.002847801,0.0019773606,0.00080824894,0.0042860047,0.014559918,0.33751962],"genre_scores_gemma":[0.052236572,0.0102810785,0.52062684,0.0047744154,0.0009736876,0.0007282724,0.02206378,0.004590924,0.3837244],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99818265,0.00015311647,0.00013752904,0.0004815724,0.0009481562,0.00009698281],"domain_scores_gemma":[0.9986124,0.00022680488,0.000037364625,0.00057264324,0.00049079827,0.0000599187],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001788386,0.0013233683,0.0011424707,0.0034539897,0.001212463,0.0060185674,0.0028563982,0.0011030152,0.054647785],"category_scores_gemma":[0.0039592716,0.00087087724,0.0013795741,0.005338562,0.0008031719,0.006489038,0.004808018,0.0021870951,0.045474477],"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":[0.00007296172,0.0001051931,0.0005111717,0.00055282254,0.00005388373,0.00012778648,0.00032763885,0.0007873684,0.007018662,0.10357781,0.152597,0.73426765],"study_design_scores_gemma":[0.000013459876,0.000028130375,0.00038207448,0.00020029707,0.000051598752,0.0004602316,0.00013970167,0.004483781,0.011677844,0.05887857,0.9236554,0.000028859657],"about_ca_topic_score_codex":0.0017354055,"about_ca_topic_score_gemma":0.001347608,"teacher_disagreement_score":0.054647785,"about_ca_system_score_codex":0.00095192326,"about_ca_system_score_gemma":0.0016348743,"threshold_uncertainty_score":0.18281507},"labels":[],"label_agreement":null},{"id":"W4236293190","doi":"10.1007/978-1-4614-8265-9_376","title":"Structural Indexing","year":2018,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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 Toronto","funders":"","keywords":"Search engine indexing; Computer science; Information retrieval","score_opus":0.018939290059797307,"score_gpt":0.24289439490907605,"score_spread":0.22395510484927875,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4236293190","genre_codex":"other","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":[0.0034398446,0.009710404,0.25978312,0.0021749642,0.0030208167,0.0005124678,0.009252549,0.01744879,0.6946571],"genre_scores_gemma":[0.05538075,0.016798522,0.2419587,0.0016838973,0.0024567195,0.0005273789,0.048488636,0.00668922,0.62601626],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99878293,0.000103424456,0.000093968265,0.0002310518,0.0006832116,0.00010545898],"domain_scores_gemma":[0.9985763,0.00020397369,0.000058836984,0.0006280559,0.00046312428,0.000069640744],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00070659816,0.0011786254,0.0009250371,0.004176548,0.0014548635,0.004621327,0.0021304789,0.0008729134,0.13939632],"category_scores_gemma":[0.0029567457,0.00061403576,0.00081608264,0.007899631,0.0011961244,0.00723944,0.002823484,0.0015935745,0.115618385],"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":[0.00005528294,0.00007193077,0.00012773566,0.00044028077,0.000012844545,0.000040125142,0.00014141531,0.000546259,0.003933069,0.17414024,0.2777145,0.5427762],"study_design_scores_gemma":[0.000013628444,0.000035041103,0.00015975573,0.00012546046,0.000016466876,0.00026737034,0.00007638236,0.001609592,0.005227783,0.113965966,0.878482,0.000020530546],"about_ca_topic_score_codex":0.0012934937,"about_ca_topic_score_gemma":0.0016825045,"teacher_disagreement_score":0.13939632,"about_ca_system_score_codex":0.0013341284,"about_ca_system_score_gemma":0.0020887435,"threshold_uncertainty_score":0.4663272},"labels":[],"label_agreement":null},{"id":"W4236324772","doi":"10.1145/564704.564707","title":"Covering indexes for branching path queries","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bell (Canada)","funders":"","keywords":"Computer science; Branching (polymer chemistry); XML; Path (computing); Inverted index; Index (typography); Path expression; Data mining; Graph; Relational database; Online analytical processing; Table (database); Theoretical computer science; Data structure; Algorithm; Information retrieval; Query language; Data warehouse; Search engine indexing","score_opus":0.02274538969717762,"score_gpt":0.22575433056606475,"score_spread":0.20300894086888713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4236324772","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":[0.052947745,0.0011307951,0.92975307,0.0004459555,0.00011063391,0.00026813897,0.0006133994,0.006673492,0.008056845],"genre_scores_gemma":[0.2874231,0.0013500649,0.7031797,0.0003176808,0.00028157188,0.00030742062,0.0029032642,0.0011671971,0.003069898],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99655235,0.0006583542,0.00048537744,0.00040395444,0.0015927128,0.0003071998],"domain_scores_gemma":[0.9880862,0.005009576,0.0010853321,0.0043213237,0.0011946923,0.000302855],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027419354,0.0006394208,0.001176185,0.0014911494,0.0009473324,0.0033383155,0.0015231582,0.0007065052,0.0037105407],"category_scores_gemma":[0.018023795,0.00055909454,0.0007642625,0.003934895,0.0009871987,0.010607802,0.002505747,0.0011326137,0.0014304189],"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":[0.0007098382,0.00022968421,0.005913632,0.00050519226,0.00008242721,0.00042506983,0.0012352036,0.03943892,0.034381803,0.37891695,0.0178177,0.5203436],"study_design_scores_gemma":[0.00014654706,0.000920549,0.0027094085,0.00019591657,0.00023069559,0.0020101883,0.00059194636,0.42984337,0.07214673,0.33477604,0.1562744,0.0001541711],"about_ca_topic_score_codex":0.00080454117,"about_ca_topic_score_gemma":0.00070512766,"teacher_disagreement_score":0.0037105407,"about_ca_system_score_codex":0.00094262854,"about_ca_system_score_gemma":0.0012943342,"threshold_uncertainty_score":0.014500916},"labels":[],"label_agreement":null},{"id":"W4236326403","doi":"10.1007/978-1-4939-7131-2_101008","title":"Routine Discovery","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Database Systems and Queries","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 Calgary","funders":"","keywords":"Computer science","score_opus":0.01710940862590676,"score_gpt":0.2295186142945256,"score_spread":0.21240920566861884,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4236326403","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":[0.005558319,0.003538824,0.48275062,0.0038022997,0.0016249561,0.0006197277,0.0038107745,0.022681024,0.47561347],"genre_scores_gemma":[0.05933181,0.004362417,0.31087798,0.0020685613,0.0012312252,0.0004423209,0.01217372,0.0073123514,0.6021997],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99664766,0.00042450667,0.000191888,0.0011293738,0.001341432,0.00026512987],"domain_scores_gemma":[0.99459547,0.0015551738,0.00014353279,0.002513062,0.0009925443,0.00020021792],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024705858,0.0015188651,0.0015092309,0.0033008594,0.0023021793,0.0068649286,0.0043819225,0.0016246206,0.08834116],"category_scores_gemma":[0.009929881,0.0012905495,0.0017561043,0.0035672567,0.002278862,0.010820694,0.0047734166,0.0039149444,0.07005716],"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":[0.00012260502,0.00008749711,0.00038638423,0.0004573372,0.000023910932,0.00010042992,0.00045605146,0.0005384588,0.0026460406,0.42355454,0.16320719,0.40841946],"study_design_scores_gemma":[0.000018155968,0.00003730938,0.00027170047,0.00014206946,0.000031936026,0.00054750644,0.00014080707,0.004181432,0.0060303994,0.19731191,0.79123974,0.000046977588],"about_ca_topic_score_codex":0.002436838,"about_ca_topic_score_gemma":0.0026826756,"teacher_disagreement_score":0.08834116,"about_ca_system_score_codex":0.001993014,"about_ca_system_score_gemma":0.003421725,"threshold_uncertainty_score":0.29553062},"labels":[],"label_agreement":null},{"id":"W4236708366","doi":"10.1007/978-1-4614-8265-9_1252","title":"Naive Tables","year":2018,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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":"Concordia University","funders":"","keywords":"Computer science","score_opus":0.01591028610874517,"score_gpt":0.23639283153991794,"score_spread":0.22048254543117277,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4236708366","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0046763816,0.0063253455,0.44706035,0.003340703,0.0025991495,0.0004053747,0.01319704,0.015962496,0.50643325],"genre_scores_gemma":[0.09453631,0.0077071874,0.430241,0.0034934299,0.0021031532,0.00042631873,0.03777138,0.005326499,0.41839477],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9980835,0.00024112985,0.00016096138,0.00052718807,0.0008605989,0.0001266583],"domain_scores_gemma":[0.9971904,0.0006752428,0.000102349724,0.0013098328,0.0006069867,0.00011524071],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009896632,0.001101461,0.0010688448,0.0023064504,0.0015164418,0.0064503304,0.0026533648,0.0010720412,0.16963422],"category_scores_gemma":[0.007667021,0.0010288483,0.0012247651,0.004074787,0.0012904438,0.013287366,0.002985939,0.0023845092,0.08663811],"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":[0.00013814986,0.00006840056,0.00036305282,0.0004918579,0.000037044247,0.000065957436,0.00015241405,0.0012659788,0.0014037715,0.35207617,0.28093362,0.36300358],"study_design_scores_gemma":[0.00003777288,0.00003131225,0.0001938842,0.00017138408,0.00004210499,0.00030818538,0.000066906316,0.0047128536,0.001832756,0.45345083,0.53912,0.000032075866],"about_ca_topic_score_codex":0.0015423401,"about_ca_topic_score_gemma":0.002311368,"teacher_disagreement_score":0.16963422,"about_ca_system_score_codex":0.0011335711,"about_ca_system_score_gemma":0.0017346251,"threshold_uncertainty_score":0.567483},"labels":[],"label_agreement":null},{"id":"W4236891725","doi":"10.1007/978-0-387-39940-9_3681","title":"State Query","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Computer science; State (computer science); Programming language","score_opus":0.01324344395891597,"score_gpt":0.2309368336074287,"score_spread":0.21769338964851273,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4236891725","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0077185864,0.0022663826,0.37240326,0.0041471664,0.0015550548,0.0011583556,0.04897873,0.08773089,0.4740416],"genre_scores_gemma":[0.17305164,0.0036952854,0.13644731,0.003808489,0.000911885,0.0011089114,0.08581478,0.014585821,0.5805758],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986614,0.00015114478,0.000095389754,0.00033498096,0.00062043837,0.00013656903],"domain_scores_gemma":[0.99885666,0.0002690126,0.000041628646,0.00044134157,0.00033747818,0.000053885804],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009415115,0.0011255998,0.0010796393,0.0022809599,0.0008915629,0.0042823018,0.0015647002,0.0009719956,0.12697315],"category_scores_gemma":[0.0037923043,0.00045468376,0.0009473428,0.0023233825,0.0006694267,0.0059252833,0.0026401393,0.001407132,0.061424576],"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":[0.00037005282,0.0001363052,0.00083652284,0.00040101315,0.00004461455,0.000111186906,0.00035889144,0.0016875702,0.0036793633,0.16088207,0.5933567,0.23813571],"study_design_scores_gemma":[0.00006477884,0.00005354756,0.00044089454,0.00010384921,0.000054162338,0.00018866581,0.00019010439,0.013701034,0.0080958465,0.07707256,0.8999899,0.000044758584],"about_ca_topic_score_codex":0.004980225,"about_ca_topic_score_gemma":0.0057132267,"teacher_disagreement_score":0.12697315,"about_ca_system_score_codex":0.001321274,"about_ca_system_score_gemma":0.0014239834,"threshold_uncertainty_score":0.4247675},"labels":[],"label_agreement":null},{"id":"W4237640382","doi":"10.1007/978-0-387-39940-9_2087","title":"Auto-administration and Auto-Tuning of Database Systems","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Administration (probate law); Database; Computer science; Political science","score_opus":0.017924751102816244,"score_gpt":0.24644849275045333,"score_spread":0.22852374164763709,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4237640382","genre_codex":"methods","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":[0.025009662,0.008784857,0.8893995,0.0008495879,0.0004865549,0.00016655624,0.00025190407,0.020329239,0.05472219],"genre_scores_gemma":[0.4980358,0.008818827,0.38615718,0.00080539373,0.0008507363,0.00025013677,0.0012830534,0.004091315,0.09970751],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9981799,0.00031050137,0.0001353722,0.0003263038,0.0009136792,0.0001342135],"domain_scores_gemma":[0.99633753,0.0009703467,0.00013861693,0.0019790747,0.00048440238,0.000090083115],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016978089,0.00053144584,0.00068256014,0.0007701464,0.0003652605,0.0029307478,0.0017238272,0.00063966314,0.005469132],"category_scores_gemma":[0.0043914127,0.00063635554,0.0004954833,0.001148616,0.00077380514,0.003379592,0.0012794873,0.0015312247,0.0026456723],"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":[0.00019023148,0.00014760833,0.0015673817,0.00042428917,0.00006264022,0.00016220233,0.00035072395,0.018558584,0.020511959,0.0899252,0.02606982,0.84202945],"study_design_scores_gemma":[0.00008239658,0.00020263906,0.0042555206,0.0002633984,0.00012540647,0.001600681,0.00015052552,0.399095,0.061278038,0.17732584,0.35551575,0.00010475016],"about_ca_topic_score_codex":0.0007580337,"about_ca_topic_score_gemma":0.00063624274,"teacher_disagreement_score":0.005469132,"about_ca_system_score_codex":0.0006655513,"about_ca_system_score_gemma":0.0009553009,"threshold_uncertainty_score":0.018296123},"labels":[],"label_agreement":null},{"id":"W4237714359","doi":"10.1007/978-1-4614-6170-8_100878","title":"Rule-Based Systems","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Database Systems and Queries","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 Calgary","funders":"","keywords":"Computer science","score_opus":0.017061231032726616,"score_gpt":0.21604058871185902,"score_spread":0.1989793576791324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4237714359","genre_codex":"methods","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":[0.0026269746,0.010814096,0.5827257,0.002589941,0.0016706199,0.00031651347,0.0008929614,0.0038612427,0.39450195],"genre_scores_gemma":[0.061192185,0.016450461,0.5548618,0.0020338732,0.0012073627,0.00035246945,0.0043514683,0.0010753905,0.358475],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9985089,0.00021146917,0.0001236129,0.00036111925,0.00073977996,0.000055210978],"domain_scores_gemma":[0.9987758,0.0004900946,0.00003223102,0.00038036628,0.00028538535,0.000036091104],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011227946,0.000961103,0.00079335936,0.0012803216,0.0007016403,0.0043297485,0.0022254928,0.0011745917,0.036928106],"category_scores_gemma":[0.0035960414,0.00059587683,0.00085057906,0.0018271933,0.0013015202,0.0045427787,0.0017358061,0.0018666249,0.02607451],"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":[0.00002774395,0.00006405988,0.00016879848,0.0003733654,0.000046894478,0.000118346245,0.00020216372,0.0039636567,0.002136241,0.29883948,0.07228887,0.6217703],"study_design_scores_gemma":[0.000017314442,0.000035293207,0.0001807089,0.0002314745,0.000037336617,0.00030133157,0.000078165314,0.016074441,0.0028948088,0.32268193,0.6574402,0.00002693321],"about_ca_topic_score_codex":0.0013884902,"about_ca_topic_score_gemma":0.0013168318,"teacher_disagreement_score":0.036928106,"about_ca_system_score_codex":0.00078796886,"about_ca_system_score_gemma":0.0011294155,"threshold_uncertainty_score":0.123536885},"labels":[],"label_agreement":null},{"id":"W4237759199","doi":"10.5334/2004-5-downes","title":"Resource Profiles","year":2004,"lang":"en","type":"article","venue":"Journal of Interactive Media in Education","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Resource (disambiguation); Computer science; Metadata; Class (philosophy); Schema (genetic algorithms); Container (type theory); World Wide Web; Web resource; Database; Information retrieval; Artificial intelligence","score_opus":0.010333132294484036,"score_gpt":0.2896785236509787,"score_spread":0.27934539135649467,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4237759199","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":[0.0011713508,0.0012799643,0.06341328,0.016273303,0.0048941243,0.0009083675,0.010101611,0.017812349,0.8841455],"genre_scores_gemma":[0.018152788,0.0024804655,0.042351577,0.009907574,0.0020893908,0.0010034338,0.015405174,0.009733064,0.8988764],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9967892,0.0008914387,0.0003335043,0.00038687282,0.0012659597,0.0003329361],"domain_scores_gemma":[0.9889158,0.0021784713,0.0004848793,0.0034931512,0.003931081,0.0009966319],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004167069,0.00093423954,0.00067078735,0.0030555718,0.0034886159,0.008583448,0.0033553124,0.0039637308,0.30056283],"category_scores_gemma":[0.018967893,0.0008414649,0.00093615387,0.004547672,0.0010552357,0.017343177,0.007647676,0.0032996328,0.21863876],"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":[0.000039675786,0.000012694235,0.00012716318,0.00016122787,0.0000030846636,0.00012270379,0.00044019343,0.00010193992,0.0004268428,0.06645662,0.8825659,0.049541958],"study_design_scores_gemma":[0.000002742485,0.0000025507882,0.000050900202,0.000043624445,0.000001173109,0.000042616935,0.00008582429,0.000063566666,0.00011722581,0.0022507098,0.99733174,0.000007372016],"about_ca_topic_score_codex":0.008996343,"about_ca_topic_score_gemma":0.008404509,"teacher_disagreement_score":0.30056283,"about_ca_system_score_codex":0.0032921487,"about_ca_system_score_gemma":0.0048093186,"threshold_uncertainty_score":0.99766225},"labels":[],"label_agreement":null},{"id":"W4237959345","doi":"10.1007/978-0-387-39940-9_2640","title":"First-Order Query","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Computer science; Order (exchange); Information retrieval; Business","score_opus":0.01356587070026074,"score_gpt":0.2285151184432262,"score_spread":0.21494924774296545,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4237959345","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":[0.0039478033,0.0125135705,0.59367436,0.003010423,0.0014720901,0.0004780679,0.0074661574,0.014658868,0.36277866],"genre_scores_gemma":[0.08852308,0.01698614,0.45272297,0.0024511688,0.0015138409,0.00041471727,0.021853376,0.0040368554,0.41149792],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9977816,0.00020236093,0.00016360311,0.00045203127,0.0012369137,0.00016363325],"domain_scores_gemma":[0.99868923,0.00039143013,0.000050834966,0.0005167907,0.00029226876,0.000059417933],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011951233,0.0013398245,0.0014611294,0.0025342193,0.0011971268,0.0057180426,0.001935788,0.0011201958,0.06943488],"category_scores_gemma":[0.0036551272,0.0007227134,0.0011115543,0.0051002153,0.0013364397,0.008646405,0.002078549,0.002212503,0.044390373],"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":[0.00010644551,0.000085137974,0.0002472452,0.0005512252,0.00003763228,0.00009099429,0.00026842265,0.0011044294,0.0036967634,0.42066252,0.22162113,0.351528],"study_design_scores_gemma":[0.000033259632,0.0000484296,0.00027085972,0.00012818434,0.000040883253,0.0007297983,0.00007879288,0.007775196,0.005257718,0.20561658,0.7799772,0.000043098953],"about_ca_topic_score_codex":0.0019867774,"about_ca_topic_score_gemma":0.002414416,"teacher_disagreement_score":0.06943488,"about_ca_system_score_codex":0.0015721014,"about_ca_system_score_gemma":0.0018106694,"threshold_uncertainty_score":0.23228282},"labels":[],"label_agreement":null},{"id":"W4238208466","doi":"10.1145/584395.584402","title":"XSLT transformation from UML models to LQN performance models","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; XSLT; Programming language; Streaming XML; Graph rewriting; Model transformation; XML; Graph; Theoretical computer science; World Wide Web; Artificial intelligence","score_opus":0.05894407867450243,"score_gpt":0.21852621033314884,"score_spread":0.1595821316586464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4238208466","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":[0.007780949,0.000034229186,0.9692941,0.00022833052,0.00007184094,0.00020407482,0.0013118255,0.01687885,0.0041958843],"genre_scores_gemma":[0.20777985,0.00032540094,0.7662623,0.0002794355,0.000053982112,0.00087619235,0.008656538,0.005184918,0.0105813835],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979665,0.00058088335,0.00022420155,0.000260686,0.00088250986,0.0000851599],"domain_scores_gemma":[0.9979297,0.00081161,0.00016273677,0.0004375342,0.00062066206,0.000037783615],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019472463,0.000671194,0.0003719266,0.0011412085,0.00037536668,0.0016858629,0.001056095,0.0006181717,0.0048993994],"category_scores_gemma":[0.0068374607,0.0004971339,0.0010623251,0.0006331149,0.0006182961,0.0012590332,0.0009305434,0.0010211758,0.0019882766],"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":[0.0004182675,0.0003014582,0.0037371155,0.0007239348,0.00013833151,0.0013349848,0.0026748884,0.40151295,0.036607996,0.20748195,0.035731923,0.30933625],"study_design_scores_gemma":[0.000080028934,0.00007558691,0.0005607939,0.000126634,0.000067772606,0.00020317758,0.0001610231,0.76876384,0.06329042,0.049614318,0.117001414,0.000054961714],"about_ca_topic_score_codex":0.0056890757,"about_ca_topic_score_gemma":0.003439088,"teacher_disagreement_score":0.0056890757,"about_ca_system_score_codex":0.001494712,"about_ca_system_score_gemma":0.0016969168,"threshold_uncertainty_score":0.016390145},"labels":[],"label_agreement":null},{"id":"W4238268284","doi":"10.4018/978-1-60566-717-1.ch005","title":"Dynamic View Selection for OLAP","year":2011,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Online analytical processing; Materialized view; Data warehouse; Computer science; Aggregate (composite); Selection (genetic algorithm); Task (project management); Set (abstract data type); Information retrieval; Order (exchange); Data mining; Database; View; Artificial intelligence; Engineering","score_opus":0.020872553266656442,"score_gpt":0.25601928551099123,"score_spread":0.2351467322443348,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4238268284","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":[0.0049584294,0.04460709,0.90959847,0.0009282344,0.0005384607,0.00014276907,0.0005521251,0.0025850919,0.036089327],"genre_scores_gemma":[0.121442705,0.033802483,0.8099684,0.00094799744,0.00087276666,0.00028880817,0.0022750539,0.0012802886,0.029121494],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989512,0.00021784975,0.000053461885,0.00020762127,0.0005056471,0.00006419435],"domain_scores_gemma":[0.9990037,0.00045938996,0.000045922898,0.0002901462,0.00013354294,0.00006724964],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009435415,0.00086253014,0.0007070808,0.001043473,0.0006549082,0.0026210085,0.0017082551,0.0007450173,0.0066432273],"category_scores_gemma":[0.00211625,0.00051662105,0.00077389285,0.002953232,0.00062447146,0.003474737,0.002012695,0.0024662637,0.002968464],"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":[0.00013795798,0.00009052511,0.00052522885,0.0005623073,0.000060051876,0.00033450848,0.0003044519,0.017854946,0.0092602065,0.10859224,0.05791864,0.80435896],"study_design_scores_gemma":[0.000042623815,0.0001110504,0.0010061854,0.000368444,0.00007870666,0.0022060897,0.0002736078,0.14993249,0.008419335,0.2872431,0.55022097,0.000097480945],"about_ca_topic_score_codex":0.0011197393,"about_ca_topic_score_gemma":0.0012798315,"teacher_disagreement_score":0.0066432273,"about_ca_system_score_codex":0.00082098367,"about_ca_system_score_gemma":0.00061967596,"threshold_uncertainty_score":0.02222383},"labels":[],"label_agreement":null},{"id":"W4238306285","doi":"10.1007/978-1-4614-6170-8_100900","title":"Query Expansion","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Database Systems and Queries","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 Calgary","funders":"","keywords":"Computer science","score_opus":0.015830664498496492,"score_gpt":0.22057990583011777,"score_spread":0.20474924133162128,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4238306285","genre_codex":"methods","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":[0.0071058352,0.009730085,0.56184864,0.0032508802,0.0015409823,0.0010243562,0.0040904796,0.015372864,0.39603594],"genre_scores_gemma":[0.10093318,0.015818024,0.43514428,0.0038617987,0.0020281835,0.00080318906,0.017973656,0.0040862714,0.41935143],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9983449,0.00023113182,0.00009063699,0.00036102746,0.000852575,0.00011968716],"domain_scores_gemma":[0.99865305,0.00039010047,0.000034962326,0.0004141998,0.00046262884,0.000044996672],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013525455,0.0013405739,0.0009827511,0.0023060576,0.0007622412,0.0023379715,0.001971769,0.00067362015,0.05913973],"category_scores_gemma":[0.0039118794,0.0004953619,0.00092851446,0.0030306012,0.00077166304,0.0054644733,0.0022452082,0.0023082197,0.03460927],"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":[0.00014992322,0.000108573935,0.00022125497,0.0006489915,0.000027364407,0.00009842289,0.00017172069,0.002144801,0.011467704,0.118653506,0.21253605,0.6537717],"study_design_scores_gemma":[0.00004214133,0.00006595978,0.0005172083,0.00023319274,0.00008357888,0.0008348517,0.0001466388,0.030098548,0.018806573,0.0778333,0.8712823,0.000055738656],"about_ca_topic_score_codex":0.002423512,"about_ca_topic_score_gemma":0.0019342914,"teacher_disagreement_score":0.05913973,"about_ca_system_score_codex":0.0010953168,"about_ca_system_score_gemma":0.0011550593,"threshold_uncertainty_score":0.19784212},"labels":[],"label_agreement":null},{"id":"W4238783465","doi":"10.1145/376284.375729","title":"Data-driven understanding and refinement of schema mappings","year":2001,"lang":"en","type":"article","venue":"ACM SIGMOD Record","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":45,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Schema (genetic algorithms); Schema evolution; Database schema; Theoretical computer science; Programming language; Information retrieval; Data mining; Database design","score_opus":0.13553835996809832,"score_gpt":0.3042947998079359,"score_spread":0.16875643983983757,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4238783465","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":[0.012513582,0.00021952407,0.9807535,0.0011355805,0.00004818093,0.00015676397,0.00028035042,0.0011198766,0.0037726746],"genre_scores_gemma":[0.10220309,0.00046154237,0.89327186,0.0003206947,0.000031809574,0.00021010042,0.0010644493,0.0005285489,0.0019079648],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.98668694,0.0058123986,0.00142797,0.0018264668,0.0038078094,0.0004385038],"domain_scores_gemma":[0.9715062,0.013892281,0.0013318717,0.007936252,0.00496078,0.00037266462],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015410757,0.001073986,0.00084076915,0.0027778153,0.0015185052,0.0071611647,0.0032632449,0.0021471188,0.003020016],"category_scores_gemma":[0.055120893,0.0014320455,0.0018751998,0.0022797447,0.0041021374,0.01617909,0.0062756357,0.004562275,0.0007389252],"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":[0.00013355253,0.00010270762,0.0030220908,0.00048381748,0.00006745932,0.00087664597,0.017892819,0.019719634,0.009585577,0.8238911,0.006660381,0.1175642],"study_design_scores_gemma":[0.00004326381,0.000065912966,0.0006466902,0.00040527986,0.00007805056,0.0008721027,0.003285484,0.14082493,0.022499492,0.6979947,0.1331951,0.00008895947],"about_ca_topic_score_codex":0.004231218,"about_ca_topic_score_gemma":0.004064025,"teacher_disagreement_score":0.015410757,"about_ca_system_score_codex":0.0016280542,"about_ca_system_score_gemma":0.0027204342,"threshold_uncertainty_score":0.08150083},"labels":[],"label_agreement":null},{"id":"W4239184142","doi":"10.1001/jama.2015.1816","title":"Incorrect Data in Text and Table","year":2015,"lang":"en","type":"erratum","venue":"JAMA","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Women's College Hospital","funders":"","keywords":"Medicine; Table (database); Data mining","score_opus":0.03277367219415316,"score_gpt":0.28190740354787475,"score_spread":0.24913373135372158,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4239184142","genre_codex":"editorial","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":[0.0011422206,0.0018160426,0.0025487295,0.1638988,0.58628815,0.00039806435,0.16225417,0.002402556,0.07925123],"genre_scores_gemma":[0.02789539,0.0049673617,0.006699709,0.23365979,0.05780442,0.001379793,0.11826033,0.0033900707,0.5459432],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99411017,0.00079951424,0.0010423773,0.00061371544,0.0028038824,0.00063032476],"domain_scores_gemma":[0.97372234,0.0093025295,0.0015314526,0.0017770822,0.01267592,0.0009907795],"candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0027375915,0.0011316324,0.001793442,0.0034907265,0.0031790743,0.0027644273,0.0025806795,0.00434923,0.25672632],"category_scores_gemma":[0.06662484,0.0008655088,0.001224182,0.004867752,0.001173328,0.0025987988,0.0015234677,0.006280303,0.13713051],"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":[0.000028197015,0.000005803919,0.00011245682,0.00003157738,0.000002707852,0.000040114468,0.000010035209,0.000017028418,0.000012077456,0.00048674655,0.99729353,0.0019597413],"study_design_scores_gemma":[0.00012260243,0.000024187571,0.0019890037,0.00035817162,0.000023373525,0.00023130502,0.00014010721,0.00014669057,0.00028350193,0.0023684504,0.9942825,0.000030207402],"about_ca_topic_score_codex":0.032264024,"about_ca_topic_score_gemma":0.03355761,"teacher_disagreement_score":0.99565077,"about_ca_system_score_codex":0.0035458598,"about_ca_system_score_gemma":0.005621113,"threshold_uncertainty_score":0.8588351},"labels":[],"label_agreement":null},{"id":"W4240454152","doi":"10.1109/ieeeconf12321.2007","title":"2007 10th Canadian Workshop on Information Theory (CWIT)","year":2007,"lang":"en","type":"paratext","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science","score_opus":0.013617628107535768,"score_gpt":0.2588927358354563,"score_spread":0.24527510772792052,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4240454152","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0063660787,0.052040752,0.3528084,0.05571669,0.03141192,0.00048347484,0.009505583,0.008483039,0.48318407],"genre_scores_gemma":[0.04100828,0.034185924,0.10558172,0.0030952722,0.0033067283,0.00024315514,0.010022653,0.0027913295,0.79976493],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9962537,0.0005626227,0.00015490387,0.00053972774,0.0018935496,0.0005955131],"domain_scores_gemma":[0.994719,0.0009880877,0.00008570238,0.0010128062,0.002400213,0.0007941227],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004852904,0.0016998734,0.0027956367,0.0039191176,0.0039712004,0.011953036,0.0041195177,0.0022046105,0.14134629],"category_scores_gemma":[0.00777107,0.0010656376,0.0016349053,0.006578192,0.0036708503,0.007423266,0.004590871,0.004645893,0.042309083],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010979513,0.000076024735,0.00024009393,0.00027468282,0.000035652163,0.000060694692,0.00023866142,0.0012901466,0.0008690495,0.1264591,0.6803243,0.19002177],"study_design_scores_gemma":[0.000019388006,0.000017298336,0.00041443462,0.00022787024,0.000044080567,0.00007500846,0.00022604305,0.0061756587,0.0014008273,0.06895423,0.9224071,0.00003804152],"about_ca_topic_score_codex":0.36776462,"about_ca_topic_score_gemma":0.39307773,"teacher_disagreement_score":0.98274076,"about_ca_system_score_codex":0.01725922,"about_ca_system_score_gemma":0.029826917,"threshold_uncertainty_score":0.731248},"labels":[],"label_agreement":null},{"id":"W4240834168","doi":"10.1002/sam.10016","title":"Discovering and Exploiting Statistical Properties for Query Optimization in Relational Databases: A Survey","year":2009,"lang":"en","type":"article","venue":"Statistical Analysis and Data Mining The ASA Data Science Journal","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Query optimization; Relational database; Data mining; Relational database management system; Cardinality (data modeling); Relational model; Sargable; View; Information retrieval; Key (lock); Exploratory data analysis; Database; Database design; Web search query; Search engine","score_opus":0.15298434666212693,"score_gpt":0.3608533658037779,"score_spread":0.20786901914165098,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4240834168","genre_codex":"methods","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021059643,0.032690395,0.94013053,0.0016848986,0.0000504741,0.0001404281,0.00051780103,0.0015653785,0.0021604467],"genre_scores_gemma":[0.25008777,0.028280666,0.7178424,0.00036943302,0.00045623936,0.00026172126,0.0016980926,0.00042925682,0.0005744135],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9850631,0.0044922484,0.001897105,0.0020190512,0.0062407604,0.00028784914],"domain_scores_gemma":[0.942894,0.041401196,0.0038713892,0.0060590114,0.0053299167,0.0004446704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0151049765,0.0012439846,0.0028313515,0.007893068,0.00067638414,0.0047251075,0.0035229616,0.0011330151,0.0009160828],"category_scores_gemma":[0.038869172,0.0012212895,0.002275746,0.010706523,0.001963967,0.006773667,0.0019104696,0.0014397728,0.00060804695],"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":[0.00017733726,0.00033937476,0.030359227,0.0029945206,0.0005229906,0.00031016397,0.0006135264,0.060854036,0.0055500437,0.049316224,0.005040434,0.8439221],"study_design_scores_gemma":[0.00007955518,0.0003201259,0.0121947685,0.0005842703,0.00033046232,0.0014934334,0.0006876361,0.7886672,0.017060697,0.13855667,0.039809387,0.00021583392],"about_ca_topic_score_codex":0.0026868798,"about_ca_topic_score_gemma":0.0016583493,"teacher_disagreement_score":0.0151049765,"about_ca_system_score_codex":0.0012732174,"about_ca_system_score_gemma":0.0022995742,"threshold_uncertainty_score":0.079883695},"labels":[],"label_agreement":null},{"id":"W4241069479","doi":"10.1145/773153.773166","title":"Concise descriptions of subsets of structured sets","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Automatic summarization; Computer science; Online analytical processing; Set (abstract data type); XML; Context (archaeology); Theoretical computer science; String (physics); Hierarchy; Focus (optics); Cover (algebra); Representation (politics); Simple (philosophy); Data mining; Information retrieval; Data warehouse; Mathematics; Programming language","score_opus":0.019359303329811398,"score_gpt":0.25055608558863074,"score_spread":0.23119678225881934,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4241069479","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":[0.059065394,0.0016101563,0.929227,0.0011521807,0.000077740944,0.00014197732,0.0019781995,0.0006079565,0.0061394135],"genre_scores_gemma":[0.44926718,0.0016217841,0.5355858,0.00033192223,0.00022046009,0.0004904038,0.005307973,0.00030124572,0.006873251],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99660575,0.0010900408,0.0004310313,0.00054273143,0.0011048731,0.0002255469],"domain_scores_gemma":[0.9922416,0.004470982,0.0009957755,0.0012743457,0.0007712399,0.0002460911],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002605577,0.0006304375,0.001018304,0.0025471577,0.0007512988,0.0034123445,0.0017137678,0.0009897212,0.0035713674],"category_scores_gemma":[0.013031365,0.00075003266,0.0010070201,0.0038910285,0.0013313968,0.008945045,0.002106548,0.0012806547,0.00070243614],"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":[0.0001753293,0.000060169466,0.00096347654,0.0004907588,0.00006691904,0.000475861,0.0012754609,0.06690529,0.0038128702,0.8266545,0.0065386784,0.09258064],"study_design_scores_gemma":[0.00004002015,0.00010992591,0.00035369516,0.00011809086,0.000057257534,0.00043877584,0.00060561806,0.19731513,0.0043713357,0.7626164,0.0339327,0.000041093746],"about_ca_topic_score_codex":0.0008945624,"about_ca_topic_score_gemma":0.0011771444,"teacher_disagreement_score":0.0035713674,"about_ca_system_score_codex":0.0013105421,"about_ca_system_score_gemma":0.00077440194,"threshold_uncertainty_score":0.013779759},"labels":[],"label_agreement":null},{"id":"W4241178178","doi":"10.1007/978-1-4899-7993-3_80772-2","title":"Order Dependency","year":2017,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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 Ontario Institute of Technology","funders":"","keywords":"Dependency (UML); Computer science; Mathematics; Artificial intelligence","score_opus":0.018688533234035926,"score_gpt":0.2512785123608264,"score_spread":0.23258997912679044,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4241178178","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0040153814,0.002474405,0.16018656,0.0019807082,0.0011272031,0.00012833391,0.0019543006,0.0018920228,0.826241],"genre_scores_gemma":[0.12668428,0.0068397075,0.10015645,0.0015916656,0.0010664705,0.00022518454,0.0064122444,0.0026666874,0.75435734],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993919,0.00007040913,0.000036993755,0.00017765167,0.00025489056,0.0000681537],"domain_scores_gemma":[0.9989287,0.0002796354,0.000039078404,0.00040263348,0.00030124898,0.000048623475],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048367798,0.0007633217,0.00049878855,0.0014159881,0.0013793218,0.0024402796,0.000931723,0.000684746,0.094332084],"category_scores_gemma":[0.0025677201,0.00057029753,0.00069154945,0.001962402,0.0013463123,0.0053755147,0.0016043863,0.0022673134,0.037132837],"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":[0.000038144866,0.000028685543,0.00015751507,0.00014315332,0.0000087676735,0.00007939276,0.00023872509,0.0006725384,0.0013029057,0.7866046,0.09274421,0.11798133],"study_design_scores_gemma":[0.0000093447825,0.000015540018,0.00017700646,0.00007133527,0.000014215661,0.0002485746,0.00006743674,0.0019823378,0.0028286525,0.45370457,0.5408648,0.000016222351],"about_ca_topic_score_codex":0.0023930683,"about_ca_topic_score_gemma":0.0028521654,"teacher_disagreement_score":0.094332084,"about_ca_system_score_codex":0.0012454968,"about_ca_system_score_gemma":0.0014771143,"threshold_uncertainty_score":0.31557226},"labels":[],"label_agreement":null},{"id":"W4241207869","doi":"10.1007/978-1-4899-7993-3_370-2","title":"Stream Models","year":2017,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Computer science; Geography; Environmental science","score_opus":0.027606537629463076,"score_gpt":0.2500868796245595,"score_spread":0.22248034199509642,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4241207869","genre_codex":"methods","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":[0.0036923848,0.004026443,0.8488653,0.0025738252,0.001216562,0.00020396741,0.0033385195,0.003679746,0.13240328],"genre_scores_gemma":[0.2566389,0.017088035,0.31481946,0.0023408812,0.0025710543,0.00082263135,0.017482858,0.0026596077,0.38557655],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9994368,0.00010078681,0.00003272715,0.00015182215,0.00022692805,0.000050852505],"domain_scores_gemma":[0.99910814,0.00028378997,0.000051492978,0.00024744694,0.00024869584,0.000060452632],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00077253126,0.0010806817,0.0007631545,0.0010192567,0.0005587565,0.003629071,0.0015552649,0.0011199377,0.03652952],"category_scores_gemma":[0.0042693024,0.00044541754,0.000986338,0.0015119517,0.00066938624,0.0042334143,0.0015098124,0.002182813,0.016798472],"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":[0.00010595915,0.00007331663,0.0004816826,0.0001829665,0.000048252554,0.00008834637,0.000099804325,0.035269618,0.0011317366,0.7236125,0.099510394,0.13939543],"study_design_scores_gemma":[0.00003714564,0.000036147805,0.00017614588,0.00008987553,0.00003977681,0.0001724178,0.00004878728,0.23190196,0.0015320388,0.5916236,0.17431659,0.000025417541],"about_ca_topic_score_codex":0.0025211973,"about_ca_topic_score_gemma":0.0023102039,"teacher_disagreement_score":0.03652952,"about_ca_system_score_codex":0.0009258347,"about_ca_system_score_gemma":0.0012197666,"threshold_uncertainty_score":0.12220341},"labels":[],"label_agreement":null},{"id":"W4241705990","doi":"10.1007/978-0-387-39940-9_2637","title":"Filter/Refinement Query Processing","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Computer science; Filter (signal processing); Information retrieval; Computer vision","score_opus":0.017593529446660115,"score_gpt":0.23818057946452026,"score_spread":0.22058705001786014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4241705990","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":[0.0040836832,0.001359289,0.89574856,0.00069603923,0.00034053792,0.00066677586,0.0043071215,0.05587464,0.03692329],"genre_scores_gemma":[0.052089896,0.0019436905,0.8265733,0.0012029477,0.00039864256,0.00033470307,0.02062998,0.0074271183,0.08939966],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99687344,0.00025050875,0.00025499202,0.0006208082,0.0017386418,0.00026155778],"domain_scores_gemma":[0.9969932,0.00075367227,0.00009226782,0.0011732497,0.0009137146,0.00007398848],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029868903,0.0018712183,0.0018631933,0.003634137,0.001317813,0.004187313,0.0033816197,0.001283539,0.06016857],"category_scores_gemma":[0.00545321,0.0009764498,0.0019203924,0.0035838205,0.0009961496,0.0038895942,0.0023012408,0.0015771713,0.04182478],"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":[0.00043263639,0.00014897954,0.00097241503,0.0006357112,0.00009720066,0.0001895433,0.00029465926,0.0023621991,0.0223701,0.043285742,0.17186177,0.75734913],"study_design_scores_gemma":[0.0001571388,0.00021680232,0.0018758383,0.00029608223,0.00029210382,0.0012661335,0.0003298528,0.10697719,0.13852932,0.08960555,0.660276,0.00017792596],"about_ca_topic_score_codex":0.008568407,"about_ca_topic_score_gemma":0.0076473355,"teacher_disagreement_score":0.06016857,"about_ca_system_score_codex":0.0011822849,"about_ca_system_score_gemma":0.0019421319,"threshold_uncertainty_score":0.20128387},"labels":[],"label_agreement":null},{"id":"W4241766855","doi":"10.1007/978-1-4939-7131-2_100206","title":"Continuous Query Processing","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Database Systems and Queries","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 Calgary","funders":"","keywords":"Computer science; Information retrieval","score_opus":0.017579278000279447,"score_gpt":0.23723991306923659,"score_spread":0.21966063506895714,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4241766855","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":[0.0033183568,0.011487741,0.8722029,0.0011555728,0.0013373245,0.00022557356,0.0013310969,0.0068699284,0.10207154],"genre_scores_gemma":[0.115852505,0.015510437,0.64527804,0.0013787949,0.0026314938,0.0004394745,0.0074686236,0.0021642311,0.20927641],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9981316,0.00017690808,0.000112614456,0.0005299133,0.00092481467,0.00012425831],"domain_scores_gemma":[0.99827886,0.0005270067,0.000059647075,0.000561726,0.000497356,0.00007550926],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012780074,0.0014390203,0.0011549554,0.0014687085,0.00073032966,0.0041617737,0.0025596968,0.0009354303,0.0349252],"category_scores_gemma":[0.0034593642,0.0006574638,0.0007799214,0.0036552243,0.0011419648,0.0046676807,0.001938383,0.0027909307,0.020012552],"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":[0.0001777459,0.00009995214,0.00018820731,0.00069960544,0.00004579556,0.000075155986,0.00015880112,0.003857455,0.009950396,0.15672502,0.1267744,0.7012475],"study_design_scores_gemma":[0.00006346368,0.00018458605,0.00087868434,0.00025141268,0.00008605204,0.00074461143,0.00016179984,0.10287148,0.020360483,0.27090853,0.6034027,0.000086209344],"about_ca_topic_score_codex":0.0016868897,"about_ca_topic_score_gemma":0.0010217124,"teacher_disagreement_score":0.0349252,"about_ca_system_score_codex":0.0010449701,"about_ca_system_score_gemma":0.001199849,"threshold_uncertainty_score":0.11683643},"labels":[],"label_agreement":null},{"id":"W4241835135","doi":"10.1145/543635.543636","title":"OLAP dimension constraints","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Online analytical processing; Dimension (graph theory); Heuristics; Computer science; Theoretical computer science; Class (philosophy); Intrinsic dimension; Set (abstract data type); Aggregate (composite); Space (punctuation); Curse of dimensionality; Algorithm; Mathematics; Data mining; Artificial intelligence; Data warehouse; Programming language; Combinatorics","score_opus":0.021910008873901855,"score_gpt":0.22386910770609347,"score_spread":0.20195909883219162,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4241835135","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":[0.02482232,0.0014915805,0.94527376,0.0029397402,0.00028418517,0.00090615975,0.008353211,0.0032782226,0.012650787],"genre_scores_gemma":[0.18959408,0.0011356723,0.7943435,0.0015067513,0.00020393977,0.0006136679,0.008728686,0.00053435937,0.0033393067],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.989077,0.0025481393,0.0013653054,0.0019041614,0.0044180164,0.0006875139],"domain_scores_gemma":[0.97650945,0.011522179,0.002230245,0.0047185025,0.0045822836,0.0004371939],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0056397286,0.0014319931,0.0011448365,0.002092673,0.0024296206,0.006653569,0.0036044645,0.0016317298,0.007695276],"category_scores_gemma":[0.03176184,0.0009968284,0.0022185706,0.004398348,0.0015321757,0.012401655,0.0053898464,0.0038045195,0.0011982773],"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":[0.0005670324,0.00023152312,0.012245605,0.0016937358,0.0004215921,0.0013640813,0.001837106,0.07739713,0.008432784,0.46837857,0.048619125,0.3788116],"study_design_scores_gemma":[0.000070903385,0.00012820703,0.0019425141,0.00047718146,0.00020215582,0.0013664088,0.0018750826,0.2614272,0.018865902,0.5688524,0.14465035,0.00014161886],"about_ca_topic_score_codex":0.0045851455,"about_ca_topic_score_gemma":0.005575138,"teacher_disagreement_score":0.007695276,"about_ca_system_score_codex":0.0015698263,"about_ca_system_score_gemma":0.0026123768,"threshold_uncertainty_score":0.029826105},"labels":[],"label_agreement":null},{"id":"W4242144543","doi":"10.1007/978-1-4899-7993-3_771-2","title":"XML Storage","year":2016,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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 Alberta","funders":"","keywords":"Computer science","score_opus":0.013747860753368066,"score_gpt":0.22798610649424136,"score_spread":0.2142382457408733,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4242144543","genre_codex":"other","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":[0.0028496357,0.011445366,0.24867964,0.0027050402,0.0021768997,0.00034655412,0.014793437,0.03362404,0.68337935],"genre_scores_gemma":[0.019012796,0.011376909,0.1076017,0.001454234,0.0008147209,0.00021853257,0.029069632,0.0057372293,0.82471424],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995215,0.000050734976,0.000052829837,0.00009131242,0.00024879212,0.000034874527],"domain_scores_gemma":[0.99939394,0.00010741253,0.000023626271,0.00026845795,0.00017068571,0.000035841702],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00058340665,0.0009927475,0.0005873999,0.002779172,0.00076764275,0.0039406107,0.0017050868,0.00089707697,0.15694025],"category_scores_gemma":[0.0015943227,0.0005770579,0.0006184699,0.004519861,0.00046649418,0.005344181,0.001998172,0.0011146076,0.12941106],"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":[0.00006794481,0.00004753796,0.00017747204,0.00053629733,0.000020022848,0.00012412631,0.00020959355,0.00059940876,0.007551465,0.06851133,0.3898412,0.5323137],"study_design_scores_gemma":[0.000008695554,0.000011693505,0.0001508672,0.0001232643,0.000011619714,0.000300041,0.00004334806,0.000860331,0.004464113,0.014159788,0.9798514,0.00001474648],"about_ca_topic_score_codex":0.0012114934,"about_ca_topic_score_gemma":0.0014690049,"teacher_disagreement_score":0.15694025,"about_ca_system_score_codex":0.00057166046,"about_ca_system_score_gemma":0.00082066376,"threshold_uncertainty_score":0.52501744},"labels":[],"label_agreement":null},{"id":"W4242182228","doi":"10.1007/978-1-4614-6170-8_3","title":"Subgraph Isomorphic Queries","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Database Systems and Queries","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 Calgary","funders":"","keywords":"Computer science; Combinatorics; Mathematics","score_opus":0.014044189443294875,"score_gpt":0.20573602503568378,"score_spread":0.1916918355923889,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4242182228","genre_codex":"other","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":[0.017123299,0.0045260815,0.41431424,0.0034396213,0.0010309618,0.0003346034,0.004291497,0.006453209,0.5484865],"genre_scores_gemma":[0.29780072,0.010721464,0.28635898,0.0034595793,0.0016328421,0.00047364223,0.029825272,0.0053002303,0.36442724],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9985996,0.00022001949,0.00006466,0.00031622613,0.0006658824,0.00013357245],"domain_scores_gemma":[0.9990195,0.0003025862,0.000031144682,0.00041980477,0.00017725333,0.000049721762],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004837942,0.00090331986,0.00076231535,0.0015908517,0.0007810917,0.0024843959,0.0013880129,0.0007777954,0.036034923],"category_scores_gemma":[0.0027260636,0.00042175155,0.00082870707,0.0038934113,0.0010473566,0.0072831106,0.0027153962,0.0021222066,0.012149155],"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":[0.000061925224,0.000065549815,0.00024759944,0.00027803585,0.000027943977,0.000087171466,0.00029854188,0.003096592,0.0027743329,0.5484713,0.16491556,0.27967542],"study_design_scores_gemma":[0.000016901717,0.00002253359,0.00024798454,0.0000783789,0.0000353634,0.00042019333,0.00014995591,0.010959528,0.0035170952,0.63184255,0.35268646,0.000023045926],"about_ca_topic_score_codex":0.0020534368,"about_ca_topic_score_gemma":0.002398397,"teacher_disagreement_score":0.036034923,"about_ca_system_score_codex":0.0014586952,"about_ca_system_score_gemma":0.0010079386,"threshold_uncertainty_score":0.120548785},"labels":[],"label_agreement":null},{"id":"W4242660427","doi":"10.22215/etd/2012-07441","title":"Repair-oriented relational schemas for multidimensional databases","year":2012,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Canadian Heritage; Library and Archives Canada","funders":"","keywords":"Relational database; Computer science; Database; Information retrieval","score_opus":0.038302410498288884,"score_gpt":0.3082945426475644,"score_spread":0.26999213214927553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4242660427","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":[0.0042788796,0.0024909559,0.97228956,0.0012730549,0.00046491885,0.0003619497,0.0023609605,0.0048148525,0.011664747],"genre_scores_gemma":[0.049825657,0.0035919172,0.9213313,0.000813987,0.00024613953,0.00040302926,0.009281504,0.0011483873,0.013358051],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9964386,0.0010093092,0.0007007428,0.00039774113,0.0012779883,0.00017562814],"domain_scores_gemma":[0.9945551,0.0010613975,0.0003652357,0.0027655258,0.0010227407,0.00022999523],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0044844723,0.0006999296,0.00063603814,0.002531309,0.00092296425,0.0072500715,0.0030624673,0.001862665,0.008025573],"category_scores_gemma":[0.008250022,0.00090481614,0.0014177711,0.004093937,0.001257616,0.00862866,0.002860885,0.0023014871,0.0043394677],"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":[0.00012725919,0.0001338955,0.0009759121,0.0007132106,0.0000708273,0.0005310794,0.0014986119,0.006298105,0.008734423,0.7656302,0.0343154,0.18097101],"study_design_scores_gemma":[0.00007415598,0.00008720878,0.00044484975,0.000590336,0.00007382257,0.0012542186,0.000818741,0.027791105,0.014837039,0.26020607,0.69374317,0.000079307996],"about_ca_topic_score_codex":0.0017163393,"about_ca_topic_score_gemma":0.0022279592,"teacher_disagreement_score":0.008025573,"about_ca_system_score_codex":0.001141065,"about_ca_system_score_gemma":0.0019086758,"threshold_uncertainty_score":0.026848257},"labels":[],"label_agreement":null},{"id":"W4242792630","doi":"10.1093/ww/9780199540884.013.u260560","title":"Brassard, Prof. Gilles, (born 1955), Professor of Computer Science, since 1988, and Canada Research Chair in Quantum Information Processing, since 2001, University of Montréal","year":2015,"lang":"en","type":"reference-entry","venue":"Who's Who","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Art history; Library science; Art; Philosophy; Sociology; Computer science","score_opus":0.03067984056271346,"score_gpt":0.27266378367829885,"score_spread":0.2419839431155854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4242792630","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001986224,0.16121532,0.0072888066,0.2547397,0.06143697,0.00019260167,0.005841986,0.0019074732,0.5053909],"genre_scores_gemma":[0.0039002323,0.023787174,0.0012298817,0.0050021475,0.0027346648,0.000022216536,0.00071065023,0.00023295825,0.96238005],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984937,0.0001279128,0.000081301296,0.00035820194,0.0007822812,0.00015666109],"domain_scores_gemma":[0.995669,0.0005688067,0.00014200354,0.00014498657,0.002312507,0.001162801],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017668717,0.00069731165,0.0009150403,0.0020264266,0.0017995395,0.0045831655,0.0009216035,0.0019186393,0.17249592],"category_scores_gemma":[0.004920577,0.00053036545,0.00037986026,0.0030540104,0.001017294,0.0035256324,0.0013035274,0.0024198396,0.12910408],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012658222,0.0000026486682,0.000117655516,0.000051355055,0.0000014960194,0.000020854799,0.000050918246,0.000021226024,0.000107339685,0.0026651737,0.96636283,0.030585837],"study_design_scores_gemma":[0.0000025362617,0.0000059416607,0.00016611432,0.000032826472,0.0000017829894,0.00008381111,0.00003964094,0.000022247988,0.00018630268,0.0004862606,0.9989675,0.000004937412],"about_ca_topic_score_codex":0.026962144,"about_ca_topic_score_gemma":0.049495686,"teacher_disagreement_score":0.97303784,"about_ca_system_score_codex":0.003668378,"about_ca_system_score_gemma":0.004616848,"threshold_uncertainty_score":0.5770563},"labels":[],"label_agreement":null},{"id":"W4243543857","doi":"10.1109/mise.2013.6595289","title":"MAV-Vis: A notation for model uncertainty","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Notation; Computer science; Programming language; Mathematics; Arithmetic","score_opus":0.020234698918561403,"score_gpt":0.2573961552306666,"score_spread":0.23716145631210522,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4243543857","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":[0.0023878666,0.00008565749,0.9883483,0.0005545717,0.000080504615,0.00011281973,0.00038891027,0.005308787,0.002732577],"genre_scores_gemma":[0.0658074,0.0002108356,0.92882985,0.00040365302,0.00005501979,0.00051051925,0.0008508217,0.0012556959,0.002076243],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99136823,0.0042801234,0.0013025393,0.0009587039,0.0018431076,0.0002471673],"domain_scores_gemma":[0.9702066,0.016117584,0.0027379321,0.0076024155,0.0027001388,0.00063532015],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010811129,0.001618861,0.0008366291,0.0019299743,0.0010909135,0.007472683,0.004901301,0.002334888,0.007245086],"category_scores_gemma":[0.050875496,0.0014332373,0.0017835839,0.0011372507,0.0030610948,0.011893394,0.0052234223,0.0044748248,0.0026384487],"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":[0.00023862733,0.00012521836,0.0016977926,0.000832549,0.00009122095,0.0003504953,0.003957765,0.0228713,0.008934899,0.8426012,0.020094428,0.09820456],"study_design_scores_gemma":[0.00013264648,0.00034268544,0.00043309666,0.00084456033,0.000107347994,0.001078433,0.0008141297,0.17884836,0.021457903,0.5216763,0.27403137,0.00023318535],"about_ca_topic_score_codex":0.0012400658,"about_ca_topic_score_gemma":0.0021514874,"teacher_disagreement_score":0.010811129,"about_ca_system_score_codex":0.001226351,"about_ca_system_score_gemma":0.002737644,"threshold_uncertainty_score":0.057175457},"labels":[],"label_agreement":null},{"id":"W4243581071","doi":"10.1145/860500.860540","title":"A light weight PDA-friendly collection fusion technique","year":2003,"lang":"en","type":"article","venue":"Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval - SIGIR '03","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Merge (version control); Computer science; Fusion; Database; Information retrieval; Artificial intelligence","score_opus":0.03804832377003618,"score_gpt":0.31421816943634956,"score_spread":0.27616984566631336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4243581071","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":[0.011628141,0.0010985562,0.96776974,0.00019845547,0.00019504751,0.00037600586,0.0006833498,0.010249235,0.0078014317],"genre_scores_gemma":[0.08287216,0.00084373716,0.889469,0.00043398992,0.00024439677,0.0003846718,0.0023356138,0.0010558268,0.022360584],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9962064,0.0002850834,0.00021132852,0.00059907255,0.0024352544,0.00026283457],"domain_scores_gemma":[0.997715,0.0004053973,0.00012731331,0.000834744,0.0008029822,0.00011462007],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018397473,0.0011131671,0.0014001289,0.00492964,0.0018196962,0.0033259431,0.0024372926,0.0011177937,0.013199636],"category_scores_gemma":[0.0035397408,0.0009284631,0.0016736104,0.006484054,0.00060887565,0.0057039815,0.005236914,0.0017018822,0.009920192],"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":[0.00075941795,0.00025817755,0.001195673,0.0003735502,0.00021246386,0.00038037184,0.0005556693,0.0015914615,0.20013317,0.008883023,0.0122998785,0.7733571],"study_design_scores_gemma":[0.00021826164,0.0009774949,0.0075952,0.00019277225,0.0006473769,0.005175667,0.00106515,0.096152924,0.61095834,0.027657017,0.24889141,0.00046828136],"about_ca_topic_score_codex":0.002772025,"about_ca_topic_score_gemma":0.0033940389,"teacher_disagreement_score":0.013199636,"about_ca_system_score_codex":0.0007478027,"about_ca_system_score_gemma":0.0012699141,"threshold_uncertainty_score":0.044157147},"labels":[],"label_agreement":null},{"id":"W4243724572","doi":"10.1007/978-0-387-39940-9_3207","title":"OODB (Object-Oriented Database)","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Computer science; Database; Programming language","score_opus":0.013584931475186435,"score_gpt":0.23743008254099907,"score_spread":0.22384515106581263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4243724572","genre_codex":"methods","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":[0.002588687,0.05182781,0.44128698,0.003944606,0.0046985275,0.0006121537,0.019756611,0.04220295,0.43308157],"genre_scores_gemma":[0.01752645,0.060121786,0.3359157,0.0057807076,0.0031928758,0.0004605293,0.05565619,0.008805184,0.5125406],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989868,0.00006831872,0.00010067814,0.00020398108,0.0005732768,0.00006701981],"domain_scores_gemma":[0.9992199,0.00018908479,0.00007413364,0.00020987962,0.0002141545,0.000092831935],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00090350705,0.0011463598,0.0011653996,0.0028185516,0.00057876075,0.0058112503,0.0022551944,0.0011764859,0.07165895],"category_scores_gemma":[0.0023304904,0.0007019245,0.00074887037,0.0064800526,0.0004888048,0.0055693067,0.0020662595,0.0020755928,0.08449822],"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":[0.000050211216,0.000060229395,0.00020559838,0.0010032528,0.000022130758,0.00011006903,0.000079349564,0.00046439096,0.0035117178,0.049615625,0.3788435,0.5660339],"study_design_scores_gemma":[0.000011371573,0.000013062376,0.00017409926,0.000130233,0.000011584129,0.00027235431,0.000014592965,0.0004113551,0.0009083682,0.010485055,0.9875552,0.000012688967],"about_ca_topic_score_codex":0.0013709696,"about_ca_topic_score_gemma":0.0010699864,"teacher_disagreement_score":0.07165895,"about_ca_system_score_codex":0.00068012386,"about_ca_system_score_gemma":0.001394012,"threshold_uncertainty_score":0.23972303},"labels":[],"label_agreement":null},{"id":"W4244155268","doi":"10.1007/978-1-4757-4828-4","title":"Computational Probability","year":2000,"lang":"en","type":"book","venue":"International series in management science/operations research/International series in operations research & management science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":92,"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":"Computer science","score_opus":0.0570833361669856,"score_gpt":0.4062515859873681,"score_spread":0.3491682498203825,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4244155268","genre_codex":"methods","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":[0.0069556655,0.009016929,0.7905788,0.0061581573,0.0021225824,0.0000546134,0.0010449855,0.0011108727,0.18295738],"genre_scores_gemma":[0.49550006,0.013991892,0.23769379,0.0019319332,0.0073614703,0.0004430834,0.004206022,0.0014852883,0.23738636],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9992938,0.00018983436,0.000036388596,0.00016920938,0.0002695809,0.000041184237],"domain_scores_gemma":[0.9965139,0.0021079031,0.00012269164,0.000774527,0.00035875913,0.00012227811],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010271099,0.00080935826,0.0012442914,0.0021098927,0.0009791912,0.0032099355,0.0011365738,0.001072249,0.031966645],"category_scores_gemma":[0.009223129,0.0005334327,0.001002107,0.002453343,0.0014924635,0.004244716,0.0016757366,0.0034721012,0.006085515],"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":[0.000013916475,0.00001752571,0.00022041942,0.00006344636,0.000024950807,0.000017644143,0.000024662615,0.009903213,0.00009486154,0.89492154,0.0381162,0.056581628],"study_design_scores_gemma":[0.0000060443745,0.0000044374606,0.00013475251,0.000016209406,0.000009538973,0.000039248334,0.0000070558017,0.044945505,0.00014907155,0.9313967,0.02328538,0.0000059782183],"about_ca_topic_score_codex":0.0013526987,"about_ca_topic_score_gemma":0.0012106588,"teacher_disagreement_score":0.031966645,"about_ca_system_score_codex":0.0012983637,"about_ca_system_score_gemma":0.000863521,"threshold_uncertainty_score":0.10693914},"labels":[],"label_agreement":null},{"id":"W4244161838","doi":"10.1007/978-0-387-39940-9_3130","title":"Multi-Version Database","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Database; Computer science","score_opus":0.01927047840469381,"score_gpt":0.2465602220159596,"score_spread":0.22728974361126578,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4244161838","genre_codex":"methods","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":[0.003834709,0.0066888463,0.6501361,0.0013337214,0.0025446706,0.00058272365,0.019176746,0.11022426,0.20547816],"genre_scores_gemma":[0.079063915,0.0072357883,0.36480358,0.0020585938,0.0013240005,0.00044085772,0.07151233,0.024164455,0.44939652],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99794525,0.00021509941,0.0002767753,0.0004259899,0.0009824166,0.00015441462],"domain_scores_gemma":[0.9961349,0.00039761004,0.000105427636,0.0024583172,0.0007117163,0.00019208947],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017574605,0.0012390487,0.0014095523,0.0026870447,0.00088514853,0.0057650115,0.003828213,0.0010663744,0.12469054],"category_scores_gemma":[0.005018868,0.0011549477,0.0012432317,0.004995504,0.00049705664,0.0077057364,0.003723707,0.0016906913,0.08796109],"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":[0.00030033814,0.00009624959,0.00066936034,0.0006407812,0.00011909734,0.00023591061,0.00014376285,0.001461211,0.005537076,0.044476848,0.44765782,0.4986616],"study_design_scores_gemma":[0.00006422437,0.000058358728,0.0005888467,0.0001410407,0.0000940605,0.0011853023,0.000057981724,0.0075996956,0.0087014865,0.03748999,0.9439607,0.00005832212],"about_ca_topic_score_codex":0.00064148824,"about_ca_topic_score_gemma":0.00093504763,"teacher_disagreement_score":0.12469054,"about_ca_system_score_codex":0.00049405167,"about_ca_system_score_gemma":0.0010055716,"threshold_uncertainty_score":0.41713136},"labels":[],"label_agreement":null},{"id":"W4245078941","doi":"10.4018/978-1-5225-5978-8.ch006","title":"New Design Approach to Handle Spatial Vagueness in Spatial OLAP Datacubes","year":2018,"lang":"en","type":"book-chapter","venue":"Advances in environmental engineering and green technologies book series","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Online analytical processing; Vagueness; Computer science; Spatial analysis; Metadata; Data mining; Data science; Information retrieval; Fuzzy logic; Data warehouse; Geography; Artificial intelligence; World Wide Web","score_opus":0.008214852799464817,"score_gpt":0.1879273721953612,"score_spread":0.1797125193958964,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4245078941","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":[0.002532236,0.00023794315,0.99260545,0.00020266263,0.000069002745,0.00013157171,0.00008610697,0.0007015779,0.0034334157],"genre_scores_gemma":[0.0656002,0.0006125411,0.9261502,0.00030347836,0.000094133065,0.0005729512,0.0005564388,0.00027290906,0.0058372207],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997445,0.00069132476,0.00025505235,0.00036047504,0.0011014085,0.00014679355],"domain_scores_gemma":[0.9982948,0.00038754512,0.00012553918,0.00038647736,0.0007037609,0.00010184094],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023253805,0.0008254766,0.0007688928,0.0012034705,0.0010969824,0.0035057098,0.0022626133,0.0011298335,0.0051806],"category_scores_gemma":[0.003996687,0.0005846964,0.0011875982,0.0020176107,0.00093099836,0.004092555,0.0034834028,0.0015357601,0.0016388437],"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":[0.00034589114,0.0002979089,0.002982037,0.0011378607,0.00019162828,0.0010379818,0.0028238152,0.11782231,0.045071088,0.36997017,0.027049074,0.43127024],"study_design_scores_gemma":[0.00007279984,0.00024199756,0.00055031787,0.00016120651,0.00010868413,0.0011121891,0.00091739814,0.6396577,0.023223786,0.11075637,0.22310558,0.00009195603],"about_ca_topic_score_codex":0.0013216541,"about_ca_topic_score_gemma":0.0012009158,"teacher_disagreement_score":0.0051806,"about_ca_system_score_codex":0.0009803113,"about_ca_system_score_gemma":0.0013216428,"threshold_uncertainty_score":0.017330825},"labels":[],"label_agreement":null},{"id":"W4245088926","doi":"10.1007/978-0-387-39940-9_2007","title":"Acquisitional Query Languages","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Computer science; Linguistics; Philosophy","score_opus":0.010893041807429567,"score_gpt":0.24295692343861422,"score_spread":0.23206388163118466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4245088926","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":[0.0037033223,0.0062525785,0.7562895,0.002640836,0.00041825997,0.00019028492,0.0025782592,0.011219079,0.21670784],"genre_scores_gemma":[0.13306084,0.0130156735,0.5788119,0.002429675,0.00083016866,0.00057584717,0.012768852,0.0064922343,0.25201482],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99821234,0.00028858896,0.00018791381,0.00037702467,0.0008242425,0.00010987583],"domain_scores_gemma":[0.9987274,0.000544281,0.000050124036,0.0003260593,0.00030949587,0.000042539876],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013712269,0.001052119,0.0009017186,0.0018369263,0.0009437289,0.00637679,0.0021305336,0.00084187393,0.032581642],"category_scores_gemma":[0.0034717268,0.0011003577,0.0008964467,0.0031666593,0.0026386972,0.010563235,0.002555855,0.0035390782,0.017656485],"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":[0.00003600156,0.000030944906,0.00013502521,0.00029848944,0.00001032385,0.000055773915,0.00052701967,0.00057507097,0.0020800077,0.777249,0.057946995,0.16105536],"study_design_scores_gemma":[0.000016696824,0.00002234951,0.00018943823,0.00015766252,0.000019696814,0.000566496,0.0001757419,0.005624052,0.004020128,0.43926388,0.5499074,0.00003649235],"about_ca_topic_score_codex":0.0012482628,"about_ca_topic_score_gemma":0.0015222426,"teacher_disagreement_score":0.032581642,"about_ca_system_score_codex":0.0013152392,"about_ca_system_score_gemma":0.0014983894,"threshold_uncertainty_score":0.10899651},"labels":[],"label_agreement":null},{"id":"W4245284870","doi":"10.1007/978-0-387-39940-9_4073","title":"XML Database Design","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Computer science; Database; XML database; XML; Programming language; World Wide Web","score_opus":0.025863512017303657,"score_gpt":0.24378663235371742,"score_spread":0.21792312033641376,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4245284870","genre_codex":"methods","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":[0.0015359547,0.0076053627,0.84363645,0.0021620365,0.0011573882,0.0003411098,0.0017897128,0.007862348,0.13390964],"genre_scores_gemma":[0.029982695,0.012082201,0.5851565,0.0018825964,0.0006538452,0.0005736231,0.008340649,0.0030538768,0.35827404],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99873656,0.00024870082,0.00014959529,0.0002297167,0.0005738267,0.00006164277],"domain_scores_gemma":[0.9992132,0.00017517962,0.000029631534,0.00028880226,0.00024623,0.000046862013],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001662788,0.00087701814,0.00059033954,0.0015119712,0.00076268736,0.0040718894,0.0020254287,0.0010831574,0.040960938],"category_scores_gemma":[0.002830879,0.00085390854,0.0008125621,0.0021162562,0.0006592705,0.0044029295,0.0015828597,0.0014123276,0.025649345],"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":[0.000057471756,0.00007654315,0.00041910258,0.0007266732,0.00004054018,0.00024781658,0.00039330928,0.0020190317,0.006722654,0.26320454,0.20307383,0.5230185],"study_design_scores_gemma":[0.000017192888,0.000029913235,0.00021888947,0.00020581874,0.000023680454,0.0007197961,0.00007377287,0.0051372903,0.00421804,0.060959037,0.92837584,0.000020664998],"about_ca_topic_score_codex":0.0010255509,"about_ca_topic_score_gemma":0.0015209038,"teacher_disagreement_score":0.040960938,"about_ca_system_score_codex":0.00081018347,"about_ca_system_score_gemma":0.0010773224,"threshold_uncertainty_score":0.13702798},"labels":[],"label_agreement":null},{"id":"W4245823248","doi":"10.1145/1114244.1114250","title":"Optimization of query streams using semantic prefetching","year":2005,"lang":"en","type":"article","venue":"ACM Transactions on Database Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Latency (audio); Context (archaeology); Server; Query optimization; STREAMS; Data mining; Information retrieval; Database; Computer network","score_opus":0.03100413104897517,"score_gpt":0.2743439780064526,"score_spread":0.24333984695747743,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4245823248","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":[0.5548804,0.00093433034,0.4227339,0.00065818895,0.00008899773,0.0002899914,0.0007340335,0.014973912,0.004706382],"genre_scores_gemma":[0.8958384,0.00017818606,0.10101369,0.00011394589,0.000048003887,0.00008303603,0.00076424266,0.00026276667,0.0016976296],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99903715,0.00017218437,0.00007690735,0.0002204392,0.00035805083,0.00013532679],"domain_scores_gemma":[0.99813026,0.0008649971,0.00014840189,0.00040845876,0.00036871008,0.00007916435],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00091900886,0.00084543234,0.00083599036,0.0006126515,0.00039553765,0.0009152305,0.0012000679,0.00049809675,0.0014795589],"category_scores_gemma":[0.005832576,0.00036942813,0.00033532106,0.0011272862,0.0004402454,0.0019122807,0.00085714564,0.000782013,0.00030321206],"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":[0.001562968,0.00058296236,0.011739608,0.00016738976,0.0000954908,0.00030821678,0.00021761586,0.47619158,0.056792077,0.0045067235,0.0087213535,0.439114],"study_design_scores_gemma":[0.00003736059,0.0000623432,0.0006391784,0.0000019619301,0.00001092353,0.00003112136,0.000027877775,0.9846859,0.012297466,0.0016246208,0.00057314296,0.000008187427],"about_ca_topic_score_codex":0.005737296,"about_ca_topic_score_gemma":0.008995467,"teacher_disagreement_score":0.005737296,"about_ca_system_score_codex":0.00080168963,"about_ca_system_score_gemma":0.0014176213,"threshold_uncertainty_score":0.011407793},"labels":[],"label_agreement":null},{"id":"W4245824124","doi":"10.1007/978-1-4614-6170-8_100655","title":"Time-Aggregated Graphs","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Database Systems and Queries","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 Calgary","funders":"","keywords":"Computer science","score_opus":0.010768710282719852,"score_gpt":0.2073191590794806,"score_spread":0.19655044879676073,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4245824124","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":[0.014209903,0.0020302169,0.78859454,0.0014393663,0.0007933394,0.000109738256,0.0023475874,0.0027738002,0.18770157],"genre_scores_gemma":[0.33814168,0.007481888,0.41001046,0.0010425439,0.0014847709,0.00025317637,0.009460713,0.0033508288,0.22877397],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99943775,0.00009482675,0.000024795254,0.00019820292,0.00019826871,0.000046197638],"domain_scores_gemma":[0.9987909,0.00029003347,0.000081706734,0.00051524123,0.00024194317,0.00008026136],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045924616,0.00068852113,0.0004700141,0.0020132295,0.00076370337,0.002062444,0.0009219219,0.00047991896,0.016687246],"category_scores_gemma":[0.0023674953,0.00039882187,0.0005498629,0.003393434,0.00070614245,0.004803204,0.0013445722,0.0017069725,0.0053104972],"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":[0.00003525767,0.000024539664,0.00020387066,0.00009797805,0.000021372258,0.000054957458,0.00014345036,0.011014152,0.0016279793,0.82911396,0.03690747,0.12075497],"study_design_scores_gemma":[0.0000045579377,0.00001123323,0.00028244825,0.00002861773,0.000020195359,0.00012302483,0.00005176929,0.027390946,0.0017019268,0.85248125,0.117892824,0.000011159683],"about_ca_topic_score_codex":0.0017646429,"about_ca_topic_score_gemma":0.0019889865,"teacher_disagreement_score":0.016687246,"about_ca_system_score_codex":0.0010807047,"about_ca_system_score_gemma":0.00048766393,"threshold_uncertainty_score":0.0558244},"labels":[],"label_agreement":null},{"id":"W4246240811","doi":"10.1109/icppw.2004.1328024","title":"A data identi .cation scheme for automatic relative debugging","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; Ontario Innovation Trust","keywords":"Debugging; Computer science; Scheme (mathematics); Artificial intelligence; Programming language; Mathematics","score_opus":0.06252080480764058,"score_gpt":0.33425745030021664,"score_spread":0.27173664549257603,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4246240811","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":[0.00713842,0.00028850432,0.96971524,0.0002817467,0.00013039599,0.0001265285,0.00042111735,0.021205414,0.0006926508],"genre_scores_gemma":[0.145579,0.00019244409,0.8468531,0.0003872362,0.00013176519,0.00021898762,0.0012395778,0.0017792832,0.0036186618],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99429274,0.0012900344,0.0008768093,0.0012320223,0.0017958595,0.0005126909],"domain_scores_gemma":[0.9789651,0.006528708,0.0012969734,0.009388576,0.0032492003,0.00057143404],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00632133,0.0017166596,0.0023003807,0.00493982,0.0021418324,0.0034046893,0.004430479,0.0025386142,0.00981406],"category_scores_gemma":[0.019983163,0.0015271119,0.0013148254,0.003648243,0.0017849342,0.008691687,0.0054666535,0.0035923035,0.004017522],"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":[0.001897966,0.00031388635,0.0035640628,0.00053208455,0.0001155229,0.00038709957,0.0008360155,0.008740704,0.048012704,0.07743792,0.031502865,0.8266592],"study_design_scores_gemma":[0.0006792006,0.0007496536,0.002098193,0.00033533393,0.00063898094,0.0012543445,0.0005007275,0.5048106,0.24320458,0.16834353,0.07686391,0.0005209775],"about_ca_topic_score_codex":0.0021446755,"about_ca_topic_score_gemma":0.003098757,"teacher_disagreement_score":0.00981406,"about_ca_system_score_codex":0.001529795,"about_ca_system_score_gemma":0.002903241,"threshold_uncertainty_score":0.033430755},"labels":[],"label_agreement":null},{"id":"W4246599120","doi":"10.1007/978-0-387-39940-9_771","title":"XML Storage","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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 Alberta","funders":"","keywords":"Computer science; XML; Programming language; Database; Operating system","score_opus":0.013784449388777376,"score_gpt":0.23039724976137607,"score_spread":0.2166128003725987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4246599120","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003093923,0.008351079,0.27580604,0.0025133968,0.001866005,0.0004252692,0.01978986,0.050991055,0.6371634],"genre_scores_gemma":[0.018557489,0.008251409,0.11940696,0.0014350818,0.0006311777,0.00024562923,0.03713477,0.006644515,0.807693],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99954116,0.000048935464,0.00005099346,0.0000895004,0.00023405372,0.00003543766],"domain_scores_gemma":[0.9993401,0.00011135946,0.000024420984,0.00030759178,0.0001785554,0.000037869795],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005880749,0.0010096048,0.0006509108,0.002673835,0.00079888484,0.003771667,0.0019039171,0.00096577103,0.169843],"category_scores_gemma":[0.0015403734,0.0006302765,0.00067142147,0.0043169707,0.00044161858,0.0049777967,0.0018643005,0.0010860593,0.144728],"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":[0.00008172655,0.000057575948,0.0002010521,0.00050495134,0.000022381653,0.00014399692,0.00018625072,0.0006179266,0.00821897,0.0563881,0.43290412,0.50067294],"study_design_scores_gemma":[0.000012642924,0.000015240667,0.00019553128,0.000115082825,0.00001573676,0.00036405737,0.000044185035,0.0011452696,0.0061466857,0.01272682,0.9792005,0.00001816038],"about_ca_topic_score_codex":0.001351984,"about_ca_topic_score_gemma":0.0016393103,"teacher_disagreement_score":0.169843,"about_ca_system_score_codex":0.0005522033,"about_ca_system_score_gemma":0.0007771364,"threshold_uncertainty_score":0.56818146},"labels":[],"label_agreement":null},{"id":"W4246693395","doi":"10.1007/978-0-387-39940-9_2994","title":"Long Running Queries","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Computer science","score_opus":0.014330355922982187,"score_gpt":0.23637548105299055,"score_spread":0.22204512513000838,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4246693395","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0072058276,0.02067849,0.40051508,0.007887978,0.0037404685,0.00055270974,0.008822944,0.022982633,0.52761394],"genre_scores_gemma":[0.06271013,0.01611354,0.16444077,0.004935421,0.0031205036,0.0004686406,0.019735718,0.010121479,0.7183538],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9960877,0.0005587086,0.0003252474,0.00073963625,0.0019665991,0.00032218432],"domain_scores_gemma":[0.99394953,0.0018763187,0.00027890145,0.0022587108,0.0013542012,0.00028237724],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002494609,0.0016473148,0.0016903437,0.0022900084,0.0015688632,0.0090861535,0.002414059,0.0017167669,0.14924827],"category_scores_gemma":[0.011427854,0.0009856762,0.0010810054,0.0055153565,0.00152231,0.017724955,0.004927088,0.0030624745,0.103729255],"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":[0.00013280343,0.00007280769,0.0004241945,0.0007650593,0.000035894507,0.00016575979,0.0005554715,0.000743838,0.0050019813,0.19889496,0.39374006,0.39946726],"study_design_scores_gemma":[0.000016393613,0.000032353135,0.00024369557,0.00017879004,0.000024757936,0.0004653707,0.00014043687,0.002050105,0.0022848663,0.08429028,0.91024375,0.000029246634],"about_ca_topic_score_codex":0.001135616,"about_ca_topic_score_gemma":0.001325764,"teacher_disagreement_score":0.14924827,"about_ca_system_score_codex":0.0013110059,"about_ca_system_score_gemma":0.0017100215,"threshold_uncertainty_score":0.49928522},"labels":[],"label_agreement":null},{"id":"W4246877953","doi":"10.4018/9781931777476.ch015","title":"On the Computation of Recursion in Relational Databases","year":2011,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Recursion (computer science); Computer science; Relational database; Directed acyclic graph; Graph database; Computation; Graph; Theoretical computer science; Directed graph; Database; Relational database management system; Algorithm; Programming language","score_opus":0.053838835537681595,"score_gpt":0.2674051544660919,"score_spread":0.21356631892841033,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4246877953","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":[0.0060247486,0.0036520245,0.97414273,0.00044967924,0.000101932725,0.00010651137,0.0002531883,0.0020411543,0.013228024],"genre_scores_gemma":[0.05629504,0.004908011,0.92592055,0.00029502512,0.00016966782,0.00022978222,0.00087233674,0.00075674045,0.010552844],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9977196,0.0006062678,0.00023876593,0.00034878802,0.00091477897,0.00017190629],"domain_scores_gemma":[0.9972584,0.001767761,0.00010555168,0.0005427076,0.000266303,0.000059263697],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002176258,0.001152381,0.0011639068,0.0016051518,0.001345301,0.0032921534,0.0023735147,0.00087123783,0.0061418545],"category_scores_gemma":[0.0076154815,0.0010629016,0.001474543,0.0054567796,0.0021023534,0.0094653675,0.002955956,0.0025282442,0.0032103062],"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":[0.000112934285,0.000055601326,0.0005369896,0.00047512524,0.00003762461,0.00020368789,0.00089821743,0.026764007,0.0036139577,0.63513136,0.012793908,0.31937668],"study_design_scores_gemma":[0.000049049988,0.0000730796,0.00036989638,0.0002357763,0.000068250134,0.00037568033,0.00014144076,0.15885437,0.005023804,0.7564227,0.078328855,0.00005718856],"about_ca_topic_score_codex":0.0060522533,"about_ca_topic_score_gemma":0.0056815497,"teacher_disagreement_score":0.0061418545,"about_ca_system_score_codex":0.0023290906,"about_ca_system_score_gemma":0.0016044582,"threshold_uncertainty_score":0.020546496},"labels":[],"label_agreement":null},{"id":"W4246910386","doi":"10.1007/978-0-387-39940-9_4009","title":"Web Query Languages","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Computer science; World Wide Web; Web search query; Web application; Information retrieval; Search engine","score_opus":0.011605445618327468,"score_gpt":0.24260632795641524,"score_spread":0.23100088233808777,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4246910386","genre_codex":"methods","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":[0.0019332806,0.01175087,0.6730673,0.0023420646,0.0007916029,0.00043834356,0.005922624,0.028587718,0.27516624],"genre_scores_gemma":[0.028534323,0.020331541,0.42150432,0.0031795313,0.0008386546,0.0007722806,0.026860459,0.01355376,0.4844251],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986457,0.00018525915,0.00015519808,0.00023540629,0.00069372513,0.00008465151],"domain_scores_gemma":[0.9991518,0.00032797497,0.000030507324,0.00021696911,0.00022055177,0.000052115956],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011357854,0.0013919306,0.0012200988,0.0030458332,0.00088922464,0.0056892885,0.0020757923,0.0009792811,0.06341804],"category_scores_gemma":[0.0027317852,0.0012382428,0.0011697982,0.005491076,0.001144681,0.009284771,0.0023824174,0.002667802,0.054007515],"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":[0.00005379423,0.00008106984,0.00014958154,0.00075115514,0.000026503094,0.00011573271,0.0004214358,0.0008906188,0.003847444,0.27588817,0.32000315,0.39777136],"study_design_scores_gemma":[0.00001604842,0.000013547404,0.00013774053,0.00021504908,0.000016011532,0.000399393,0.00007071616,0.0030820977,0.002059058,0.08278372,0.9111816,0.000024977444],"about_ca_topic_score_codex":0.0019726418,"about_ca_topic_score_gemma":0.0023090106,"teacher_disagreement_score":0.06341804,"about_ca_system_score_codex":0.0010547563,"about_ca_system_score_gemma":0.0011545478,"threshold_uncertainty_score":0.21215445},"labels":[],"label_agreement":null},{"id":"W4246953364","doi":"10.4018/978-1-4666-9845-1.ch089","title":"New Design Approach to Handle Spatial Vagueness in Spatial OLAP Datacubes","year":2016,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Online analytical processing; Vagueness; Computer science; Spatial analysis; Metadata; Data mining; Information retrieval; Data science; Fuzzy logic; Geography; Data warehouse; Artificial intelligence; World Wide Web","score_opus":0.03196983879979877,"score_gpt":0.2492643120506512,"score_spread":0.21729447325085244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4246953364","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":[0.0022674561,0.0001892888,0.9936453,0.00021420672,0.000058859398,0.00012718237,0.00008710178,0.00063635025,0.0027743392],"genre_scores_gemma":[0.061843816,0.00047755428,0.93183565,0.00025994005,0.0000846943,0.0004832941,0.0004896999,0.0002708649,0.004254534],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9966994,0.0010055704,0.00036976606,0.00042748472,0.0013201858,0.00017758732],"domain_scores_gemma":[0.99750805,0.000648721,0.0001891923,0.00065131224,0.00085614104,0.00014653428],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033460334,0.0008541148,0.0008497042,0.001274739,0.0011440439,0.0041718944,0.0026209299,0.0012505519,0.005222664],"category_scores_gemma":[0.0054073003,0.0006755524,0.0013065117,0.0022751973,0.0012076533,0.0049962075,0.0041883034,0.0017983853,0.0016987878],"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":[0.00034735783,0.00028490133,0.0030115233,0.0012682584,0.00020530156,0.0010028613,0.0035536094,0.117286175,0.03510593,0.42831293,0.022289813,0.38733143],"study_design_scores_gemma":[0.000077831966,0.00023724609,0.0005396479,0.00020278226,0.000115354895,0.0010752429,0.0010733628,0.6156535,0.01971056,0.14380288,0.21741772,0.000093869305],"about_ca_topic_score_codex":0.0012051912,"about_ca_topic_score_gemma":0.0012360888,"teacher_disagreement_score":0.005222664,"about_ca_system_score_codex":0.001009432,"about_ca_system_score_gemma":0.001330166,"threshold_uncertainty_score":0.017695785},"labels":[],"label_agreement":null},{"id":"W4247000102","doi":"10.1007/978-0-387-39940-9_2749","title":"Heterogeneously Distributed Data","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Computer science","score_opus":0.029445509542297778,"score_gpt":0.2559260366822411,"score_spread":0.22648052713994335,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4247000102","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":[0.0074905893,0.0071430244,0.8685778,0.0019869204,0.0011694987,0.00022424327,0.0009955211,0.0053101066,0.10710217],"genre_scores_gemma":[0.18925002,0.010160165,0.5651264,0.001180382,0.0011949042,0.000392327,0.006573478,0.0022588514,0.22386344],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990879,0.00011308069,0.00006921811,0.00020755209,0.0004620874,0.00006008867],"domain_scores_gemma":[0.9988563,0.00021182174,0.000034834637,0.0006880076,0.00014776023,0.000061264924],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011125348,0.00059501705,0.0006960635,0.0008475811,0.00083318393,0.0038265171,0.0018424382,0.0006352621,0.016084723],"category_scores_gemma":[0.0020688511,0.00060427585,0.00051627966,0.002311899,0.00079862645,0.0042127427,0.0028385927,0.0014081756,0.0062742415],"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":[0.00018009124,0.000086801534,0.00074630947,0.00042920752,0.00008291149,0.0003092514,0.00043566898,0.009130917,0.010658373,0.3027009,0.1059507,0.5692889],"study_design_scores_gemma":[0.000042515807,0.000057447563,0.00071555673,0.00016359391,0.00007105792,0.0007833143,0.0001610103,0.04349117,0.012187392,0.21710493,0.72518396,0.000038139973],"about_ca_topic_score_codex":0.00065780064,"about_ca_topic_score_gemma":0.00089519547,"teacher_disagreement_score":0.016084723,"about_ca_system_score_codex":0.0006306748,"about_ca_system_score_gemma":0.0008336258,"threshold_uncertainty_score":0.05380881},"labels":[],"label_agreement":null},{"id":"W4247383316","doi":"10.22215/etd/2005-07766","title":"Peer-to-peer data integration using distributed bridges","year":2005,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Canadian Heritage; Library and Archives Canada","funders":"","keywords":"Computer science; Upload; Metadata; Peer-to-peer; Data integration; Server; Schema (genetic algorithms); Database; Information retrieval; World Wide Web","score_opus":0.05457033343232302,"score_gpt":0.3435342373300692,"score_spread":0.2889639038977462,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4247383316","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":[0.067739,0.00092513737,0.908387,0.0006813249,0.00019803298,0.00053615094,0.00023685176,0.008386345,0.012910189],"genre_scores_gemma":[0.49040425,0.0008943457,0.48348382,0.00024056977,0.00019064586,0.00046244115,0.0019331606,0.0008016095,0.021589095],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977997,0.00052422343,0.0001968258,0.00043016832,0.0008824166,0.0001665333],"domain_scores_gemma":[0.99600863,0.0008763989,0.00016743946,0.001821867,0.00090618915,0.00021946432],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023133657,0.00045968348,0.0008339206,0.0013466746,0.0012381036,0.0029342333,0.0024717494,0.0012998255,0.005307624],"category_scores_gemma":[0.0064019524,0.000610227,0.00056473416,0.0020125974,0.00048340604,0.005741777,0.0041960147,0.0009847953,0.002250398],"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":[0.0008498337,0.00074512203,0.004505367,0.00057612953,0.00028710117,0.00075170555,0.0018187485,0.02988027,0.07066278,0.06939768,0.021159708,0.7993655],"study_design_scores_gemma":[0.00036923712,0.0010903736,0.0028037168,0.00018721541,0.00029648756,0.000959543,0.0011578924,0.5863861,0.12337735,0.114467986,0.16875568,0.00014842847],"about_ca_topic_score_codex":0.0010910804,"about_ca_topic_score_gemma":0.0011224685,"teacher_disagreement_score":0.005307624,"about_ca_system_score_codex":0.0004894035,"about_ca_system_score_gemma":0.0010342889,"threshold_uncertainty_score":0.017755747},"labels":[],"label_agreement":null},{"id":"W4247409544","doi":"10.4018/9781599049311.ch085","title":"Knowledge Representation in Pattern Management","year":2011,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Representation (politics); Knowledge management; Computer science; Political science","score_opus":0.03622542228260181,"score_gpt":0.2781625574007968,"score_spread":0.241937135118195,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4247409544","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":[0.0026797967,0.023256829,0.8546995,0.0067947507,0.0007613516,0.00023357612,0.0005377143,0.0017393815,0.10929718],"genre_scores_gemma":[0.050862715,0.02512439,0.8456492,0.0024965676,0.0008188096,0.0006159143,0.0025241326,0.0006234396,0.07128485],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99847335,0.0004837272,0.00017628378,0.00030395814,0.0004650881,0.00009761903],"domain_scores_gemma":[0.99849486,0.0006976858,0.0000929446,0.0004571531,0.0001811449,0.000076182594],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022664291,0.00084522413,0.00073144096,0.0029545142,0.001169293,0.0068518138,0.0029350496,0.0018222651,0.013710631],"category_scores_gemma":[0.0048836903,0.000691133,0.0011772257,0.005826737,0.0032736047,0.010926717,0.002942421,0.0024313175,0.0067577516],"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":[0.00002047594,0.00005288109,0.0002521156,0.0006334361,0.000028176148,0.00016803875,0.0011526387,0.0024634842,0.00079097244,0.49412787,0.04173534,0.45857462],"study_design_scores_gemma":[0.000010711685,0.00001900872,0.00021521788,0.0004593338,0.000018425922,0.0004296268,0.00029727837,0.006350729,0.0007657841,0.5880819,0.4033285,0.000023466033],"about_ca_topic_score_codex":0.0022874821,"about_ca_topic_score_gemma":0.0019196403,"teacher_disagreement_score":0.013710631,"about_ca_system_score_codex":0.0019344545,"about_ca_system_score_gemma":0.0015971905,"threshold_uncertainty_score":0.04586661},"labels":[],"label_agreement":null},{"id":"W4247440078","doi":"10.1007/978-1-4614-8265-9_641","title":"Database Design","year":2018,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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 Toronto","funders":"","keywords":"Database; Computer science","score_opus":0.02929296541303814,"score_gpt":0.24823931780317107,"score_spread":0.21894635239013294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4247440078","genre_codex":"methods","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":[0.0016695572,0.020601228,0.581339,0.0049635675,0.0040766643,0.00087789807,0.0071795494,0.010876015,0.36841655],"genre_scores_gemma":[0.03410989,0.023036156,0.33208326,0.0044202725,0.0022206716,0.0009628617,0.020848218,0.003130756,0.5791878],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9973803,0.0004419645,0.0003099962,0.000521534,0.0012308644,0.000115338975],"domain_scores_gemma":[0.99700767,0.00052450714,0.000091676055,0.0011632185,0.001054436,0.00015855029],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023207853,0.0010443367,0.0010365207,0.002103281,0.0010097303,0.00719513,0.0025389872,0.0010832446,0.09052961],"category_scores_gemma":[0.006936526,0.00081605697,0.0007610288,0.003574875,0.00078841386,0.004875075,0.001991682,0.0015362866,0.09202457],"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":[0.000059971127,0.000056839875,0.00028049672,0.00092187093,0.000035371395,0.00008380273,0.0001824663,0.0008153802,0.003240027,0.119477615,0.39947885,0.47536725],"study_design_scores_gemma":[0.000012679142,0.000021810738,0.000118158874,0.00012311104,0.000012452642,0.00024186131,0.000041289135,0.0010964243,0.0012631633,0.029765045,0.9672927,0.000011295994],"about_ca_topic_score_codex":0.0008066741,"about_ca_topic_score_gemma":0.0009270577,"teacher_disagreement_score":0.09052961,"about_ca_system_score_codex":0.0011238545,"about_ca_system_score_gemma":0.0019993484,"threshold_uncertainty_score":0.30285174},"labels":[],"label_agreement":null},{"id":"W4247976931","doi":"10.1007/978-0-387-39940-9_2099","title":"AXML","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Computer science","score_opus":0.014039522109604607,"score_gpt":0.23179252214730614,"score_spread":0.21775300003770154,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4247976931","genre_codex":"software","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":[0.0010442112,0.001439381,0.27919495,0.0009199062,0.00060658396,0.00029008725,0.054620557,0.42529997,0.23658434],"genre_scores_gemma":[0.019167269,0.0028042374,0.23623344,0.0016819896,0.00025870642,0.0007157546,0.21116863,0.08694194,0.44102803],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987839,0.00020134966,0.00012691965,0.00023321623,0.00053964084,0.00011505482],"domain_scores_gemma":[0.99880135,0.00035871268,0.000048893653,0.00040602588,0.00030426396,0.00008077176],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00096210296,0.0020495874,0.0011466525,0.0025164522,0.00092601596,0.0057978574,0.0032227878,0.0015089221,0.352959],"category_scores_gemma":[0.0033193517,0.001377543,0.0012577316,0.0019100369,0.0005710971,0.00517415,0.0031800687,0.0023575223,0.35355532],"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":[0.00014234723,0.000056912253,0.00017807697,0.0006544039,0.000023157061,0.00008545228,0.00014928034,0.0010561417,0.0026829392,0.035059396,0.7547348,0.20517719],"study_design_scores_gemma":[0.000030374958,0.000014155808,0.00011473452,0.00011093397,0.000014063138,0.00012791128,0.00003842495,0.0034342892,0.003728565,0.011671222,0.9806898,0.000025599022],"about_ca_topic_score_codex":0.0043329666,"about_ca_topic_score_gemma":0.005630383,"teacher_disagreement_score":0.64704096,"about_ca_system_score_codex":0.000937592,"about_ca_system_score_gemma":0.0014124808,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W4248079095","doi":"10.1145/3393673.3276951","title":"HorseIR: bringing array programming languages together with database query processing","year":2020,"lang":"en","type":"article","venue":"ACM SIGPLAN Notices","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Relational database management system; Compiler; SQL; Database; Programming language; Parallel computing; Relational database; Query plan; Optimizing compiler; Sargable; Information retrieval; Web search query; Search engine","score_opus":0.023832372065614782,"score_gpt":0.2653052282002212,"score_spread":0.2414728561346064,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4248079095","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":[0.014940155,0.0002585714,0.92850244,0.0003570098,0.00012686597,0.000115524,0.00028146038,0.051338125,0.004079928],"genre_scores_gemma":[0.13296135,0.00042622696,0.8450055,0.00077810837,0.00012145678,0.0002371221,0.0019884491,0.012605477,0.005876334],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9978631,0.0004120786,0.00023508322,0.00048793107,0.00074311934,0.00025876224],"domain_scores_gemma":[0.9976163,0.0008591635,0.00020758958,0.00080476253,0.0003959244,0.00011620634],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023100334,0.001036929,0.00065301376,0.0008303714,0.0005107394,0.002716888,0.003251672,0.00079823536,0.00329788],"category_scores_gemma":[0.0042428356,0.00084265403,0.0013661106,0.0010212867,0.0017062016,0.004428662,0.0029112245,0.0028069774,0.0013098059],"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":[0.001604078,0.00077326404,0.007951016,0.00106194,0.00024017727,0.0009596175,0.002287536,0.08814373,0.08541652,0.15318732,0.057789125,0.6005856],"study_design_scores_gemma":[0.00025702812,0.0008901311,0.0018708952,0.00019998691,0.00025112988,0.000638784,0.00048946985,0.5545628,0.20247681,0.09913467,0.13899091,0.00023739116],"about_ca_topic_score_codex":0.0020654416,"about_ca_topic_score_gemma":0.0023720644,"teacher_disagreement_score":0.00329788,"about_ca_system_score_codex":0.00081568037,"about_ca_system_score_gemma":0.0014569965,"threshold_uncertainty_score":0.012216806},"labels":[],"label_agreement":null},{"id":"W4248969572","doi":"10.1007/978-1-4899-7993-3_1252-2","title":"Naive Tables","year":2016,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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":"Concordia University","funders":"","keywords":"Computer science","score_opus":0.014156782424647685,"score_gpt":0.23010998679266276,"score_spread":0.21595320436801507,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4248969572","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":[0.0051114927,0.0064302087,0.4637181,0.003247961,0.0025612765,0.00042072183,0.013430208,0.01615623,0.48892385],"genre_scores_gemma":[0.100281745,0.0074595027,0.43607026,0.003430332,0.002037434,0.0004274411,0.03748528,0.005239646,0.40756834],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9979652,0.00026212557,0.00017342751,0.00055341364,0.0009106042,0.00013525483],"domain_scores_gemma":[0.9970667,0.0006953643,0.000109708075,0.0013802368,0.00062846066,0.00011963428],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001040782,0.0011142503,0.0011048875,0.0023762204,0.001558142,0.006692103,0.0027320476,0.001086158,0.16520683],"category_scores_gemma":[0.007938122,0.0010478796,0.0012403995,0.0041404474,0.0013386823,0.013448105,0.0031265735,0.0023537637,0.08242586],"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":[0.00015079758,0.00007153072,0.0004022694,0.00049030565,0.00003880252,0.00006951878,0.00016092195,0.0012978674,0.0014032328,0.35929453,0.26823318,0.3683871],"study_design_scores_gemma":[0.00004004687,0.000033069868,0.00020426155,0.00017374662,0.000044406766,0.00032540032,0.00006972526,0.0049276943,0.0018842526,0.4707073,0.52155674,0.000033513075],"about_ca_topic_score_codex":0.0016200676,"about_ca_topic_score_gemma":0.00242892,"teacher_disagreement_score":0.16520683,"about_ca_system_score_codex":0.001152706,"about_ca_system_score_gemma":0.001821699,"threshold_uncertainty_score":0.5526719},"labels":[],"label_agreement":null},{"id":"W4248988812","doi":"10.1007/978-0-387-39940-9_4069","title":"XML Cardinality Estimation","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Cardinality (data modeling); Computer science; XML; Database; World Wide Web","score_opus":0.015670192585425076,"score_gpt":0.2458018369471075,"score_spread":0.23013164436168243,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4248988812","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":[0.010541309,0.0016603667,0.9394776,0.000534819,0.00019860212,0.00022299026,0.0074277623,0.010454569,0.029481877],"genre_scores_gemma":[0.15388127,0.002338949,0.7614029,0.00023635243,0.00027894415,0.0003716594,0.035207067,0.0019664862,0.044316404],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99738544,0.0005312865,0.0002188203,0.0005316997,0.0012062086,0.00012663877],"domain_scores_gemma":[0.99555737,0.0015937415,0.0003038982,0.0015238897,0.0009206122,0.00010049455],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021882306,0.0010592524,0.00093095755,0.004387724,0.00063768483,0.003164879,0.0016685494,0.00083259493,0.022431133],"category_scores_gemma":[0.012261512,0.0006283008,0.0008994366,0.0041864524,0.0003726622,0.004142184,0.0016874302,0.001303199,0.011434897],"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":[0.00023369343,0.0001361812,0.0068077417,0.0003579373,0.00009191617,0.00017492432,0.00015487804,0.030060843,0.008810776,0.059034463,0.058920622,0.8352161],"study_design_scores_gemma":[0.00005438138,0.00010620725,0.008414315,0.00038633455,0.00014421654,0.0012708623,0.0003883518,0.5840172,0.056441106,0.1071459,0.24151702,0.00011417838],"about_ca_topic_score_codex":0.002081235,"about_ca_topic_score_gemma":0.0024517844,"teacher_disagreement_score":0.022431133,"about_ca_system_score_codex":0.0009081687,"about_ca_system_score_gemma":0.0009946285,"threshold_uncertainty_score":0.075039625},"labels":[],"label_agreement":null},{"id":"W4249004309","doi":"10.1007/978-0-387-39940-9_3767","title":"Temporal Middleware","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Computer science; Middleware (distributed applications); Operating system","score_opus":0.01719272950821877,"score_gpt":0.23280159013376184,"score_spread":0.21560886062554308,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4249004309","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":[0.0024291936,0.0055191442,0.6815722,0.0018945554,0.0017213353,0.00016339557,0.0015999082,0.014862312,0.29023796],"genre_scores_gemma":[0.07303858,0.010388176,0.4092844,0.0015941769,0.0012855825,0.00033275742,0.005688114,0.005330241,0.49305797],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99938405,0.00007740409,0.00006053297,0.00017067295,0.0002485125,0.000058837315],"domain_scores_gemma":[0.99917966,0.00019434564,0.0000389696,0.0003401692,0.00018128105,0.00006560645],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00084297603,0.0008803328,0.00054994866,0.0010399434,0.0008255171,0.0041304226,0.0017866829,0.0008577389,0.054784175],"category_scores_gemma":[0.0023316103,0.0006071465,0.00083609385,0.0015806457,0.0007561528,0.005548954,0.002128494,0.0016371064,0.028109055],"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":[0.00013662985,0.000052377352,0.00019338608,0.00054028933,0.00002659534,0.00015570663,0.00040265644,0.0021356612,0.008570288,0.4762609,0.116985016,0.39454043],"study_design_scores_gemma":[0.000017440949,0.000019762749,0.00010535928,0.00013538478,0.0000245032,0.0003388862,0.000095948824,0.0056842486,0.0046810894,0.14136182,0.8475163,0.000019167577],"about_ca_topic_score_codex":0.0015337791,"about_ca_topic_score_gemma":0.0020273873,"teacher_disagreement_score":0.054784175,"about_ca_system_score_codex":0.0010100342,"about_ca_system_score_gemma":0.0013313644,"threshold_uncertainty_score":0.18327135},"labels":[],"label_agreement":null},{"id":"W4249247065","doi":"10.1007/978-1-4939-7131-2_101013","title":"Rule-Based Systems","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Database Systems and Queries","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 Calgary","funders":"","keywords":"Computer science","score_opus":0.022009871719087058,"score_gpt":0.22961715551500275,"score_spread":0.2076072837959157,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4249247065","genre_codex":"methods","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":[0.0028485511,0.011863306,0.5706921,0.0029325932,0.0019744597,0.00032058428,0.0010223322,0.0041650953,0.40418106],"genre_scores_gemma":[0.066490136,0.017901342,0.5445332,0.0022073938,0.00144981,0.00035089182,0.0050009163,0.0011995952,0.36086684],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99847203,0.00021497275,0.00012778398,0.00037976334,0.0007484712,0.000056930505],"domain_scores_gemma":[0.99863786,0.0005352768,0.000035111687,0.00043638423,0.00031445574,0.000040977597],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011873302,0.0009665571,0.0007909114,0.0012876936,0.00071778346,0.0045142584,0.002247101,0.0012083454,0.038198873],"category_scores_gemma":[0.0039795833,0.0005847823,0.00087273004,0.0018994967,0.0012759434,0.004706692,0.0018227571,0.0019518713,0.028532162],"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":[0.000029884915,0.00006953409,0.00018216536,0.00040379976,0.000049094553,0.00011826636,0.00020198799,0.003885238,0.0022429447,0.29627767,0.07656299,0.6199763],"study_design_scores_gemma":[0.000017113949,0.00003605077,0.0001886074,0.00022326015,0.000038521484,0.00029085058,0.00007687699,0.015619268,0.0029144813,0.32280818,0.6577608,0.000025948124],"about_ca_topic_score_codex":0.0012608586,"about_ca_topic_score_gemma":0.0011511248,"teacher_disagreement_score":0.038198873,"about_ca_system_score_codex":0.0007859078,"about_ca_system_score_gemma":0.0011246722,"threshold_uncertainty_score":0.12778789},"labels":[],"label_agreement":null},{"id":"W4249316706","doi":"10.4018/978-1-59904-951-9.ch201","title":"Improved Data Partitioning for Building Large ROLAP Data Cubes in Parallel","year":2008,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University; Carleton University; Dalhousie University","funders":"","keywords":"Computer science; Parallel computing; Speedup; Scalability; Data cube; Cube (algebra); Data warehouse; Multiprocessing; External Data Representation; Representation (politics); Data structure; Data mining; Database; Operating system; Mathematics","score_opus":0.06416059204949666,"score_gpt":0.3066803096538637,"score_spread":0.24251971760436708,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4249316706","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":[0.007818692,0.00019333001,0.9882218,0.00006717219,0.000032816133,0.00006977845,0.00012785001,0.0012818251,0.002186649],"genre_scores_gemma":[0.04602296,0.00019415292,0.9505257,0.000045635556,0.00002327156,0.00019943669,0.0008547871,0.0003287514,0.0018051857],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993032,0.00012487583,0.000044275683,0.00011608092,0.0003506367,0.000060866296],"domain_scores_gemma":[0.99945015,0.0001655329,0.00002562808,0.00019004938,0.00015071667,0.000017979988],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004641898,0.0007284435,0.0006565277,0.0007303666,0.00066743884,0.0009447253,0.0015974727,0.00039796543,0.0024913882],"category_scores_gemma":[0.0012456124,0.00043960338,0.0008892679,0.0017293567,0.0005080778,0.0015020417,0.0017496162,0.0011018205,0.0012027095],"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":[0.0003267208,0.00017533176,0.0010366152,0.000501963,0.00011907042,0.0003873764,0.0006340731,0.18493475,0.072416544,0.042774193,0.021262577,0.6754307],"study_design_scores_gemma":[0.00011748849,0.0001181352,0.00054586283,0.00002853601,0.00005103713,0.0004757458,0.0001870935,0.8543038,0.061182037,0.03305184,0.049885523,0.000052932122],"about_ca_topic_score_codex":0.002258694,"about_ca_topic_score_gemma":0.0028720652,"teacher_disagreement_score":0.0024913882,"about_ca_system_score_codex":0.00046038974,"about_ca_system_score_gemma":0.00061803445,"threshold_uncertainty_score":0.0083345175},"labels":[],"label_agreement":null},{"id":"W4250221826","doi":"10.1007/978-1-4939-7131-2_101347","title":"Time-Aggregated Graphs","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Database Systems and Queries","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 Calgary","funders":"","keywords":"Computer science","score_opus":0.013693244006937248,"score_gpt":0.21954859232267174,"score_spread":0.2058553483157345,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4250221826","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":[0.014728336,0.0021319576,0.80071086,0.0016285029,0.0009224099,0.000110960915,0.002621181,0.002921778,0.17422396],"genre_scores_gemma":[0.35456103,0.007801881,0.40529108,0.001186771,0.0017989501,0.00026849905,0.01080943,0.0037060627,0.21457621],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9993777,0.000103596336,0.000027605265,0.00022512065,0.00021531021,0.000050604274],"domain_scores_gemma":[0.99856573,0.00034293055,0.000093987794,0.000620087,0.000282407,0.000094925526],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051030633,0.0007322518,0.0005011081,0.0020926113,0.0007808104,0.0022215564,0.00097534666,0.0005231253,0.016750043],"category_scores_gemma":[0.0028226692,0.0004134576,0.0005829717,0.0034929817,0.0007243903,0.0051657166,0.0014834299,0.0018874526,0.005616656],"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":[0.000037960515,0.000026291169,0.00021351437,0.000108754604,0.000023934343,0.000054373173,0.00014135108,0.011400379,0.0015650712,0.8348198,0.03820375,0.11340493],"study_design_scores_gemma":[0.0000046464156,0.0000115292205,0.00027867503,0.000029476572,0.000021335754,0.00011344291,0.00004830312,0.027222674,0.0015724446,0.8627371,0.10794935,0.0000109408265],"about_ca_topic_score_codex":0.0016184356,"about_ca_topic_score_gemma":0.0017781301,"teacher_disagreement_score":0.016750043,"about_ca_system_score_codex":0.0011122682,"about_ca_system_score_gemma":0.0005088026,"threshold_uncertainty_score":0.056034446},"labels":[],"label_agreement":null},{"id":"W4250461979","doi":"10.4018/978-1-59904-943-4.ch026","title":"XML Schema Integration and E-Commerce","year":2008,"lang":"en","type":"book-chapter","venue":"Electronic Commerce","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Laurentian University","funders":"","keywords":"XML Schema Editor; Document Structure Description; Computer science; XML validation; RELAX NG; Information retrieval; Efficient XML Interchange; XML Schema (W3C); Streaming XML; XML database; Schema (genetic algorithms); XML; Document type definition; Database; World Wide Web","score_opus":0.016432522132058067,"score_gpt":0.23722873978271225,"score_spread":0.2207962176506542,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4250461979","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0025199929,0.24815223,0.16828974,0.010697157,0.0033648293,0.00034033856,0.000540529,0.0018435457,0.5642518],"genre_scores_gemma":[0.038288962,0.30867743,0.34774604,0.009524654,0.0029310687,0.0006603186,0.0060886797,0.0016100626,0.28447276],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99825305,0.00051033567,0.00017632371,0.00019593288,0.00078251946,0.000081751714],"domain_scores_gemma":[0.9986576,0.0007408006,0.00007074076,0.00021807564,0.00024618718,0.000066563625],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00250919,0.0011525309,0.0009415712,0.0044280267,0.00095599965,0.0074669984,0.0017944316,0.0032687725,0.016737662],"category_scores_gemma":[0.003553198,0.00094285764,0.0010678036,0.012959409,0.0020413352,0.012099531,0.0027381787,0.003730081,0.010250367],"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":[0.000026223173,0.00009639945,0.00024007933,0.000781827,0.00004385453,0.00037396187,0.0010312689,0.0018326362,0.00076023524,0.5486541,0.088428944,0.35773045],"study_design_scores_gemma":[0.000011470456,0.000012424077,0.00018521067,0.0008133442,0.000014838989,0.000779065,0.00020062481,0.002314756,0.00032105343,0.121146016,0.8741853,0.000015960424],"about_ca_topic_score_codex":0.002311534,"about_ca_topic_score_gemma":0.0017171304,"teacher_disagreement_score":0.016737662,"about_ca_system_score_codex":0.002250777,"about_ca_system_score_gemma":0.002120062,"threshold_uncertainty_score":0.05599308},"labels":[],"label_agreement":null},{"id":"W4250589658","doi":"10.3886/ddiotherpapers01","title":"Exploring the relationship between DDI, SDMX and the Generic Statistical Business Process Model","year":2011,"lang":"en","type":"report","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Microdata (statistics); Interoperability; Metadata; Computer science; Statistical model; Process (computing); Data science; World Wide Web; Artificial intelligence; Sociology; Population","score_opus":0.39270104903248837,"score_gpt":0.3420542621130724,"score_spread":0.05064678691941599,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4250589658","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":[0.15131734,0.0012728324,0.7687387,0.0051831934,0.00008547532,0.00034042515,0.0011650119,0.0007401916,0.07115687],"genre_scores_gemma":[0.85136974,0.00076776906,0.14204921,0.00032516304,0.000038985825,0.00024838146,0.0012083236,0.00013914704,0.003853275],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.995255,0.0026346943,0.0003082722,0.00051569997,0.00096521515,0.00032122378],"domain_scores_gemma":[0.9819563,0.012947886,0.0016669724,0.0012805235,0.0016060912,0.0005422833],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0075987144,0.0006423432,0.0005191519,0.0027096777,0.00083590235,0.0057171695,0.00131256,0.0010597015,0.0050272136],"category_scores_gemma":[0.02786248,0.00041343964,0.001037015,0.004408912,0.0020936113,0.008981654,0.003839298,0.0021693006,0.00070482027],"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":[0.00007140062,0.00006481179,0.015651673,0.00013294941,0.00003136142,0.00011279053,0.0010633002,0.017891616,0.00030923163,0.9394911,0.0011547277,0.024024988],"study_design_scores_gemma":[0.00003478041,0.00012423977,0.008607745,0.000116888004,0.000048948565,0.00025889988,0.0020287281,0.2791159,0.00057535607,0.6906866,0.018356038,0.000045958983],"about_ca_topic_score_codex":0.007450075,"about_ca_topic_score_gemma":0.005273036,"teacher_disagreement_score":0.0075987144,"about_ca_system_score_codex":0.0051788576,"about_ca_system_score_gemma":0.0031686453,"threshold_uncertainty_score":0.040186346},"labels":[],"label_agreement":null},{"id":"W4251308493","doi":"10.1007/978-0-387-39940-9_3438","title":"Recursive Query Evaluation","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Computer science; Query optimization; Information retrieval","score_opus":0.021859913118165115,"score_gpt":0.26147866613334075,"score_spread":0.23961875301517563,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4251308493","genre_codex":"methods","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":[0.0072277817,0.005741445,0.8472943,0.0009405414,0.00038554452,0.00030588813,0.0012612785,0.016785474,0.120057814],"genre_scores_gemma":[0.18892762,0.0039427746,0.6247888,0.00093998824,0.0005459679,0.0003447694,0.007312128,0.005124352,0.16807353],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9966538,0.00063216424,0.00019305549,0.00065291923,0.0016010741,0.00026698096],"domain_scores_gemma":[0.9975802,0.00086806045,0.000056449928,0.0008123609,0.0006298691,0.00005297198],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020002916,0.0013606203,0.001495236,0.0015980996,0.0008960932,0.0035753183,0.002483009,0.00088231964,0.03988859],"category_scores_gemma":[0.0066850986,0.0006751962,0.0010344781,0.0022884172,0.0012350166,0.004632795,0.00243183,0.0019448152,0.021750536],"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":[0.00016945311,0.00010491274,0.00045900888,0.00032579256,0.00004102999,0.000074955446,0.00022442061,0.0032457765,0.007075217,0.17260425,0.087328345,0.7283468],"study_design_scores_gemma":[0.00008719191,0.00017982956,0.0013909716,0.0002657265,0.00017623081,0.0008777396,0.00021531055,0.13903894,0.044223975,0.363864,0.44956115,0.000118924145],"about_ca_topic_score_codex":0.0028724037,"about_ca_topic_score_gemma":0.003615668,"teacher_disagreement_score":0.03988859,"about_ca_system_score_codex":0.0015137943,"about_ca_system_score_gemma":0.0014737808,"threshold_uncertainty_score":0.13344061},"labels":[],"label_agreement":null},{"id":"W4251491334","doi":"10.1145/956895.956898","title":"XML parsing","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada)","funders":"","keywords":"Computer science; XML validation; Streaming XML; Efficient XML Interchange; XML Schema (W3C); XML Schema Editor; XML database; Document Structure Description; Simple API for XML; Parsing; Database; XML Encryption; Information retrieval; XML Signature; XML; Programming language; World Wide Web","score_opus":0.012970241435078281,"score_gpt":0.2293582252718944,"score_spread":0.21638798383681612,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4251491334","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":[0.010633454,0.0017456358,0.60134596,0.0021266532,0.0012225362,0.0014618755,0.03933866,0.17633514,0.16579008],"genre_scores_gemma":[0.101201445,0.002581486,0.54642147,0.0036625639,0.00052759657,0.00091042137,0.12506558,0.031161437,0.188468],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9976362,0.0003690386,0.0003190055,0.0005018379,0.0009521693,0.00022188111],"domain_scores_gemma":[0.9943949,0.00126973,0.00022800245,0.002334155,0.0016241123,0.00014912862],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024392607,0.001290877,0.00087997137,0.0020314367,0.0011523892,0.0039918935,0.0022577515,0.0015047996,0.071487166],"category_scores_gemma":[0.008584016,0.0007471449,0.0011981403,0.0024417613,0.00064437825,0.0038932539,0.003211092,0.0015094603,0.07830489],"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":[0.00063298305,0.00020554673,0.0035208745,0.0010472152,0.000115473376,0.00078893825,0.0007924589,0.0031954069,0.02643517,0.0753057,0.369233,0.5187272],"study_design_scores_gemma":[0.00005332685,0.000088204644,0.0017740689,0.00015489553,0.00005135152,0.0008479715,0.00022484484,0.010794122,0.038996816,0.032256138,0.91466945,0.0000889212],"about_ca_topic_score_codex":0.0017503202,"about_ca_topic_score_gemma":0.0016885118,"teacher_disagreement_score":0.071487166,"about_ca_system_score_codex":0.0006869386,"about_ca_system_score_gemma":0.001384668,"threshold_uncertainty_score":0.23914838},"labels":[],"label_agreement":null},{"id":"W4251762724","doi":"10.1007/978-1-4614-6170-8_100071","title":"Routine Discovery","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Database Systems and Queries","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 Calgary","funders":"","keywords":"Medicine; Computer science","score_opus":0.01303042247303963,"score_gpt":0.21505459215529948,"score_spread":0.20202416968225986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4251762724","genre_codex":"methods","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":[0.005321247,0.003250069,0.4934617,0.0032809277,0.0014045199,0.0006177742,0.0035786303,0.0231395,0.46594566],"genre_scores_gemma":[0.05256836,0.0039365906,0.30277434,0.0017963669,0.0009860115,0.0004200992,0.011284078,0.0070950924,0.6191391],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9969158,0.00038870057,0.00017265978,0.0010060543,0.001272615,0.00024413291],"domain_scores_gemma":[0.99524105,0.0013847885,0.0001272561,0.0021643504,0.00090399716,0.00017848579],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022673965,0.0014999998,0.0014875366,0.0032630265,0.0021928884,0.0063951192,0.0043073874,0.0015263981,0.09167981],"category_scores_gemma":[0.008956238,0.0012778712,0.0017196096,0.0034422497,0.002088987,0.009818733,0.0045364522,0.0036215186,0.07117748],"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":[0.000121711804,0.00008619653,0.00037840093,0.00043808308,0.000023155582,0.000100510675,0.00043933318,0.0005500098,0.0028082072,0.3807617,0.17017938,0.44411328],"study_design_scores_gemma":[0.000017876322,0.000036473295,0.00026832457,0.00013818542,0.000029772444,0.00053341896,0.00013422249,0.0042853123,0.006371052,0.17277491,0.8153641,0.000046290686],"about_ca_topic_score_codex":0.0025564313,"about_ca_topic_score_gemma":0.0029249194,"teacher_disagreement_score":0.09167981,"about_ca_system_score_codex":0.0019182949,"about_ca_system_score_gemma":0.0033281946,"threshold_uncertainty_score":0.3066995},"labels":[],"label_agreement":null},{"id":"W4251774540","doi":"10.1145/956061.956062","title":"Attribute value reordering for efficient hybrid OLAP","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Research and Productivity Council; University of New Brunswick","funders":"","keywords":"Online analytical processing; Normalization (sociology); Cube (algebra); Computer science; Data cube; Data warehouse; Data mining; Database; Mathematics; Combinatorics","score_opus":0.017431506484908835,"score_gpt":0.2518439901560493,"score_spread":0.23441248367114048,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4251774540","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":[0.13185813,0.00086400314,0.8446139,0.00045358835,0.00014535182,0.0002381619,0.0010164176,0.014240821,0.0065696305],"genre_scores_gemma":[0.50229037,0.00031176256,0.49080968,0.00019149129,0.00006401199,0.0002575335,0.0019772982,0.0006717917,0.0034260016],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99742955,0.00067262235,0.00025640705,0.0002863151,0.0011086544,0.00024652263],"domain_scores_gemma":[0.9950741,0.001046608,0.0002507754,0.0024486193,0.0010743642,0.00010559384],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019039777,0.00078898465,0.0008987396,0.0011004962,0.00075567485,0.002615696,0.0019491527,0.00034985357,0.002148839],"category_scores_gemma":[0.0052253627,0.00054827565,0.0004934067,0.0036904977,0.00071050884,0.0037985295,0.001980318,0.0009035423,0.0010197894],"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":[0.0017057272,0.00044707983,0.006426049,0.00035797572,0.00017854587,0.00042714062,0.00067171163,0.09973302,0.07732516,0.053181585,0.022182422,0.7373636],"study_design_scores_gemma":[0.00017776733,0.0002652123,0.0029712724,0.000046493522,0.0001029394,0.00046628134,0.00055294076,0.6970566,0.16911466,0.09325329,0.035836294,0.00015627229],"about_ca_topic_score_codex":0.0036980112,"about_ca_topic_score_gemma":0.0051542046,"teacher_disagreement_score":0.0036980112,"about_ca_system_score_codex":0.00094485894,"about_ca_system_score_gemma":0.0021623804,"threshold_uncertainty_score":0.010069311},"labels":[],"label_agreement":null},{"id":"W4251930730","doi":"10.1017/9781108989817.035","title":"User-Centric Architecture Technologies","year":2021,"lang":"en","type":"book-chapter","venue":"Cambridge University Press eBooks","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Huawei Technologies (Canada)","funders":"","keywords":"Architecture; Computer science; Computer architecture; Human–computer interaction; Art; Visual arts","score_opus":0.0138993230268205,"score_gpt":0.18962004161699567,"score_spread":0.17572071859017516,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4251930730","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":[0.0035325212,0.027874641,0.5336854,0.0035508953,0.0014387773,0.00020061304,0.00070453144,0.010248741,0.4187639],"genre_scores_gemma":[0.05905221,0.04483842,0.32299787,0.002428421,0.00080056005,0.0005046383,0.0030427577,0.00349945,0.5628357],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9988985,0.00023633473,0.000060147504,0.00016284086,0.00052472414,0.000117347496],"domain_scores_gemma":[0.9991805,0.0001788191,0.000018803821,0.00034737927,0.00020701542,0.000067421584],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017444296,0.0010792983,0.00047789898,0.0014100778,0.0007750844,0.0053906487,0.0021176995,0.0014156476,0.03000677],"category_scores_gemma":[0.0015667918,0.0010221964,0.00053940073,0.002550393,0.0008358622,0.008311332,0.002034452,0.0029764688,0.018323816],"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":[0.000031346826,0.000042124044,0.00022547945,0.0003764205,0.000021183601,0.00009242475,0.0007210121,0.0013843921,0.004608349,0.5287199,0.13747717,0.32630017],"study_design_scores_gemma":[0.000005400588,0.000021852598,0.0001701766,0.00017804716,0.000012211757,0.00035023878,0.00011279159,0.0040259273,0.0025128177,0.07919703,0.9134004,0.000013109377],"about_ca_topic_score_codex":0.0016833056,"about_ca_topic_score_gemma":0.0024697443,"teacher_disagreement_score":0.03000677,"about_ca_system_score_codex":0.0017566117,"about_ca_system_score_gemma":0.0013583493,"threshold_uncertainty_score":0.100382626},"labels":[],"label_agreement":null},{"id":"W4251990890","doi":"10.1007/978-0-387-39940-9_4062","title":"XML (Almost)","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Computer science; XML; Programming language; World Wide Web","score_opus":0.013899828094901782,"score_gpt":0.23232980805166384,"score_spread":0.21842997995676205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4251990890","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0017168872,0.0032964486,0.12083099,0.0023921493,0.0022891709,0.00033763147,0.07467457,0.06515274,0.7293095],"genre_scores_gemma":[0.007523712,0.002936108,0.044437382,0.0024799274,0.00045995164,0.00023506171,0.088232145,0.013381667,0.840314],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.999443,0.000085297856,0.00006438927,0.00010360438,0.00024629015,0.000057538837],"domain_scores_gemma":[0.99919635,0.00014895719,0.000042784694,0.00031905924,0.00022660878,0.00006635698],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007002295,0.001173089,0.0006575882,0.002433949,0.00066490244,0.0042462256,0.0014178812,0.0012935861,0.33182833],"category_scores_gemma":[0.0021427914,0.0006302581,0.0006610482,0.004368689,0.0004799684,0.0049193865,0.0021418047,0.0012832541,0.36236745],"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":[0.000057438352,0.00003520373,0.0001364812,0.0004251693,0.0000135963965,0.00008875066,0.0001256136,0.00025687396,0.0026261068,0.025050541,0.69484055,0.27634364],"study_design_scores_gemma":[0.0000059962863,0.0000067313526,0.00012922582,0.000058980975,0.000004005561,0.00010916863,0.000019077468,0.00015148471,0.0008247277,0.0031209653,0.995561,0.000008625524],"about_ca_topic_score_codex":0.0029090839,"about_ca_topic_score_gemma":0.0036185156,"teacher_disagreement_score":0.33182833,"about_ca_system_score_codex":0.00052055693,"about_ca_system_score_gemma":0.00076456665,"threshold_uncertainty_score":0.9530658},"labels":[],"label_agreement":null},{"id":"W4252007972","doi":"10.1007/978-1-4614-6170-8_100448","title":"Incremental Computation","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Database Systems and Queries","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 Calgary","funders":"","keywords":"Computer science; Computation; Algorithm","score_opus":0.01897505238301491,"score_gpt":0.24046038491249141,"score_spread":0.2214853325294765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4252007972","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":[0.003873199,0.0061572744,0.5800565,0.0016485485,0.0012981128,0.0001608426,0.00089234754,0.0040586866,0.40185454],"genre_scores_gemma":[0.15195581,0.009342376,0.4687474,0.0008417756,0.0016136949,0.00033520506,0.0044610035,0.0027107135,0.35999203],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99947256,0.000054119944,0.000024251303,0.0001466422,0.00025882493,0.000043580425],"domain_scores_gemma":[0.9993449,0.00017812035,0.000015069197,0.000277085,0.00015744781,0.00002741855],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037711463,0.00082666986,0.0006219317,0.0010373563,0.0007371518,0.0021298646,0.0015120669,0.0005428797,0.03952332],"category_scores_gemma":[0.0023642776,0.0004319334,0.00066922227,0.0018561834,0.00092407607,0.0033725137,0.0014336782,0.0017452203,0.014135751],"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":[0.000055788947,0.000031169482,0.00012493705,0.00024637795,0.00001834944,0.000033139142,0.00008757594,0.003942049,0.0018070181,0.39651525,0.11036664,0.48677164],"study_design_scores_gemma":[0.000023074319,0.000024318448,0.000342959,0.00012069894,0.000036020498,0.00022775079,0.00004636791,0.034094606,0.004900773,0.46651527,0.49364045,0.000027711478],"about_ca_topic_score_codex":0.0016890815,"about_ca_topic_score_gemma":0.0023317058,"teacher_disagreement_score":0.03952332,"about_ca_system_score_codex":0.0010358538,"about_ca_system_score_gemma":0.0009913854,"threshold_uncertainty_score":0.13221872},"labels":[],"label_agreement":null},{"id":"W4252033244","doi":"10.1145/502200.502201","title":"Requirements for XML document database systems","year":2001,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; XML Schema Editor; XML validation; Document Structure Description; Efficient XML Interchange; XML database; Streaming XML; Database; XML; cXML; SGML; Document type definition; XML framework; XML Schema (W3C); Information retrieval; World Wide Web","score_opus":0.04224744876906887,"score_gpt":0.309840036945367,"score_spread":0.2675925881762981,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4252033244","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":[0.011074369,0.006438637,0.8529834,0.028081665,0.0014654794,0.0024903517,0.0017624663,0.0043165255,0.0913871],"genre_scores_gemma":[0.13470389,0.008445167,0.81012976,0.006450403,0.0019329448,0.0037925174,0.0058867405,0.0014561327,0.02720241],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9446034,0.013343863,0.011440954,0.0027636592,0.025809428,0.0020387606],"domain_scores_gemma":[0.93437713,0.027310664,0.004050356,0.011696757,0.02015456,0.0024104703],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.027205592,0.0009310445,0.0017819946,0.002594486,0.0031299996,0.014915153,0.0051686335,0.0074137817,0.007291311],"category_scores_gemma":[0.09239114,0.0020564476,0.0014547749,0.0033054056,0.0032492403,0.016940877,0.008038882,0.005653005,0.008720909],"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":[0.0001424952,0.000155873,0.0011395074,0.0016106062,0.00005813621,0.0013749967,0.0027273884,0.005025209,0.007416635,0.8735167,0.038474053,0.0683584],"study_design_scores_gemma":[0.00011073722,0.000105334184,0.00052237447,0.00072012446,0.00006272611,0.0038841835,0.000918618,0.016964203,0.0039032958,0.26252165,0.7101893,0.00009741679],"about_ca_topic_score_codex":0.0017968665,"about_ca_topic_score_gemma":0.0010276571,"teacher_disagreement_score":0.027205592,"about_ca_system_score_codex":0.0018259648,"about_ca_system_score_gemma":0.0045189536,"threshold_uncertainty_score":0.14387864},"labels":[],"label_agreement":null},{"id":"W4252522402","doi":"10.1007/978-1-4614-6170-8_100446","title":"Continuous Query Processing","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Database Systems and Queries","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 Calgary","funders":"","keywords":"Computer science; Information retrieval","score_opus":0.013654420741514564,"score_gpt":0.22353149477507203,"score_spread":0.20987707403355746,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4252522402","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":[0.0031845053,0.010934703,0.86825854,0.0010133055,0.0011285401,0.00021578936,0.0012168024,0.006673253,0.10737449],"genre_scores_gemma":[0.10704735,0.014929237,0.6365506,0.001223595,0.0021135134,0.0004062057,0.0068637235,0.002062523,0.2288033],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982376,0.00016581667,0.00010434486,0.00047165045,0.0009052968,0.000115164316],"domain_scores_gemma":[0.99854976,0.00044581539,0.000050225262,0.00045738215,0.0004347366,0.000062121144],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011576484,0.0013927845,0.0011185453,0.0014616442,0.000708834,0.003882252,0.002464446,0.0008770846,0.03498171],"category_scores_gemma":[0.0030229161,0.000646304,0.0007404333,0.0035201788,0.001087416,0.0043519996,0.001813659,0.0025218918,0.019349402],"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":[0.00015760034,0.00008811269,0.00017241627,0.0006044516,0.000040067745,0.00007446131,0.00015378371,0.003553591,0.0095853405,0.14247234,0.12094081,0.722157],"study_design_scores_gemma":[0.000059566533,0.00016722313,0.0008428542,0.0002476144,0.00007963611,0.00077388325,0.00016180963,0.09915407,0.020499215,0.24751103,0.63041717,0.00008603822],"about_ca_topic_score_codex":0.0018590647,"about_ca_topic_score_gemma":0.0011918922,"teacher_disagreement_score":0.03498171,"about_ca_system_score_codex":0.001004401,"about_ca_system_score_gemma":0.001167629,"threshold_uncertainty_score":0.117025435},"labels":[],"label_agreement":null},{"id":"W4252671246","doi":"10.1007/978-3-642-28804-3_10","title":"Conclusion","year":2012,"lang":"en","type":"book-chapter","venue":"Lecture notes in control and information sciences","topic":"Advanced Database Systems and Queries","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 Toronto","funders":"","keywords":"Distributed computing; Computer science; Range (aeronautics); Autonomy; Engineering; Political science","score_opus":0.011655441259374587,"score_gpt":0.23639002454731498,"score_spread":0.22473458328794038,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4252671246","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0040908344,0.0019495778,0.008518545,0.032037377,0.006637746,0.00011577096,0.0017607829,0.00065893796,0.9442305],"genre_scores_gemma":[0.084056556,0.002914209,0.0073516564,0.032585964,0.0023531483,0.0001949098,0.0036786897,0.0008500127,0.8660148],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99797446,0.00030859612,0.000058557758,0.00045523985,0.0009090625,0.00029414927],"domain_scores_gemma":[0.99662614,0.00056648185,0.00011965078,0.00044593445,0.0017532088,0.00048862584],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0020163725,0.00058819546,0.00032428154,0.0011213383,0.0017893123,0.004727232,0.0014065572,0.0016367261,0.30157033],"category_scores_gemma":[0.008810193,0.0001628064,0.0006412498,0.0007907366,0.0010427311,0.0027049554,0.0020967328,0.0018753919,0.10021192],"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":[0.00024102777,0.000088162895,0.0029985292,0.0004868119,0.000037800975,0.00034848027,0.0010722756,0.00036896454,0.0012894627,0.18081084,0.5814246,0.23083305],"study_design_scores_gemma":[0.000016315755,0.000017905342,0.0012502174,0.00023206521,0.000016132255,0.00016037097,0.000875415,0.000103006016,0.0007937712,0.022773186,0.97375363,0.000008058695],"about_ca_topic_score_codex":0.0056857937,"about_ca_topic_score_gemma":0.0056316857,"teacher_disagreement_score":0.6984297,"about_ca_system_score_codex":0.0024721127,"about_ca_system_score_gemma":0.0031073624,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W4253177353","doi":"10.1007/978-0-387-39940-9_2420","title":"Database Materialization","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Database; Computer science","score_opus":0.014856073953725695,"score_gpt":0.23564091642735407,"score_spread":0.22078484247362837,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4253177353","genre_codex":"other","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":[0.0028280264,0.0065062013,0.20730802,0.0023814803,0.0022062568,0.0014740955,0.021971209,0.03443253,0.72089213],"genre_scores_gemma":[0.03547716,0.012051074,0.16696285,0.0024016174,0.0014238621,0.00077389576,0.06798563,0.010192944,0.70273095],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980921,0.00019464966,0.00017709656,0.00037194724,0.0010218497,0.00014244202],"domain_scores_gemma":[0.9977494,0.00027871638,0.0000611106,0.0009920105,0.0008152751,0.0001035678],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013925425,0.0012622494,0.0011867355,0.005579441,0.001401756,0.0065182857,0.0026889967,0.00073622924,0.27529976],"category_scores_gemma":[0.0049930396,0.00074596715,0.0011014605,0.0062675024,0.0007545139,0.005856403,0.0031035375,0.0016210297,0.22288176],"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":[0.000103327344,0.00008526292,0.0001829272,0.0007414948,0.000017284141,0.00013384924,0.00016536246,0.0003857559,0.0063920757,0.052464027,0.43849078,0.50083786],"study_design_scores_gemma":[0.000011894896,0.000021939259,0.0001905346,0.00010859462,0.0000130353255,0.0002441858,0.000068227244,0.00054266973,0.0043508145,0.010737957,0.983696,0.000014112759],"about_ca_topic_score_codex":0.0010360754,"about_ca_topic_score_gemma":0.000999716,"teacher_disagreement_score":0.27529976,"about_ca_system_score_codex":0.001167649,"about_ca_system_score_gemma":0.001662617,"threshold_uncertainty_score":0.9209694},"labels":[],"label_agreement":null},{"id":"W4254154584","doi":"10.1007/978-1-4939-7131-2_100937","title":"Query Model","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Database Systems and Queries","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 Calgary","funders":"","keywords":"Computer science","score_opus":0.02852788509428963,"score_gpt":0.23886690965853727,"score_spread":0.21033902456424763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4254154584","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":[0.004262369,0.0020840454,0.8069071,0.005792574,0.0009860588,0.0011913212,0.008288697,0.006116658,0.16437118],"genre_scores_gemma":[0.16263902,0.0063596666,0.4948476,0.0051878965,0.0017663037,0.0022420776,0.031259704,0.0025664824,0.29313117],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9942206,0.0008034093,0.0004559361,0.0012313679,0.002884376,0.0004041975],"domain_scores_gemma":[0.9969312,0.0006455325,0.000103478924,0.0011339413,0.0010275999,0.00015819981],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029354028,0.0012267838,0.0011115914,0.002306467,0.0012828399,0.007848115,0.0039076027,0.0021247054,0.04005043],"category_scores_gemma":[0.00856596,0.0006241752,0.001629495,0.0030993342,0.0014587542,0.010757467,0.0030141298,0.0033137312,0.03505757],"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":[0.00011462718,0.00012201535,0.0002519561,0.0003407026,0.000029631101,0.00011507781,0.0001446567,0.0053741033,0.0029175,0.8361278,0.07684392,0.077617936],"study_design_scores_gemma":[0.00007645812,0.00010311127,0.00018306209,0.00016091806,0.00008268939,0.0006032376,0.00014013241,0.08264141,0.005404387,0.4636315,0.4469124,0.000060643455],"about_ca_topic_score_codex":0.0036770222,"about_ca_topic_score_gemma":0.0022813862,"teacher_disagreement_score":0.04005043,"about_ca_system_score_codex":0.0024464012,"about_ca_system_score_gemma":0.0034938282,"threshold_uncertainty_score":0.133982},"labels":[],"label_agreement":null},{"id":"W4254188198","doi":"10.1007/978-3-030-26253-2_6","title":"Data Replication","year":2019,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Replication (statistics); Computer science; Biology; Virology","score_opus":0.07479275522507631,"score_gpt":0.2929061313876551,"score_spread":0.21811337616257878,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4254188198","genre_codex":"other","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":[0.006168377,0.0065276553,0.46991414,0.0042347317,0.005258945,0.0011893414,0.0031960374,0.016586188,0.48692456],"genre_scores_gemma":[0.082612544,0.0059144585,0.23807698,0.001821678,0.0017296206,0.00080254336,0.005702372,0.0030929316,0.66024685],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9982705,0.00023326802,0.000116248404,0.00044266408,0.0008359467,0.00010130001],"domain_scores_gemma":[0.99540627,0.00054191827,0.00011975646,0.0026951246,0.0010721401,0.00016486863],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019030791,0.00089617557,0.00075330184,0.0016173897,0.0016665268,0.004103287,0.0025138848,0.0009428697,0.060232706],"category_scores_gemma":[0.0059542065,0.00073007116,0.0008078622,0.002874524,0.0008284082,0.005370321,0.0029837424,0.0016961205,0.03762994],"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":[0.00015913267,0.00009089453,0.00043778334,0.0005313602,0.00003190369,0.00011810916,0.00039787818,0.0015777388,0.009074041,0.18101041,0.23212071,0.5744501],"study_design_scores_gemma":[0.000028025695,0.00006288636,0.00024340383,0.00011019483,0.000025721232,0.00045980854,0.00012827471,0.005611156,0.009788755,0.057300765,0.9262097,0.00003129621],"about_ca_topic_score_codex":0.0017802082,"about_ca_topic_score_gemma":0.0014566144,"teacher_disagreement_score":0.060232706,"about_ca_system_score_codex":0.0011480522,"about_ca_system_score_gemma":0.0023530617,"threshold_uncertainty_score":0.20149845},"labels":[],"label_agreement":null},{"id":"W4254217685","doi":"10.1007/978-0-387-39940-9_3387","title":"Query Optimization for Multidimensional Systems","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Query optimization; Computer science; Information retrieval","score_opus":0.016395880431880477,"score_gpt":0.24094776928066483,"score_spread":0.22455188884878435,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4254217685","genre_codex":"methods","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":[0.0027247756,0.0078024142,0.97958344,0.0005683384,0.00010105475,0.000069882386,0.0002623689,0.0010119135,0.007875783],"genre_scores_gemma":[0.14700213,0.010752272,0.8159828,0.00045602815,0.0006368818,0.00042776967,0.0022081945,0.0010645785,0.02146935],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99576205,0.0010284809,0.00034439482,0.00044781753,0.0021921243,0.00022519632],"domain_scores_gemma":[0.9981688,0.000900124,0.00008344045,0.0004903413,0.00030851614,0.000048732527],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020576762,0.0013305588,0.002332437,0.0011776036,0.0006842988,0.0037168215,0.002121082,0.0008336087,0.009205072],"category_scores_gemma":[0.0060274485,0.00071387156,0.0010088884,0.0038663468,0.001018995,0.003902374,0.002667335,0.0023238268,0.0028403588],"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":[0.00024810625,0.00015412866,0.0007121931,0.0013138646,0.00017646654,0.00013767798,0.00028746622,0.107375234,0.007971383,0.25537103,0.06331043,0.56294197],"study_design_scores_gemma":[0.000056154753,0.000088227804,0.0004593148,0.00009962514,0.00007249113,0.00037644198,0.00012262097,0.6794558,0.0063474234,0.25221446,0.06065781,0.000049669663],"about_ca_topic_score_codex":0.0018197473,"about_ca_topic_score_gemma":0.0016661992,"teacher_disagreement_score":0.009205072,"about_ca_system_score_codex":0.0013549416,"about_ca_system_score_gemma":0.00094436534,"threshold_uncertainty_score":0.030794024},"labels":[],"label_agreement":null},{"id":"W4254658414","doi":"10.1090/fic/058/02","title":"Schoof’s point counting algorithm","year":2010,"lang":"en","type":"other","venue":"","topic":"Advanced Database Systems and Queries","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 Toronto","funders":"","keywords":"Computer science; Point (geometry); Algorithm; Mathematics; Geometry","score_opus":0.006925289132610386,"score_gpt":0.2328207926076977,"score_spread":0.2258955034750873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4254658414","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":[0.0055534556,0.00072106614,0.94075406,0.00069682614,0.00044574376,0.00018112833,0.0007553754,0.004394126,0.046498206],"genre_scores_gemma":[0.08524453,0.0010031064,0.8412383,0.00049188954,0.000445858,0.00028670236,0.0034451478,0.0028116747,0.06503279],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9967816,0.00051866454,0.0002473923,0.0006548586,0.001463013,0.00033449807],"domain_scores_gemma":[0.9957249,0.00110086,0.00010372944,0.0016423342,0.0012968747,0.00013127008],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019708974,0.0017690355,0.0018747038,0.0058250576,0.002389442,0.00413282,0.0036797076,0.00241572,0.049932774],"category_scores_gemma":[0.012267784,0.00089169625,0.0021505328,0.008698049,0.001580043,0.007052136,0.0039596907,0.0032735346,0.029335264],"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":[0.0002945963,0.00011701871,0.0005956607,0.00020867189,0.000063692634,0.00006275459,0.00010986729,0.013466523,0.0030233336,0.24313843,0.070869654,0.6680498],"study_design_scores_gemma":[0.00017758267,0.0001059307,0.00054082007,0.0001276907,0.00011306987,0.00050643244,0.00007443595,0.25870565,0.013565704,0.57188684,0.15407702,0.00011877351],"about_ca_topic_score_codex":0.0033386012,"about_ca_topic_score_gemma":0.0033555848,"teacher_disagreement_score":0.049932774,"about_ca_system_score_codex":0.0013803961,"about_ca_system_score_gemma":0.0026185426,"threshold_uncertainty_score":0.16704178},"labels":[],"label_agreement":null},{"id":"W4254798139","doi":"10.1007/978-3-030-26253-2_1","title":"Introduction","year":2019,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Computer science; sort; Scope (computer science); Distributed computing; Distributed database; Distributed Computing Environment; The Internet; Mainstream; Database; World Wide Web","score_opus":0.011363879345130225,"score_gpt":0.21093855771417724,"score_spread":0.19957467836904702,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4254798139","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00026240997,0.00250047,0.005880791,0.002123097,0.0038659507,0.0001237267,0.0016969937,0.0008855907,0.98266095],"genre_scores_gemma":[0.00083084684,0.001442419,0.0014762772,0.00077292364,0.0006018405,0.00005582528,0.0011370954,0.00021987205,0.9934628],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9994567,0.000047958107,0.00001767979,0.0001108751,0.00031284697,0.00005398568],"domain_scores_gemma":[0.99925584,0.00010136683,0.000025603604,0.000112135036,0.0003715361,0.00013351308],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005639467,0.0009302798,0.0005241058,0.0018878165,0.001242953,0.0039718132,0.0015576407,0.0015083201,0.5705429],"category_scores_gemma":[0.0020246308,0.00034922615,0.0005204039,0.0018457877,0.0005732775,0.003062648,0.0021922176,0.0017041279,0.49989387],"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":[0.000018614322,0.000030575866,0.00006249677,0.00014376965,0.0000016928898,0.0000327596,0.00007773844,0.00011142327,0.0004179437,0.032182973,0.7855324,0.1813876],"study_design_scores_gemma":[0.0000012328038,0.0000046073037,0.00004325572,0.000042633947,7.402846e-7,0.000025055437,0.000019238245,0.000020858017,0.00007300005,0.0030418825,0.99672556,0.000001924774],"about_ca_topic_score_codex":0.002296609,"about_ca_topic_score_gemma":0.0035980924,"teacher_disagreement_score":0.5705429,"about_ca_system_score_codex":0.0011797145,"about_ca_system_score_gemma":0.0017459166,"threshold_uncertainty_score":0.6125685},"labels":[],"label_agreement":null},{"id":"W4254852241","doi":"10.1145/872858.872862","title":"TIMBER","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; XML database; Streaming XML; Relational database; XML Schema Editor; Efficient XML Interchange; XML; XML validation; XML Encryption; Database; XPath; Document Structure Description; Information retrieval; Set (abstract data type); XML Schema (W3C); XML Signature; Programming language; World Wide Web","score_opus":0.009750939769700621,"score_gpt":0.2239954742367677,"score_spread":0.21424453446706707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4254852241","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003759963,0.002672447,0.09672111,0.0034512868,0.0019538193,0.00043430898,0.026599994,0.07198195,0.79242516],"genre_scores_gemma":[0.022082262,0.0030080536,0.09115864,0.0026672103,0.0007297239,0.00031629985,0.06697035,0.019292079,0.7937754],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.998733,0.000109404755,0.00009202293,0.00023723896,0.0007132399,0.00011505544],"domain_scores_gemma":[0.9982204,0.00021718048,0.00008273121,0.00054100953,0.0006917038,0.00024695796],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0011114473,0.000780582,0.0006691652,0.0022602365,0.0015823127,0.004708806,0.0022708199,0.0016164051,0.27757478],"category_scores_gemma":[0.0029159482,0.00068124675,0.00064642355,0.0032671308,0.0006227695,0.00612546,0.0032971357,0.0016838242,0.2469548],"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":[0.00016619137,0.00006251952,0.00054844696,0.00030356247,0.000017327879,0.00023256615,0.00025591307,0.00034826752,0.0050605475,0.05455037,0.7135612,0.224893],"study_design_scores_gemma":[0.000010868489,0.000015762349,0.00022516972,0.00003239058,0.0000054198485,0.00013885618,0.00003956703,0.0005585428,0.00114614,0.006888738,0.990926,0.000012576767],"about_ca_topic_score_codex":0.0041283616,"about_ca_topic_score_gemma":0.0068855574,"teacher_disagreement_score":0.7224252,"about_ca_system_score_codex":0.0008417652,"about_ca_system_score_gemma":0.0014808323,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W4255585933","doi":"10.1007/978-0-387-39940-9_4010","title":"Web Resource Discovery","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Web resource; Resource (disambiguation); World Wide Web; Computer science; Computer network","score_opus":0.012432443637746872,"score_gpt":0.22627616681926968,"score_spread":0.2138437231815228,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4255585933","genre_codex":"other","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003884479,0.014629542,0.35545412,0.0039534816,0.0015823006,0.00084718363,0.009546204,0.027906284,0.5821965],"genre_scores_gemma":[0.022183966,0.018189091,0.25944933,0.0016823382,0.0006317654,0.00036102402,0.029207109,0.0040430385,0.66425234],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99893993,0.000101762256,0.000073842166,0.00021258972,0.00060099224,0.00007091972],"domain_scores_gemma":[0.99888724,0.00030544467,0.00003964831,0.00041567456,0.0002577681,0.00009416055],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010430515,0.0010925006,0.0011681526,0.0054907924,0.0012103335,0.005425994,0.0021520313,0.0010979013,0.06304466],"category_scores_gemma":[0.0029259862,0.00090935914,0.0009036392,0.0064371354,0.00061912753,0.0061702523,0.0026273958,0.0016039403,0.075166844],"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":[0.0000421132,0.000104156956,0.00026728565,0.0005465862,0.000033091586,0.0001726279,0.00014101953,0.00055686187,0.004580767,0.04927147,0.32514414,0.61913985],"study_design_scores_gemma":[0.0000072076327,0.000012853822,0.00031657337,0.00019437619,0.000024439585,0.00056482846,0.00007071464,0.003905198,0.0044836793,0.02736902,0.9630234,0.000027574084],"about_ca_topic_score_codex":0.002406478,"about_ca_topic_score_gemma":0.004196234,"teacher_disagreement_score":0.06304466,"about_ca_system_score_codex":0.0010051898,"about_ca_system_score_gemma":0.001571716,"threshold_uncertainty_score":0.21090543},"labels":[],"label_agreement":null},{"id":"W4255601651","doi":"10.1007/978-1-4939-7131-2_101287","title":"Subgraph Isomorphic Queries","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Database Systems and Queries","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 Calgary","funders":"","keywords":"Computer science; Subgraph isomorphism problem; Information retrieval; Theoretical computer science; Graph","score_opus":0.01875992630334525,"score_gpt":0.22083429273410404,"score_spread":0.2020743664307588,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4255601651","genre_codex":"other","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":[0.016837778,0.0047175675,0.4206709,0.0039386507,0.0012688132,0.000351723,0.004808187,0.0068207053,0.5405857],"genre_scores_gemma":[0.30041534,0.011159319,0.28941503,0.0039794976,0.0020183378,0.0005197911,0.033510633,0.0057940846,0.35318792],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9985078,0.00023328853,0.00006956018,0.00035174427,0.0006933833,0.00014431207],"domain_scores_gemma":[0.99884975,0.00035273272,0.000035325484,0.00050036155,0.00020239083,0.00005939003],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005325437,0.000959719,0.00079863897,0.001637136,0.0008382234,0.0027083317,0.0014742379,0.00085141347,0.038173653],"category_scores_gemma":[0.003162927,0.00044460007,0.00089250965,0.004037694,0.0010834917,0.007825346,0.0029079847,0.002370263,0.013558304],"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":[0.00006548316,0.0000683888,0.00023868214,0.00030415508,0.000029904531,0.0000855865,0.0002904217,0.0030981612,0.0026062971,0.5667507,0.17016065,0.25630155],"study_design_scores_gemma":[0.000016870446,0.000022876597,0.00023138987,0.00007765283,0.00003715523,0.00039630354,0.000139346,0.010002608,0.003232941,0.64718115,0.3386394,0.000022243516],"about_ca_topic_score_codex":0.0018817398,"about_ca_topic_score_gemma":0.002123828,"teacher_disagreement_score":0.038173653,"about_ca_system_score_codex":0.0015006806,"about_ca_system_score_gemma":0.0010684131,"threshold_uncertainty_score":0.12770355},"labels":[],"label_agreement":null},{"id":"W4255656012","doi":"10.1007/978-1-4939-7131-2_101448","title":"W3C XML Query Language","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Database Systems and Queries","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 Calgary","funders":"","keywords":"Computer science; XML; Programming language; Information retrieval; Database; World Wide Web","score_opus":0.0134700343315286,"score_gpt":0.2381551514119655,"score_spread":0.2246851170804369,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4255656012","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":[0.0012260905,0.0026449745,0.7897344,0.0029895455,0.0012024974,0.00042647583,0.011224591,0.02947011,0.1610813],"genre_scores_gemma":[0.016667362,0.00775855,0.5040508,0.0046066805,0.000724898,0.001032899,0.053723816,0.029229857,0.38220522],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99795204,0.00023125205,0.00021418446,0.00023188564,0.0012232987,0.00014737692],"domain_scores_gemma":[0.9987908,0.0003205495,0.00003898279,0.0002873209,0.0005054362,0.000056995243],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018857215,0.0016444502,0.0012557685,0.0028722999,0.001131059,0.004838891,0.0032408175,0.0016653531,0.05525539],"category_scores_gemma":[0.0041178865,0.0010375896,0.0013968599,0.0061308937,0.00088108465,0.0058500464,0.0024774063,0.003727298,0.05146207],"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":[0.000074774915,0.000043891385,0.00008722221,0.00071520265,0.00003112045,0.00011819275,0.00025883882,0.001781283,0.00532659,0.17770451,0.5734735,0.24038482],"study_design_scores_gemma":[0.000017613127,0.00000985938,0.000068711815,0.00014754578,0.000020994525,0.00020909276,0.000040569943,0.006043083,0.0038447797,0.041819263,0.9477431,0.00003548488],"about_ca_topic_score_codex":0.013465057,"about_ca_topic_score_gemma":0.008875612,"teacher_disagreement_score":0.05525539,"about_ca_system_score_codex":0.0017606163,"about_ca_system_score_gemma":0.00317881,"threshold_uncertainty_score":0.18484765},"labels":[],"label_agreement":null},{"id":"W4285407558","doi":"10.1109/cwit55308.2022.9817661","title":"17th Canadian Workshop on Information Theory","year":2022,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Data science","score_opus":0.009714776102892458,"score_gpt":0.21619692540304053,"score_spread":0.20648214930014808,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285407558","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005455801,0.15871285,0.1943185,0.07170814,0.03531075,0.00023257414,0.0071638324,0.0022566207,0.524841],"genre_scores_gemma":[0.10071398,0.08408847,0.10571714,0.004615218,0.0074324515,0.00024875766,0.0058910954,0.0017911165,0.68950164],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9959395,0.00075423834,0.00018728757,0.00053597754,0.0019607411,0.0006223802],"domain_scores_gemma":[0.99449414,0.0013454861,0.000087249384,0.0011212925,0.0024335661,0.00051821704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004870742,0.0018080977,0.0028883845,0.005592677,0.0046490203,0.011475622,0.004209803,0.0023614191,0.07597765],"category_scores_gemma":[0.0072394297,0.0013472909,0.0022751063,0.0079548685,0.0055156914,0.0075153955,0.003648149,0.0047031976,0.013315064],"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":[0.0001343148,0.000063813066,0.00037466304,0.00042148968,0.000074850184,0.00009913835,0.00032682353,0.0025513945,0.0006038586,0.33150727,0.50225216,0.16159016],"study_design_scores_gemma":[0.000022498887,0.000015261667,0.0005447868,0.00034403606,0.000054104672,0.00006922476,0.00020378447,0.0052446453,0.0009390831,0.16119714,0.8313202,0.000045308137],"about_ca_topic_score_codex":0.46848688,"about_ca_topic_score_gemma":0.48220557,"teacher_disagreement_score":0.46848688,"about_ca_system_score_codex":0.03431473,"about_ca_system_score_gemma":0.030237503,"threshold_uncertainty_score":0.93152},"labels":[],"label_agreement":null},{"id":"W4287284732","doi":"10.5281/zenodo.4571616","title":"Precisely and Persistently Identifying and Citing Arbitrary Subsets of Dynamic Data","year":2021,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Österreichische Forschungsförderungsgesellschaft; European Commission; Canarie; Rural Development Administration; National Science Foundation","keywords":"Computer science; Mathematics","score_opus":0.06710193405807836,"score_gpt":0.2758524705499475,"score_spread":0.20875053649186914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4287284732","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":[0.02680802,0.005790425,0.8316667,0.03664755,0.0040208907,0.0027266382,0.02331548,0.04797593,0.021048386],"genre_scores_gemma":[0.074310705,0.0052742446,0.8409697,0.004966242,0.0017423623,0.0016362892,0.045419656,0.011531252,0.014149509],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.93013567,0.0185479,0.0138647165,0.01127972,0.024042286,0.0021297086],"domain_scores_gemma":[0.5497432,0.09631709,0.022023596,0.26665187,0.05856982,0.006694505],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.10864054,0.0017127425,0.0037280668,0.024543388,0.0068256906,0.030401163,0.007842914,0.004730953,0.0059272135],"category_scores_gemma":[0.30022302,0.0029185698,0.002870655,0.023123577,0.005864935,0.060287587,0.024235966,0.008896891,0.011701537],"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":[0.00087058946,0.00032536002,0.026763674,0.002919748,0.0005035028,0.0005284364,0.01093101,0.0027545444,0.015095523,0.11921705,0.19821844,0.62187207],"study_design_scores_gemma":[0.00012317156,0.00017047042,0.0068946523,0.002022309,0.00028554574,0.0007304995,0.0048655886,0.009461294,0.020771721,0.10592982,0.8482818,0.0004630423],"about_ca_topic_score_codex":0.0068484168,"about_ca_topic_score_gemma":0.008065074,"teacher_disagreement_score":0.9695988,"about_ca_system_score_codex":0.0034857013,"about_ca_system_score_gemma":0.015138333,"threshold_uncertainty_score":0.57455295},"labels":[],"label_agreement":null},{"id":"W4289921636","doi":"10.4000/jtei.3874","title":"Getting Along with Relational Databases","year":2021,"lang":"en","type":"article","venue":"Journal of the Text Encoding Initiative","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Metadata; Computer science; XML database; XML; Relational database; Information retrieval; Database; Relational database management system; World Wide Web","score_opus":0.054529919931670806,"score_gpt":0.2771809470700565,"score_spread":0.22265102713838572,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4289921636","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":[0.0015726384,0.010355132,0.8709724,0.02503578,0.0036589203,0.0004896895,0.004619126,0.029790148,0.053506114],"genre_scores_gemma":[0.03345331,0.018185407,0.86755186,0.012198755,0.0049166437,0.0006233292,0.015507178,0.009711774,0.037851784],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.95384914,0.01271262,0.008209474,0.0059421267,0.017755609,0.001531125],"domain_scores_gemma":[0.9221316,0.020304166,0.0029205435,0.033136178,0.018205477,0.0033020119],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.033202868,0.0018788859,0.0026608442,0.0071580186,0.004205228,0.031524587,0.008641947,0.004169844,0.035535652],"category_scores_gemma":[0.08666973,0.0026900442,0.0038404106,0.01574019,0.004321154,0.055269245,0.016358042,0.011672375,0.041017532],"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":[0.00015020295,0.00009084917,0.0013545159,0.0009998363,0.00018997972,0.00042057596,0.0017942699,0.0019040335,0.0020374728,0.4909713,0.20266101,0.29742604],"study_design_scores_gemma":[0.000024646031,0.000028624543,0.00021515899,0.00035268426,0.00004640412,0.0003312369,0.00043700574,0.0028006602,0.0014218754,0.20471364,0.7895566,0.000071383285],"about_ca_topic_score_codex":0.0056518363,"about_ca_topic_score_gemma":0.0024772603,"teacher_disagreement_score":0.035535652,"about_ca_system_score_codex":0.0031503937,"about_ca_system_score_gemma":0.0059903357,"threshold_uncertainty_score":0.17559564},"labels":[],"label_agreement":null},{"id":"W4292830130","doi":"10.23919/annsim55834.2022.9859309","title":"Boolean Logical Operator Driven Selective Data Filtering For Large Datasets","year":2022,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Operator (biology); Set (abstract data type); Data mining; Conjunction (astronomy); SPARK (programming language); Information retrieval; Data set; Bitwise operation; Boolean function; Boolean expression; Artificial intelligence; Algorithm; Programming language","score_opus":0.051549378165809484,"score_gpt":0.31101748689580644,"score_spread":0.2594681087299969,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4292830130","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":[0.057580058,0.0004768882,0.9335226,0.00069678936,0.0000799926,0.00024592926,0.00069108536,0.0039300676,0.002776618],"genre_scores_gemma":[0.47895822,0.0005043462,0.51383066,0.00055713736,0.00017493246,0.00029636789,0.0018728286,0.00021998225,0.0035855186],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99736965,0.00050061836,0.00021196727,0.00040308767,0.0012551647,0.00025942703],"domain_scores_gemma":[0.993608,0.003569025,0.0005268048,0.0010388495,0.0010639549,0.00019331058],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035211022,0.0005201262,0.0009736045,0.0014827797,0.0009353029,0.0018306464,0.001292253,0.0005493213,0.0026247443],"category_scores_gemma":[0.0072370586,0.00028300265,0.00092420983,0.0023366248,0.00092851836,0.0025733025,0.0011628103,0.0009175945,0.00066296814],"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":[0.002303967,0.0004935183,0.011527908,0.00096657156,0.00025325964,0.00093355076,0.00062915514,0.06579903,0.13441207,0.063233845,0.018755814,0.7006913],"study_design_scores_gemma":[0.00015413758,0.00043721567,0.003834953,0.00004587989,0.00007818802,0.0008002926,0.00041911745,0.83094877,0.081259884,0.06241007,0.019558564,0.00005297969],"about_ca_topic_score_codex":0.0036639313,"about_ca_topic_score_gemma":0.0071377754,"teacher_disagreement_score":0.0036639313,"about_ca_system_score_codex":0.0011127659,"about_ca_system_score_gemma":0.0020543116,"threshold_uncertainty_score":0.018621564},"labels":[],"label_agreement":null},{"id":"W4293657573","doi":"10.1007/978-3-031-15740-0_16","title":"Querying Temporal Anomalies in Healthcare Information Systems and Beyond","year":2022,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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":"Université de Sherbrooke","funders":"","keywords":"Computer science; Tuple; Temporal database; Redundancy (engineering); Relation (database); Operator (biology); Data redundancy; Information retrieval; Contradiction; Relational database; Data mining; Database; Mathematics","score_opus":0.014082681555149603,"score_gpt":0.2426607450001257,"score_spread":0.22857806344497608,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293657573","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":[0.051245462,0.03083112,0.86780137,0.011174128,0.0012513933,0.0001269327,0.0040725055,0.007310267,0.02618679],"genre_scores_gemma":[0.5567969,0.016509129,0.40396163,0.0014062551,0.0010852859,0.00008866652,0.0055361963,0.00067944644,0.013936498],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99843055,0.00030272867,0.00018272683,0.00027670426,0.00071409094,0.00009314519],"domain_scores_gemma":[0.9969901,0.0021259168,0.00017729284,0.00034737756,0.0002724297,0.00008690926],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001990618,0.0005866619,0.0010165307,0.002217761,0.000421009,0.0040789824,0.0013019659,0.0011421122,0.0034880985],"category_scores_gemma":[0.008411995,0.0004494103,0.00072661217,0.0038351566,0.0010824667,0.007895868,0.0015760334,0.0017713087,0.0007642203],"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":[0.0002857505,0.000088019944,0.0054037953,0.0008318645,0.00011398223,0.00083752186,0.001155649,0.037073236,0.0090258615,0.387042,0.039829917,0.5183124],"study_design_scores_gemma":[0.000020841931,0.000062822044,0.0018035418,0.00022187886,0.00008395222,0.0015685156,0.000647819,0.3144332,0.008335063,0.55842227,0.11434059,0.000059465616],"about_ca_topic_score_codex":0.0035442882,"about_ca_topic_score_gemma":0.0028245167,"teacher_disagreement_score":0.0040789824,"about_ca_system_score_codex":0.0012888286,"about_ca_system_score_gemma":0.00076854223,"threshold_uncertainty_score":0.011668861},"labels":[],"label_agreement":null},{"id":"W4294805134","doi":"10.5206/mt.v2i1.14469","title":"Substituting Units into Multivariate Power Series","year":2022,"lang":"en","type":"article","venue":"Maple Transactions","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Series (stratigraphy); Formal power series; Maple; Unit (ring theory); Multivariate statistics; Power (physics); Computer science; Power series; Mathematics; Mathematics education; Machine learning","score_opus":0.016557306488486623,"score_gpt":0.23402007360846838,"score_spread":0.21746276711998175,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294805134","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":[0.011008688,0.0007635617,0.9571883,0.0006399552,0.0010433691,0.000035001052,0.00021684772,0.0014929438,0.027611287],"genre_scores_gemma":[0.27352184,0.002365071,0.68144757,0.0012241974,0.0011931699,0.00029894948,0.0005663412,0.0056284918,0.03375428],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9970438,0.001136342,0.00021125053,0.0004262044,0.0009912427,0.00019120329],"domain_scores_gemma":[0.99723935,0.0011360305,0.00023916569,0.00075066695,0.0005269182,0.000107852975],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003331928,0.0013567758,0.0007878603,0.001544858,0.0007033186,0.0026950727,0.0017008537,0.00073204737,0.016154988],"category_scores_gemma":[0.0120312,0.0004552458,0.0010850814,0.00285934,0.0020932965,0.006263663,0.0028180534,0.0025012481,0.0060749534],"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":[0.000042497784,0.000017134473,0.00023658939,0.00007830058,0.000014981371,0.00016244927,0.0002524974,0.0026584088,0.0018755248,0.94882435,0.0046444656,0.04119291],"study_design_scores_gemma":[0.0000239922,0.000059512455,0.0002147766,0.00008417819,0.000026073456,0.0004099701,0.00014226185,0.033657126,0.008413862,0.7794988,0.17742497,0.000044477692],"about_ca_topic_score_codex":0.00051191647,"about_ca_topic_score_gemma":0.00051927863,"teacher_disagreement_score":0.016154988,"about_ca_system_score_codex":0.00059828145,"about_ca_system_score_gemma":0.00070307404,"threshold_uncertainty_score":0.05404377},"labels":[],"label_agreement":null},{"id":"W4297283065","doi":"10.1007/978-3-031-17718-7_7","title":"Performance Evaluation of Embedded Time Series Indexes Using Bitmaps, Partitioning, and Trees","year":2022,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Advanced Database Systems and Queries","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 British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Search engine indexing; Bitmap; Partition (number theory); Index (typography); Hash function; Database index; Data structure; Range query (database); Series (stratigraphy)","score_opus":0.056605889095519786,"score_gpt":0.3088618256095822,"score_spread":0.2522559365140624,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4297283065","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":[0.861922,0.008084816,0.10022895,0.00037314635,0.00042733626,0.00015829978,0.0020940427,0.0120224785,0.014688888],"genre_scores_gemma":[0.92161125,0.0014982361,0.069751404,0.00005560446,0.00010725464,0.000053098946,0.0024070155,0.00046198835,0.0040541277],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99786854,0.0006115134,0.00022386739,0.00024174555,0.0008621928,0.00019208787],"domain_scores_gemma":[0.99196225,0.0052865124,0.00035629826,0.0007820757,0.0013175728,0.0002953588],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019024886,0.0011543042,0.0013794269,0.0015940974,0.0005554352,0.002145835,0.0015487256,0.00063867203,0.005231826],"category_scores_gemma":[0.00751775,0.0003295675,0.0003243947,0.0047241813,0.00042901788,0.0030152646,0.0007930218,0.00042602062,0.00074358843],"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":[0.010985068,0.0010193664,0.008127218,0.001018418,0.00041937054,0.00028071876,0.0003267566,0.3596832,0.03646237,0.011260644,0.020022707,0.5503942],"study_design_scores_gemma":[0.00021877598,0.0009934604,0.0025219573,0.000024600706,0.0001018323,0.00015804755,0.000113958595,0.9677798,0.023828957,0.0020171914,0.002201792,0.00003965817],"about_ca_topic_score_codex":0.0076246117,"about_ca_topic_score_gemma":0.0048114965,"teacher_disagreement_score":0.0076246117,"about_ca_system_score_codex":0.0013607168,"about_ca_system_score_gemma":0.0010381923,"threshold_uncertainty_score":0.017502189},"labels":[],"label_agreement":null},{"id":"W4297570618","doi":"","title":"Exploiting spatial vagueness in spatial OLAP: Towards a new hybrid risk-aware design approach","year":2013,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Database Systems and Queries","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":"Université Laval","funders":"","keywords":"Online analytical processing; Computer science; Vagueness; Spatial analysis; Data mining; Artificial intelligence; Data warehouse; Fuzzy logic; Geography; Remote sensing","score_opus":0.026156176493958336,"score_gpt":0.22952002120099524,"score_spread":0.2033638447070369,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4297570618","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":[0.0046166526,0.000080128324,0.9941216,0.00014962492,0.000009906996,0.000032370444,0.000024263498,0.00020130354,0.0007641339],"genre_scores_gemma":[0.21905039,0.00022169937,0.7784727,0.00014874968,0.00003118284,0.00011122047,0.000107519714,0.00022277859,0.0016336364],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9935423,0.0018462345,0.0006036201,0.0006795873,0.002984596,0.00034370215],"domain_scores_gemma":[0.9899171,0.0032880425,0.001061684,0.002880251,0.0025277075,0.0003251445],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0070019616,0.0010502283,0.0010273953,0.0012114322,0.00071900757,0.004441912,0.0034059272,0.0012944278,0.0022351916],"category_scores_gemma":[0.013268481,0.0013196693,0.0017695515,0.0012109517,0.0014921302,0.007215651,0.004160952,0.0023321186,0.0004438649],"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":[0.00027912078,0.00028513058,0.0056247883,0.00083377765,0.00047511343,0.0005196738,0.0019141914,0.44982007,0.03220181,0.2721104,0.00255094,0.23338495],"study_design_scores_gemma":[0.000020176229,0.000108275606,0.00039466633,0.00009645546,0.00019039496,0.00023557032,0.00028178646,0.850784,0.0120081175,0.12609449,0.009729573,0.000056528243],"about_ca_topic_score_codex":0.0015602569,"about_ca_topic_score_gemma":0.0030398648,"teacher_disagreement_score":0.0070019616,"about_ca_system_score_codex":0.0009857969,"about_ca_system_score_gemma":0.002321343,"threshold_uncertainty_score":0.0370304},"labels":[],"label_agreement":null},{"id":"W4298392820","doi":"","title":"A new design method for managing spatial vagueness in classical relational Spatial OLAP Architectures","year":2014,"lang":"en","type":"other","venue":"","topic":"Advanced Database Systems and Queries","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 Laval","funders":"","keywords":"Online analytical processing; Computer science; Vagueness; Relational database; Data mining; Database; Data warehouse; Artificial intelligence; Fuzzy logic","score_opus":0.026094142781995254,"score_gpt":0.29067751844355566,"score_spread":0.2645833756615604,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4298392820","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":[0.0021160184,0.0000566733,0.99553776,0.000118606746,0.000044654545,0.00008145715,0.00003239842,0.00079453835,0.0012179465],"genre_scores_gemma":[0.051347457,0.00010153241,0.9416535,0.00018001863,0.00005357821,0.00024496616,0.000117522155,0.00032448876,0.005976979],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9968843,0.0005172228,0.00040428442,0.00046259782,0.0015171159,0.00021448359],"domain_scores_gemma":[0.9959759,0.00084820366,0.00027156642,0.0013672464,0.0013574489,0.00017967564],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033221247,0.000664454,0.00067744567,0.0011907308,0.0011459799,0.0039839917,0.0030998485,0.0012725125,0.0054633096],"category_scores_gemma":[0.0066441647,0.0008919287,0.00088970095,0.0012394782,0.001916729,0.0056094723,0.0029276866,0.0022009853,0.0012316504],"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":[0.00028307983,0.00029287278,0.0017473788,0.0006217271,0.00013816124,0.00031861276,0.0018561279,0.03367383,0.04597941,0.45156124,0.01459198,0.44893563],"study_design_scores_gemma":[0.00015155012,0.00029047206,0.00046354858,0.00017307683,0.00027557838,0.0006787577,0.00058253773,0.5895831,0.060667507,0.21229899,0.1346563,0.00017872216],"about_ca_topic_score_codex":0.0021821733,"about_ca_topic_score_gemma":0.004926616,"teacher_disagreement_score":0.0054633096,"about_ca_system_score_codex":0.0011099867,"about_ca_system_score_gemma":0.002393551,"threshold_uncertainty_score":0.018276572},"labels":[],"label_agreement":null},{"id":"W4299610662","doi":"10.1007/978-3-031-01881-7_6","title":"Updating Data","year":2011,"lang":"en","type":"book-chapter","venue":"Synthesis lectures on data management","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Computer science; Tuple; Schema (genetic algorithms); Relation (database); Consistency (knowledge bases); Data integrity; Set (abstract data type); Theoretical computer science; Programming language; Database; Information retrieval; Mathematics; Artificial intelligence","score_opus":0.10257417112385193,"score_gpt":0.2771190980116017,"score_spread":0.1745449268877498,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4299610662","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":[0.00948101,0.0036185596,0.5682369,0.0050800126,0.0054676724,0.00081197335,0.011966841,0.0430012,0.3523358],"genre_scores_gemma":[0.082209975,0.0049704695,0.3021552,0.0035727634,0.0015351697,0.00046783432,0.021577623,0.010435903,0.57307506],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980679,0.0002454557,0.00015250912,0.0004760484,0.0009367537,0.000121316356],"domain_scores_gemma":[0.9957035,0.0005655862,0.000120394885,0.0027779273,0.0007194175,0.00011319181],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021172764,0.0011966496,0.00081758096,0.0021698538,0.0009228508,0.0044118348,0.0024819225,0.0007660369,0.06835495],"category_scores_gemma":[0.008005534,0.0007378707,0.0008567587,0.002785985,0.0009253368,0.0066843894,0.0032261317,0.0019700965,0.040168546],"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":[0.00013583033,0.00006817705,0.00082777586,0.00043341692,0.000041678813,0.00013049066,0.00048121077,0.0013364071,0.007005145,0.07833052,0.23447455,0.67673475],"study_design_scores_gemma":[0.000017211221,0.000025939984,0.00031009034,0.000089673675,0.000053534754,0.00025506242,0.00010171956,0.003365596,0.014519581,0.024843771,0.9563912,0.00002656952],"about_ca_topic_score_codex":0.0018256423,"about_ca_topic_score_gemma":0.0014861899,"teacher_disagreement_score":0.06835495,"about_ca_system_score_codex":0.0007909091,"about_ca_system_score_gemma":0.0012853574,"threshold_uncertainty_score":0.22867006},"labels":[],"label_agreement":null},{"id":"W4299904045","doi":"10.1007/978-3-031-01885-5_4","title":"Queries for Disk-based Indexes","year":2012,"lang":"en","type":"book-chapter","venue":"Synthesis lectures on data management","topic":"Advanced Database Systems and Queries","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 Victoria","funders":"","keywords":"Computer science","score_opus":0.05805241371313015,"score_gpt":0.2748976804022351,"score_spread":0.21684526668910498,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4299904045","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":[0.0077458313,0.037228134,0.72412866,0.004670619,0.0031162892,0.00023051482,0.0021425704,0.010575167,0.21016222],"genre_scores_gemma":[0.1313535,0.033076514,0.46088913,0.0023343184,0.005395507,0.0004873328,0.0065401928,0.0062045376,0.35371897],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99768233,0.0002759353,0.00022079897,0.00031680794,0.001367736,0.0001364773],"domain_scores_gemma":[0.99847025,0.00064959883,0.000048041446,0.00048044376,0.00029652638,0.000055162054],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012932621,0.0011956181,0.0012721979,0.0014808741,0.0010227457,0.006239801,0.0019527253,0.0013193161,0.02826964],"category_scores_gemma":[0.0054985834,0.0010000007,0.0007289554,0.004655824,0.001772842,0.011563472,0.0019866677,0.0026772371,0.013272845],"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":[0.000096018855,0.000055201443,0.00019447853,0.00056541106,0.000027413042,0.00009812551,0.00043518294,0.0025806688,0.0055506737,0.5705007,0.15460426,0.2652918],"study_design_scores_gemma":[0.000032848115,0.000036446057,0.0002815513,0.00018189815,0.000031641826,0.00037464045,0.00011647499,0.018911727,0.005044387,0.4660245,0.5089237,0.000040088562],"about_ca_topic_score_codex":0.0011988955,"about_ca_topic_score_gemma":0.0011051659,"teacher_disagreement_score":0.02826964,"about_ca_system_score_codex":0.001915467,"about_ca_system_score_gemma":0.0007840243,"threshold_uncertainty_score":0.09457141},"labels":[],"label_agreement":null},{"id":"W4300637421","doi":"10.1007/978-3-031-01839-8_10","title":"Other Aspects of Replication","year":2010,"lang":"en","type":"book-chapter","venue":"Synthesis lectures on data management","topic":"Advanced Database Systems and Queries","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":"McGill University","funders":"","keywords":"Replication (statistics); Psychology; Computer science; Biology; Virology","score_opus":0.03869562300640143,"score_gpt":0.2710489913433356,"score_spread":0.23235336833693415,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4300637421","genre_codex":"other","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":[0.003199299,0.014857274,0.092976965,0.011989091,0.0057217404,0.00008198911,0.00016191218,0.00044658064,0.8705651],"genre_scores_gemma":[0.21244618,0.013449284,0.04855884,0.007036538,0.010105353,0.00042673486,0.000396832,0.0008556873,0.70672464],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99836534,0.00049630785,0.00006172056,0.00033153617,0.0005998989,0.00014511035],"domain_scores_gemma":[0.99765223,0.00066941546,0.00009326494,0.0011337296,0.0003405653,0.00011081508],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016366489,0.0006542943,0.00074112514,0.0008309903,0.0025834662,0.0047103907,0.00192937,0.0023622024,0.03667115],"category_scores_gemma":[0.006038955,0.00046244884,0.00085550605,0.0018989154,0.004415363,0.009468815,0.0021599764,0.003321408,0.008662139],"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":[0.000009397144,0.0000102977765,0.000031278083,0.00004364869,0.0000038593357,0.00002891448,0.00018848441,0.00036369127,0.00024829738,0.9558835,0.02361037,0.0195783],"study_design_scores_gemma":[0.000007210417,0.0000099566305,0.000056475597,0.000033513632,0.0000046109317,0.00013006016,0.000082014776,0.00074598787,0.00027186502,0.76236224,0.23628896,0.0000070977026],"about_ca_topic_score_codex":0.0019145911,"about_ca_topic_score_gemma":0.0013496887,"teacher_disagreement_score":0.03667115,"about_ca_system_score_codex":0.0019825802,"about_ca_system_score_gemma":0.0013363538,"threshold_uncertainty_score":0.12267727},"labels":[],"label_agreement":null},{"id":"W4300916332","doi":"10.1007/978-3-031-01881-7_1","title":"Introduction","year":2011,"lang":"en","type":"book-chapter","venue":"Synthesis lectures on data management","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Computer science; Geology","score_opus":0.042258180871965624,"score_gpt":0.23903430150067678,"score_spread":0.19677612062871117,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4300916332","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0004159429,0.0030615963,0.0070437505,0.003070222,0.006071924,0.00012689938,0.0023118716,0.0011665846,0.9767313],"genre_scores_gemma":[0.0011682983,0.001399576,0.0015718899,0.0008205437,0.00079204125,0.00006355159,0.0014970055,0.00026688966,0.99242026],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993944,0.00005242615,0.000019199662,0.0001324884,0.00033429652,0.000067162735],"domain_scores_gemma":[0.99926263,0.00008237113,0.000024334888,0.000106934414,0.00035454036,0.0001693016],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005578091,0.0009499586,0.0005587352,0.0015888738,0.0011550769,0.00374819,0.0014815595,0.001484552,0.5875006],"category_scores_gemma":[0.0019482586,0.00031431988,0.0005171369,0.0014542767,0.00050795457,0.002723928,0.0023601276,0.0016409563,0.51209307],"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":[0.000023444769,0.000031484185,0.000083189974,0.00013985414,0.0000023512714,0.00003651261,0.00007838166,0.00013902673,0.000488466,0.02664315,0.78087413,0.19145998],"study_design_scores_gemma":[0.0000016926325,0.000005837864,0.00006066127,0.000045226898,9.559826e-7,0.000023270137,0.000023211269,0.000026177393,0.00008954944,0.0033186013,0.9964026,0.000002245483],"about_ca_topic_score_codex":0.0018800193,"about_ca_topic_score_gemma":0.0032655413,"teacher_disagreement_score":0.5875006,"about_ca_system_score_codex":0.0012660826,"about_ca_system_score_gemma":0.0017646225,"threshold_uncertainty_score":0.58838034},"labels":[],"label_agreement":null},{"id":"W4301036419","doi":"10.1007/978-3-031-01837-4_2","title":"Data Stream Management Systems","year":2010,"lang":"en","type":"book-chapter","venue":"Synthesis lectures on data management","topic":"Advanced Database Systems and Queries","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":"Computer science","score_opus":0.05484729722792187,"score_gpt":0.27223055054017625,"score_spread":0.2173832533122544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4301036419","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":[0.0064389193,0.008263849,0.6584716,0.0033892023,0.0035698498,0.0005422098,0.0020592695,0.022771375,0.29449373],"genre_scores_gemma":[0.056880355,0.011628128,0.25124797,0.0017997497,0.0024753616,0.00043765915,0.007201429,0.0027897737,0.6655396],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99944085,0.00005372566,0.000036660505,0.00009079933,0.00033860526,0.000039339684],"domain_scores_gemma":[0.9993899,0.00011776856,0.000020663536,0.00017104791,0.00024162004,0.000059008264],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00095688907,0.0008301463,0.0005489772,0.00128983,0.0006446851,0.0030705244,0.0011963408,0.00074675167,0.04164145],"category_scores_gemma":[0.0019261937,0.00051921105,0.00041552563,0.0019264844,0.00042553316,0.0030899316,0.0015027391,0.0013220249,0.02347762],"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":[0.000120807745,0.00010571563,0.00037482663,0.00023430161,0.000026233767,0.00010720206,0.00019898996,0.0022703586,0.008459018,0.08250519,0.25694892,0.64864844],"study_design_scores_gemma":[0.00003251856,0.000048965347,0.00041445906,0.00009036286,0.000024130553,0.00021843793,0.00006170733,0.022757674,0.00829382,0.042374484,0.9256631,0.000020337102],"about_ca_topic_score_codex":0.00091025466,"about_ca_topic_score_gemma":0.0009554838,"teacher_disagreement_score":0.04164145,"about_ca_system_score_codex":0.0006239848,"about_ca_system_score_gemma":0.0008395771,"threshold_uncertainty_score":0.13930452},"labels":[],"label_agreement":null},{"id":"W4301385930","doi":"10.1007/978-3-031-01881-7_5","title":"Query Compilation and Plan Synthesis","year":2011,"lang":"en","type":"book-chapter","venue":"Synthesis lectures on data management","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Computer science; Query optimization; Query language; Sargable; Query plan; Plan (archaeology); Query expansion; Web query classification; Information retrieval; RDF query language; Online aggregation; Web search query; Theoretical computer science; Database; Search engine","score_opus":0.06647717028824002,"score_gpt":0.2419019282067119,"score_spread":0.1754247579184719,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4301385930","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":[0.0032157796,0.0016608735,0.9343953,0.00073441357,0.00029021964,0.0001937617,0.0005046545,0.0043466776,0.054658215],"genre_scores_gemma":[0.11593293,0.0028787907,0.8063751,0.0005486239,0.00039298786,0.00045841892,0.0024723643,0.0034458265,0.06749498],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9983707,0.00028879882,0.00009841322,0.0003763708,0.000728278,0.00013750432],"domain_scores_gemma":[0.9990914,0.00044358257,0.000025259826,0.00023928104,0.00017583612,0.000024754581],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012768424,0.0011723316,0.0009824857,0.0010435291,0.00077150017,0.0031494936,0.0013598294,0.0006304874,0.024521079],"category_scores_gemma":[0.003978521,0.001026237,0.001414626,0.0013452165,0.0015223657,0.0035304888,0.0020746586,0.0023534333,0.0051062214],"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":[0.00011777886,0.000059116843,0.00016792148,0.0004712844,0.00005711933,0.00008924819,0.0003890474,0.023250842,0.0062469705,0.51337814,0.03526771,0.42050487],"study_design_scores_gemma":[0.000050321512,0.00006294924,0.00021853855,0.00018651636,0.00008574906,0.00015788445,0.0002117831,0.10765926,0.023374861,0.66966015,0.19828297,0.000048977676],"about_ca_topic_score_codex":0.0026393146,"about_ca_topic_score_gemma":0.0025209433,"teacher_disagreement_score":0.024521079,"about_ca_system_score_codex":0.0016352782,"about_ca_system_score_gemma":0.0015122995,"threshold_uncertainty_score":0.08203119},"labels":[],"label_agreement":null},{"id":"W4301751611","doi":"10.1007/978-3-031-01656-1_3","title":"Detection and Analysis of Oriented Patterns","year":2013,"lang":"en","type":"book-chapter","venue":"Synthesis lectures on biomedical engineering","topic":"Advanced Database Systems and Queries","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 Calgary","funders":"","keywords":"Computer science","score_opus":0.006240432679673185,"score_gpt":0.19496517525382537,"score_spread":0.18872474257415217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4301751611","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":[0.0325941,0.0023897944,0.9527581,0.00034199058,0.0001378291,0.00013306813,0.00091800274,0.0033880586,0.0073390724],"genre_scores_gemma":[0.15623182,0.0026204833,0.8199088,0.00019287517,0.00013726931,0.00017916804,0.0039345426,0.0006828573,0.01611229],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99922335,0.000067992056,0.000055346463,0.00023164669,0.00034795317,0.00007370972],"domain_scores_gemma":[0.9989215,0.0003754836,0.00013811143,0.00019798004,0.000307475,0.000059470134],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000708884,0.0008198782,0.00076095626,0.0032361492,0.0004027827,0.0017893116,0.0013680728,0.00065701874,0.004232944],"category_scores_gemma":[0.0025840362,0.0004977429,0.0008370209,0.002707725,0.0005553635,0.0015405641,0.0010885975,0.0008551164,0.0031817453],"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":[0.00013536146,0.000082748746,0.003897964,0.00032979198,0.00005794417,0.0003093046,0.0002021141,0.0037003225,0.038343977,0.020852478,0.009939055,0.922149],"study_design_scores_gemma":[0.000077206525,0.00029172862,0.017526845,0.00035094077,0.00024779685,0.0033497,0.00072324544,0.42889825,0.18385623,0.23613769,0.12842786,0.00011259954],"about_ca_topic_score_codex":0.00088051945,"about_ca_topic_score_gemma":0.0010619649,"teacher_disagreement_score":0.004232944,"about_ca_system_score_codex":0.00038079842,"about_ca_system_score_gemma":0.000541141,"threshold_uncertainty_score":0.014160633},"labels":[],"label_agreement":null},{"id":"W4301896648","doi":"","title":"Generating relational database transactions from EB3 attribute definitions","year":2009,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Database Systems and Queries","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 Sherbrooke","funders":"","keywords":"Computer science; Relational database; Database; Database design; Information retrieval","score_opus":0.030721557924531667,"score_gpt":0.23030740427838997,"score_spread":0.19958584635385831,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4301896648","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":[0.090893485,0.0003301233,0.87676096,0.00046419803,0.00024158209,0.0005598187,0.0035804487,0.018780272,0.008389],"genre_scores_gemma":[0.3803972,0.00026088842,0.5947082,0.00019347848,0.00009541358,0.00044144006,0.014222377,0.0037405377,0.0059404494],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973464,0.00060769764,0.00020720653,0.0003833553,0.0012050001,0.0002503369],"domain_scores_gemma":[0.99271566,0.003642853,0.0002498532,0.0015190967,0.001728137,0.00014446254],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016221537,0.00082345353,0.0006933348,0.0013627025,0.00054480025,0.00213837,0.00174185,0.0011668953,0.010345889],"category_scores_gemma":[0.01294197,0.00078332826,0.0018346013,0.002147321,0.0006960641,0.002260372,0.0025802942,0.0014679933,0.004526096],"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":[0.0024069145,0.0004940241,0.009087218,0.0014114532,0.00024756778,0.0021464422,0.0016393636,0.09951744,0.076453626,0.08242354,0.049856734,0.67431563],"study_design_scores_gemma":[0.00033344686,0.00044766229,0.0024859305,0.00015176527,0.00015961404,0.00097209745,0.00094547414,0.7156214,0.13310523,0.10302974,0.042656314,0.00009126246],"about_ca_topic_score_codex":0.0013058648,"about_ca_topic_score_gemma":0.0018673856,"teacher_disagreement_score":0.010345889,"about_ca_system_score_codex":0.0006264249,"about_ca_system_score_gemma":0.0011650232,"threshold_uncertainty_score":0.03461039},"labels":[],"label_agreement":null},{"id":"W4302017498","doi":"10.5753/jidm.2022.2488","title":"Integrating Heterogeneous Stream and Historical Data Sources using SQL","year":2022,"lang":"en","type":"article","venue":"Journal of Information and Data Management","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Computer science; SQL; Data integration; Task (project management); Context (archaeology); Stored procedure; Relational database; Point (geometry); Database; Data science; Information retrieval; Query by Example","score_opus":0.057902451114118035,"score_gpt":0.2842145215236848,"score_spread":0.22631207040956677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4302017498","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":[0.009122495,0.00030279782,0.97126657,0.00035014458,0.000048538248,0.00035571112,0.0016911384,0.014873653,0.0019889798],"genre_scores_gemma":[0.16257723,0.00093980035,0.8212779,0.0005399126,0.00013796982,0.0005144079,0.009640555,0.0017767834,0.0025954724],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9917747,0.0017037487,0.0021107632,0.0010958023,0.0030350005,0.00027998025],"domain_scores_gemma":[0.99294984,0.0026484,0.0006830267,0.0020256124,0.0014062674,0.00028690055],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011930678,0.0014459182,0.0015218932,0.0037155433,0.0008413105,0.0076015373,0.0027200978,0.0011145029,0.0022688932],"category_scores_gemma":[0.011247604,0.0009403672,0.0018088872,0.0036504173,0.0011089351,0.007967812,0.0043276106,0.0019071936,0.0014409312],"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":[0.002449266,0.0011213914,0.027917156,0.0029318782,0.0016436953,0.0043414775,0.009128624,0.06223062,0.08240816,0.24191144,0.026842112,0.53707427],"study_design_scores_gemma":[0.00033545127,0.00056261424,0.0057729455,0.0007374975,0.00064083206,0.0023627486,0.0032103376,0.52199775,0.09468822,0.17717248,0.19200721,0.0005120202],"about_ca_topic_score_codex":0.003010027,"about_ca_topic_score_gemma":0.0023124118,"teacher_disagreement_score":0.011930678,"about_ca_system_score_codex":0.0007883301,"about_ca_system_score_gemma":0.0019756772,"threshold_uncertainty_score":0.063096166},"labels":[],"label_agreement":null},{"id":"W4302041524","doi":"10.1007/978-3-031-01846-6_3","title":"Query Semantics","year":2011,"lang":"en","type":"book-chapter","venue":"Synthesis lectures on data management","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Semantics (computer science); Ranking (information retrieval); Tuple; Rank (graph theory); Computer science; Set (abstract data type); Possible world; Position (finance); Information retrieval; Theoretical computer science; Mathematics; Programming language; Discrete mathematics; Combinatorics","score_opus":0.06341861255133178,"score_gpt":0.2510255668324861,"score_spread":0.18760695428115431,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4302041524","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":[0.0025510127,0.0045253416,0.73980075,0.004199472,0.001176148,0.00029286565,0.0020640416,0.0051752017,0.24021523],"genre_scores_gemma":[0.13568068,0.011130953,0.4791474,0.004722642,0.0027611272,0.00088014745,0.013475994,0.005515828,0.34668526],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99615896,0.0006504574,0.00037827756,0.0008466796,0.001750451,0.00021522344],"domain_scores_gemma":[0.99837935,0.00052814384,0.00005071312,0.00053150667,0.00044309333,0.00006715738],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002347947,0.001551256,0.0012421653,0.0024761693,0.0015184162,0.008373818,0.002146711,0.0015076761,0.03680983],"category_scores_gemma":[0.005685093,0.0010944429,0.0015327944,0.0034735564,0.0028173926,0.015073974,0.0030218717,0.0040257596,0.021649584],"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":[0.000029948847,0.00003084988,0.0000639625,0.00017725627,0.000014089798,0.000030096298,0.00021880527,0.0006383572,0.0010594762,0.87109804,0.039214026,0.08742511],"study_design_scores_gemma":[0.000014138592,0.000016223537,0.00006330854,0.00009523207,0.000022429278,0.00016858849,0.0001022894,0.0049965633,0.0018581365,0.64891756,0.3437265,0.000018990335],"about_ca_topic_score_codex":0.001870823,"about_ca_topic_score_gemma":0.001183715,"teacher_disagreement_score":0.03680983,"about_ca_system_score_codex":0.0022659742,"about_ca_system_score_gemma":0.0018805849,"threshold_uncertainty_score":0.12314117},"labels":[],"label_agreement":null},{"id":"W4302313749","doi":"10.1007/978-3-319-63962-8_193-2","title":"Types of Stream Processing Algorithms","year":2012,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Big Data Technologies","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Computer science; Algorithm","score_opus":0.06233396227928956,"score_gpt":0.2686606870886226,"score_spread":0.20632672480933306,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4302313749","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":[0.0024324527,0.013084229,0.85499144,0.0025089947,0.004362893,0.00047606992,0.0029595664,0.004499866,0.11468457],"genre_scores_gemma":[0.046072654,0.026081624,0.74061483,0.0025277117,0.008242809,0.0010042472,0.010566071,0.0033636144,0.16152646],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99760795,0.00027870663,0.00031852286,0.0005593575,0.0010825992,0.0001529307],"domain_scores_gemma":[0.99684286,0.00092715246,0.00014615947,0.0011732775,0.0007762393,0.00013428753],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001729113,0.0019082387,0.0012554821,0.004290811,0.0011564294,0.0063444832,0.003064008,0.0021880495,0.03864665],"category_scores_gemma":[0.0072455322,0.0010151989,0.002435319,0.006099337,0.001506568,0.007958275,0.0022818444,0.004163497,0.025499713],"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":[0.0001537912,0.000097949654,0.00038952928,0.00079959846,0.000057890356,0.00013334637,0.000111929774,0.004076772,0.0017866815,0.5240074,0.09295377,0.37543136],"study_design_scores_gemma":[0.000048564456,0.00006307091,0.0003755719,0.00024354739,0.000058999176,0.00096202997,0.000042439504,0.028532896,0.0057809143,0.57631266,0.38752046,0.000058820577],"about_ca_topic_score_codex":0.000522022,"about_ca_topic_score_gemma":0.00045325502,"teacher_disagreement_score":0.03864665,"about_ca_system_score_codex":0.0010794973,"about_ca_system_score_gemma":0.0013264485,"threshold_uncertainty_score":0.12928587},"labels":[],"label_agreement":null},{"id":"W4302611369","doi":"10.1007/978-1-4614-8265-9_642","title":"Conceptual Schema Design","year":2018,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Advanced Database Systems and Queries","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 Toronto","funders":"","keywords":"Schema (genetic algorithms); Conceptual design; Computer science; Information retrieval; Human–computer interaction","score_opus":0.034048731495356525,"score_gpt":0.24705142151054196,"score_spread":0.21300269001518543,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4302611369","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":[0.0019595756,0.004334061,0.8919047,0.0022217527,0.00043965687,0.00025159182,0.0012161667,0.0025279014,0.0951447],"genre_scores_gemma":[0.045150336,0.0077562938,0.82729506,0.001141662,0.00023810839,0.0004895282,0.007152209,0.0015856426,0.10919125],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99792814,0.00053356454,0.00024142179,0.000492263,0.00070394325,0.00010070429],"domain_scores_gemma":[0.9985091,0.00042938473,0.00004982582,0.00053378765,0.00040925707,0.00006862723],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027897512,0.00087379554,0.00059577177,0.0018774038,0.0011144138,0.007997557,0.0024102312,0.00129265,0.032393716],"category_scores_gemma":[0.005459241,0.0009829412,0.0013927858,0.0034038709,0.0017411213,0.009681529,0.0032119283,0.0025025513,0.012843146],"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":[0.00001683478,0.000035685618,0.0002046531,0.00033893657,0.000025263924,0.00005749354,0.00059235736,0.0008692346,0.0011553046,0.7768439,0.039493687,0.18036671],"study_design_scores_gemma":[0.000011951875,0.000015559504,0.00011006516,0.00028327116,0.00002650244,0.0003424603,0.00023157398,0.0044127875,0.002054571,0.3060785,0.6864162,0.000016523705],"about_ca_topic_score_codex":0.0019138586,"about_ca_topic_score_gemma":0.0019461641,"teacher_disagreement_score":0.032393716,"about_ca_system_score_codex":0.0019329957,"about_ca_system_score_gemma":0.0024157094,"threshold_uncertainty_score":0.1083678},"labels":[],"label_agreement":null},{"id":"W4302793582","doi":"10.1007/978-3-319-63962-8_193-1","title":"Types of Stream Processing Algorithms","year":2018,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Big Data Technologies","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Computer science; Stream processing; Algorithm; Parallel computing","score_opus":0.057271102919070734,"score_gpt":0.27130034106951445,"score_spread":0.21402923815044372,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4302793582","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":[0.00239245,0.01620864,0.8193616,0.0030601788,0.0052893735,0.0005152007,0.003220828,0.0047766776,0.14517498],"genre_scores_gemma":[0.04432336,0.03183991,0.7146947,0.0029637916,0.0095784385,0.0010305882,0.011312987,0.0036514483,0.18060482],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99764794,0.00026369456,0.00029365538,0.00056129997,0.001085448,0.00014799515],"domain_scores_gemma":[0.99686265,0.0009332097,0.00013601372,0.0011186332,0.00081417774,0.0001353303],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017447583,0.001915705,0.0011893389,0.004444555,0.0011162747,0.006477907,0.0029885648,0.0021572453,0.041440047],"category_scores_gemma":[0.007254912,0.0010337092,0.0023957891,0.0060521127,0.0015137093,0.008086647,0.0022677125,0.0043612327,0.02906941],"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":[0.00014639016,0.000094245115,0.00034827244,0.00084613136,0.000054973527,0.0001135109,0.00010735626,0.0037998555,0.0017291625,0.49320465,0.10064058,0.39891475],"study_design_scores_gemma":[0.000043537948,0.000058171718,0.0003465067,0.0002803002,0.000050548802,0.00080700486,0.00004136637,0.024310246,0.005476625,0.53287077,0.43565884,0.00005606828],"about_ca_topic_score_codex":0.00052715826,"about_ca_topic_score_gemma":0.0004458472,"teacher_disagreement_score":0.041440047,"about_ca_system_score_codex":0.0011419207,"about_ca_system_score_gemma":0.0013827955,"threshold_uncertainty_score":0.13863075},"labels":[],"label_agreement":null},{"id":"W4310584182","doi":"10.1109/uemcon54665.2022.9965665","title":"Processing of a Continuous Data Stream on a Mobile Device","year":2022,"lang":"en","type":"article","venue":"2022 IEEE 13th Annual Ubiquitous Computing, Electronics &amp; Mobile Communication Conference (UEMCON)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Computer science; Tuple; Android (operating system); Mobile device; Database; Table (database); Focus (optics); Server; Database server; Mobile database; Process (computing); World Wide Web; Operating system; Mobile station","score_opus":0.035930263142365075,"score_gpt":0.3131570604990089,"score_spread":0.2772267973566438,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4310584182","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":[0.29972562,0.0010831384,0.67255884,0.00091322296,0.00055949925,0.0005941401,0.0024515656,0.011253598,0.01086032],"genre_scores_gemma":[0.76487255,0.001007259,0.22082499,0.0003688095,0.00033369596,0.00027841274,0.0033428315,0.00038203303,0.008589459],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993938,0.000062362495,0.000049832885,0.00013592672,0.000292536,0.000065657005],"domain_scores_gemma":[0.9984915,0.00059751485,0.00006979466,0.00025843995,0.00045700205,0.00012578757],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00058041606,0.00061509747,0.00088477036,0.0006837265,0.000535538,0.0019887849,0.00068285584,0.0006178834,0.003964186],"category_scores_gemma":[0.0025882893,0.00022884508,0.00042367814,0.0009705307,0.00022620735,0.0012424114,0.0007204545,0.0005697773,0.0015790466],"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":[0.004521019,0.00063971296,0.016118133,0.0009735114,0.0003114342,0.0040126876,0.0015619694,0.02720524,0.3488075,0.012282374,0.027874427,0.55569196],"study_design_scores_gemma":[0.00027930914,0.0013792578,0.012971739,0.0001455722,0.00019315259,0.0020869882,0.0015056783,0.7113702,0.20105864,0.017529745,0.05135199,0.00012767385],"about_ca_topic_score_codex":0.0012386782,"about_ca_topic_score_gemma":0.0011250633,"teacher_disagreement_score":0.003964186,"about_ca_system_score_codex":0.00030435785,"about_ca_system_score_gemma":0.00044561157,"threshold_uncertainty_score":0.013261497},"labels":[],"label_agreement":null},{"id":"W4312121203","doi":"10.1109/rasse54974.2022.9989603","title":"DW vs OLTP Performance Optimization in the Cloud on PostgreSQL (A Case Study)","year":2022,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Langara College; Okanagan College","funders":"","keywords":"Online transaction processing; Computer science; Data warehouse; Database; Analytics; Cloud computing; Online analytical processing; Big data; Materialized view; Transaction processing; Database transaction; Data mining; Operating system; Database design; View","score_opus":0.018608535586038897,"score_gpt":0.25353232874720627,"score_spread":0.23492379316116738,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312121203","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":[0.98052865,0.00039627118,0.0080396235,0.0006020568,0.000044847617,0.00018829654,0.0009623197,0.0037996308,0.0054383953],"genre_scores_gemma":[0.97662705,0.00016187398,0.020163553,0.00014363536,0.00001649646,0.000051246134,0.0013079179,0.00032076216,0.0012075717],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99400806,0.001135908,0.00046651857,0.0008953194,0.0024163744,0.0010777878],"domain_scores_gemma":[0.991299,0.0032586632,0.00055341347,0.0014024889,0.0027945004,0.0006918886],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005259787,0.0008990695,0.00067347835,0.0010496025,0.0010351924,0.002358057,0.0019450446,0.00092834106,0.0019107978],"category_scores_gemma":[0.008624219,0.00041204935,0.0004957105,0.0028884038,0.00085320795,0.0030025768,0.0011458511,0.0010977936,0.00083856896],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.013736904,0.0066879313,0.061673257,0.001994306,0.00035369798,0.0043736272,0.003941048,0.30641317,0.17998907,0.010644441,0.05887258,0.35131994],"study_design_scores_gemma":[0.0008529674,0.0033706764,0.042680435,0.000074258525,0.00011596191,0.00074981357,0.0029507454,0.81035274,0.121517666,0.002633591,0.014530915,0.00017024016],"about_ca_topic_score_codex":0.031906992,"about_ca_topic_score_gemma":0.018217523,"teacher_disagreement_score":0.031906992,"about_ca_system_score_codex":0.002651309,"about_ca_system_score_gemma":0.0017337936,"threshold_uncertainty_score":0.06344253},"labels":[],"label_agreement":null},{"id":"W4312235560","doi":"10.1007/978-3-031-21541-4_13","title":"Magic Sets in Interpolation-Based Rule Driven Query Optimization","year":2022,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Computer science; Query optimization; MAGIC (telescope); Transformation (genetics); Query language; Sargable; Interpolation (computer graphics); Query expansion; Set (abstract data type); Theoretical computer science; Extension (predicate logic); RDF query language; Algorithm; Web search query; Web query classification; Data mining; Information retrieval; Programming language; Artificial intelligence; Search engine","score_opus":0.012400352977995079,"score_gpt":0.24266850787988348,"score_spread":0.2302681549018884,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312235560","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":[0.007350672,0.0006752861,0.9882068,0.00012733847,0.000054020304,0.00006645504,0.00009166249,0.00077184686,0.0026559657],"genre_scores_gemma":[0.19535036,0.0006317977,0.7969186,0.00025776585,0.0001374894,0.00022771653,0.0005573033,0.00051928795,0.0053997096],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9961604,0.0011530522,0.0002944988,0.00045490882,0.0016700939,0.00026702392],"domain_scores_gemma":[0.99500555,0.0035882865,0.00012866015,0.0007732776,0.0004158194,0.0000883926],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035503136,0.0007992903,0.0024830312,0.0015693629,0.0007642152,0.0019513189,0.0034811622,0.0012479936,0.0063186293],"category_scores_gemma":[0.009745836,0.0011725036,0.0015102769,0.0029963837,0.0017667069,0.0038477676,0.003723693,0.0033461365,0.0012341171],"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":[0.0009461164,0.00023754522,0.0006836792,0.00035320557,0.00012508815,0.00015326646,0.00023135285,0.31394356,0.006118107,0.25645378,0.00780379,0.41295046],"study_design_scores_gemma":[0.00002779059,0.0000706046,0.00007101518,0.000025429948,0.000023553355,0.000048145583,0.000023052526,0.8793576,0.0023425492,0.11553838,0.0024534233,0.000018449127],"about_ca_topic_score_codex":0.0037541508,"about_ca_topic_score_gemma":0.0030888151,"teacher_disagreement_score":0.0063186293,"about_ca_system_score_codex":0.0010116826,"about_ca_system_score_gemma":0.0013543332,"threshold_uncertainty_score":0.021137893},"labels":[],"label_agreement":null},{"id":"W4312312306","doi":"10.14778/3554821.3554894","title":"Modern techniques for querying graph-structured relations","year":2022,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Graph; Graph database; Theoretical computer science; Query optimization; Distributed computing; Information retrieval","score_opus":0.012329831228488347,"score_gpt":0.23290806312094914,"score_spread":0.22057823189246079,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312312306","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":[0.0034911109,0.0045411247,0.9731663,0.0014001549,0.000152634,0.00028870965,0.0030198775,0.0080908155,0.0058492185],"genre_scores_gemma":[0.053044736,0.0124683175,0.91854334,0.0008785646,0.0004202713,0.00046041506,0.009319064,0.0010322398,0.0038331172],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99422425,0.00082288316,0.0005965268,0.0010402174,0.0030689777,0.00024715753],"domain_scores_gemma":[0.99549073,0.0017234745,0.0002700414,0.0017894589,0.00063953764,0.000086796106],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021522413,0.0018596257,0.0017714639,0.005239758,0.001146183,0.005082619,0.0046092616,0.0015569653,0.010118665],"category_scores_gemma":[0.010377114,0.0013370017,0.002194356,0.013376918,0.0016036081,0.012012816,0.0041449266,0.003002394,0.0058956225],"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":[0.00019831867,0.00019461123,0.001646116,0.0027213302,0.0002868239,0.000315734,0.0010848602,0.023249716,0.01975613,0.35555285,0.06527062,0.52972287],"study_design_scores_gemma":[0.000097200464,0.00010721009,0.0009896352,0.0003022836,0.00011945639,0.0013124917,0.0006402634,0.16770935,0.01427056,0.63042885,0.18391125,0.00011146065],"about_ca_topic_score_codex":0.0040946463,"about_ca_topic_score_gemma":0.0056875623,"teacher_disagreement_score":0.010118665,"about_ca_system_score_codex":0.001592321,"about_ca_system_score_gemma":0.0016293577,"threshold_uncertainty_score":0.033850312},"labels":[],"label_agreement":null},{"id":"W4312701113","doi":"10.14778/3551793.3551847","title":"ConnectorX","year":2022,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Overhead (engineering); Bridge (graph theory); Database; Process (computing); Interface (matter); Distributed computing; Operating system","score_opus":0.007993055508866007,"score_gpt":0.19490780951306425,"score_spread":0.18691475400419824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312701113","genre_codex":"software","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":"software","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0053043487,0.0014185964,0.19293667,0.0008809072,0.00073713256,0.0007744188,0.022099042,0.68228364,0.09356519],"genre_scores_gemma":[0.06961286,0.0032204876,0.20451187,0.003754862,0.00066421105,0.0018971192,0.26586214,0.20220779,0.24826859],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99639314,0.00048827962,0.00034225298,0.00074949727,0.0015870353,0.0004398288],"domain_scores_gemma":[0.99555296,0.000829061,0.00023475157,0.0019533876,0.001023228,0.00040663395],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003107788,0.0026840498,0.0016016039,0.002301936,0.0012339278,0.0061694128,0.0060127596,0.0018876322,0.15285912],"category_scores_gemma":[0.009569264,0.0017835202,0.0019154405,0.0036001855,0.0009868264,0.009604281,0.008015667,0.0029464513,0.13033104],"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":[0.0013615052,0.00024122788,0.0022635753,0.0011592505,0.00015209756,0.00034726443,0.00037911092,0.0013263345,0.008796874,0.037102748,0.7396827,0.20718738],"study_design_scores_gemma":[0.00017390342,0.00014557858,0.0013345665,0.00011918879,0.00004823802,0.00038166606,0.00009257457,0.0077321553,0.0098891435,0.011303293,0.9686997,0.00007997752],"about_ca_topic_score_codex":0.003236249,"about_ca_topic_score_gemma":0.0032201814,"teacher_disagreement_score":0.15285912,"about_ca_system_score_codex":0.0012607024,"about_ca_system_score_gemma":0.0026697498,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W4313485774","doi":"","title":"A Mereological System for Informational Templates","year":2022,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Mereology; Computer science; Template; Information retrieval; Programming language; Epistemology; Philosophy","score_opus":0.019150514271786524,"score_gpt":0.24040452080084568,"score_spread":0.22125400652905916,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313485774","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":[0.0044688513,0.000282987,0.9484449,0.00055876275,0.00036311272,0.00020989355,0.0014795146,0.032035597,0.0121563645],"genre_scores_gemma":[0.15825284,0.00080719223,0.7937612,0.00071842276,0.0007609115,0.00044610264,0.0066558295,0.010294327,0.028303199],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9934064,0.0016726218,0.0012849661,0.001234485,0.0019427659,0.00045876062],"domain_scores_gemma":[0.990498,0.0028881347,0.00035826597,0.0044244607,0.0013720954,0.00045907072],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0067606294,0.0011120288,0.0020897326,0.004803662,0.0029070461,0.01197467,0.004280228,0.0029608672,0.029373292],"category_scores_gemma":[0.015199695,0.0025006654,0.0031221996,0.0062297857,0.0035566944,0.017394783,0.007798746,0.003368858,0.014436179],"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":[0.00023925575,0.000054747252,0.0006642305,0.0003930166,0.000046768673,0.000365454,0.0011836804,0.0017143715,0.004449976,0.8589363,0.025244124,0.10670808],"study_design_scores_gemma":[0.00009660063,0.00009026506,0.00025670824,0.00019400154,0.00019047006,0.00072873733,0.00035189564,0.034872875,0.014980502,0.49998605,0.4480836,0.00016826637],"about_ca_topic_score_codex":0.0018760774,"about_ca_topic_score_gemma":0.0020640092,"teacher_disagreement_score":0.029373292,"about_ca_system_score_codex":0.0021549105,"about_ca_system_score_gemma":0.00273933,"threshold_uncertainty_score":0.09826344},"labels":[],"label_agreement":null},{"id":"W4318485822","doi":"10.1080/00031305.2022.2160590","title":"Object Oriented Data Analysis","year":2023,"lang":"en","type":"article","venue":"The American Statistician","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science","score_opus":0.03783203117561788,"score_gpt":0.3352063899743726,"score_spread":0.2973743587987547,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4318485822","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":[0.00068239495,0.0047964845,0.94099015,0.0023199448,0.0012354716,0.00038555777,0.0024930947,0.019312121,0.027784832],"genre_scores_gemma":[0.011988778,0.006213785,0.9227381,0.0022128588,0.0009840905,0.0006874302,0.008594262,0.0058083073,0.040772516],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99233025,0.0017588397,0.00074005616,0.0010344991,0.0039049636,0.00023144296],"domain_scores_gemma":[0.98907334,0.0044806455,0.00047880024,0.0037464553,0.0018669222,0.0003538499],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007865197,0.001953787,0.0014377539,0.003963693,0.0012250283,0.010308442,0.0025514122,0.0014456689,0.02782735],"category_scores_gemma":[0.016241606,0.0012286596,0.0023155524,0.0052175536,0.0015253418,0.006550588,0.003965318,0.0030453918,0.029508399],"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":[0.00008904435,0.00007213384,0.0009045786,0.0010063952,0.00018761231,0.00017368604,0.00051830383,0.0017300989,0.002355303,0.15036032,0.23355217,0.6090504],"study_design_scores_gemma":[0.00002496688,0.00003020094,0.00046956068,0.00030002557,0.000044927016,0.0003796667,0.00015848567,0.010963501,0.0022722753,0.123027496,0.8622867,0.000042176012],"about_ca_topic_score_codex":0.0012174329,"about_ca_topic_score_gemma":0.000983439,"teacher_disagreement_score":0.02782735,"about_ca_system_score_codex":0.00095452345,"about_ca_system_score_gemma":0.0018754944,"threshold_uncertainty_score":0.093091786},"labels":[],"label_agreement":null},{"id":"W4318541682","doi":"10.1145/3575693.3575704","title":"TiLT: A Time-Centric Approach for Stream Query Optimization and Parallelization","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Amazon Web Services; Canada Foundation for Innovation; Facebook","keywords":"Computer science; Analytics; Stream processing; Compiler; Query optimization; Throughput; Query language; Distributed computing; Parallel computing; Database; Programming language; Operating system","score_opus":0.031085570829696867,"score_gpt":0.2593872367556795,"score_spread":0.2283016659259826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4318541682","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":[0.0067749247,0.00032964494,0.95302296,0.0003038383,0.00015850703,0.00019973614,0.0008274649,0.034683965,0.0036989867],"genre_scores_gemma":[0.14658774,0.00055309327,0.83563244,0.0006711194,0.00021469708,0.0005186585,0.0052646208,0.006074828,0.0044827675],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99783903,0.00032932468,0.00028138427,0.0003971234,0.00089518534,0.00025783057],"domain_scores_gemma":[0.9978884,0.00049313897,0.0001417344,0.00082166004,0.00052574056,0.00012936805],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019403177,0.0013679184,0.00087495905,0.0010700505,0.0005799311,0.0029724836,0.003216556,0.00072336115,0.0043398137],"category_scores_gemma":[0.006017732,0.00067078095,0.001708074,0.0017154302,0.001182281,0.0034852503,0.003062533,0.0026432667,0.002287566],"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":[0.0019370358,0.0005237983,0.0058300416,0.0010312876,0.00030601202,0.00060009345,0.0011824179,0.14799705,0.0858634,0.19011022,0.14777191,0.4168467],"study_design_scores_gemma":[0.000225501,0.0003137625,0.0005718336,0.0000667753,0.00010826716,0.00026558325,0.00018121985,0.8288982,0.052617244,0.055818822,0.060841855,0.000090952635],"about_ca_topic_score_codex":0.0037956797,"about_ca_topic_score_gemma":0.0044284808,"teacher_disagreement_score":0.0043398137,"about_ca_system_score_codex":0.0011934896,"about_ca_system_score_gemma":0.002879183,"threshold_uncertainty_score":0.014518142},"labels":[],"label_agreement":null},{"id":"W4323343708","doi":"10.14778/3579075.3579080","title":"Change Propagation Without Joins","year":2023,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Joins; Computer science; Query plan; Latency (audio); Query optimization; Constant (computer programming); Operator (biology); Theoretical computer science; Plan (archaeology); Space (punctuation); Distributed computing; Information retrieval; Sargable; Search engine; Web search query; Telecommunications","score_opus":0.040322326480228064,"score_gpt":0.2605863433371262,"score_spread":0.22026401685689814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323343708","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":[0.0077371295,0.00043968653,0.9821978,0.00045981433,0.00011831453,0.000226772,0.0003277047,0.00523567,0.0032570306],"genre_scores_gemma":[0.22339979,0.000566147,0.7663136,0.0005835231,0.0003354818,0.0002907382,0.0010734772,0.001248972,0.006188314],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9934189,0.00074705057,0.000473275,0.0013741947,0.0033867725,0.00059985707],"domain_scores_gemma":[0.99220335,0.002151669,0.00049775746,0.003632263,0.0012742887,0.0002406231],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0041432814,0.0011198876,0.0012057648,0.002069676,0.0011246963,0.003889123,0.0047351983,0.0013571455,0.005205759],"category_scores_gemma":[0.010759964,0.00086176535,0.0015128814,0.0027608015,0.0018748199,0.010351041,0.0042137248,0.0033338098,0.0012700568],"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":[0.0005826576,0.00040700307,0.003581031,0.00059119676,0.00016364937,0.00048067668,0.00076023757,0.06489197,0.029851321,0.19518769,0.022112759,0.6813898],"study_design_scores_gemma":[0.00013249334,0.00046584583,0.0013298292,0.00008263711,0.00018949296,0.00071587384,0.0002397372,0.7195623,0.050522406,0.14312704,0.083493315,0.00013904463],"about_ca_topic_score_codex":0.006749473,"about_ca_topic_score_gemma":0.0054418244,"teacher_disagreement_score":0.006749473,"about_ca_system_score_codex":0.0013686123,"about_ca_system_score_gemma":0.0019848733,"threshold_uncertainty_score":0.021912038},"labels":[],"label_agreement":null},{"id":"W4323826068","doi":"10.4171/owr/2022/8","title":"Mini-Workshop: Descriptive Combinatorics, LOCAL Algorithms and Random Processes","year":2023,"lang":"en","type":"article","venue":"Oberwolfach Reports","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Algebraic combinatorics; Algorithm; Mathematics; Combinatorics","score_opus":0.023283839684186045,"score_gpt":0.2563696372297606,"score_spread":0.23308579754557454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323826068","genre_codex":"editorial","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":[0.048254594,0.07490195,0.25090188,0.20964187,0.2610953,0.0008625075,0.003445414,0.002034762,0.14886175],"genre_scores_gemma":[0.23109974,0.04391019,0.06690153,0.022415247,0.15828767,0.0020358663,0.007103443,0.0033314365,0.46491477],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9976521,0.0010101857,0.00010779692,0.00044952755,0.00040882977,0.00037159538],"domain_scores_gemma":[0.99273336,0.0031397133,0.00016642791,0.00068264076,0.0012824001,0.0019955253],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005532585,0.0016270446,0.0013902799,0.0013198043,0.0018633868,0.0051458445,0.0035049322,0.002734053,0.039927464],"category_scores_gemma":[0.006636075,0.0006727717,0.00249264,0.0011832628,0.0012954903,0.007222041,0.0052572326,0.006698353,0.012785841],"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":[0.0005949941,0.0003104351,0.000657773,0.0008150101,0.00014984784,0.00051917986,0.00094174733,0.003563901,0.004733378,0.14707983,0.7403096,0.10032441],"study_design_scores_gemma":[0.00012002353,0.0003719798,0.0016037299,0.00076890364,0.000102824706,0.00054120907,0.0011249062,0.011024199,0.0038096302,0.104260884,0.8761629,0.000108748594],"about_ca_topic_score_codex":0.0007579084,"about_ca_topic_score_gemma":0.0011698189,"teacher_disagreement_score":0.039927464,"about_ca_system_score_codex":0.0022511103,"about_ca_system_score_gemma":0.0020501884,"threshold_uncertainty_score":0.13357061},"labels":[],"label_agreement":null},{"id":"W4327590965","doi":"10.1007/s10115-023-01850-5","title":"Towards intelligent database systems using clusters of SQL transactions","year":2023,"lang":"en","type":"article","venue":"Knowledge and Information Systems","topic":"Advanced Database Systems and Queries","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":"Huawei Technologies (Canada)","funders":"","keywords":"Computer science; Online transaction processing; Troubleshooting; Database transaction; Database; DBSCAN; Credit card; Cluster analysis; Transaction processing; Data mining; SQL; Overhead (engineering); Artificial intelligence; Operating system; World Wide Web","score_opus":0.036835463230279156,"score_gpt":0.2875389323398121,"score_spread":0.25070346910953295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4327590965","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":[0.0143580325,0.00038332015,0.9773766,0.00035689538,0.00008555419,0.00016297259,0.00013036527,0.005610904,0.001535406],"genre_scores_gemma":[0.11731863,0.00051619275,0.8766449,0.0002113275,0.00009397063,0.00016490283,0.0006434356,0.00041583952,0.0039908127],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973104,0.0007212698,0.00030689125,0.0005052381,0.0009931062,0.00016321536],"domain_scores_gemma":[0.9937495,0.0017155465,0.00032385392,0.002376423,0.0015403334,0.00029434246],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004038421,0.00089885015,0.0016897154,0.0016994026,0.00095838535,0.004647743,0.0028695317,0.001205182,0.0037172963],"category_scores_gemma":[0.009229136,0.0014357659,0.0011941686,0.0030426423,0.0012705203,0.0077427193,0.0032768317,0.002396765,0.0026078508],"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":[0.0013575379,0.00063052156,0.00683278,0.00069106615,0.00052242324,0.0003164846,0.0012028501,0.12833638,0.036666695,0.15666659,0.026399875,0.6403768],"study_design_scores_gemma":[0.00015599422,0.00027415407,0.0010182476,0.00008156579,0.00021059328,0.00020402586,0.00039226943,0.75755274,0.024290511,0.18526591,0.030485315,0.000068747475],"about_ca_topic_score_codex":0.0028180466,"about_ca_topic_score_gemma":0.004285206,"teacher_disagreement_score":0.004647743,"about_ca_system_score_codex":0.0008357335,"about_ca_system_score_gemma":0.001607596,"threshold_uncertainty_score":0.021357477},"labels":[],"label_agreement":null},{"id":"W4361840222","doi":"10.1007/978-1-4842-9253-2_13","title":"Intelligent Cataloging and Metadata Management","year":2023,"lang":"en","type":"book-chapter","venue":"Apress eBooks","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Haystack; Metadata; Computer science; Data science; Cataloging; Task (project management); Quarter (Canadian coin); Data warehouse; World Wide Web; Big data; Database; Data mining; Engineering; Geography","score_opus":0.046709965675325114,"score_gpt":0.248627541474407,"score_spread":0.20191757579908187,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4361840222","genre_codex":"other","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0037019218,0.03230828,0.39387152,0.010464305,0.002289042,0.0003646267,0.0019834451,0.006099946,0.54891694],"genre_scores_gemma":[0.04836709,0.034685828,0.40102178,0.0030492865,0.0017864973,0.00029978465,0.006061525,0.0014551509,0.503273],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99879044,0.00020129453,0.000105581246,0.00020694586,0.00061150594,0.000084215644],"domain_scores_gemma":[0.9983778,0.00039850472,0.00006815087,0.000696367,0.00037361708,0.000085546555],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001760216,0.0007345781,0.00069814525,0.0052394504,0.0021057562,0.011055543,0.002110233,0.0015754002,0.025199367],"category_scores_gemma":[0.0037444474,0.0007678725,0.00079033803,0.008084441,0.00219319,0.015591937,0.0034208,0.0016581125,0.01966811],"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":[0.000020505324,0.00004246116,0.00034866895,0.00027242932,0.000014368104,0.0000891671,0.0007407918,0.0011156028,0.0013104886,0.46200392,0.14212118,0.39192042],"study_design_scores_gemma":[0.00000533624,0.000009200064,0.00018796082,0.00015054729,0.000008695606,0.00018777807,0.00025898474,0.0021096969,0.00075927284,0.15435316,0.84195364,0.000015757048],"about_ca_topic_score_codex":0.0055829394,"about_ca_topic_score_gemma":0.006220252,"teacher_disagreement_score":0.025199367,"about_ca_system_score_codex":0.0023023852,"about_ca_system_score_gemma":0.002535021,"threshold_uncertainty_score":0.08430022},"labels":[],"label_agreement":null},{"id":"W4366660902","doi":"10.14778/3583140.3583143","title":"<i> B <sup>link</sup> </i> -hash: An Adaptive Hybrid Index for In-Memory Time-Series Databases","year":2023,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Hash function; B-tree; Scalability; Hash table; Node (physics); Merkle tree; Parallel computing; Timestamp; Throughput; Tree (set theory); Data structure; Computer network; Cryptographic hash function; Database; Mathematics; Operating system","score_opus":0.025771553727448302,"score_gpt":0.2545432789060886,"score_spread":0.22877172517864028,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4366660902","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":[0.25138208,0.0020726186,0.71083635,0.00060103496,0.0003647099,0.0003368383,0.002057378,0.02287848,0.009470521],"genre_scores_gemma":[0.6748664,0.00062024605,0.31525373,0.0003011264,0.00017601959,0.00015373871,0.003114666,0.0006862202,0.0048279203],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996101,0.000038898226,0.000045534085,0.000056522196,0.00020455537,0.000044336317],"domain_scores_gemma":[0.99901175,0.00016560315,0.00009737666,0.00032718238,0.00028277765,0.000115260984],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045648013,0.0004238583,0.0003883107,0.0009197372,0.00045327732,0.0011009906,0.0016385629,0.00038787306,0.001945168],"category_scores_gemma":[0.001605009,0.00023668332,0.00021776586,0.0019769883,0.0003609868,0.002258882,0.0010204979,0.00039039316,0.00095291005],"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":[0.002380871,0.0005708164,0.01632721,0.0004899832,0.0001968541,0.00056555547,0.00041972278,0.04880072,0.26339003,0.015265246,0.045324787,0.60626817],"study_design_scores_gemma":[0.00020598274,0.0012662745,0.005279397,0.000030524272,0.00013873584,0.0010809911,0.000292908,0.72109604,0.21134323,0.008453148,0.05068952,0.00012329621],"about_ca_topic_score_codex":0.0017572072,"about_ca_topic_score_gemma":0.0025458934,"teacher_disagreement_score":0.001945168,"about_ca_system_score_codex":0.00055964076,"about_ca_system_score_gemma":0.0006368631,"threshold_uncertainty_score":0.006507218},"labels":[],"label_agreement":null},{"id":"W4375829778","doi":"10.15215/aupress/9781927356395.01","title":"Open Data Structures: An Introduction","year":2013,"lang":"en","type":"book","venue":"Athabasca University Press eBooks","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Government of Alberta; Government of Canada; Athabasca University","keywords":"Computer science","score_opus":0.05582977145785307,"score_gpt":0.25782886358357154,"score_spread":0.20199909212571848,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4375829778","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":[0.0031474717,0.25640962,0.20861919,0.008411659,0.011967069,0.00053462764,0.0067149196,0.008489959,0.4957055],"genre_scores_gemma":[0.015281175,0.20345022,0.15738891,0.008513764,0.012582256,0.000990846,0.012596448,0.0064480463,0.5827484],"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99890554,0.00008052359,0.00007325481,0.00015525741,0.00071463647,0.00007082469],"domain_scores_gemma":[0.99895406,0.00038562814,0.000056175028,0.00015196679,0.00030380272,0.00014838419],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.00078195153,0.0015751048,0.001215913,0.0030945248,0.0012839742,0.004943429,0.0018161591,0.0016617498,0.06524168],"category_scores_gemma":[0.0027152386,0.0016284364,0.0011620866,0.006919539,0.0012594464,0.008598301,0.0027807679,0.0038706448,0.047249228],"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":[0.000039782713,0.00015852755,0.00027422758,0.0010505322,0.000018542209,0.00014868303,0.00032656483,0.0018429952,0.001748966,0.0646231,0.5494253,0.38034272],"study_design_scores_gemma":[0.0000070126207,0.000023312954,0.00025995195,0.00034870877,0.0000038020605,0.00034251687,0.000046232566,0.00043127884,0.00022525412,0.036927946,0.96136945,0.0000145395525],"about_ca_topic_score_codex":0.0012474766,"about_ca_topic_score_gemma":0.0016699639,"teacher_disagreement_score":0.99818385,"about_ca_system_score_codex":0.0012817272,"about_ca_system_score_gemma":0.0016791518,"threshold_uncertainty_score":0.21825516},"labels":[],"label_agreement":null},{"id":"W4375832259","doi":"10.17706/ijapm.2023.13.2.19-23","title":"Sequential Coordinates","year":2023,"lang":"en","type":"article","venue":"International Journal of Applied Physics and Mathematics","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Mathematics","score_opus":0.01993657751132917,"score_gpt":0.2771901868008976,"score_spread":0.2572536092895684,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4375832259","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":[0.0061373445,0.0014276608,0.9399371,0.00036392623,0.0012834782,0.00020115825,0.0012014967,0.0023907449,0.047057036],"genre_scores_gemma":[0.14304812,0.0032321373,0.7758778,0.00033297492,0.0012120088,0.00060304604,0.0048626256,0.001088676,0.069742575],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99813336,0.0003081059,0.00019632705,0.0005951937,0.00062210206,0.00014495687],"domain_scores_gemma":[0.9985324,0.00017141696,0.00012130593,0.0005900644,0.00048070535,0.000104179264],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009433041,0.0013618701,0.0009662165,0.0018643191,0.0012084956,0.003252448,0.0015274165,0.000605847,0.024923105],"category_scores_gemma":[0.0027190633,0.0004583649,0.0008274536,0.0026475277,0.0012879862,0.0041356804,0.003083566,0.0011875926,0.012323808],"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":[0.00028325015,0.000036811656,0.0011228061,0.00030460424,0.000042130374,0.00026250124,0.0003853293,0.00806142,0.0058969893,0.6874098,0.029522432,0.266672],"study_design_scores_gemma":[0.00010687752,0.000272605,0.0006976784,0.00008717268,0.00005599429,0.0009433802,0.00021859497,0.03968517,0.008469715,0.22861335,0.72076875,0.000080706704],"about_ca_topic_score_codex":0.0020654318,"about_ca_topic_score_gemma":0.0019503401,"teacher_disagreement_score":0.024923105,"about_ca_system_score_codex":0.00085293234,"about_ca_system_score_gemma":0.0012176719,"threshold_uncertainty_score":0.08337611},"labels":[],"label_agreement":null},{"id":"W4379390231","doi":"10.1145/3555041.3589729","title":"Aggregation and Exploration of High-Dimensional Data Using the Sudokube Data Cube Engine","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Materialized view; Data cube; Cube (algebra); Information retrieval; Online analytical processing; Data mining; Data exploration; Query optimization; Data warehouse; Search engine; Database; View; Visualization; Database design","score_opus":0.1662931678440266,"score_gpt":0.3287438363806134,"score_spread":0.1624506685365868,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4379390231","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":[0.06004358,0.0007743899,0.91814876,0.0003874792,0.00009273657,0.000120082856,0.0012503663,0.014093868,0.0050888266],"genre_scores_gemma":[0.2705312,0.00067003473,0.72287506,0.00013219932,0.00004275473,0.00018864109,0.0028220275,0.0008665308,0.001871563],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99824226,0.00033207372,0.00015125709,0.00021868187,0.0009124236,0.00014338485],"domain_scores_gemma":[0.9978389,0.0007038085,0.000100418416,0.00078693096,0.00044462708,0.00012533044],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013014036,0.000874239,0.0011981855,0.0014298978,0.0013078593,0.0031692702,0.0023075885,0.00074566825,0.0031602297],"category_scores_gemma":[0.0048809755,0.00055340363,0.0012045979,0.00341238,0.0011271944,0.0037660329,0.0047580595,0.0011148582,0.00097335683],"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":[0.0019803306,0.0003277715,0.011533118,0.0008709329,0.00058569503,0.0016532574,0.0024406745,0.30434772,0.064424805,0.12625703,0.03540415,0.45017454],"study_design_scores_gemma":[0.000068397225,0.000096071344,0.00086052576,0.000037957423,0.000037403963,0.0003360695,0.0003035417,0.9187613,0.02737865,0.034585256,0.017466377,0.00006840231],"about_ca_topic_score_codex":0.009018706,"about_ca_topic_score_gemma":0.013466825,"teacher_disagreement_score":0.009018706,"about_ca_system_score_codex":0.0008247587,"about_ca_system_score_gemma":0.0018858712,"threshold_uncertainty_score":0.017932475},"labels":[],"label_agreement":null},{"id":"W4379507305","doi":"10.1007/978-3-031-34241-7_12","title":"Principles of Universal Conceptual Modeling","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in business information processing","topic":"Advanced Database Systems and Queries","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":"Memorial University of Newfoundland","funders":"","keywords":"Computer science; Flexibility (engineering); Conceptual model; Modularity (biology); Data science; Conceptual framework; Minimalism (technical communication); Focus (optics); Set (abstract data type); Artificial intelligence; Management science; Engineering; Human–computer interaction; Database; Epistemology; Programming language; Mathematics","score_opus":0.03568499721975415,"score_gpt":0.2417563029103003,"score_spread":0.20607130569054616,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4379507305","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":[0.0024935708,0.003984829,0.85184133,0.003720918,0.0004016032,0.00013494141,0.00035519083,0.000722163,0.13634542],"genre_scores_gemma":[0.24186102,0.005449497,0.68359977,0.0020308031,0.0008942734,0.0010112929,0.0014279685,0.0005075256,0.063217856],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9973368,0.0009381109,0.00026263946,0.0005350657,0.00074016873,0.00018713299],"domain_scores_gemma":[0.9978199,0.0008550968,0.00010466878,0.00073540834,0.00038450691,0.00010038252],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033899073,0.0010798316,0.001057764,0.0024357408,0.0029122585,0.0076563368,0.0027935263,0.0018525699,0.0098321345],"category_scores_gemma":[0.007063565,0.0013141895,0.0024223975,0.0026120015,0.009787462,0.011677194,0.0041645137,0.004623543,0.0036238148],"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":[0.0000014546171,0.000002851497,0.000021935854,0.000011550635,0.0000029124335,0.000008898551,0.00015070249,0.00018432943,0.000027926224,0.99504507,0.0012439515,0.003298368],"study_design_scores_gemma":[0.0000025414404,0.0000018057293,0.000024499683,0.000023618053,0.000005757365,0.000030695188,0.000050705105,0.0012055251,0.000072504095,0.9675917,0.030987082,0.0000035270073],"about_ca_topic_score_codex":0.0055465125,"about_ca_topic_score_gemma":0.0034823236,"teacher_disagreement_score":0.0098321345,"about_ca_system_score_codex":0.0029578267,"about_ca_system_score_gemma":0.0022025597,"threshold_uncertainty_score":0.03289181},"labels":[],"label_agreement":null},{"id":"W4379797318","doi":"10.1145/3604437.3604439","title":"TECHNICAL PERSPECTIVE: Ad Hoc Transactions: What They Are and Why We Should Care","year":2023,"lang":"en","type":"article","venue":"ACM SIGMOD Record","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Perspective (graphical); Set (abstract data type); Data science; Programming language; Artificial intelligence","score_opus":0.04067911802497789,"score_gpt":0.3036587340324514,"score_spread":0.26297961600747355,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4379797318","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006473368,0.047884073,0.11488879,0.75153434,0.006639385,0.000094207426,0.00033047723,0.00033264366,0.071822725],"genre_scores_gemma":[0.46752176,0.08010297,0.12092388,0.2569579,0.02662958,0.0004093403,0.000596398,0.0008807864,0.045977432],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98589104,0.0069203973,0.00090165855,0.001966021,0.0033138597,0.0010070164],"domain_scores_gemma":[0.9379139,0.03679234,0.0031332038,0.0054027922,0.013220209,0.0035375452],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015778873,0.0009781562,0.0009173563,0.0020925435,0.0032078964,0.015887482,0.0028814867,0.00981984,0.010096075],"category_scores_gemma":[0.042235024,0.0009843502,0.0006755573,0.002557318,0.026475355,0.036370583,0.003151754,0.013747375,0.0043179076],"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":[0.000064187436,0.00008189101,0.0019262319,0.00079593627,0.000030848616,0.0002529192,0.003994606,0.00051027193,0.0005492696,0.8554536,0.08733588,0.049004365],"study_design_scores_gemma":[0.000043458054,0.00006107516,0.00095202925,0.00088744593,0.00003010877,0.00096698187,0.006598729,0.0013607497,0.00057409756,0.65606385,0.33240768,0.000053861644],"about_ca_topic_score_codex":0.004608076,"about_ca_topic_score_gemma":0.003056904,"teacher_disagreement_score":0.015887482,"about_ca_system_score_codex":0.0054168687,"about_ca_system_score_gemma":0.006526047,"threshold_uncertainty_score":0.083447635},"labels":[],"label_agreement":null},{"id":"W4379932427","doi":"10.1145/3604437.3604458","title":"Accurate Summary-based Cardinality Estimation Through the Lens of Cardinality Estimation Graphs","year":2023,"lang":"en","type":"article","venue":"ACM SIGMOD Record","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Estimator; Cardinality (data modeling); Computer science; Graph; Joins; Proxy (statistics); Context (archaeology); Theoretical computer science; Mathematical optimization; Mathematics; Statistics; Data mining; Machine learning","score_opus":0.0549768818470338,"score_gpt":0.31388724108751587,"score_spread":0.25891035924048206,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4379932427","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":[0.018265795,0.0005975461,0.9788296,0.00054024864,0.000021513106,0.000025900805,0.00022142188,0.0003176435,0.0011802682],"genre_scores_gemma":[0.64190465,0.0012383953,0.3535456,0.00033230678,0.0002181594,0.00013601709,0.00079058344,0.00029321748,0.0015410616],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99371403,0.002701094,0.00028756532,0.001121107,0.0018196418,0.00035649133],"domain_scores_gemma":[0.9453303,0.0398453,0.005074413,0.006354347,0.0028462757,0.0005493555],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009126582,0.00088211783,0.001346527,0.0028645764,0.0007589264,0.0040199743,0.0024969783,0.001455837,0.0014926142],"category_scores_gemma":[0.0838493,0.00096194627,0.00056610035,0.0032978598,0.0019574985,0.011179333,0.0028350372,0.0027690586,0.0003047623],"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":[0.00023705246,0.000051534764,0.0077653527,0.00024285422,0.00010724819,0.00018250234,0.0006181816,0.34764233,0.0027109173,0.5525037,0.0032472871,0.084690966],"study_design_scores_gemma":[0.000010567747,0.000026294732,0.000741105,0.00003657262,0.000022777687,0.00007431861,0.00007831089,0.7698411,0.0017587516,0.22455211,0.0028349336,0.000023272303],"about_ca_topic_score_codex":0.0031498398,"about_ca_topic_score_gemma":0.0021175474,"teacher_disagreement_score":0.009126582,"about_ca_system_score_codex":0.0024143688,"about_ca_system_score_gemma":0.0013428708,"threshold_uncertainty_score":0.04826659},"labels":[],"label_agreement":null},{"id":"W4380433188","doi":"10.1145/3588711","title":"dbET: Execution Time Distribution-based Plan Selection","year":2023,"lang":"en","type":"article","venue":"Proceedings of the ACM on Management of Data","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Huawei Technologies (Canada); University of Toronto; York University","funders":"","keywords":"Computer science; Query plan; Plan (archaeology); Complement (music); Selection (genetic algorithm); Execution time; Overhead (engineering); Query optimization; Database; Sargable; Distributed computing; Programming language; Information retrieval; Web search query; Search engine; Artificial intelligence","score_opus":0.04636754490894221,"score_gpt":0.2778059725457491,"score_spread":0.23143842763680691,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380433188","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":[0.023332823,0.00033332102,0.96577823,0.00018436354,0.000042509982,0.0002542114,0.00079448003,0.0065883994,0.0026916915],"genre_scores_gemma":[0.41753024,0.00028528887,0.5763616,0.00017572912,0.000066574496,0.00035493466,0.0024134545,0.0009348546,0.001877265],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99792564,0.00044771604,0.0001201095,0.0003379941,0.0010142792,0.00015421805],"domain_scores_gemma":[0.99660563,0.0018154035,0.000288767,0.0005627452,0.00057880965,0.00014858728],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021914253,0.0009194135,0.00071753317,0.0013389119,0.00036496896,0.0012182565,0.0015187019,0.0005092492,0.0025058899],"category_scores_gemma":[0.0072328323,0.00036098354,0.0006459228,0.0013095888,0.0005338353,0.0012826878,0.0010265767,0.000994251,0.000575365],"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":[0.0007843677,0.00036006232,0.010170035,0.0003150172,0.00016899778,0.00017621086,0.00018205839,0.3799504,0.022441281,0.023871839,0.018450364,0.54312944],"study_design_scores_gemma":[0.00005490303,0.00009687094,0.0009474748,0.000009824093,0.00002137434,0.00008734859,0.000030840692,0.9794613,0.007938948,0.007705579,0.0036251163,0.000020450423],"about_ca_topic_score_codex":0.0035831511,"about_ca_topic_score_gemma":0.0049920725,"teacher_disagreement_score":0.0035831511,"about_ca_system_score_codex":0.001070235,"about_ca_system_score_gemma":0.0019369086,"threshold_uncertainty_score":0.011589527},"labels":[],"label_agreement":null},{"id":"W4381329253","doi":"10.1145/3589298","title":"Computing the Difference of Conjunctive Queries Efficiently","year":2023,"lang":"en","type":"article","venue":"Proceedings of the ACM on Management of Data","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Rewriting; Computer science; Query optimization; Heuristics; Operator (biology); Spatial query; Benchmark (surveying); Boolean conjunctive query; Set (abstract data type); Class (philosophy); Conjunctive query; SQL; Theoretical computer science; Algorithm; Sargable; Relational database; Search engine; Database; Information retrieval; Web search query","score_opus":0.06453656104710064,"score_gpt":0.3010111735680607,"score_spread":0.23647461252096003,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4381329253","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":[0.17870839,0.0009691645,0.7968478,0.0011376198,0.00023965223,0.00039425743,0.0015758644,0.013153995,0.0069732442],"genre_scores_gemma":[0.47659075,0.0002503703,0.51562315,0.0005904895,0.00015879884,0.0001527021,0.00338564,0.0011777936,0.0020702162],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9888194,0.001160105,0.0010443678,0.0025585052,0.0053662155,0.0010513626],"domain_scores_gemma":[0.9839484,0.009363238,0.0008428504,0.0034914897,0.0020431061,0.00031091392],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0039043375,0.0014991137,0.0025491503,0.0018798314,0.0010742259,0.004431486,0.0048096133,0.0010956273,0.0063353786],"category_scores_gemma":[0.018756459,0.0012852565,0.002298489,0.0032072377,0.001956907,0.012546078,0.0042231954,0.0030028836,0.0017436433],"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":[0.003098646,0.0011084514,0.01603581,0.0017017031,0.00081554835,0.0010970645,0.0014317619,0.13717954,0.0947395,0.12805423,0.020710148,0.5940276],"study_design_scores_gemma":[0.00028664386,0.0004769873,0.0022619653,0.000040863248,0.00023812412,0.0006232569,0.00046659753,0.7633927,0.05571991,0.16887096,0.0075191758,0.00010278566],"about_ca_topic_score_codex":0.0070763254,"about_ca_topic_score_gemma":0.00864323,"teacher_disagreement_score":0.0070763254,"about_ca_system_score_codex":0.002686167,"about_ca_system_score_gemma":0.002971568,"threshold_uncertainty_score":0.021193922},"labels":[],"label_agreement":null},{"id":"W4383033823","doi":"10.59350/mm0wh-a5v18","title":"A Julia Package for the Data Retriever","year":2018,"lang":"en","type":"preprint","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Labrador Retriever; Computer science; Medicine","score_opus":0.10435222393271223,"score_gpt":0.33655990681584075,"score_spread":0.2322076828831285,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4383033823","genre_codex":"software","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":"software","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00083004177,0.00047578907,0.41754484,0.0003857521,0.00047401825,0.0003622617,0.027799167,0.5396035,0.012524606],"genre_scores_gemma":[0.01302908,0.0009266673,0.3821948,0.0014058729,0.0006008929,0.0016652317,0.10554719,0.4695014,0.025128925],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99479467,0.0008165848,0.00087648386,0.000818202,0.0021022104,0.0005918822],"domain_scores_gemma":[0.9894198,0.0028692372,0.0005339267,0.0038446924,0.0028408496,0.00049141026],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0046648304,0.0030503976,0.0028710617,0.0037287609,0.0013046433,0.006868109,0.0060910573,0.0021285932,0.15181258],"category_scores_gemma":[0.02314266,0.0035946663,0.0044219894,0.0036815598,0.0010836449,0.0057907593,0.0059376997,0.0074683838,0.2498241],"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":[0.000741502,0.00013477831,0.0010271112,0.0011450558,0.00027950853,0.00038065776,0.0003775759,0.0016949261,0.0080087455,0.02351709,0.85070777,0.11198532],"study_design_scores_gemma":[0.0004348494,0.00006852741,0.00091492484,0.00021743207,0.00010378897,0.00072894373,0.00010605619,0.014349088,0.019520286,0.034065887,0.9292386,0.00025164802],"about_ca_topic_score_codex":0.0021624453,"about_ca_topic_score_gemma":0.0017275533,"teacher_disagreement_score":0.15181258,"about_ca_system_score_codex":0.0013898211,"about_ca_system_score_gemma":0.0024816238,"threshold_uncertainty_score":0.50786364},"labels":[],"label_agreement":null},{"id":"W4383749527","doi":"10.1109/fccm57271.2023.00028","title":"SQL2FPGA: Automatic Acceleration of SQL Query Processing on Modern CPU-FPGA Platforms","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Query plan; Query optimization; Compiler; SQL; Field-programmable gate array; Central processing unit; Sargable; Speedup; Parallel computing; Database; Embedded system; Operating system; Web search query; Search engine; Information retrieval","score_opus":0.03630541845629274,"score_gpt":0.28277180417488923,"score_spread":0.2464663857185965,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4383749527","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":[0.13661104,0.00096242566,0.4852728,0.0002883742,0.0002193237,0.00042111293,0.002343052,0.35783604,0.016045775],"genre_scores_gemma":[0.7148837,0.00042917609,0.25329053,0.0005767176,0.0000634855,0.00035484455,0.00737639,0.014877168,0.00814802],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991947,0.00009501122,0.000057541223,0.00019957768,0.00028528212,0.00016796192],"domain_scores_gemma":[0.99944705,0.00019490108,0.000048655016,0.00012683035,0.00013436413,0.000048206726],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00060213346,0.0015384047,0.00039455568,0.0006542837,0.00028119664,0.0011422667,0.001224263,0.00032187783,0.005219207],"category_scores_gemma":[0.0014817141,0.00056278956,0.0006243325,0.00042224597,0.0004832365,0.0010708342,0.00085766776,0.00090534345,0.0020994402],"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":[0.0046619065,0.00071696454,0.021538794,0.0011212961,0.00033918855,0.0019076682,0.0016456243,0.061764553,0.19554345,0.020655189,0.17162868,0.5184767],"study_design_scores_gemma":[0.0006384262,0.0007779823,0.008474006,0.00010092974,0.00010732035,0.0007646669,0.0003736226,0.6581437,0.23686856,0.008215302,0.085383296,0.0001522718],"about_ca_topic_score_codex":0.005388149,"about_ca_topic_score_gemma":0.0043547363,"teacher_disagreement_score":0.005388149,"about_ca_system_score_codex":0.00068469514,"about_ca_system_score_gemma":0.0014386333,"threshold_uncertainty_score":0.017460048},"labels":[],"label_agreement":null},{"id":"W4385705493","doi":"10.1007/978-3-031-39831-5_31","title":"Data-driven and On-Demand Conceptual Modeling","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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 Ottawa","funders":"","keywords":"Computer science; Schema (genetic algorithms); Novelty; Conceptual schema; Data modeling; Data mining; A priori and a posteriori; Graph; Data science; Theoretical computer science; Information retrieval; Software engineering","score_opus":0.060756966184347255,"score_gpt":0.2838812804370962,"score_spread":0.22312431425274895,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385705493","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":[0.006176662,0.000091736336,0.98672396,0.00025629863,0.000026820664,0.000111748624,0.00089612463,0.0009358435,0.0047808792],"genre_scores_gemma":[0.23746112,0.000617401,0.7459067,0.00016212167,0.000045934077,0.0003782153,0.0046799215,0.00078704406,0.0099615585],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99780005,0.00060691545,0.00016152732,0.00031519524,0.00096206024,0.00015426632],"domain_scores_gemma":[0.9954848,0.0022334734,0.00015106486,0.0012202639,0.0007861691,0.00012415713],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019861346,0.0008436815,0.00083940517,0.0012160932,0.00064566283,0.004480446,0.0040358976,0.0011660075,0.009810938],"category_scores_gemma":[0.009769884,0.0010291178,0.0023390972,0.0018871829,0.00097626017,0.0055837263,0.0030039244,0.0018937051,0.002020774],"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":[0.00018556128,0.00017451715,0.0017410289,0.00037355386,0.0000953698,0.0003886324,0.0007550703,0.39344507,0.004411418,0.45728013,0.009160786,0.13198887],"study_design_scores_gemma":[0.0000110278925,0.000014745048,0.00011625387,0.00002450194,0.000021565429,0.000076584736,0.00010385847,0.86331606,0.0024144158,0.12065219,0.013234677,0.00001422197],"about_ca_topic_score_codex":0.008283807,"about_ca_topic_score_gemma":0.011244852,"teacher_disagreement_score":0.009810938,"about_ca_system_score_codex":0.0016332476,"about_ca_system_score_gemma":0.0017414239,"threshold_uncertainty_score":0.03282082},"labels":[],"label_agreement":null},{"id":"W4385918011","doi":"10.1086/727000","title":"Geometric Pooling: A User’s Guide","year":2023,"lang":"en","type":"article","venue":"The British Journal for the Philosophy of Science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Pooling; Computer science; Mathematical economics; Mathematics; Artificial intelligence","score_opus":0.04641039688571996,"score_gpt":0.30459521319372024,"score_spread":0.2581848163080003,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385918011","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":[0.0008274329,0.027715895,0.5440294,0.05464939,0.009077633,0.0025131886,0.033621367,0.07175579,0.25581002],"genre_scores_gemma":[0.011250187,0.024949849,0.6644065,0.050275434,0.008570084,0.006344752,0.012469476,0.03865553,0.18307821],"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9935135,0.0028511107,0.0009990792,0.0006856216,0.0017354367,0.00021519566],"domain_scores_gemma":[0.94391716,0.03348273,0.0011588723,0.006381358,0.012875647,0.0021842546],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013159195,0.0034903386,0.0036454496,0.0074836398,0.0021010842,0.008568367,0.0067255306,0.006661244,0.27544722],"category_scores_gemma":[0.0926905,0.0022165477,0.0027133774,0.010316997,0.0033721707,0.014068925,0.0060297144,0.006023733,0.25867978],"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":[0.000045004937,0.000029466757,0.00012555569,0.00039413865,0.000020484269,0.0001207121,0.00022186247,0.0003186669,0.0002046286,0.009707972,0.93468153,0.054130007],"study_design_scores_gemma":[0.00003497035,0.00001225765,0.00010797298,0.00037170955,0.0000082173365,0.00019773151,0.000127058,0.00070560555,0.00014688917,0.021447752,0.97680366,0.000036317182],"about_ca_topic_score_codex":0.004402386,"about_ca_topic_score_gemma":0.0076647326,"teacher_disagreement_score":0.27544722,"about_ca_system_score_codex":0.0017554548,"about_ca_system_score_gemma":0.005395322,"threshold_uncertainty_score":0.9214628},"labels":[],"label_agreement":null},{"id":"W4386324444","doi":"10.1145/3609027.3609406","title":"Infix-Extensible Record Types for Tabular Data","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Google (Canada)","funders":"","keywords":"Computer science; Concatenation (mathematics); Data type; Table (database); Class (philosophy); Frame (networking); Benchmark (surveying); Programming language; Extensibility; Theoretical computer science; Artificial intelligence; Data mining; Arithmetic; Mathematics","score_opus":0.09560218146417815,"score_gpt":0.32947700523312484,"score_spread":0.2338748237689467,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386324444","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":[0.004928902,0.00043278618,0.9708746,0.00038195797,0.0004255737,0.00018256086,0.0017772904,0.014664535,0.0063318685],"genre_scores_gemma":[0.06495596,0.0011179674,0.9022784,0.0007431794,0.00042803193,0.0005677079,0.0037052035,0.0067606014,0.019442873],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99404055,0.00089123944,0.0008708338,0.00081397773,0.0027358045,0.0006475655],"domain_scores_gemma":[0.99287826,0.0014033542,0.00058182195,0.0033755437,0.0014314614,0.00032948895],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00937061,0.000907359,0.0011771658,0.0027127282,0.0023164195,0.0074152355,0.0045233853,0.001791906,0.009989312],"category_scores_gemma":[0.014224371,0.0014636451,0.0028862443,0.0043707304,0.0026452106,0.010421209,0.0074104075,0.004120954,0.005263703],"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":[0.00024242868,0.00010635724,0.0015756469,0.0003737999,0.000059309514,0.0003170106,0.00076382473,0.0052768355,0.008155521,0.8463576,0.021146137,0.115625575],"study_design_scores_gemma":[0.00009020153,0.00016445424,0.000585473,0.0003545629,0.00014673863,0.00092082063,0.00027833384,0.031994004,0.029825345,0.3559454,0.5794886,0.00020614498],"about_ca_topic_score_codex":0.004139089,"about_ca_topic_score_gemma":0.0040857755,"teacher_disagreement_score":0.009989312,"about_ca_system_score_codex":0.002632122,"about_ca_system_score_gemma":0.005439221,"threshold_uncertainty_score":0.04955709},"labels":[],"label_agreement":null},{"id":"W4386431490","doi":"10.1007/978-3-031-39626-7_11","title":"Business Intelligence","year":2023,"lang":"en","type":"book-chapter","venue":"EAI/Springer Innovations in Communication and Computing","topic":"Advanced Database Systems and Queries","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 Canada West","funders":"","keywords":"Business intelligence; Data science; Analytics; Computer science; Data warehouse; Business analytics; Knowledge management; Context (archaeology); Big data; Process management; Business; Business model; Electronic business; Marketing; Data mining","score_opus":0.05796044596972088,"score_gpt":0.2932789813369785,"score_spread":0.2353185353672576,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386431490","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00026710218,0.0028141276,0.0020137888,0.0022144404,0.0007287909,0.00003292217,0.00032096368,0.00031184938,0.99129605],"genre_scores_gemma":[0.0039705853,0.0030220654,0.0014508183,0.0010281472,0.00038722443,0.00003157025,0.00057215866,0.00011334523,0.98942417],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99938273,0.00006950384,0.00002424806,0.000106259606,0.0003717153,0.000045426936],"domain_scores_gemma":[0.99945134,0.00009616468,0.000031617652,0.0001384448,0.00017686398,0.000105724175],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006317596,0.00088634144,0.0005721925,0.0020332925,0.0010014323,0.0072841006,0.00083384983,0.0012849107,0.28839335],"category_scores_gemma":[0.0016772378,0.00039606894,0.00034072335,0.0027292662,0.0007205349,0.004244696,0.0018320298,0.0015283725,0.2625499],"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":[0.000020094507,0.000036369034,0.00013826796,0.00016878471,0.000006250585,0.000049788436,0.00016275549,0.00013669372,0.0006406208,0.0862488,0.5630713,0.3493203],"study_design_scores_gemma":[0.000002220948,0.000004563613,0.00011909565,0.000055174904,0.0000016953593,0.000033734854,0.00004413049,0.000086790475,0.00010615006,0.00886189,0.99068236,0.0000022175873],"about_ca_topic_score_codex":0.0014005518,"about_ca_topic_score_gemma":0.0022981118,"teacher_disagreement_score":0.28839335,"about_ca_system_score_codex":0.0011666535,"about_ca_system_score_gemma":0.0014535168,"threshold_uncertainty_score":0.96477187},"labels":[],"label_agreement":null},{"id":"W4386719007","doi":"10.1145/3568812.3603471","title":"MSMI1: Towards a Validated SQL Misconceptions Instrument","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","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 Toronto","funders":"","keywords":"Computer science; SQL; SQL/PSM; Database; World Wide Web; Query by Example","score_opus":0.04383012856794518,"score_gpt":0.28468541103503725,"score_spread":0.24085528246709206,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386719007","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":[0.21564189,0.00064920477,0.60448784,0.0044406573,0.00053358957,0.004818518,0.051485203,0.08233312,0.03561006],"genre_scores_gemma":[0.4173127,0.00030583199,0.4721406,0.002376364,0.00020656656,0.0040223496,0.0883206,0.0034113077,0.011903676],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9754023,0.0065513887,0.0030372909,0.0026131084,0.011333547,0.0010624278],"domain_scores_gemma":[0.92655385,0.02559207,0.008019219,0.008560057,0.028896557,0.002378314],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.024137266,0.0012922955,0.0007697528,0.005711253,0.0012601177,0.0048861965,0.002730598,0.0017563215,0.006168644],"category_scores_gemma":[0.08426537,0.0006968892,0.000867496,0.0025872346,0.0014790891,0.005256058,0.0074388464,0.002534599,0.006715024],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0034176342,0.002834464,0.2494877,0.002792431,0.0006190274,0.00036888575,0.0070996447,0.0069816005,0.05116891,0.058296964,0.14425991,0.4726728],"study_design_scores_gemma":[0.0005273651,0.0038206044,0.13603544,0.0023333137,0.00084079953,0.0013759608,0.0067398464,0.17518315,0.22868079,0.044601116,0.39912188,0.00073972304],"about_ca_topic_score_codex":0.0031916378,"about_ca_topic_score_gemma":0.0028963238,"teacher_disagreement_score":0.024137266,"about_ca_system_score_codex":0.0017145086,"about_ca_system_score_gemma":0.0062346794,"threshold_uncertainty_score":0.12765163},"labels":[],"label_agreement":null},{"id":"W4387098977","doi":"10.1007/s00778-023-00814-z","title":"A survey on transactional stream processing","year":2023,"lang":"en","type":"article","venue":"The VLDB Journal","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Banting and Best Diabetes Centre, University of Toronto; Singapore University of Technology and Design; National Research Foundation; Deutsche Forschungsgemeinschaft; Bundesministerium für Bildung und Forschung; Info-communications Media Development Authority; National Research Foundation Singapore; Bundesministerium für Bildung, Wissenschaft, Forschung und Technologie; Technische Universität Berlin","keywords":"Transactional leadership; Transactional analysis; Computer science; Perspective (graphical); Stream processing; Data science; Transaction processing; Database transaction; Distributed computing; Database; Artificial intelligence; Management; Economics; Psychology","score_opus":0.048473666201916135,"score_gpt":0.2954808845975803,"score_spread":0.2470072183956642,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387098977","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":[0.008918214,0.7758262,0.1561585,0.003554551,0.0018197277,0.00026340326,0.0007852322,0.0011605023,0.05151368],"genre_scores_gemma":[0.051203508,0.85205764,0.08086892,0.0017136047,0.0034488111,0.00019875877,0.0017702408,0.0003311789,0.008407349],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99776363,0.0004211985,0.00029717173,0.00034238872,0.0010054572,0.0001701778],"domain_scores_gemma":[0.9962425,0.0019540808,0.00019713919,0.00034534693,0.0010884046,0.0001725063],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021380547,0.0009378541,0.000983917,0.0040611015,0.000626496,0.00355887,0.0018648001,0.0012013603,0.007193884],"category_scores_gemma":[0.004273574,0.0007748754,0.00079907867,0.013782946,0.00079868163,0.006126662,0.0013425837,0.0020283011,0.0027670076],"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":[0.00019590772,0.00018291459,0.0021231945,0.006775458,0.000113580856,0.00024061651,0.00030879452,0.008410766,0.0026092126,0.07204111,0.049171373,0.857827],"study_design_scores_gemma":[0.000029882134,0.00027345304,0.0020170703,0.0024917484,0.000084416315,0.0012390073,0.00032375855,0.02592468,0.0027561435,0.051299587,0.9134897,0.00007053261],"about_ca_topic_score_codex":0.0015295867,"about_ca_topic_score_gemma":0.0007388945,"teacher_disagreement_score":0.007193884,"about_ca_system_score_codex":0.00093907467,"about_ca_system_score_gemma":0.0018244036,"threshold_uncertainty_score":0.024065971},"labels":[],"label_agreement":null},{"id":"W4388976844","doi":"10.1007/978-3-031-45043-3_3","title":"Data and Query Model","year":2023,"lang":"en","type":"book-chapter","venue":"Synthesis lectures on data management","topic":"Advanced Database Systems and Queries","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 Alberta","funders":"","keywords":"Syntax; Computer science; Programming language; Grammar; Abstract syntax; Natural language processing; Query language; Linguistics; Artificial intelligence; Information retrieval; Philosophy","score_opus":0.10586423601112353,"score_gpt":0.2897658059866748,"score_spread":0.18390156997555124,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388976844","genre_codex":"methods","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":[0.0015299396,0.007978225,0.6399617,0.010419521,0.0024093387,0.00026907286,0.0034039,0.0030758067,0.33095247],"genre_scores_gemma":[0.07942048,0.012595945,0.2986651,0.0078047127,0.0037172837,0.0011615194,0.009106786,0.0036273587,0.58390087],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99711394,0.0004715153,0.00023469445,0.0007076444,0.0013036871,0.0001685756],"domain_scores_gemma":[0.9984195,0.00045183394,0.000045870795,0.000692784,0.00031699092,0.000073054696],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023304503,0.0016349613,0.0012984112,0.0020559123,0.001563336,0.010191795,0.0029424995,0.001969118,0.048257995],"category_scores_gemma":[0.005355025,0.001311295,0.0013863293,0.0035068197,0.0036196555,0.017532803,0.0032351066,0.005634194,0.030326683],"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":[0.000010717157,0.000016906793,0.000034312954,0.00007794262,0.000005260557,0.000020494832,0.00010473213,0.0005153848,0.000464311,0.9342508,0.037544437,0.026954662],"study_design_scores_gemma":[0.000009072537,0.000013716941,0.000047530168,0.000066559325,0.000015045183,0.00012040217,0.0000619467,0.0055991574,0.0007695153,0.5766057,0.4166764,0.000014898958],"about_ca_topic_score_codex":0.0038012897,"about_ca_topic_score_gemma":0.002258291,"teacher_disagreement_score":0.048257995,"about_ca_system_score_codex":0.0030997174,"about_ca_system_score_gemma":0.0024185933,"threshold_uncertainty_score":0.16143912},"labels":[],"label_agreement":null},{"id":"W4389113257","doi":"10.1007/978-3-031-47627-3","title":"Indexing on Non-Volatile Memory","year":2023,"lang":"en","type":"book","venue":"SpringerBriefs in computer science","topic":"Advanced Database Systems and Queries","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":"Simon Fraser University","funders":"","keywords":"Online transaction processing; Computer science; Search engine indexing; Non-volatile memory; Information retrieval; Database; Database transaction; Transaction processing; Computer hardware","score_opus":0.017711871637228115,"score_gpt":0.2557428349563351,"score_spread":0.23803096331910698,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389113257","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":[0.061693933,0.061168455,0.58562016,0.0019791455,0.0059663616,0.00042364848,0.00517842,0.0257496,0.2522204],"genre_scores_gemma":[0.3720424,0.02599415,0.22770724,0.0009266083,0.0024590332,0.0004947534,0.011110755,0.0044806395,0.3547845],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99935323,0.00006754639,0.00006875511,0.000065269836,0.00032421586,0.00012100051],"domain_scores_gemma":[0.99864596,0.00035939645,0.000058464422,0.0006464307,0.00023028851,0.00005953651],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004064797,0.00094366824,0.0016258322,0.0022303944,0.0010757538,0.0032414494,0.0021090514,0.00052368134,0.028377673],"category_scores_gemma":[0.0017333679,0.0005903184,0.0005549883,0.0064445753,0.00076513295,0.00635256,0.0023381794,0.00087202305,0.008044907],"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":[0.00036391304,0.0000783032,0.00037600598,0.0008591698,0.00005142694,0.00017883521,0.00019650628,0.007845892,0.012342684,0.1576506,0.11862824,0.7014284],"study_design_scores_gemma":[0.00012807727,0.00028409658,0.0012746395,0.00037551817,0.00012965612,0.0009222769,0.00026112844,0.07614251,0.02875332,0.5278737,0.3637562,0.00009885273],"about_ca_topic_score_codex":0.0015229355,"about_ca_topic_score_gemma":0.002381854,"teacher_disagreement_score":0.028377673,"about_ca_system_score_codex":0.0011552998,"about_ca_system_score_gemma":0.0010564462,"threshold_uncertainty_score":0.094932795},"labels":[],"label_agreement":null},{"id":"W4389327929","doi":"10.1130/abs/2023am-390011","title":"INTEGRATION OF DEEP-TIME DATABASES: TOWARDS BUILDING A DEEP-TIME DIGITAL EARTH","year":2023,"lang":"en","type":"article","venue":"Abstracts with programs - Geological Society of America","topic":"Advanced Database Systems and Queries","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":"Future Earth","funders":"","keywords":"Computer science; Deep time; Database; Earth (classical element); Geology","score_opus":0.023600499413013187,"score_gpt":0.26828043391176104,"score_spread":0.24467993449874786,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389327929","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":[0.011119858,0.0016223164,0.96704817,0.0014134288,0.0002281067,0.000100880585,0.0027654266,0.012675864,0.003025855],"genre_scores_gemma":[0.090361856,0.0019738302,0.88479924,0.0009382467,0.00013959086,0.000097281314,0.015678048,0.0024668335,0.0035451602],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99747926,0.00031423566,0.00044336607,0.0005871412,0.000979798,0.00019616714],"domain_scores_gemma":[0.98633504,0.001685003,0.00085110613,0.0067612124,0.0032008677,0.001166739],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005739409,0.0008847366,0.0013543888,0.003823094,0.0007970093,0.006818357,0.0031212675,0.0014288846,0.003408369],"category_scores_gemma":[0.014493059,0.0011753658,0.0014659571,0.006000793,0.001135662,0.016338916,0.00904462,0.003067083,0.0019516533],"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":[0.00042573488,0.00041310533,0.019103901,0.0009984864,0.00037084313,0.000312708,0.0021284167,0.021865712,0.026576338,0.10377849,0.04748805,0.77653825],"study_design_scores_gemma":[0.000094594885,0.0002958678,0.006847345,0.00067809375,0.00064779015,0.00047664627,0.001178438,0.2947387,0.041500464,0.20598553,0.44732285,0.00023362071],"about_ca_topic_score_codex":0.007311851,"about_ca_topic_score_gemma":0.010065175,"teacher_disagreement_score":0.007311851,"about_ca_system_score_codex":0.0012110024,"about_ca_system_score_gemma":0.0037164965,"threshold_uncertainty_score":0.030353248},"labels":[],"label_agreement":null},{"id":"W4389523781","doi":"10.18653/v1/2023.emnlp-main.99","title":"Evaluating Cross-Domain Text-to-SQL Models and Benchmarks","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Benchmark (surveying); SQL; Ranking (information retrieval); Field (mathematics); Query by Example; Domain (mathematical analysis); Matching (statistics); Information retrieval; Programming language; Data mining; Web search query; Search engine","score_opus":0.07326356775616878,"score_gpt":0.3835356209260535,"score_spread":0.3102720531698847,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389523781","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":[0.7413418,0.008957331,0.15143815,0.002590128,0.0014929048,0.0015718634,0.022443894,0.052262787,0.017901137],"genre_scores_gemma":[0.7117868,0.0015339699,0.19409005,0.0013767987,0.00017599591,0.0006556017,0.082367465,0.004407899,0.0036054365],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9698509,0.0129624335,0.00324519,0.0042179353,0.008673256,0.0010502491],"domain_scores_gemma":[0.9526342,0.024670878,0.0018903475,0.009436723,0.009961664,0.0014061996],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.018473493,0.0028038784,0.0011510174,0.0035596632,0.0008882221,0.0031888976,0.0041889297,0.0019098313,0.002962074],"category_scores_gemma":[0.064291105,0.00056380965,0.0014810129,0.0043941946,0.0013528179,0.0049982914,0.0032903932,0.0023457722,0.0021209782],"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":[0.0040989,0.0053929198,0.049952902,0.0065570106,0.0017119999,0.001568559,0.002008558,0.4075428,0.04059866,0.016780108,0.15034395,0.31344357],"study_design_scores_gemma":[0.00039759965,0.0020891125,0.012108719,0.0004117255,0.0002313671,0.0006336959,0.0014521452,0.88862056,0.052211076,0.009403858,0.032250166,0.00019009282],"about_ca_topic_score_codex":0.011895272,"about_ca_topic_score_gemma":0.014894437,"teacher_disagreement_score":0.018473493,"about_ca_system_score_codex":0.0028696228,"about_ca_system_score_gemma":0.0025918975,"threshold_uncertainty_score":0.09769833},"labels":[],"label_agreement":null},{"id":"W4389611627","doi":"10.1145/3626750","title":"Rethink Query Optimization in HTAP Databases","year":2023,"lang":"en","type":"article","venue":"Proceedings of the ACM on Management of Data","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Online analytical processing; Online transaction processing; Database; Schedule; Isolation (microbiology); Parallel computing; Database transaction; Transaction processing; Data warehouse; Operating system","score_opus":0.09719269435293139,"score_gpt":0.32207878026332337,"score_spread":0.224886085910392,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389611627","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":[0.47205648,0.003075907,0.49925956,0.001585273,0.00015171827,0.00029664795,0.0006037639,0.013795867,0.009174848],"genre_scores_gemma":[0.7739594,0.0004374286,0.22189687,0.00036828892,0.00005826372,0.000087510496,0.0004923144,0.0008221208,0.0018777917],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9977642,0.0005690016,0.00017117012,0.00037240825,0.0008748528,0.00024837628],"domain_scores_gemma":[0.9982565,0.0007570561,0.00014852075,0.000515947,0.00024173303,0.00008024688],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019031859,0.0010182671,0.0005647843,0.00044204967,0.00066654925,0.0020145138,0.0018861899,0.00068106106,0.00089212926],"category_scores_gemma":[0.00313869,0.0005935167,0.0007143142,0.0009996183,0.0011848017,0.0028456917,0.001481822,0.001609954,0.00028958765],"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":[0.0016031512,0.0005429073,0.016162524,0.0004601394,0.00034443167,0.0005720763,0.0013055234,0.4459093,0.15007564,0.024534255,0.0112626115,0.3472274],"study_design_scores_gemma":[0.00008435783,0.00028200168,0.0026702997,0.000018982495,0.00008517593,0.00017971915,0.0003435395,0.92751706,0.050522596,0.011530779,0.006723115,0.000042410422],"about_ca_topic_score_codex":0.0071837823,"about_ca_topic_score_gemma":0.009549847,"teacher_disagreement_score":0.0071837823,"about_ca_system_score_codex":0.0010943302,"about_ca_system_score_gemma":0.0016377532,"threshold_uncertainty_score":0.014283955},"labels":[],"label_agreement":null},{"id":"W4390077597","doi":"10.1007/978-3-031-49333-1","title":"Model and Data Engineering","year":2023,"lang":"en","type":"book","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"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":"Universidad de Almería; Université de Sfax; Université de Nantes; Shenzhen University; Università degli Studi di Salerno; Eidgenössisches Nuklearsicherheitsinspektorat; Université de Bordeaux; Tartu Ülikool; Università di Bologna; Nile University; Orta Doğu Teknik Üniversitesi; Hunan University; Université de Lorraine; University of Macedonia; Univerzita Karlova v Praze; Universitat Politècnica de Catalunya; University of Cyprus; Université Grenoble Alpes; Universidade do Minho; Université de Moncton; University of Ioannina; University of Ontario Institute of Technology; Università degli Studi di Milano; Iowa State University; Indian Institute of Technology, Patna; University College Dublin; Universidad de Oviedo","keywords":"Computer science","score_opus":0.03537076435315042,"score_gpt":0.2713369866540428,"score_spread":0.2359662223008924,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390077597","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":[0.0023032008,0.011808526,0.8744505,0.0058975886,0.0016132707,0.00007607978,0.00086675247,0.0014484011,0.10153565],"genre_scores_gemma":[0.1865448,0.027972262,0.4714721,0.0038945163,0.0029758888,0.0005434666,0.0042674863,0.0024774373,0.29985216],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987029,0.0002762015,0.000104673316,0.00026632403,0.0005980282,0.00005194411],"domain_scores_gemma":[0.9986117,0.0004974211,0.000045001543,0.00058345596,0.00022570319,0.000036727124],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013627951,0.0011244885,0.0013889737,0.0015353741,0.0008034,0.0045476155,0.0014107514,0.0010581521,0.018759912],"category_scores_gemma":[0.004609441,0.00077612104,0.0011293165,0.0024413574,0.0018426279,0.0064460104,0.0025014551,0.003100889,0.010023776],"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":[0.000013249312,0.00002465974,0.00013969121,0.00015497707,0.000022704817,0.000047992806,0.00010846737,0.0028413357,0.0004893581,0.83153176,0.043390695,0.121235095],"study_design_scores_gemma":[0.000004982982,0.000009437227,0.00005396201,0.000050199164,0.000016023347,0.000111900314,0.000036410427,0.009286157,0.00057401217,0.8494827,0.14036676,0.0000075247026],"about_ca_topic_score_codex":0.0019934676,"about_ca_topic_score_gemma":0.0011212565,"teacher_disagreement_score":0.018759912,"about_ca_system_score_codex":0.0016492382,"about_ca_system_score_gemma":0.0011481013,"threshold_uncertainty_score":0.06275815},"labels":[],"label_agreement":null},{"id":"W4390679439","doi":"10.1109/aike59827.2023.00030","title":"A Hybrid Cost Model for Evaluating Query Execution Plans","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"University of Ottawa","keywords":"Computer science; Query optimization; Sargable; Query plan; Online aggregation; Query expansion; Cardinality (data modeling); Web query classification; Relational database; Execution time; RDF query language; Cost estimate; Plan (archaeology); Web search query; Data mining; Query language; View; Search engine; Database; Information retrieval; Distributed computing; Database design","score_opus":0.099629376899836,"score_gpt":0.3551715906951283,"score_spread":0.2555422137952923,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390679439","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":[0.036669604,0.0006310879,0.9566843,0.00065963,0.000046144618,0.00025648723,0.00068632903,0.0017312667,0.002635158],"genre_scores_gemma":[0.6338449,0.00041878322,0.3609036,0.00023318658,0.00008322735,0.0005866247,0.0012368637,0.00026703122,0.0024258152],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9958883,0.0011720925,0.00029537568,0.0006017658,0.0017626254,0.0002799157],"domain_scores_gemma":[0.9930924,0.00412446,0.0006624919,0.00069083454,0.0012412061,0.00018868705],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034062348,0.0015679059,0.0013259124,0.002183297,0.00047866598,0.0023327556,0.0027520603,0.0013496407,0.0024502],"category_scores_gemma":[0.0129159,0.00062657864,0.00094624044,0.0021347397,0.00076667586,0.003686,0.0011343413,0.0014448864,0.000414403],"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":[0.00022159673,0.00013985037,0.0023829914,0.000118354765,0.000078783996,0.000056560508,0.000043338372,0.9130551,0.0019228866,0.011101238,0.0020874739,0.06879182],"study_design_scores_gemma":[0.0000064306323,0.00003492001,0.00017230098,0.0000044074227,0.000009821145,0.000015177234,0.0000047956187,0.9968566,0.0003433873,0.0023095678,0.00023678849,0.0000057689413],"about_ca_topic_score_codex":0.0138083715,"about_ca_topic_score_gemma":0.014614448,"teacher_disagreement_score":0.0138083715,"about_ca_system_score_codex":0.003503294,"about_ca_system_score_gemma":0.0027934653,"threshold_uncertainty_score":0.027455986},"labels":[],"label_agreement":null},{"id":"W4391093809","doi":"10.1109/bigdata59044.2023.10386560","title":"Machine-Learning-Based Multidimensional Big Data Analytics over Clouds via Multi-Columnar Big OLAP Data Cube Compression","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Online analytical processing; Big data; Computer science; Data cube; Analytics; Data science; Knowledge extraction; Cube (algebra); Representation (politics); Cloud computing; Business intelligence; Data mining; Data warehouse","score_opus":0.13767151419297674,"score_gpt":0.3226442802585133,"score_spread":0.1849727660655366,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391093809","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":[0.013796576,0.00065443356,0.9795945,0.0010594198,0.00014328954,0.00009288067,0.00040449967,0.0018483412,0.0024060037],"genre_scores_gemma":[0.39498544,0.0017026094,0.5981206,0.00068736484,0.00031929387,0.00023953951,0.0016975353,0.00021224869,0.0020352802],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99892825,0.00018914681,0.0000872037,0.00014197765,0.0005364275,0.000116972216],"domain_scores_gemma":[0.9983551,0.0003916391,0.0001227947,0.00067793345,0.00038914222,0.000063281135],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008267424,0.00077775534,0.00089912425,0.0011914468,0.0007462174,0.0029443817,0.0018803182,0.0005759883,0.0014937972],"category_scores_gemma":[0.0037379637,0.00029848216,0.000742786,0.003636816,0.0009527422,0.0046010907,0.0025939879,0.0017347431,0.0007807877],"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":[0.0004999049,0.00029819927,0.002959615,0.0003925938,0.00018414132,0.00049266504,0.00047248285,0.28156915,0.02365707,0.22378065,0.025554411,0.44013903],"study_design_scores_gemma":[0.000019317307,0.000042573793,0.00026630177,0.000030637362,0.000019698195,0.00011135962,0.00012437502,0.91655076,0.01213271,0.06253449,0.008146867,0.00002098172],"about_ca_topic_score_codex":0.003333211,"about_ca_topic_score_gemma":0.0028774957,"teacher_disagreement_score":0.003333211,"about_ca_system_score_codex":0.000904964,"about_ca_system_score_gemma":0.0014448707,"threshold_uncertainty_score":0.0066276193},"labels":[],"label_agreement":null},{"id":"W4391668427","doi":"10.1090/conm/796","title":"LuCaNT: LMFDB, Computation, and Number Theory","year":2024,"lang":"en","type":"book","venue":"Contemporary mathematics - American Mathematical Society","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computation; Mathematics; Algorithm","score_opus":0.02259973674110301,"score_gpt":0.2804926072747349,"score_spread":0.2578928705336319,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391668427","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006441236,0.28025803,0.019289197,0.06476215,0.023921276,0.00008926978,0.0013332228,0.0017491038,0.60795367],"genre_scores_gemma":[0.012594172,0.081552036,0.012837182,0.013724063,0.018531347,0.0002588281,0.0019450042,0.0021610404,0.8563964],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99773324,0.0007463684,0.0000835847,0.0002611137,0.0010372581,0.00013839712],"domain_scores_gemma":[0.99701166,0.001240612,0.00013466582,0.000362336,0.00091808935,0.0003325762],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002463362,0.001057217,0.00096298975,0.0042920276,0.0019116785,0.0070742783,0.0015930503,0.0020572687,0.10313782],"category_scores_gemma":[0.006957566,0.00065353396,0.0006598422,0.0072767665,0.0023799695,0.0077938586,0.0021787207,0.0037643248,0.059378877],"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":[0.000014632074,0.0000046558707,0.000038552775,0.00020163198,0.0000028750314,0.000018722369,0.00004053399,0.00014674103,0.00006418416,0.042152077,0.90890735,0.04840803],"study_design_scores_gemma":[0.000002956024,0.000003906219,0.00011317478,0.00023695422,0.0000014658089,0.00008952546,0.000016956905,0.00014912894,0.000056146568,0.0073171137,0.99200726,0.0000055061932],"about_ca_topic_score_codex":0.007382202,"about_ca_topic_score_gemma":0.010966035,"teacher_disagreement_score":0.10313782,"about_ca_system_score_codex":0.0065732673,"about_ca_system_score_gemma":0.0026484483,"threshold_uncertainty_score":0.34503037},"labels":[],"label_agreement":null},{"id":"W4392139269","doi":"10.1145/3649133","title":"Sharing Queries with Nonequivalent User-defined Aggregate Functions","year":2024,"lang":"en","type":"article","venue":"ACM Transactions on Database Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Rewriting; Computer science; Aggregate (composite); Class (philosophy); Query language; Function (biology); Materialized view; Extension (predicate logic); Theoretical computer science; Database query; Reuse; Programming language; Information retrieval; Artificial intelligence; View","score_opus":0.026689537956721236,"score_gpt":0.25969814733779084,"score_spread":0.2330086093810696,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392139269","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":[0.09895613,0.00037984285,0.89235604,0.0003024645,0.000069215304,0.00015700005,0.00023068335,0.004731388,0.0028173118],"genre_scores_gemma":[0.69474125,0.00024679335,0.29968706,0.00030424935,0.000078305464,0.00013059158,0.0006433126,0.0012459776,0.0029224628],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.98776054,0.0036362149,0.001595194,0.0016684488,0.004347802,0.0009918321],"domain_scores_gemma":[0.97336835,0.010247345,0.0013320915,0.012475062,0.002146706,0.0004304407],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009485825,0.00084518705,0.0015963567,0.00086781563,0.00097114727,0.0038174342,0.0031080141,0.0012296272,0.0015451426],"category_scores_gemma":[0.020337464,0.0007015517,0.0020416044,0.0011309303,0.0019133859,0.007458214,0.004144976,0.0020487742,0.00043514604],"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":[0.0018093642,0.0006966187,0.016060162,0.000853774,0.0007167416,0.0018968729,0.005172081,0.11247293,0.11157442,0.42761987,0.0069220657,0.31420502],"study_design_scores_gemma":[0.00012900963,0.0004955193,0.0019889006,0.00009090883,0.00043075328,0.0010568423,0.00083796796,0.57156587,0.18344888,0.19807321,0.04166315,0.00021904359],"about_ca_topic_score_codex":0.0022336196,"about_ca_topic_score_gemma":0.0019320355,"teacher_disagreement_score":0.009485825,"about_ca_system_score_codex":0.0015157777,"about_ca_system_score_gemma":0.0019947535,"threshold_uncertainty_score":0.050166428},"labels":[],"label_agreement":null},{"id":"W4392741924","doi":"10.1214/24-ejs2228","title":"Merging sequential e-values via martingales","year":2024,"lang":"en","type":"article","venue":"Electronic Journal of Statistics","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Mathematics; Econometrics; Statistics","score_opus":0.009082415661675813,"score_gpt":0.27207184348480773,"score_spread":0.2629894278231319,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392741924","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":[0.021882962,0.000310299,0.9762131,0.00025284695,0.000034566427,0.00007099838,0.000045896908,0.00013094691,0.0010584929],"genre_scores_gemma":[0.41673657,0.00059831905,0.5772626,0.0003687786,0.00017058518,0.00040735994,0.00026960252,0.00021400572,0.003972143],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99026287,0.004711256,0.0006464012,0.0018085064,0.0017559113,0.0008150819],"domain_scores_gemma":[0.9468873,0.04050838,0.004182544,0.004964072,0.0022383598,0.0012193682],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.023868911,0.0012705759,0.0018553565,0.0030467876,0.0013707569,0.0034632953,0.003335572,0.0023780523,0.003595136],"category_scores_gemma":[0.0651875,0.0011555376,0.0023184163,0.0030878657,0.0049773525,0.011225804,0.0059280535,0.0039329855,0.00073820056],"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":[0.00028711246,0.00014615733,0.0053350967,0.00026018635,0.00017691126,0.00034198829,0.0008676353,0.10984803,0.0034676578,0.77850884,0.0008763136,0.0998841],"study_design_scores_gemma":[0.000050577604,0.00022582579,0.00086129527,0.00010654363,0.0000684251,0.00017843567,0.00013487066,0.3011792,0.007728289,0.68469244,0.004696935,0.00007715408],"about_ca_topic_score_codex":0.0010483084,"about_ca_topic_score_gemma":0.000668209,"teacher_disagreement_score":0.023868911,"about_ca_system_score_codex":0.0018600957,"about_ca_system_score_gemma":0.001609561,"threshold_uncertainty_score":0.12623233},"labels":[],"label_agreement":null},{"id":"W4392800119","doi":"10.1007/978-3-031-56066-8_6","title":"Estimating Query Performance Through Rich Contextualized Query Representations","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University; University of Waterloo; University of Guelph","funders":"","keywords":"Computer science; Query optimization; Sargable; Query expansion; Query language; Information retrieval; Web search query; Query by Example; RDF query language; Web query classification; Search engine","score_opus":0.025940496674701653,"score_gpt":0.29490498782356644,"score_spread":0.2689644911488648,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392800119","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":[0.3118572,0.004091743,0.6733056,0.00046164988,0.00012359206,0.00013249266,0.0021181668,0.005852184,0.0020574173],"genre_scores_gemma":[0.85029066,0.0010601865,0.14282061,0.00013337571,0.0002642356,0.000088066816,0.0039902627,0.00029622094,0.0010564042],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99814665,0.00045877355,0.00010408103,0.0004072175,0.0006766233,0.00020674798],"domain_scores_gemma":[0.99645305,0.0022653656,0.00028382914,0.0004760173,0.0004397638,0.00008199952],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015072046,0.0010513428,0.0014710958,0.0016005368,0.00030801576,0.0018528196,0.00093746645,0.0011508026,0.0010174221],"category_scores_gemma":[0.008389334,0.00047270302,0.0006353783,0.0022226973,0.0004699041,0.002844731,0.00088090333,0.0011677904,0.00083646324],"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":[0.0026696373,0.00080613646,0.016907807,0.00037337793,0.0003745018,0.0002322304,0.00018708901,0.35688236,0.09464466,0.0046215197,0.0098014595,0.51249933],"study_design_scores_gemma":[0.00001835182,0.00020523713,0.0026470055,0.000007598762,0.000056660738,0.000102588085,0.00002974071,0.98604685,0.007882692,0.002357596,0.000623715,0.000021914477],"about_ca_topic_score_codex":0.0035435809,"about_ca_topic_score_gemma":0.004210273,"teacher_disagreement_score":0.0035435809,"about_ca_system_score_codex":0.0006763197,"about_ca_system_score_gemma":0.0007576531,"threshold_uncertainty_score":0.007970989},"labels":[],"label_agreement":null},{"id":"W4393074478","doi":"10.1007/978-3-031-56069-9_51","title":"Query Performance Prediction: From Fundamentals to Advanced Techniques","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University; University of Waterloo","funders":"","keywords":"Computer science; Artificial intelligence; Data mining","score_opus":0.01214727380455557,"score_gpt":0.24604263346519262,"score_spread":0.23389535966063704,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393074478","genre_codex":"methods","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017779095,0.033964403,0.9311739,0.0022993523,0.00034736918,0.00008130188,0.0008950225,0.003529443,0.009930024],"genre_scores_gemma":[0.540013,0.04031794,0.39688504,0.0007410107,0.004050068,0.00025351628,0.0026504924,0.0006579193,0.014430975],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9979207,0.00033167118,0.00010693328,0.00042747418,0.0010770257,0.00013620952],"domain_scores_gemma":[0.9949856,0.003275052,0.00035600347,0.0006036656,0.0006699503,0.00010988012],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023480186,0.0016627715,0.0019535301,0.0019344451,0.00032039845,0.0026570738,0.0022742439,0.00095580565,0.0028404912],"category_scores_gemma":[0.008214742,0.0006895485,0.0006119979,0.0038147965,0.000653363,0.003089645,0.0010670446,0.0023852661,0.0022547687],"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":[0.00011968428,0.00019436312,0.009024246,0.0003956703,0.00008771149,0.000051284616,0.00010268506,0.064008795,0.003680251,0.024703408,0.029686589,0.8679453],"study_design_scores_gemma":[0.00001656958,0.00011494396,0.0065903426,0.0001891379,0.00006019851,0.00021529377,0.000060702427,0.914969,0.0041447743,0.059207473,0.014377819,0.000053733896],"about_ca_topic_score_codex":0.0024288325,"about_ca_topic_score_gemma":0.0018847298,"teacher_disagreement_score":0.0028404912,"about_ca_system_score_codex":0.0008124007,"about_ca_system_score_gemma":0.0006100188,"threshold_uncertainty_score":0.012417674},"labels":[],"label_agreement":null},{"id":"W4393144966","doi":"10.1109/tkde.2024.3381192","title":"DIBA: A Re-Configurable Stream Processor","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Knowledge and Data Engineering","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Alexander von Humboldt-Stiftung","keywords":"Computer science; Stream processing; Computer architecture; Parallel computing","score_opus":0.02496765267250139,"score_gpt":0.2756281570028197,"score_spread":0.2506605043303183,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393144966","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":[0.0546198,0.0007812241,0.8946455,0.00059400895,0.000500386,0.0006729995,0.0009150777,0.0383758,0.008895188],"genre_scores_gemma":[0.5303336,0.0008430482,0.44389772,0.0015470675,0.00027769976,0.0008073162,0.003828695,0.00256521,0.015899654],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99900275,0.000111400026,0.00009632451,0.00025087033,0.00037886287,0.00015984123],"domain_scores_gemma":[0.99882644,0.00019567036,0.00008007094,0.0003664438,0.00037208138,0.00015934157],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008902764,0.0007819143,0.00055972906,0.00096543116,0.00040275755,0.0020230282,0.0026043272,0.00065370154,0.004569407],"category_scores_gemma":[0.0022691719,0.00047339674,0.0004247305,0.000823638,0.0006282332,0.0023701095,0.0016683548,0.001952532,0.0021513198],"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":[0.0041185813,0.0010185589,0.01125085,0.0009179252,0.00024758137,0.00091439404,0.0008514746,0.039384943,0.31752175,0.03289125,0.08441967,0.5064631],"study_design_scores_gemma":[0.00078251114,0.0010606729,0.0032967562,0.00008171822,0.00018633647,0.0012403438,0.00022342277,0.5659038,0.21427387,0.011224431,0.20151116,0.00021496607],"about_ca_topic_score_codex":0.0017986121,"about_ca_topic_score_gemma":0.0012555944,"teacher_disagreement_score":0.004569407,"about_ca_system_score_codex":0.0009378372,"about_ca_system_score_gemma":0.0012960723,"threshold_uncertainty_score":0.015286207},"labels":[],"label_agreement":null},{"id":"W4393156209","doi":"10.1609/aaai.v38i9.28936","title":"Auditable Algorithms for Approximate Model Counting","year":2024,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Ministry of Education, India; National Research Foundation Singapore; National Research Foundation","keywords":"Computer science; Algorithm","score_opus":0.10483359672075183,"score_gpt":0.3236140129499684,"score_spread":0.21878041622921657,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393156209","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":[0.010253907,0.00041055132,0.9792979,0.0011977575,0.00012080412,0.00013337996,0.0002701788,0.003537077,0.0047784843],"genre_scores_gemma":[0.3767339,0.00068265316,0.6134857,0.0008117754,0.00025806352,0.0004885597,0.0010866984,0.00083144,0.0056212563],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9908217,0.0026788858,0.00064744265,0.0019134162,0.0029228902,0.0010156487],"domain_scores_gemma":[0.9734948,0.013059295,0.0014958831,0.010284741,0.0011728926,0.0004923527],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004186999,0.0011466898,0.0014912658,0.0012819013,0.0014259999,0.0052054944,0.004852061,0.002562695,0.0070504434],"category_scores_gemma":[0.03603654,0.0011064695,0.0024037687,0.0024582937,0.0025218572,0.012199136,0.00682839,0.0058250553,0.0017734019],"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":[0.00039494835,0.0002612327,0.0017820988,0.00032458486,0.000097065415,0.00015974257,0.0003789819,0.16265114,0.004668413,0.6771298,0.009905743,0.14224628],"study_design_scores_gemma":[0.00005456317,0.00003244507,0.00011439413,0.000043418037,0.000024250228,0.00011280582,0.000044581648,0.5537166,0.002625626,0.4380031,0.0052009015,0.000027302525],"about_ca_topic_score_codex":0.0027598867,"about_ca_topic_score_gemma":0.003910774,"teacher_disagreement_score":0.0070504434,"about_ca_system_score_codex":0.004635888,"about_ca_system_score_gemma":0.00446315,"threshold_uncertainty_score":0.033635855},"labels":[],"label_agreement":null},{"id":"W4393212300","doi":"10.1145/3639311","title":"Fast Shapley Value Computation in Data Assemblage Tasks as Cooperative Simple Games","year":2024,"lang":"en","type":"article","venue":"Proceedings of the ACM on Management of Data","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Shapley value; Simple (philosophy); Computation; Assemblage (archaeology); Value (mathematics); Computer science; Mathematical economics; Mathematics; Game theory; Algorithm; Geography; Machine learning; Archaeology","score_opus":0.06813038036782831,"score_gpt":0.34676075998945977,"score_spread":0.27863037962163145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393212300","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":[0.09026507,0.00011835322,0.90468854,0.00039236643,0.000043728767,0.00028785478,0.00021229008,0.00037881773,0.0036129963],"genre_scores_gemma":[0.6199874,0.00014667466,0.37516466,0.00018560699,0.000050501276,0.00040404737,0.00047561858,0.00018059883,0.0034048988],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99709046,0.0012300321,0.00015585049,0.0006239296,0.0005024816,0.00039725617],"domain_scores_gemma":[0.990493,0.007098612,0.0004899684,0.000984392,0.0004252312,0.00050884456],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004068304,0.001234872,0.0024423236,0.0010255831,0.0013008639,0.0034589448,0.0024684325,0.0014624957,0.006154745],"category_scores_gemma":[0.014121107,0.00081950444,0.0016164259,0.0016914392,0.0021123146,0.007486124,0.0032600733,0.0027620068,0.00064989267],"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":[0.0005371847,0.0002946581,0.0018496836,0.00039746103,0.0001610624,0.00028813092,0.00070389896,0.52611446,0.0041306964,0.38876852,0.0037057672,0.073048435],"study_design_scores_gemma":[0.00005681674,0.00004371314,0.00009468983,0.000011855371,0.000016178075,0.000029348093,0.000076885,0.69230145,0.0009437691,0.30560657,0.000806148,0.000012573643],"about_ca_topic_score_codex":0.002089321,"about_ca_topic_score_gemma":0.0028947336,"teacher_disagreement_score":0.006154745,"about_ca_system_score_codex":0.0022863378,"about_ca_system_score_gemma":0.0025816837,"threshold_uncertainty_score":0.021515489},"labels":[],"label_agreement":null},{"id":"W4393546112","doi":"10.5281/zenodo.8356598","title":"Combinatorial_lib_raw","year":2023,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Mathematics","score_opus":0.03311675707871347,"score_gpt":0.2575673716389602,"score_spread":0.22445061456024673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393546112","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00111357,0.00012728857,0.0009284162,0.000044568438,0.000050033046,0.000050966613,0.99227715,0.0038123154,0.0015956569],"genre_scores_gemma":[0.00090762175,0.000053820135,0.0014835293,0.00005418052,0.0000057311477,0.00011007834,0.99649733,0.0003391834,0.0005485951],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988451,0.00012486859,0.000079806836,0.00046519405,0.00028035935,0.00020459248],"domain_scores_gemma":[0.99885917,0.0002606441,0.000091432754,0.0004409409,0.000219856,0.00012803251],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012375306,0.005577362,0.0018051019,0.0031791348,0.0014212555,0.0025250607,0.004117611,0.002492251,0.051573373],"category_scores_gemma":[0.0027434963,0.0012921774,0.0023671067,0.0045525315,0.0009654275,0.001278864,0.0019569304,0.0030123105,0.07142897],"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":[0.00038515928,0.00013140566,0.0011720303,0.0013301391,0.00011887122,0.000066925924,0.00003815729,0.0022978764,0.0047197975,0.0015159565,0.9793434,0.008880276],"study_design_scores_gemma":[0.00094476977,0.00017067847,0.005081212,0.00021658944,0.0001617385,0.000248425,0.00008557252,0.004988049,0.015607898,0.0071081356,0.9652546,0.00013220227],"about_ca_topic_score_codex":0.013110346,"about_ca_topic_score_gemma":0.0246707,"teacher_disagreement_score":0.051573373,"about_ca_system_score_codex":0.0015959798,"about_ca_system_score_gemma":0.0033479072,"threshold_uncertainty_score":0.17253011},"labels":[],"label_agreement":null},{"id":"W4393830948","doi":"10.5281/zenodo.8356597","title":"Combinatorial_lib_raw","year":2023,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Mathematics; Combinatorics","score_opus":0.03311675707871347,"score_gpt":0.2575673716389602,"score_spread":0.22445061456024673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393830948","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00111357,0.00012728857,0.0009284162,0.000044568438,0.000050033046,0.000050966613,0.99227715,0.0038123154,0.0015956569],"genre_scores_gemma":[0.00090762175,0.000053820135,0.0014835293,0.00005418052,0.0000057311477,0.00011007834,0.99649733,0.0003391834,0.0005485951],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988451,0.00012486859,0.000079806836,0.00046519405,0.00028035935,0.00020459248],"domain_scores_gemma":[0.99885917,0.0002606441,0.000091432754,0.0004409409,0.000219856,0.00012803251],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012375306,0.005577362,0.0018051019,0.0031791348,0.0014212555,0.0025250607,0.004117611,0.002492251,0.051573373],"category_scores_gemma":[0.0027434963,0.0012921774,0.0023671067,0.0045525315,0.0009654275,0.001278864,0.0019569304,0.0030123105,0.07142897],"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":[0.00038515928,0.00013140566,0.0011720303,0.0013301391,0.00011887122,0.000066925924,0.00003815729,0.0022978764,0.0047197975,0.0015159565,0.9793434,0.008880276],"study_design_scores_gemma":[0.00094476977,0.00017067847,0.005081212,0.00021658944,0.0001617385,0.000248425,0.00008557252,0.004988049,0.015607898,0.0071081356,0.9652546,0.00013220227],"about_ca_topic_score_codex":0.013110346,"about_ca_topic_score_gemma":0.0246707,"teacher_disagreement_score":0.051573373,"about_ca_system_score_codex":0.0015959798,"about_ca_system_score_gemma":0.0033479072,"threshold_uncertainty_score":0.17253011},"labels":[],"label_agreement":null},{"id":"W4394629225","doi":"10.1109/csce60160.2023.00362","title":"Meta Generative Data Augmentation Optimization","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Hokkaido University","keywords":"Computer science; Generative grammar; Artificial intelligence","score_opus":0.19682598453240926,"score_gpt":0.33988278073199335,"score_spread":0.14305679619958409,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394629225","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":[0.00972426,0.0003224706,0.98569864,0.0001988949,0.000067798355,0.000055197204,0.00017267404,0.0017241505,0.002035773],"genre_scores_gemma":[0.5071397,0.0003446678,0.48164573,0.00081844744,0.00013263628,0.00047226046,0.0016211652,0.00084271986,0.0069826394],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992669,0.00020466933,0.000032600357,0.00021669445,0.00019575236,0.000083307415],"domain_scores_gemma":[0.9988921,0.0005757734,0.00007047876,0.0002678752,0.00014021588,0.000053528052],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010847849,0.0013973668,0.0013162663,0.0008609097,0.00037472186,0.0010111984,0.0020778517,0.001282728,0.0041758404],"category_scores_gemma":[0.0029854465,0.00065510045,0.0013805322,0.0008083031,0.0012649568,0.001588046,0.0026438814,0.0024231179,0.0011573944],"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":[0.00017933137,0.00015360574,0.0013918959,0.00015686823,0.000096448806,0.00018829324,0.00013678116,0.75531554,0.010064492,0.021664549,0.007291507,0.20336063],"study_design_scores_gemma":[0.00000857952,0.00002405087,0.000059263704,0.000008105229,0.0000068255995,0.00003797332,0.000009632811,0.98947424,0.0021258742,0.0067375256,0.0015008688,0.000007013856],"about_ca_topic_score_codex":0.0014470553,"about_ca_topic_score_gemma":0.0020855563,"teacher_disagreement_score":0.0041758404,"about_ca_system_score_codex":0.0007229177,"about_ca_system_score_gemma":0.00088611094,"threshold_uncertainty_score":0.0139696},"labels":[],"label_agreement":null},{"id":"W4394654232","doi":"10.48550/arxiv.2404.04703","title":"Aleph Filter: To Infinity in Constant Time","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Infinity; Constant (computer programming); Aleph; Filter (signal processing); Mathematics; Time constant; Physics; Mathematical analysis; Computer science; Engineering; Electrical engineering; Particle physics","score_opus":0.0546729987628575,"score_gpt":0.19162486162957995,"score_spread":0.13695186286672245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394654232","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":[0.009076217,0.00095979526,0.95286644,0.0013279819,0.00035584814,0.00017190517,0.0009897791,0.023032052,0.011219947],"genre_scores_gemma":[0.11675774,0.0007735835,0.85348547,0.0020330825,0.00065065833,0.0006553563,0.0020929307,0.00475405,0.01879713],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99260396,0.0011281971,0.00054612535,0.0016749294,0.0032205188,0.00082633365],"domain_scores_gemma":[0.98239523,0.007205268,0.00068743574,0.006900408,0.0023757021,0.00043591083],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006117175,0.0022417938,0.0027009733,0.0029566402,0.0022882682,0.006403051,0.0044105756,0.0026606445,0.019497572],"category_scores_gemma":[0.034496628,0.0012037319,0.0022449733,0.0035727895,0.0030795143,0.015084532,0.007486361,0.0038429054,0.011665836],"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":[0.0019222781,0.00025304788,0.0029323695,0.0006615836,0.00014089541,0.0003352001,0.0007434937,0.026140163,0.012034972,0.23991573,0.08566945,0.6292509],"study_design_scores_gemma":[0.00029036106,0.00023563046,0.0004617787,0.00019204144,0.000118245836,0.00068211,0.00024979952,0.36052972,0.021543244,0.5339394,0.0816344,0.00012323467],"about_ca_topic_score_codex":0.004252176,"about_ca_topic_score_gemma":0.004770108,"teacher_disagreement_score":0.019497572,"about_ca_system_score_codex":0.0027328166,"about_ca_system_score_gemma":0.0045431973,"threshold_uncertainty_score":0.0652259},"labels":[],"label_agreement":null},{"id":"W4394659840","doi":"10.1145/3656418","title":"From Batch to Stream: Automatic Generation of Online Algorithms","year":2024,"lang":"en","type":"article","venue":"Proceedings of the ACM on Programming Languages","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Computer science; Online algorithm; Set (abstract data type); Algorithm; Function (biology); Online and offline; Computation; Theoretical computer science; Programming language","score_opus":0.026518647595186642,"score_gpt":0.3049339642941108,"score_spread":0.27841531669892416,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394659840","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":[0.009061443,0.00010786024,0.97744536,0.00013507267,0.000060519982,0.000113945396,0.00020661535,0.010690908,0.0021782874],"genre_scores_gemma":[0.13355553,0.00011841275,0.86054254,0.00015949897,0.000055362547,0.00023885019,0.0008666551,0.002562634,0.0019005504],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99755764,0.0006777642,0.00023680388,0.0005120198,0.00084460835,0.00017121434],"domain_scores_gemma":[0.991302,0.005103288,0.00036549065,0.0020592208,0.0009907627,0.00017921814],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031697059,0.0012765045,0.0009992237,0.0010147252,0.0005358239,0.0020172908,0.002584239,0.0009908543,0.007933197],"category_scores_gemma":[0.014883603,0.0006803157,0.001219407,0.0008509106,0.0012590789,0.0035029026,0.001814265,0.0018569193,0.002603844],"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":[0.00094263454,0.00035538236,0.002690295,0.0006184941,0.000120133576,0.00035102837,0.0003969139,0.16181423,0.03069096,0.10040721,0.019461302,0.6821514],"study_design_scores_gemma":[0.000113817085,0.00009558099,0.0001428,0.00003031947,0.000023128237,0.00010365209,0.0000648564,0.9114978,0.029098766,0.048926137,0.00988342,0.00001977141],"about_ca_topic_score_codex":0.0010770581,"about_ca_topic_score_gemma":0.0015591683,"teacher_disagreement_score":0.007933197,"about_ca_system_score_codex":0.0009567601,"about_ca_system_score_gemma":0.002455393,"threshold_uncertainty_score":0.026539207},"labels":[],"label_agreement":null},{"id":"W4395686962","doi":"10.1145/3626246.3654743","title":"OpenIVM: a SQL-to-SQL Compiler for Incremental Computations","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"Computer science; SQL; Compiler; Stored procedure; Materialized view; Query by Example; Database; Programming language; Online analytical processing; SQL/PSM; PL/SQL; Data definition language; Table (database); Operating system; Data warehouse; View; Information retrieval; Database design; Search engine","score_opus":0.040955892810934084,"score_gpt":0.3310760966211035,"score_spread":0.2901202038101694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4395686962","genre_codex":"methods","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0024614735,0.00015681778,0.84298563,0.00015803265,0.00013361398,0.00015761062,0.0015625058,0.1469442,0.005440124],"genre_scores_gemma":[0.042301245,0.00032435046,0.8780206,0.0005170684,0.00010711724,0.0006183015,0.008286995,0.06425599,0.0055682673],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99678636,0.0005190295,0.00041276825,0.00050901365,0.0014019271,0.00037086842],"domain_scores_gemma":[0.99515414,0.0023742653,0.00022484004,0.0011117918,0.00090224313,0.00023278077],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038881018,0.0013293726,0.00084346376,0.0012137595,0.00060861517,0.0032472736,0.0041104467,0.0009913174,0.0156068085],"category_scores_gemma":[0.011202925,0.0019051905,0.0016569842,0.0009859181,0.0011566823,0.0052037146,0.0048774956,0.0038216414,0.009105631],"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":[0.0013158879,0.0006574457,0.004506996,0.0013848414,0.00020365938,0.0010584525,0.0015087167,0.021615122,0.028812867,0.19064817,0.27757302,0.47071484],"study_design_scores_gemma":[0.00049370993,0.00021546007,0.0014264842,0.00042275165,0.00010187241,0.0010627361,0.00030089414,0.3101048,0.0741007,0.13326454,0.47824803,0.0002580604],"about_ca_topic_score_codex":0.0014706581,"about_ca_topic_score_gemma":0.0021346684,"teacher_disagreement_score":0.0156068085,"about_ca_system_score_codex":0.0009796036,"about_ca_system_score_gemma":0.0025666188,"threshold_uncertainty_score":0.052210033},"labels":[],"label_agreement":null},{"id":"W4396214235","doi":"10.1145/3649849","title":"VeriEQL: Bounded Equivalence Verification for Complex SQL Queries with Integrity Constraints","year":2024,"lang":"en","type":"article","venue":"Proceedings of the ACM on Programming Languages","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Data integrity; Computer science; Equivalence (formal languages); Bounded function; SQL; Programming language; Database; Theoretical computer science; Mathematics; Discrete mathematics","score_opus":0.039721195698417415,"score_gpt":0.3154632234301081,"score_spread":0.27574202773169065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396214235","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":[0.015589935,0.00058534084,0.8982455,0.0009862529,0.00026526581,0.00038474874,0.0024456365,0.07543015,0.0060671302],"genre_scores_gemma":[0.37157717,0.0006084921,0.5972393,0.0021861943,0.00024434726,0.0007113607,0.010144003,0.010850918,0.006438221],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.98314166,0.005407745,0.0014773763,0.0019171116,0.006540702,0.0015154295],"domain_scores_gemma":[0.961682,0.024094708,0.0020420211,0.0082139345,0.0035751555,0.00039209516],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011710518,0.0018719274,0.0012506043,0.002436852,0.0015735405,0.0048048254,0.006791669,0.0023485012,0.021040373],"category_scores_gemma":[0.041212615,0.0016620615,0.0035613873,0.0015990951,0.0053173024,0.011549072,0.008307191,0.004374546,0.0047462853],"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":[0.002322327,0.00092810416,0.0115757575,0.003980674,0.0005976032,0.0016857402,0.00177014,0.15590896,0.051548723,0.27583328,0.10704402,0.38680458],"study_design_scores_gemma":[0.00057011726,0.00043264517,0.0010407327,0.00039894754,0.00019689428,0.0006966177,0.00036049073,0.70917183,0.08460478,0.15451467,0.04781914,0.000193142],"about_ca_topic_score_codex":0.009002251,"about_ca_topic_score_gemma":0.009964707,"teacher_disagreement_score":0.021040373,"about_ca_system_score_codex":0.0029976177,"about_ca_system_score_gemma":0.008106749,"threshold_uncertainty_score":0.070387065},"labels":[],"label_agreement":null},{"id":"W4396886508","doi":"10.1109/tkde.2024.3400824","title":"Natural Language Interfaces for Tabular Data Querying and Visualization: A Survey","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Knowledge and Data Engineering","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Visualization; Data visualization; Natural language; Information retrieval; Information visualization; Programming language; Database; World Wide Web; Natural language processing; Data mining","score_opus":0.042755576037026975,"score_gpt":0.33400078138952005,"score_spread":0.2912452053524931,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396886508","genre_codex":"methods","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009992749,0.26234147,0.6530475,0.0048023555,0.0005292224,0.00094129494,0.005453424,0.028720539,0.03417145],"genre_scores_gemma":[0.047398943,0.21793886,0.7016841,0.0040038824,0.00084849406,0.0018032391,0.010954658,0.0057541346,0.009613626],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9929212,0.0021452259,0.0010852385,0.00068439584,0.0029200637,0.00024383624],"domain_scores_gemma":[0.96929306,0.024292333,0.00082355214,0.0020270203,0.0031368434,0.00042726236],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009524159,0.0016481135,0.0018571854,0.008704691,0.0007255728,0.007277838,0.003302865,0.0016380419,0.011427456],"category_scores_gemma":[0.02837188,0.0010964198,0.0016517406,0.0100739775,0.0013943851,0.014924523,0.0030291984,0.0025549752,0.004918026],"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":[0.00022465758,0.00018640191,0.002273111,0.0108728735,0.00013525161,0.00021088793,0.0030878682,0.0015310304,0.006245496,0.062071644,0.07334028,0.83982056],"study_design_scores_gemma":[0.00005092949,0.0001457877,0.0023054185,0.0044633523,0.00010732266,0.0013518287,0.0012813378,0.012866205,0.0066021276,0.044759378,0.925866,0.00020033156],"about_ca_topic_score_codex":0.0022291765,"about_ca_topic_score_gemma":0.0017109596,"teacher_disagreement_score":0.011427456,"about_ca_system_score_codex":0.0013983692,"about_ca_system_score_gemma":0.001582293,"threshold_uncertainty_score":0.050369143},"labels":[],"label_agreement":null},{"id":"W4398213997","doi":"10.46298/lmcs-20(2:6)2024","title":"Executable First-Order Queries in the Logic of Information Flows","year":2024,"lang":"en","type":"article","venue":"Logical Methods in Computer Science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Bijzonder Onderzoeksfonds UGent; Vlaamse regering; Universiteit Hasselt; Fonds Wetenschappelijk Onderzoek","keywords":"Executable; Computer science; Programming language; Description logic; Order (exchange); First-order logic; Theoretical computer science","score_opus":0.04447146521058413,"score_gpt":0.3685387176116963,"score_spread":0.32406725240111217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4398213997","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":[0.022930145,0.00090353907,0.95845157,0.0032649247,0.00015153836,0.00013112726,0.00039451622,0.0007247028,0.013047861],"genre_scores_gemma":[0.46217784,0.0019528847,0.5207882,0.0021173635,0.0006995326,0.00048006905,0.0010041886,0.0003394626,0.010440515],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99507904,0.0017269021,0.00045722537,0.00090900465,0.0013455888,0.00048233866],"domain_scores_gemma":[0.9946437,0.0037239776,0.0004119348,0.00042397444,0.0005913671,0.00020510376],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0075558033,0.000874984,0.0007168722,0.0017559947,0.0015937459,0.005764126,0.0015898091,0.0016201494,0.0027863467],"category_scores_gemma":[0.008014587,0.00085124804,0.002231822,0.002109273,0.0073657664,0.010627579,0.003047964,0.0046359035,0.0004943539],"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":[0.000034575838,0.000015862146,0.00013208431,0.000054701788,0.0000103581315,0.00010945236,0.00036042256,0.004628061,0.00055536017,0.987364,0.00066477794,0.0060703964],"study_design_scores_gemma":[0.000029459356,0.00002703466,0.00008444477,0.000032167987,0.00002387282,0.00009772,0.000098678036,0.035944607,0.0013730107,0.95365804,0.008608985,0.00002188104],"about_ca_topic_score_codex":0.0052518495,"about_ca_topic_score_gemma":0.0028899754,"teacher_disagreement_score":0.0075558033,"about_ca_system_score_codex":0.0039792014,"about_ca_system_score_gemma":0.0024413688,"threshold_uncertainty_score":0.03995937},"labels":[],"label_agreement":null},{"id":"W4398599273","doi":"10.7910/dvn/6me9uj/rxwjgq","title":"Construct Tables.do","year":2020,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Construct (python library); Computer science; Programming language","score_opus":0.014971506519300503,"score_gpt":0.23465077661319894,"score_spread":0.21967927009389843,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4398599273","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00017667777,0.000107214764,0.00050195976,0.00014515361,0.000077286815,0.000032481905,0.9868672,0.008456615,0.0036353313],"genre_scores_gemma":[0.0007491266,0.00010282957,0.0013253404,0.00011939569,0.000020171863,0.00008891718,0.99540377,0.0011280143,0.0010625144],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99811184,0.00022752222,0.00020211616,0.00075367687,0.00040492587,0.00029990004],"domain_scores_gemma":[0.9953205,0.0008862027,0.0002427767,0.0022263501,0.00084142777,0.00048273694],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0015576294,0.005087656,0.001913427,0.007473019,0.0012913832,0.00499888,0.004668722,0.003130351,0.2653085],"category_scores_gemma":[0.010135577,0.0018540678,0.001989526,0.0072433855,0.00078249385,0.005933046,0.004532118,0.0025556595,0.35588655],"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":[0.000052655552,0.00002117007,0.00051557214,0.00040266768,0.000018048688,0.000009233862,0.000019971028,0.00014204315,0.00013410044,0.0008115383,0.9940309,0.0038420458],"study_design_scores_gemma":[0.0002235612,0.000022411266,0.0013252305,0.00018626475,0.000013155444,0.00004606179,0.000054684446,0.000971539,0.0009648578,0.003818125,0.9923498,0.000024228337],"about_ca_topic_score_codex":0.009752208,"about_ca_topic_score_gemma":0.015506858,"teacher_disagreement_score":0.7346915,"about_ca_system_score_codex":0.0019376554,"about_ca_system_score_gemma":0.0029116785,"threshold_uncertainty_score":0.88754535},"labels":[],"label_agreement":null},{"id":"W4399156413","doi":"10.1145/3654985","title":"Wii: Dynamic Budget Reallocation In Index Tuning","year":2024,"lang":"en","type":"article","venue":"Proceedings of the ACM on Management of Data","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Workload; Spurious relationship; Index (typography); Set (abstract data type); Process (computing); Mathematical optimization; Budget constraint; Resource allocation; Constraint (computer-aided design); Operations research; Operating system; Mathematics; Economics","score_opus":0.032554998589815504,"score_gpt":0.30317395140419895,"score_spread":0.2706189528143834,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399156413","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":[0.030578515,0.0016963229,0.9256335,0.0006408496,0.0002107261,0.000445145,0.00046217357,0.032693755,0.007639083],"genre_scores_gemma":[0.37965587,0.0006171966,0.6092455,0.0005121783,0.0001631668,0.0007158569,0.0011588976,0.0032408552,0.0046904953],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9960472,0.00086237397,0.00028865255,0.00079378625,0.0012955721,0.00071245426],"domain_scores_gemma":[0.9949787,0.0020004185,0.0005429355,0.0018059241,0.0003574446,0.0003145262],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038337323,0.0020559153,0.0015979656,0.0017442793,0.0013437849,0.003018651,0.0057807695,0.0017499136,0.006150592],"category_scores_gemma":[0.013945741,0.0012133747,0.00072020944,0.0021307515,0.001431858,0.0054889806,0.0048302836,0.0027702134,0.0025098633],"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":[0.0013669684,0.000721878,0.0058592753,0.00065804203,0.00018256044,0.0002672613,0.0007492848,0.2060806,0.047629155,0.03774072,0.04254052,0.65620375],"study_design_scores_gemma":[0.00016299548,0.0001813528,0.00097318937,0.00006143509,0.000053686323,0.0001660452,0.00011220842,0.9469015,0.01715155,0.020879844,0.013272435,0.00008381068],"about_ca_topic_score_codex":0.0041381004,"about_ca_topic_score_gemma":0.0050067957,"teacher_disagreement_score":0.006150592,"about_ca_system_score_codex":0.0017644488,"about_ca_system_score_gemma":0.0034433948,"threshold_uncertainty_score":0.020575821},"labels":[],"label_agreement":null},{"id":"W4399208580","doi":"10.14778/3659437.3659439","title":"Accelerating String-Key Learned Index Structures via Memoization-Based Incremental Training","year":2024,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Computer science; Memoization; Bottleneck; Leverage (statistics); Key (lock); Matrix decomposition; Theoretical computer science; Parallel computing; Artificial intelligence; Machine learning; Embedded system; Operating system; Eigenvalues and eigenvectors","score_opus":0.03452865552063113,"score_gpt":0.26440748166450906,"score_spread":0.22987882614387795,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399208580","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":[0.1029036,0.001456555,0.8429489,0.0004096483,0.00036589146,0.00023300856,0.00096267817,0.042843983,0.007875793],"genre_scores_gemma":[0.5372015,0.0004879992,0.44994304,0.00046958835,0.00010976449,0.00031305125,0.0029093295,0.0007243096,0.00784138],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996847,0.000025414458,0.000025070483,0.00008812884,0.00012060452,0.000056097753],"domain_scores_gemma":[0.9992269,0.0001972367,0.000063965264,0.00027065116,0.0001905655,0.00005067806],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032660546,0.00076261285,0.0007396293,0.00051569316,0.000403486,0.00076652976,0.0030117263,0.0005729964,0.0039442806],"category_scores_gemma":[0.002373518,0.0003546165,0.0004394201,0.00084811874,0.0004690791,0.003050634,0.0012659288,0.0013099225,0.0017165486],"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":[0.0004977796,0.00037402782,0.0038037905,0.00034044578,0.00010169661,0.00026323646,0.00024340715,0.14010434,0.035968766,0.011834785,0.030139772,0.7763279],"study_design_scores_gemma":[0.000036848112,0.00014259756,0.00035756163,0.0000101941505,0.00002394099,0.000101804966,0.00003203854,0.96684664,0.02276483,0.004541242,0.0051272125,0.000015131798],"about_ca_topic_score_codex":0.004285426,"about_ca_topic_score_gemma":0.006922049,"teacher_disagreement_score":0.004285426,"about_ca_system_score_codex":0.0007485799,"about_ca_system_score_gemma":0.0016199542,"threshold_uncertainty_score":0.013194919},"labels":[],"label_agreement":null},{"id":"W4399261805","doi":"10.1609/socs.v17i1.31582","title":"On Parallel External-Memory Bidirectional Search (Extended Abstract)","year":2024,"lang":"en","type":"article","venue":"Proceedings of the International Symposium on Combinatorial Search","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Israel Science Foundation; United States-Israel Binational Science Foundation; Natural Sciences and Engineering Research Council of Canada; Canadian Institute for Advanced Research","keywords":"Computer science; Parallel computing","score_opus":0.016956833660931404,"score_gpt":0.27971612351035874,"score_spread":0.2627592898494273,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399261805","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":[0.023645021,0.0013974091,0.94665915,0.0005156953,0.00016125909,0.000090816786,0.00013450401,0.0010113732,0.026384827],"genre_scores_gemma":[0.53719634,0.002200874,0.43212104,0.0008068486,0.00025741698,0.00041284398,0.0005245082,0.0005496728,0.0259305],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99942386,0.0002062096,0.000029692214,0.00007697696,0.00016048245,0.00010281234],"domain_scores_gemma":[0.99912995,0.00041913768,0.00004887682,0.00018975128,0.00017843206,0.000033956934],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010161191,0.0005071812,0.0005109259,0.0006404958,0.0005143569,0.0008296786,0.0011244082,0.00049189484,0.00793499],"category_scores_gemma":[0.0036128587,0.00020161743,0.00033959612,0.0015103316,0.00085248344,0.0019995759,0.0021463556,0.0008095329,0.0012929197],"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":[0.00064954365,0.00019201956,0.0009019999,0.00042796414,0.00006353432,0.00017984821,0.00017971294,0.22409755,0.0081655225,0.36703393,0.015505812,0.38260254],"study_design_scores_gemma":[0.00011623488,0.00011857625,0.00024723832,0.00008129297,0.00004116522,0.00015628901,0.00006219493,0.64048415,0.008715269,0.3257345,0.024217868,0.000025203713],"about_ca_topic_score_codex":0.0017277481,"about_ca_topic_score_gemma":0.0018956909,"teacher_disagreement_score":0.00793499,"about_ca_system_score_codex":0.00035123766,"about_ca_system_score_gemma":0.0007688877,"threshold_uncertainty_score":0.026545167},"labels":[],"label_agreement":null},{"id":"W4400059322","doi":"10.17615/g6d0-5n51","title":"Interpretable boosted-decision-tree analysis for the Majorana Demonstrator","year":2024,"lang":"en","type":"article","venue":"UNC Libraries","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Lawrence Berkeley National Laboratory; Natural Sciences and Engineering Research Council of Canada; Nuclear Physics; Los Alamos National Laboratory; Pacific Northwest National Laboratory; National Energy Research Scientific Computing Center; Oak Ridge National Laboratory; South Dakota Board of Regents; Laboratory Directed Research and Development; U.S. Department of Energy; Office of Science; National Science Foundation","keywords":"Decision tree; MAJORANA; Computer science; Tree (set theory); Artificial intelligence; Forestry; Mathematics; Geography; Physics; Particle physics; Combinatorics; Neutrino","score_opus":0.014306931229808544,"score_gpt":0.24890768502905009,"score_spread":0.23460075379924153,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400059322","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":[0.15322839,0.0003748559,0.8404511,0.0015917192,0.00006429204,0.00010393337,0.0005757902,0.0009291351,0.002680734],"genre_scores_gemma":[0.78669286,0.00012449511,0.20969854,0.00020698935,0.000047681937,0.00011333291,0.0010055972,0.00009646834,0.0020141175],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990024,0.0005259657,0.000038364513,0.00013845389,0.00020690315,0.00008803494],"domain_scores_gemma":[0.9933414,0.0050738123,0.00024135395,0.00043704972,0.0007747301,0.0001317435],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003668169,0.00064194965,0.00065755117,0.00082486053,0.00052050164,0.001103846,0.0010999107,0.0009183773,0.00213907],"category_scores_gemma":[0.010522536,0.00021558652,0.0007405314,0.0005463002,0.0005580588,0.0012462502,0.0006847157,0.0019786214,0.00042401932],"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":[0.0008805141,0.00044926323,0.009641667,0.0001792488,0.00010982074,0.0004390765,0.00036828217,0.67353135,0.0073383837,0.09555771,0.010213933,0.20129083],"study_design_scores_gemma":[0.000008092847,0.000018957158,0.00033178076,0.00000438112,0.0000043467526,0.000011026284,0.000015015666,0.97795105,0.0006431158,0.02066552,0.00034213293,0.000004508714],"about_ca_topic_score_codex":0.00427622,"about_ca_topic_score_gemma":0.0051422226,"teacher_disagreement_score":0.00427622,"about_ca_system_score_codex":0.0013051715,"about_ca_system_score_gemma":0.0012742141,"threshold_uncertainty_score":0.019399405},"labels":[],"label_agreement":null},{"id":"W4400227515","doi":"10.1145/3674843","title":"SQL2FPGA: Automated Acceleration of SQL Query Processing on Modern CPU-FPGA Platforms","year":2024,"lang":"en","type":"article","venue":"ACM Transactions on Reconfigurable Technology and Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"National Alliance for Accessible Golf","keywords":"Computer science; SQL; Field-programmable gate array; Acceleration; SQL/PSM; Central processing unit; Database; Operating system; Query by Example; Embedded system; Web search query; World Wide Web; Search engine","score_opus":0.023347255661126005,"score_gpt":0.2686226609111317,"score_spread":0.24527540525000568,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400227515","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":[0.1259066,0.0010571876,0.5670498,0.00034931104,0.0002039573,0.00038484138,0.002040939,0.28728807,0.015719298],"genre_scores_gemma":[0.6616801,0.000480612,0.31092468,0.00059468905,0.000066796056,0.00031831596,0.0061713983,0.012220173,0.007543223],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991961,0.00009958625,0.000054185843,0.00019103233,0.00030146926,0.00015760688],"domain_scores_gemma":[0.9993819,0.00023865611,0.00005380956,0.0001429488,0.0001390409,0.000043532527],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005717779,0.001637058,0.00044179126,0.00064922316,0.00030241124,0.0012268669,0.0013064177,0.00036602683,0.005328264],"category_scores_gemma":[0.0015211536,0.0005677509,0.0007417123,0.0004266776,0.00055169454,0.0011410933,0.00092746934,0.0010199298,0.0022031069],"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":[0.003556008,0.000694118,0.01931796,0.0010264545,0.00030303822,0.0017527272,0.0014470132,0.09762135,0.16140564,0.02579152,0.13553509,0.5515491],"study_design_scores_gemma":[0.00041372763,0.0005963575,0.004744549,0.000077589655,0.00008158225,0.00053306384,0.00026786028,0.76775074,0.16325445,0.009233427,0.05293621,0.00011037888],"about_ca_topic_score_codex":0.0055469675,"about_ca_topic_score_gemma":0.0050594606,"teacher_disagreement_score":0.0055469675,"about_ca_system_score_codex":0.00076351746,"about_ca_system_score_gemma":0.001460564,"threshold_uncertainty_score":0.017824829},"labels":[],"label_agreement":null},{"id":"W4401608896","doi":"10.1109/icdabi60145.2023.10629374","title":"Talk to your data: Enhancing Business Intelligence and Inventory Management with LLM-Driven Semantic Parsing and Text-to-SQL for Database Querying","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"University of Bahrain","keywords":"Computer science; Business intelligence; SQL; Parsing; Information retrieval; Database; Stored procedure; Natural language processing; Query by Example; Search engine","score_opus":0.06720865886490134,"score_gpt":0.30790329347454654,"score_spread":0.24069463460964519,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401608896","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":[0.014893544,0.0002853258,0.95696783,0.0022881327,0.00013660737,0.00018168491,0.0016312563,0.017449124,0.006166536],"genre_scores_gemma":[0.17440788,0.00031644214,0.8144327,0.0012165228,0.00006656733,0.00019945884,0.0041986895,0.0019290813,0.0032327033],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9957765,0.001664833,0.0003489658,0.0005628146,0.0014441756,0.00020271183],"domain_scores_gemma":[0.99268943,0.0032328763,0.00043371538,0.0023135515,0.0010756874,0.00025475762],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005389769,0.000874102,0.0007070832,0.0013689513,0.0006341506,0.0056878137,0.0024671403,0.0011359082,0.00490052],"category_scores_gemma":[0.020002045,0.00053400703,0.0014577056,0.0017003331,0.0016423113,0.009693094,0.004001192,0.0019677887,0.0023949402],"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":[0.00075298134,0.0004657542,0.008288212,0.0009952462,0.00017842122,0.0005948645,0.0036494364,0.06609584,0.015134834,0.40916955,0.04461065,0.4500642],"study_design_scores_gemma":[0.00006744961,0.00015246666,0.0009383525,0.00018861014,0.000082813145,0.00037884567,0.0010639408,0.63004535,0.025135793,0.25525007,0.08659608,0.00010026853],"about_ca_topic_score_codex":0.003954464,"about_ca_topic_score_gemma":0.0043108854,"teacher_disagreement_score":0.0056878137,"about_ca_system_score_codex":0.0015395933,"about_ca_system_score_gemma":0.0023772132,"threshold_uncertainty_score":0.028504133},"labels":[],"label_agreement":null},{"id":"W4402043623","doi":"10.14778/3681954.3682026","title":"Blueprinting the Cloud: Unifying and Automatically Optimizing Cloud Data Infrastructures with BRAD","year":2024,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Cloud computing; Computer science; Blueprint; Operating system; Engineering","score_opus":0.016380022218180846,"score_gpt":0.24502677028409897,"score_spread":0.22864674806591812,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402043623","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":[0.27481413,0.0024407476,0.6706065,0.00090731133,0.00013451588,0.0006403705,0.0006931291,0.04036662,0.009396693],"genre_scores_gemma":[0.37406224,0.00035008392,0.6209478,0.00025646907,0.000014186257,0.00015349427,0.0009749384,0.0011705098,0.002070254],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982132,0.00056204986,0.00010288159,0.00030019463,0.00057567656,0.00024601264],"domain_scores_gemma":[0.99770725,0.0010612179,0.00025280134,0.00060887635,0.00025482493,0.00011488445],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002198945,0.0020217588,0.0009332817,0.0013532727,0.00050482893,0.0016765696,0.0018812796,0.0010176764,0.0016517336],"category_scores_gemma":[0.0048048226,0.0012457086,0.0010958961,0.0010928217,0.0010657244,0.0029202867,0.0016689777,0.0016616724,0.0006851096],"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":[0.00034552568,0.00041712762,0.009309129,0.00038098585,0.00008555908,0.00020753624,0.00027687443,0.6316691,0.021874035,0.009335623,0.007139113,0.31895947],"study_design_scores_gemma":[0.00003021579,0.00010101067,0.00034680244,0.000011872009,0.00001928282,0.000029488412,0.0000604187,0.9886878,0.005307218,0.003081123,0.0023102267,0.000014572771],"about_ca_topic_score_codex":0.0093350755,"about_ca_topic_score_gemma":0.018294215,"teacher_disagreement_score":0.0093350755,"about_ca_system_score_codex":0.0017956131,"about_ca_system_score_gemma":0.0038966748,"threshold_uncertainty_score":0.018561482},"labels":[],"label_agreement":null},{"id":"W4402293703","doi":"10.1002/9781119912965.ch9","title":"Data Indexing and Filtering Techniques for Big Data Systems","year":2024,"lang":"en","type":"other","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Search engine indexing; Computer science; Big data; Information retrieval; Data mining","score_opus":0.15313666659214387,"score_gpt":0.3376372985522201,"score_spread":0.1845006319600762,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402293703","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":[0.002723854,0.012708522,0.9567968,0.0023179094,0.00081371394,0.000501067,0.001093879,0.006939369,0.01610487],"genre_scores_gemma":[0.037723146,0.015843635,0.9230123,0.001176239,0.0014749122,0.00058177934,0.0025475232,0.0009894362,0.016651005],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99559915,0.00059362425,0.00045399027,0.00048211077,0.002648665,0.00022248559],"domain_scores_gemma":[0.9950288,0.0016712149,0.00034266748,0.0017460673,0.0011039785,0.00010725888],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003455431,0.0012771654,0.0015384291,0.0054242723,0.0020728025,0.0046744533,0.0022597697,0.0014356949,0.011244842],"category_scores_gemma":[0.008283274,0.00088426634,0.0015773968,0.010311132,0.0013048211,0.006602536,0.0019682634,0.0023245732,0.007521554],"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":[0.00018040923,0.00013156996,0.0009368666,0.0011090576,0.00012160111,0.00024660805,0.00046865226,0.005486789,0.013275441,0.098834835,0.06592749,0.81328076],"study_design_scores_gemma":[0.0001144846,0.0002232763,0.0018186735,0.00051033933,0.00015326208,0.0016894937,0.00047245735,0.09317286,0.031198481,0.24560554,0.6248914,0.00014975117],"about_ca_topic_score_codex":0.0022201184,"about_ca_topic_score_gemma":0.0022146842,"teacher_disagreement_score":0.011244842,"about_ca_system_score_codex":0.0013967927,"about_ca_system_score_gemma":0.0014762896,"threshold_uncertainty_score":0.037617743},"labels":[],"label_agreement":null},{"id":"W4402293731","doi":"10.1002/9781119912965.ch8","title":"Streaming Data and Complex Event Processing","year":2024,"lang":"en","type":"other","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Event (particle physics); Computer science; Event data; Complex event processing; Data science; Programming language; Process (computing); Physics","score_opus":0.05310762498746117,"score_gpt":0.3256240673361346,"score_spread":0.2725164423486734,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402293731","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":[0.0059187533,0.06191199,0.79787326,0.008224227,0.003880647,0.00041309098,0.0012523019,0.0018869452,0.11863883],"genre_scores_gemma":[0.15376979,0.14393048,0.5534043,0.0046639987,0.009884986,0.00077659875,0.0040250723,0.0013635897,0.1281812],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989833,0.0001955153,0.00008427088,0.0001797921,0.00049730844,0.000059738482],"domain_scores_gemma":[0.9984804,0.0009738313,0.00006621742,0.00013569141,0.00028554563,0.00005843511],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010487594,0.0007186448,0.00053771393,0.0010154006,0.0005093963,0.0031239558,0.00077921833,0.0012862037,0.011659801],"category_scores_gemma":[0.0030454712,0.00043095025,0.0005422315,0.0017841528,0.0010772516,0.0028918239,0.0012706654,0.0019069967,0.0029295622],"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":[0.00009918646,0.00011694111,0.0009543135,0.0013095073,0.00006360992,0.00060238363,0.00093933864,0.019424003,0.0050735343,0.48378828,0.10470163,0.38292724],"study_design_scores_gemma":[0.000015570902,0.00006614892,0.0007926664,0.00052119204,0.000025922975,0.0007494958,0.00031902973,0.052656107,0.0038056239,0.26974672,0.671253,0.000048518694],"about_ca_topic_score_codex":0.001218783,"about_ca_topic_score_gemma":0.0009713998,"teacher_disagreement_score":0.011659801,"about_ca_system_score_codex":0.00069393206,"about_ca_system_score_gemma":0.00066417345,"threshold_uncertainty_score":0.039005935},"labels":[],"label_agreement":null},{"id":"W4402642427","doi":"10.1037/met0000689","title":"Solving variables with Monte Carlo simulation experiments: A stochastic root-solving approach.","year":2024,"lang":"en","type":"article","venue":"Psychological Methods","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Monte Carlo method; Monte Carlo method in statistical physics; Statistical physics; Applied mathematics; Computer science; Statistics; Econometrics; Mathematics; Hybrid Monte Carlo; Markov chain Monte Carlo; Physics","score_opus":0.07748759442895121,"score_gpt":0.4205089106345848,"score_spread":0.3430213162056336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402642427","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":[0.029586636,0.00026912565,0.95853627,0.0006010007,0.00012694339,0.001818524,0.00044333926,0.0006514596,0.007966701],"genre_scores_gemma":[0.27001408,0.0003278002,0.7202843,0.00035428043,0.00007334251,0.006511974,0.00050409493,0.0001865606,0.0017435632],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9606832,0.035300653,0.0006928362,0.0017687848,0.001214756,0.00033971437],"domain_scores_gemma":[0.61430955,0.36554906,0.008272648,0.009171704,0.0018392937,0.00085780915],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04517084,0.0014999462,0.001903445,0.0015956599,0.0009329124,0.0030398532,0.003984951,0.0028615773,0.021196207],"category_scores_gemma":[0.29434055,0.0011133803,0.0012691788,0.0027367899,0.0026505913,0.004427531,0.002286328,0.0042414363,0.0009723989],"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":[0.0014441333,0.0012589832,0.005058652,0.00061446,0.00084630435,0.0001138354,0.001000873,0.43376508,0.0004130033,0.45103985,0.0071214265,0.09732338],"study_design_scores_gemma":[0.0005010419,0.00026999527,0.0006217112,0.0001334957,0.0001393473,0.000030464635,0.00010767658,0.7453506,0.00042426607,0.25001284,0.0023667938,0.000041795538],"about_ca_topic_score_codex":0.004843419,"about_ca_topic_score_gemma":0.0064152996,"teacher_disagreement_score":0.04517084,"about_ca_system_score_codex":0.0020854957,"about_ca_system_score_gemma":0.0029553107,"threshold_uncertainty_score":0.2388891},"labels":[],"label_agreement":null},{"id":"W4403635895","doi":"10.1109/tse.2024.3484586","title":"Refactoring-Aware Block Tracking in Commit History","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Software Engineering","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Code refactoring; Computer science; Commit; Block (permutation group theory); Programming language; Software engineering; Database; Software","score_opus":0.01952255369704392,"score_gpt":0.23632262482171681,"score_spread":0.2168000711246729,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403635895","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":[0.20872681,0.004636234,0.53194755,0.00067003095,0.00035252364,0.0005572064,0.01546168,0.23207062,0.005577373],"genre_scores_gemma":[0.5561901,0.0011065201,0.39164034,0.00031622322,0.00011536499,0.00034231527,0.03949745,0.006205742,0.004585888],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9964485,0.0005239846,0.00040020648,0.0010786146,0.0013628597,0.00018581057],"domain_scores_gemma":[0.9809871,0.006446318,0.0028352195,0.005057792,0.0042660553,0.00040743843],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002606224,0.001185277,0.0008518598,0.005468538,0.00045700764,0.001804505,0.0013542862,0.00091253896,0.0012774057],"category_scores_gemma":[0.02717429,0.00064801,0.00064564095,0.0028660176,0.00040210233,0.0031124197,0.0015965686,0.0010625679,0.0018153285],"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":[0.00055393076,0.000213141,0.100355454,0.0013889411,0.00017678471,0.0005748653,0.0015222853,0.019327296,0.030917685,0.0034634597,0.042727903,0.79877836],"study_design_scores_gemma":[0.00017408645,0.0006171641,0.082888514,0.00055505143,0.0003086576,0.0018565671,0.0006498584,0.66435117,0.13895647,0.014057836,0.09528254,0.00030212261],"about_ca_topic_score_codex":0.00678495,"about_ca_topic_score_gemma":0.010923259,"teacher_disagreement_score":0.00678495,"about_ca_system_score_codex":0.00046382204,"about_ca_system_score_gemma":0.001670305,"threshold_uncertainty_score":0.0137832165},"labels":[],"label_agreement":null},{"id":"W4403730653","doi":"10.23952/jnva.8.2024.6.03","title":"A random-key GRASP for combinatorial optimization","year":2024,"lang":"en","type":"article","venue":"Journal of Nonlinear and Variational Analysis","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Universidade de Pernambuco; Universidade Federal de Pernambuco; Fundação de Amparo à Ciência e Tecnologia do Estado de Pernambuco; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"GRASP; Key (lock); Computer science; Combinatorial optimization; Theoretical computer science; Algorithm; Software engineering; Computer security","score_opus":0.009905021172891314,"score_gpt":0.26743825049622993,"score_spread":0.2575332293233386,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403730653","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":[0.0054783197,0.00030652233,0.9901494,0.00015418396,0.00004126741,0.00005109524,0.00003460774,0.00036171274,0.0034230114],"genre_scores_gemma":[0.28135684,0.00057478034,0.71154594,0.0003743789,0.000081220634,0.0004611314,0.00021439968,0.00045172672,0.0049395333],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990181,0.0003554332,0.00004264806,0.00015354728,0.00033970023,0.000090599555],"domain_scores_gemma":[0.9990614,0.000487818,0.00009222683,0.0001590415,0.00014459588,0.00005499867],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012910609,0.0011398162,0.0013107449,0.00097036327,0.00052119547,0.0010963979,0.0015387813,0.0014236532,0.0032480808],"category_scores_gemma":[0.0031120116,0.00054074015,0.0011889107,0.00096215756,0.0014069155,0.0022551,0.0016666449,0.0016249956,0.0008013273],"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":[0.00007999719,0.00005847944,0.00024783664,0.00015852094,0.00004917029,0.00005578625,0.000049738224,0.8604214,0.0035675904,0.08319285,0.0019568796,0.050161745],"study_design_scores_gemma":[0.000021867025,0.00007708528,0.000042649244,0.000019678511,0.000012226873,0.00003182122,0.000011915058,0.9695199,0.0008238171,0.027224839,0.0022010312,0.00001320183],"about_ca_topic_score_codex":0.0012202837,"about_ca_topic_score_gemma":0.0009840848,"teacher_disagreement_score":0.0032480808,"about_ca_system_score_codex":0.0011857406,"about_ca_system_score_gemma":0.00157713,"threshold_uncertainty_score":0.010865986},"labels":[],"label_agreement":null},{"id":"W4403821479","doi":"10.48550/arxiv.2410.00838","title":"Better Boosting of Communication Oracles, or Not","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Boosting (machine learning); Computer science; Artificial intelligence","score_opus":0.1017879772693964,"score_gpt":0.21472373057783853,"score_spread":0.11293575330844213,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403821479","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":[0.06751088,0.0019899763,0.8810418,0.011620881,0.00065436785,0.0002791301,0.0003399883,0.0049888263,0.03157409],"genre_scores_gemma":[0.7214285,0.00088292174,0.255514,0.004691278,0.0011544835,0.00047301716,0.00055815093,0.0009925578,0.014305059],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9853196,0.005570321,0.00058330246,0.0033688764,0.0031443003,0.0020135962],"domain_scores_gemma":[0.95552635,0.01878613,0.0015614253,0.01991915,0.0028765604,0.0013303568],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015431484,0.0014706803,0.0026952315,0.0007780953,0.0017458925,0.004434251,0.0036031357,0.0036715863,0.009715677],"category_scores_gemma":[0.050583012,0.0012337504,0.0016930188,0.0012253491,0.0040576067,0.02279589,0.005969882,0.009140537,0.004029369],"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":[0.0013597211,0.00074693677,0.0025160913,0.00043761195,0.000112321075,0.00013324156,0.00053367624,0.045855694,0.014706479,0.8106853,0.02114661,0.101766355],"study_design_scores_gemma":[0.00032287024,0.0003797856,0.0011751663,0.000107703236,0.000112103604,0.00029780448,0.00013858799,0.36268693,0.0205233,0.590952,0.0232144,0.000089429224],"about_ca_topic_score_codex":0.0014284172,"about_ca_topic_score_gemma":0.0010528027,"teacher_disagreement_score":0.015431484,"about_ca_system_score_codex":0.002358415,"about_ca_system_score_gemma":0.0026403454,"threshold_uncertainty_score":0.08161044},"labels":[],"label_agreement":null},{"id":"W4404130423","doi":"10.1145/3695835","title":"Computing A Well-Representative Summary of Conjunctive Query Results","year":2024,"lang":"en","type":"article","venue":"Proceedings of the ACM on Management of Data","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Conjunctive query; Boolean conjunctive query; Computer science; Query optimization; Query expansion; Information retrieval; Theoretical computer science; Web search query; Sargable; Data mining; Search engine; Relational database","score_opus":0.052421053948253374,"score_gpt":0.32084299875920125,"score_spread":0.2684219448109479,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404130423","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":[0.12023291,0.001285593,0.8692543,0.0008227641,0.00009340795,0.0002964107,0.0020094144,0.0045837783,0.0014213934],"genre_scores_gemma":[0.40213993,0.0005813177,0.58961916,0.00020750533,0.00016875486,0.00023631615,0.0054775877,0.0003584222,0.0012109805],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99651766,0.0004423555,0.0005561039,0.0009240954,0.0012649632,0.00029484864],"domain_scores_gemma":[0.9915677,0.003514435,0.0011407828,0.0017974216,0.0016127464,0.00036696135],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025030738,0.0015338259,0.0028599603,0.002158416,0.0008257327,0.0036531007,0.0023298287,0.001562423,0.0020033838],"category_scores_gemma":[0.017379662,0.0007958171,0.0011603119,0.0035117636,0.00083130674,0.0063770353,0.0018423541,0.0013802095,0.0011630506],"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":[0.0022342494,0.00051512435,0.013603477,0.0016048938,0.0005805501,0.00082893367,0.0017321219,0.34882572,0.06622405,0.025096007,0.015311513,0.52344334],"study_design_scores_gemma":[0.000059565544,0.00032946415,0.0022847063,0.000037220714,0.00013523051,0.00038636907,0.00045458396,0.94372463,0.023980442,0.024680609,0.003879738,0.00004740794],"about_ca_topic_score_codex":0.0021994978,"about_ca_topic_score_gemma":0.003327274,"teacher_disagreement_score":0.0036531007,"about_ca_system_score_codex":0.0012439626,"about_ca_system_score_gemma":0.0016549132,"threshold_uncertainty_score":0.013237655},"labels":[],"label_agreement":null},{"id":"W4404134085","doi":"10.1145/3649329.3658489","title":"Engineering an Efficient Preprocessor for Model Counting","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"National Research Foundation Singapore","keywords":"Computer science; Preprocessor; Programming language","score_opus":0.017583885768897925,"score_gpt":0.2694032089683168,"score_spread":0.2518193231994189,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404134085","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":[0.015901435,0.00049217354,0.9421699,0.0004404009,0.00017564319,0.00031321877,0.00092893536,0.036319368,0.0032588693],"genre_scores_gemma":[0.09609418,0.00029478018,0.89193743,0.00073631725,0.0001285088,0.0003745373,0.003636193,0.0030348317,0.0037633197],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99558073,0.0008847807,0.0003441299,0.001180684,0.001494584,0.0005149985],"domain_scores_gemma":[0.98801744,0.005237506,0.00068228965,0.004175457,0.0016525919,0.00023468283],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024685864,0.0021369266,0.0016185205,0.0018806797,0.0009077153,0.0036317362,0.0042582024,0.0014411014,0.012789147],"category_scores_gemma":[0.012795914,0.0016881902,0.0032701495,0.0025786944,0.0010261143,0.006565857,0.0033941015,0.004238332,0.006020559],"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":[0.0014777543,0.0007639615,0.0046564196,0.0015067869,0.00031354924,0.0006117031,0.0004980803,0.07846972,0.050646156,0.09851843,0.06647956,0.6960579],"study_design_scores_gemma":[0.00020823382,0.00048025526,0.00094522187,0.00015506384,0.0001619223,0.00050769345,0.00017893447,0.7997579,0.08141464,0.0772826,0.038800944,0.00010655766],"about_ca_topic_score_codex":0.0028736468,"about_ca_topic_score_gemma":0.0060103144,"teacher_disagreement_score":0.012789147,"about_ca_system_score_codex":0.0017507809,"about_ca_system_score_gemma":0.0043687676,"threshold_uncertainty_score":0.042783976},"labels":[],"label_agreement":null},{"id":"W4404181435","doi":"10.14778/3685800.3685894","title":"Demonstration of the VeriEQL Equivalence Checker for Complex SQL Queries","year":2024,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Programming language; Computer science; Equivalence (formal languages); SQL; SQL/PSM; Database; Stored procedure; Information retrieval; Query by Example; Mathematics; Discrete mathematics; Web search query","score_opus":0.02881900024655679,"score_gpt":0.2677268580327518,"score_spread":0.23890785778619503,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404181435","genre_codex":"methods","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04982857,0.0002558432,0.88954806,0.0020705117,0.00040429094,0.00040246444,0.0013601447,0.048801776,0.0073284646],"genre_scores_gemma":[0.52368224,0.00025897112,0.46136978,0.00222539,0.00016994508,0.00044267447,0.0028094486,0.0047568753,0.0042845826],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9787724,0.0063833673,0.0018746763,0.0026707589,0.008314859,0.0019839485],"domain_scores_gemma":[0.9415306,0.03611302,0.0017466496,0.013439334,0.0065159965,0.0006543318],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012074768,0.0011602057,0.00095624424,0.001375407,0.0015239959,0.0038099685,0.004953372,0.0023933358,0.008913528],"category_scores_gemma":[0.048192494,0.0014127292,0.0023106313,0.0010978978,0.0055511408,0.009109594,0.009176444,0.005701418,0.0022834092],"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":[0.0038143133,0.0022180942,0.014934069,0.0015476377,0.0004337449,0.003075618,0.002696302,0.084019184,0.16613698,0.3663023,0.06386595,0.2909558],"study_design_scores_gemma":[0.00091275835,0.0006307596,0.0011784786,0.00020536319,0.00017783849,0.0006168956,0.00028106655,0.56772244,0.262283,0.13266282,0.033113807,0.0002147417],"about_ca_topic_score_codex":0.0069583734,"about_ca_topic_score_gemma":0.0055294014,"teacher_disagreement_score":0.012074768,"about_ca_system_score_codex":0.002280068,"about_ca_system_score_gemma":0.005235538,"threshold_uncertainty_score":0.06385827},"labels":[],"label_agreement":null},{"id":"W4406659575","doi":"10.1016/b978-0-340-65292-3.50033-8","title":"10.1016/b978-0-340-65292-3.50033-8","year":2000,"lang":"en","type":"book-chapter","venue":"Time to knit","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"String (physics); Computer science; Physics; Theoretical physics","score_opus":0.009318465613322249,"score_gpt":0.18037123987420645,"score_spread":0.1710527742608842,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406659575","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00024325612,0.00043041818,0.0013629739,0.00033383246,0.00016113475,0.000061305196,0.0010388592,0.0014798851,0.99488825],"genre_scores_gemma":[0.0005428444,0.00023847632,0.00046607494,0.00015048246,0.000036841247,0.00004360619,0.0006385589,0.0003077425,0.99757534],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993524,0.00003586476,0.0000416528,0.00024801522,0.00019638133,0.00012568968],"domain_scores_gemma":[0.9975751,0.00075348065,0.00017593682,0.00036779125,0.0004049614,0.0007228063],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0012767251,0.0028618155,0.0019170757,0.0023569681,0.00171614,0.0053067855,0.0035029943,0.0054214927,0.98527664],"category_scores_gemma":[0.002036335,0.0011260648,0.0010798336,0.0028001799,0.0014306628,0.0061979517,0.0040469454,0.0024865356,0.9933947],"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":[0.00017072323,0.0001547256,0.00049364544,0.0004688028,0.00002443249,0.00013266415,0.000095008916,0.00045590827,0.002459253,0.006484835,0.3896083,0.59945166],"study_design_scores_gemma":[0.00002815891,0.0000710771,0.000663636,0.00031728085,0.000013499509,0.00022012874,0.00010982965,0.00021987571,0.00041866457,0.0011043304,0.99681324,0.0000202311],"about_ca_topic_score_codex":0.003529974,"about_ca_topic_score_gemma":0.002750417,"teacher_disagreement_score":0.014723361,"about_ca_system_score_codex":0.001095006,"about_ca_system_score_gemma":0.00083204376,"threshold_uncertainty_score":0.0210011},"labels":[],"label_agreement":null},{"id":"W4406734274","doi":"10.4230/lipics.icdt.2025.15","title":"Query Repairs","year":2025,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Deutsche Forschungsgemeinschaft; National Science Foundation","keywords":"Computer science; Information retrieval","score_opus":0.038907759889149365,"score_gpt":0.2869774644331143,"score_spread":0.24806970454396493,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406734274","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":[0.053227164,0.001504889,0.93312955,0.0021240131,0.00020969797,0.00055834785,0.0009670064,0.00426125,0.0040181],"genre_scores_gemma":[0.5695687,0.00072093727,0.41660908,0.0010320988,0.00034523997,0.0004684183,0.0023117862,0.0010225261,0.007921339],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.97209924,0.007823709,0.0024540431,0.005896566,0.01003227,0.0016941902],"domain_scores_gemma":[0.8919139,0.065060444,0.006842258,0.02321942,0.010955054,0.002008942],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01596083,0.001701423,0.0028764273,0.0021266078,0.0020122086,0.0040186653,0.0061827237,0.0036358142,0.0069893682],"category_scores_gemma":[0.09080753,0.0011211049,0.0022199738,0.0022069719,0.00341832,0.009608839,0.0060023153,0.004546094,0.0019563865],"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":[0.002964044,0.0010293375,0.01363784,0.0029876216,0.0005433594,0.0020739955,0.006585414,0.19117692,0.038932957,0.19033705,0.028303128,0.52142835],"study_design_scores_gemma":[0.00018602457,0.0010114611,0.0026220172,0.00028635334,0.00034581247,0.0023027128,0.00243382,0.6917108,0.04043806,0.22111724,0.037366875,0.000178757],"about_ca_topic_score_codex":0.005003965,"about_ca_topic_score_gemma":0.0031178365,"teacher_disagreement_score":0.01596083,"about_ca_system_score_codex":0.002312029,"about_ca_system_score_gemma":0.0030691423,"threshold_uncertainty_score":0.08440995},"labels":[],"label_agreement":null},{"id":"W4406789555","doi":"10.48550/arxiv.2501.13596","title":"New Oracles and Labeling Schemes for Vertex Cut Queries","year":2025,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Azrieli Foundation; European Commission","keywords":"Vertex (graph theory); Computer science; Mathematics; Theoretical computer science; Graph","score_opus":0.04378213249893968,"score_gpt":0.30329863829587994,"score_spread":0.25951650579694024,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406789555","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":[0.036801215,0.0011519813,0.94174916,0.0029177193,0.00023111425,0.0004235327,0.0017257315,0.0050555123,0.009944053],"genre_scores_gemma":[0.5006622,0.0009415267,0.47863364,0.0019011628,0.00059547846,0.0009985203,0.0037621977,0.0013536164,0.011151676],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9859174,0.0038285805,0.0010781824,0.0030250007,0.004102795,0.0020480128],"domain_scores_gemma":[0.95728105,0.02027807,0.0024789008,0.017063895,0.0018502654,0.0010478423],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008208187,0.0016771604,0.002788177,0.0015276682,0.0017351311,0.0070552113,0.007520579,0.0043805293,0.012849357],"category_scores_gemma":[0.03625541,0.0015296253,0.0023929065,0.0042527756,0.005053768,0.031107778,0.008985484,0.011083079,0.0026436185],"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":[0.0017915803,0.00045730255,0.0020244443,0.00063567545,0.00009373048,0.00021810413,0.0010599007,0.092216566,0.0076757283,0.7423962,0.013746082,0.13768479],"study_design_scores_gemma":[0.00030230786,0.0002500673,0.00036450272,0.00010920438,0.000092920134,0.000272109,0.00020241442,0.3175062,0.00808444,0.6623595,0.010354178,0.00010215348],"about_ca_topic_score_codex":0.0026910128,"about_ca_topic_score_gemma":0.0024004835,"teacher_disagreement_score":0.012849357,"about_ca_system_score_codex":0.0051669953,"about_ca_system_score_gemma":0.004204771,"threshold_uncertainty_score":0.043409526},"labels":[],"label_agreement":null},{"id":"W4406890913","doi":"10.1109/tkde.2025.3527380","title":"Computing Shapley Values for Dynamic Data","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Knowledge and Data Engineering","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"National Natural Science Foundation of China","keywords":"Computer science; Data mining","score_opus":0.031760860730233605,"score_gpt":0.31844716841906573,"score_spread":0.28668630768883213,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406890913","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":[0.042587996,0.00026023007,0.9512601,0.0005085382,0.00007096573,0.00015754245,0.00025246403,0.00033749267,0.00456468],"genre_scores_gemma":[0.56651235,0.00040931228,0.42568332,0.0003333021,0.00012634903,0.00036468057,0.001015503,0.00023691662,0.005318293],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9962792,0.0013733428,0.0002330244,0.0009796894,0.00079797953,0.00033681237],"domain_scores_gemma":[0.9886777,0.0076191747,0.00067202083,0.0015498642,0.0009243737,0.000556885],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005810303,0.0016506762,0.0022837352,0.0022746443,0.0015617098,0.004341244,0.0029183824,0.002131727,0.006887015],"category_scores_gemma":[0.025541136,0.0008974206,0.0015241976,0.0031024108,0.0023772663,0.009851926,0.0044760886,0.003601003,0.0008336588],"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":[0.00023614835,0.00019628686,0.0016293062,0.00024737327,0.0001753221,0.0001493951,0.00034572821,0.52546054,0.0015833497,0.35478565,0.003804387,0.11138655],"study_design_scores_gemma":[0.000022326982,0.00003641158,0.00010706276,0.000017820072,0.0000124805565,0.000028686136,0.00004821745,0.60698974,0.00067426154,0.39122462,0.0008224511,0.000015823733],"about_ca_topic_score_codex":0.0016395568,"about_ca_topic_score_gemma":0.0024424815,"teacher_disagreement_score":0.006887015,"about_ca_system_score_codex":0.0035868357,"about_ca_system_score_gemma":0.0024340139,"threshold_uncertainty_score":0.030728221},"labels":[],"label_agreement":null},{"id":"W4407070067","doi":"10.5206/tba.v6i1.18951","title":"Mining for Some Sort of Continuity","year":2025,"lang":"en","type":"article","venue":"tba Journal of Art Media and Visual Culture","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"sort; Computer science; Information retrieval","score_opus":0.014821208112709927,"score_gpt":0.31221057877905334,"score_spread":0.2973893706663434,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407070067","genre_codex":"empirical","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":[0.52213186,0.0045648976,0.41599596,0.010732723,0.00081519864,0.0005540491,0.024603643,0.0043604486,0.016241215],"genre_scores_gemma":[0.7529232,0.0010228372,0.20142442,0.0011532445,0.00063260755,0.0003032579,0.034940716,0.00036610418,0.007233674],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9949668,0.00035978627,0.0005076121,0.0024076311,0.0013097725,0.0004482641],"domain_scores_gemma":[0.9886431,0.005063085,0.0011700275,0.0030552952,0.0014387667,0.00062972785],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002117098,0.0010206009,0.0015171935,0.0052130907,0.0023105666,0.0034331048,0.0034456702,0.0023197478,0.009557936],"category_scores_gemma":[0.019264434,0.0009740462,0.0022110583,0.005948004,0.001490632,0.009941674,0.002508733,0.0038260242,0.0027201744],"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":[0.0024739718,0.0018837819,0.23986457,0.0021463379,0.0014075566,0.006019011,0.0035054283,0.020219639,0.03359013,0.08743583,0.06470303,0.5367507],"study_design_scores_gemma":[0.0004397914,0.0016772808,0.09743614,0.0008551497,0.0011023689,0.00855676,0.0069613317,0.3629465,0.041043364,0.34246308,0.13625896,0.0002593087],"about_ca_topic_score_codex":0.0030633616,"about_ca_topic_score_gemma":0.004650956,"teacher_disagreement_score":0.009557936,"about_ca_system_score_codex":0.00074801303,"about_ca_system_score_gemma":0.0018240234,"threshold_uncertainty_score":0.031974494},"labels":[],"label_agreement":null},{"id":"W4408818601","doi":"10.63485/2y4sr-haw86","title":"Background on CLA support for IRs","year":2007,"lang":"en","type":"preprint","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Business","score_opus":0.06494334957661553,"score_gpt":0.34002444373160867,"score_spread":0.27508109415499316,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408818601","genre_codex":"other","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006220324,0.018942472,0.029464992,0.12179785,0.0017420632,0.0003498437,0.0015797267,0.0014832307,0.81841946],"genre_scores_gemma":[0.22663002,0.04714964,0.097112015,0.04345125,0.008369782,0.0007049683,0.006771453,0.00204295,0.567768],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9883866,0.003047743,0.00092712586,0.0014579034,0.004024944,0.0021556437],"domain_scores_gemma":[0.9709999,0.011396268,0.0011674415,0.004137416,0.009373524,0.0029254535],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.014046481,0.0007675447,0.0005233819,0.0061892085,0.0058343434,0.014561401,0.0045477757,0.0055607883,0.12451022],"category_scores_gemma":[0.035245933,0.00073235855,0.0008382294,0.008158606,0.0058329,0.015162466,0.0066340487,0.0052803042,0.03560872],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000058856782,0.00015144738,0.0015516483,0.00062557997,0.000012953778,0.00033801602,0.004046767,0.0008487606,0.0007269392,0.5806567,0.19418254,0.21679983],"study_design_scores_gemma":[0.000005539964,0.000016563128,0.00046722416,0.0006291537,0.0000042096935,0.00017744741,0.0013631391,0.00042279137,0.0003601221,0.022844808,0.9736893,0.000019649664],"about_ca_topic_score_codex":0.061803415,"about_ca_topic_score_gemma":0.039610513,"teacher_disagreement_score":0.99156326,"about_ca_system_score_codex":0.00843673,"about_ca_system_score_gemma":0.012268165,"threshold_uncertainty_score":0.41652822},"labels":[],"label_agreement":null},{"id":"W4408854317","doi":"10.32920/28669544.v1","title":"Canadian Time Machine","year":2025,"lang":"en","type":"preprint","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Business","score_opus":0.007547568364727046,"score_gpt":0.2343226262005837,"score_spread":0.22677505783585664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408854317","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014001054,0.0012259763,0.0034929959,0.012883194,0.0064607244,0.00009252539,0.033265214,0.005186271,0.9359929],"genre_scores_gemma":[0.005896767,0.0006551104,0.0015401983,0.0005755079,0.00037134287,0.000022410906,0.008369035,0.00093798136,0.98163176],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99856085,0.000036037254,0.00002535574,0.00024082427,0.0008249274,0.00031201376],"domain_scores_gemma":[0.9955141,0.00013164729,0.00008863289,0.0004276247,0.002562992,0.0012749628],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009998146,0.0010325847,0.00071269553,0.0021958412,0.0072161388,0.0069272043,0.0012222164,0.0013365861,0.5551091],"category_scores_gemma":[0.0040014293,0.00050821126,0.0005269427,0.0049027037,0.0011735623,0.0032537575,0.0018643013,0.0021946274,0.26150393],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001788466,0.0000048398424,0.00014571798,0.000012393837,0.0000012302202,0.00001703558,0.000024128143,0.00006419339,0.00011736437,0.0067453342,0.97996646,0.012883405],"study_design_scores_gemma":[0.0000030561273,0.0000024114017,0.0003718926,0.000007171753,9.776031e-7,0.000009733466,0.000043891698,0.00018773068,0.00012707838,0.0004452415,0.9987948,0.000005966689],"about_ca_topic_score_codex":0.84159076,"about_ca_topic_score_gemma":0.90579987,"teacher_disagreement_score":0.5551091,"about_ca_system_score_codex":0.019032186,"about_ca_system_score_gemma":0.028814744,"threshold_uncertainty_score":0.6345829},"labels":[],"label_agreement":null},{"id":"W4409310616","doi":"10.1145/3720436","title":"IncIDFA: An Efficient and Generic Algorithm for Incremental Iterative Dataflow Analysis","year":2025,"lang":"en","type":"article","venue":"Proceedings of the ACM on Programming Languages","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Science and Engineering Research Board; IBM Canada","keywords":"Dataflow; Algorithm; Computer science; Parallel computing","score_opus":0.013148370357277754,"score_gpt":0.29266248176762827,"score_spread":0.27951411141035054,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409310616","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":[0.0027060395,0.00013946605,0.9797086,0.000109695146,0.00006144386,0.00017015633,0.00018400287,0.0148141,0.0021065085],"genre_scores_gemma":[0.049206078,0.0001493044,0.9439449,0.00017865119,0.000042246425,0.00032589812,0.0010774323,0.0023508028,0.0027246107],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9984376,0.00020830824,0.00014006777,0.000327778,0.0006660672,0.00022020144],"domain_scores_gemma":[0.9970464,0.0012825613,0.00016050304,0.0007280969,0.0006877074,0.000094749375],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017030864,0.0021333524,0.001041251,0.00245549,0.0010661148,0.0021964961,0.0032923315,0.0016146271,0.009282737],"category_scores_gemma":[0.007922081,0.0010031812,0.0022004189,0.0012625295,0.0017231758,0.003306691,0.004502345,0.0026655723,0.0045746784],"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":[0.0005063084,0.00018034405,0.0030968923,0.00069219794,0.00013455936,0.00040269838,0.000532449,0.07520683,0.023652311,0.06504758,0.033679985,0.79686785],"study_design_scores_gemma":[0.00021775639,0.00021121981,0.00054559286,0.00017710711,0.00008681407,0.00048352848,0.00019748269,0.80829084,0.036818143,0.0984377,0.05441203,0.0001217489],"about_ca_topic_score_codex":0.003621381,"about_ca_topic_score_gemma":0.0060111955,"teacher_disagreement_score":0.009282737,"about_ca_system_score_codex":0.0014540808,"about_ca_system_score_gemma":0.003471578,"threshold_uncertainty_score":0.031053841},"labels":[],"label_agreement":null},{"id":"W4410049332","doi":"10.1145/3680256.3721313","title":"DMML: A Machine-learning Performance Model for Data Migration","year":2025,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"IBM (Canada); York University","funders":"","keywords":"Computer science; Data modeling; Artificial intelligence; Machine learning; Database","score_opus":0.04217106096514987,"score_gpt":0.29308691776124696,"score_spread":0.25091585679609707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410049332","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":[0.0951495,0.000685931,0.88900656,0.0017768397,0.00017984337,0.0003164971,0.0025383902,0.0063691367,0.0039772806],"genre_scores_gemma":[0.7885907,0.00042006432,0.20130114,0.0005669314,0.00013330171,0.0008640361,0.0030416811,0.0003970669,0.004685068],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99864286,0.0005178311,0.00008781629,0.00032765942,0.00026138863,0.00016242004],"domain_scores_gemma":[0.9954261,0.0029772096,0.00044898543,0.0002935353,0.00075151416,0.000102670194],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034628971,0.0015533661,0.00093876745,0.0016712865,0.0005096195,0.0016308677,0.0026740702,0.0019162447,0.0021416622],"category_scores_gemma":[0.0118029,0.00058415835,0.0009840482,0.0012968348,0.00067777827,0.0019229065,0.0007764084,0.002291788,0.0009779274],"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":[0.000054137297,0.0000821765,0.0019909525,0.00003509238,0.00002648634,0.000017798951,0.000020999269,0.9803197,0.00027390104,0.0015765554,0.0016284881,0.013973809],"study_design_scores_gemma":[0.0000034227362,0.000012367615,0.0002030166,0.0000041896983,0.0000029506953,0.000005767971,0.0000032740588,0.9984042,0.00013659507,0.0009878734,0.00023267558,0.0000036542465],"about_ca_topic_score_codex":0.015639603,"about_ca_topic_score_gemma":0.011701627,"teacher_disagreement_score":0.015639603,"about_ca_system_score_codex":0.0022519287,"about_ca_system_score_gemma":0.0012405992,"threshold_uncertainty_score":0.031097114},"labels":[],"label_agreement":null},{"id":"W4411141648","doi":"10.1145/3725241","title":"Output-Optimal Algorithms for Join-Aggregate Queries","year":2025,"lang":"en","type":"article","venue":"Proceedings of the ACM on Management of Data","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Join (topology); Aggregate (composite); Computer science; Algorithm; Theoretical computer science; Mathematics; Combinatorics","score_opus":0.06301675797609008,"score_gpt":0.3193127812564128,"score_spread":0.25629602328032275,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411141648","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":[0.041534714,0.001066912,0.93523663,0.0005878003,0.00011483612,0.00022550346,0.0010930034,0.009313324,0.010827305],"genre_scores_gemma":[0.36144364,0.0007742166,0.62116784,0.00065856404,0.00032640764,0.00054139184,0.004926794,0.0023089703,0.007852244],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.991699,0.0012270834,0.0009802621,0.0017777069,0.0030433189,0.0012725779],"domain_scores_gemma":[0.99010324,0.004178574,0.0006068093,0.0035609733,0.0012300235,0.00032042403],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036039967,0.001711749,0.0017805877,0.0014837867,0.0013460873,0.0052784965,0.003008788,0.0016681484,0.009325603],"category_scores_gemma":[0.013654062,0.00088356814,0.0019805583,0.0033567331,0.0014831864,0.010811654,0.005173522,0.0027885444,0.0039592623],"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":[0.004086814,0.0009916375,0.004244715,0.001530201,0.00026203305,0.00022671255,0.0016036232,0.119201705,0.04411084,0.27541992,0.033173125,0.51514876],"study_design_scores_gemma":[0.0003238949,0.00036362396,0.000888912,0.000088224384,0.00013434868,0.00034258552,0.00040748564,0.58417636,0.032464966,0.36375436,0.016971154,0.000084069885],"about_ca_topic_score_codex":0.0018048545,"about_ca_topic_score_gemma":0.0021819635,"teacher_disagreement_score":0.009325603,"about_ca_system_score_codex":0.0024971934,"about_ca_system_score_gemma":0.0022923911,"threshold_uncertainty_score":0.03119719},"labels":[],"label_agreement":null},{"id":"W4411267937","doi":"10.1145/3729319","title":"Graphiti: Bridging Graph and Relational Database Queries","year":2025,"lang":"en","type":"article","venue":"Proceedings of the ACM on Programming Languages","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Computer science; SQL; Relational database; Programming language; Graph database; Theoretical computer science; Relational model; Embedding; Conjunctive query; Equivalence (formal languages); Data definition language; Graph; Database; Artificial intelligence; Mathematics; Discrete mathematics","score_opus":0.011738424468465536,"score_gpt":0.2616002780033099,"score_spread":0.24986185353484439,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411267937","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":[0.013162083,0.000111630965,0.95326185,0.0006303834,0.00006685627,0.00029067698,0.0005939335,0.028782882,0.0030996865],"genre_scores_gemma":[0.31336126,0.00027402968,0.67457867,0.001183885,0.00008317533,0.000330133,0.0022756031,0.004074809,0.0038383177],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.98859954,0.0032594735,0.0010658978,0.002580618,0.0034791513,0.0010152048],"domain_scores_gemma":[0.9817046,0.010427472,0.0013575961,0.0045990394,0.0016116826,0.00029952702],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0069223507,0.0013556328,0.0010456055,0.003049393,0.0016425609,0.00430327,0.0050619817,0.0021138135,0.0062966356],"category_scores_gemma":[0.021447467,0.0015894701,0.002648011,0.0019901206,0.005283852,0.013778917,0.005947372,0.004495178,0.0014691708],"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":[0.0015428092,0.0005637735,0.007893685,0.0011038127,0.0003114813,0.0018360956,0.003287883,0.052036006,0.03722276,0.61576957,0.028419849,0.2500123],"study_design_scores_gemma":[0.00018909498,0.00040954963,0.001679207,0.0002882058,0.0003148519,0.0012558976,0.0008763925,0.4154043,0.1424712,0.36603376,0.07085886,0.00021874423],"about_ca_topic_score_codex":0.009688966,"about_ca_topic_score_gemma":0.008985458,"teacher_disagreement_score":0.009688966,"about_ca_system_score_codex":0.002888666,"about_ca_system_score_gemma":0.0040494446,"threshold_uncertainty_score":0.036609292},"labels":[],"label_agreement":null},{"id":"W4411329653","doi":"10.1016/j.jss.2025.112529","title":"Continuous learning of event-based systems by using pre-conceptual schemas","year":2025,"lang":"en","type":"article","venue":"Journal of Systems and Software","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"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 Toronto","funders":"Instituto Colombiano de Crédito Educativo y Estudios Técnicos en el Exterior; Fondation L’Oréal; University of Toronto; Ministerio de Ciencia, Tecnología e Innovación","keywords":"Event (particle physics); Computer science; Natural language processing; Artificial intelligence; Physics","score_opus":0.011573487388826114,"score_gpt":0.25955515404616,"score_spread":0.24798166665733387,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411329653","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":[0.043266796,0.00010585881,0.9543058,0.00021633679,0.000022575103,0.00006978847,0.00010603714,0.00072816334,0.0011786433],"genre_scores_gemma":[0.70431834,0.00020226018,0.29360998,0.00009637011,0.000024850977,0.00012435103,0.0005052448,0.00009782744,0.0010207826],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980856,0.0006755719,0.00018004747,0.00054763036,0.00040954683,0.00010164633],"domain_scores_gemma":[0.9801657,0.014724479,0.00078410143,0.0022119118,0.0017548479,0.00035889723],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003916343,0.0004759886,0.00048399623,0.00074264756,0.00036063063,0.0023677624,0.0021207125,0.0007653725,0.0031304534],"category_scores_gemma":[0.026072744,0.00051872677,0.000841614,0.0006459472,0.0010464729,0.0070300526,0.0024188303,0.0021157386,0.000402718],"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":[0.0008367111,0.0006437263,0.013324973,0.00037092587,0.00020452305,0.00030399417,0.002303453,0.27941105,0.007895714,0.16765961,0.0023158009,0.5247295],"study_design_scores_gemma":[0.000048490503,0.000094586976,0.00055856403,0.000039305825,0.000041606785,0.000047804653,0.00021022376,0.92516696,0.004498762,0.06769398,0.0015814784,0.000018233119],"about_ca_topic_score_codex":0.0025990312,"about_ca_topic_score_gemma":0.0035173215,"teacher_disagreement_score":0.003916343,"about_ca_system_score_codex":0.0010460842,"about_ca_system_score_gemma":0.0014503781,"threshold_uncertainty_score":0.02071184},"labels":[],"label_agreement":null},{"id":"W4411337257","doi":"10.1109/sp61157.2025.00032","title":"TreePIR: Efficient Private Retrieval of Merkle Proofs via Tree Colorings with Fast Indexing and Zero Storage Overhead","year":2025,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Australian Research Council","keywords":"Search engine indexing; Computer science; Overhead (engineering); Merkle tree; Tree (set theory); Zero-knowledge proof; Mathematical proof; Parallel computing; Algorithm; Information retrieval; Mathematics; Cryptography; Combinatorics; Operating system","score_opus":0.00631531205370263,"score_gpt":0.22307407614101052,"score_spread":0.21675876408730788,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411337257","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":[0.045643657,0.00095871865,0.9284138,0.0006636718,0.00018630024,0.00056592026,0.0009141725,0.0136966435,0.008957114],"genre_scores_gemma":[0.5984253,0.0005929316,0.38791645,0.00041614796,0.00011593619,0.0004111565,0.0015476923,0.0010080799,0.009566183],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99659866,0.0006693434,0.00022646671,0.0005165815,0.0014510757,0.0005378828],"domain_scores_gemma":[0.9885994,0.0023426928,0.00081691897,0.006718824,0.0010552503,0.0004668817],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022341383,0.0006311932,0.0013140787,0.0011607286,0.0011867824,0.002763167,0.002834758,0.0010341243,0.00563304],"category_scores_gemma":[0.009350629,0.0006201043,0.00085280876,0.0020672842,0.0013461341,0.0070716157,0.0046293684,0.0020096947,0.0031400567],"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":[0.0016115811,0.0005626019,0.0017872853,0.00080627715,0.00012276588,0.00059101696,0.00092571526,0.07940605,0.072376415,0.22141354,0.041945387,0.57845134],"study_design_scores_gemma":[0.00042570397,0.0005004341,0.000545169,0.00008096647,0.00006763492,0.0009573956,0.00027777522,0.7071957,0.05875978,0.19938521,0.03162141,0.00018294131],"about_ca_topic_score_codex":0.0018864637,"about_ca_topic_score_gemma":0.00195745,"teacher_disagreement_score":0.00563304,"about_ca_system_score_codex":0.0017116823,"about_ca_system_score_gemma":0.004418418,"threshold_uncertainty_score":0.018844366},"labels":[],"label_agreement":null},{"id":"W4411371930","doi":"10.1016/j.jpdc.2025.105134","title":"QPOPSS: Query and Parallelism Optimized Space-Saving for finding frequent stream elements","year":2025,"lang":"en","type":"article","venue":"Journal of Parallel and Distributed Computing","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"ASTER","funders":"H2020 Marie Skłodowska-Curie Actions; HORIZON EUROPE Framework Programme; Vetenskapsrådet; Energimyndigheten; European Commission","keywords":"Computer science; Parallel computing; Parallelism (grammar); Space (punctuation); Query optimization; Database; Operating system","score_opus":0.016478283240236122,"score_gpt":0.28756216858391154,"score_spread":0.2710838853436754,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411371930","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":[0.068515584,0.0016144053,0.91547346,0.00040869333,0.00025294608,0.0003196291,0.0012567159,0.010044306,0.002114259],"genre_scores_gemma":[0.34598297,0.00066642667,0.64561725,0.00018480145,0.00018311622,0.00032528237,0.003270498,0.00067674933,0.0030929404],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983216,0.00024539215,0.00016089188,0.000268041,0.0008346034,0.00016944745],"domain_scores_gemma":[0.9964109,0.0013387402,0.00032318546,0.0011541983,0.00054014585,0.00023289924],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016975793,0.0010631786,0.0013587051,0.0014457213,0.00065195194,0.0019528666,0.0031332192,0.00061450567,0.0025307885],"category_scores_gemma":[0.00693492,0.00055664673,0.00078579923,0.0024192412,0.0010410636,0.002531651,0.0027885563,0.0010139878,0.0010649703],"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":[0.001837324,0.0004883691,0.012311078,0.0007417551,0.00028403767,0.0002746306,0.0006538822,0.19976737,0.040795136,0.021537459,0.032006416,0.6893026],"study_design_scores_gemma":[0.00014953414,0.00022892746,0.000938062,0.000018840497,0.000040366114,0.00016181405,0.00011111712,0.9695952,0.011499208,0.01133766,0.0058942265,0.000025086896],"about_ca_topic_score_codex":0.00458013,"about_ca_topic_score_gemma":0.006125977,"teacher_disagreement_score":0.00458013,"about_ca_system_score_codex":0.0008630731,"about_ca_system_score_gemma":0.003140584,"threshold_uncertainty_score":0.009106934},"labels":[],"label_agreement":null},{"id":"W4411374479","doi":"10.1145/3722212.3724450","title":"Rel: A Programming Language for Relational Data","year":2025,"lang":"en","type":"preprint","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Programming language; Relational database; First-generation programming language; Programming paradigm; Database","score_opus":0.07988886116019198,"score_gpt":0.3570106729641249,"score_spread":0.2771218118039329,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411374479","genre_codex":"methods","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0013790977,0.00060056685,0.97547066,0.0006066983,0.00016383782,0.00012404169,0.0012006705,0.014427873,0.006026576],"genre_scores_gemma":[0.056317784,0.0015206207,0.9103518,0.002209102,0.0003779735,0.00069476484,0.004597523,0.007165775,0.016764605],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9970898,0.00066609646,0.00041370804,0.0005688578,0.0009938442,0.00026774706],"domain_scores_gemma":[0.9980318,0.0007002595,0.00026344354,0.0005385217,0.00031284784,0.00015315831],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032311894,0.00094039046,0.00080537534,0.0010396151,0.00085211516,0.0032780794,0.0031671321,0.001165253,0.010107004],"category_scores_gemma":[0.004633858,0.0010787032,0.001637754,0.0016371157,0.0021170054,0.008240119,0.0040669865,0.003930963,0.0065709352],"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":[0.000220168,0.000094998344,0.00048682425,0.001373555,0.00005871765,0.0004985611,0.0016116962,0.0041302233,0.0106072705,0.7322153,0.08680305,0.16189966],"study_design_scores_gemma":[0.0001015876,0.0001323583,0.00023261484,0.00022884955,0.000052713905,0.0015411368,0.0002665597,0.016576936,0.008551687,0.21947238,0.7527524,0.00009073606],"about_ca_topic_score_codex":0.0012305833,"about_ca_topic_score_gemma":0.0013737738,"teacher_disagreement_score":0.010107004,"about_ca_system_score_codex":0.0006749372,"about_ca_system_score_gemma":0.001586768,"threshold_uncertainty_score":0.03381133},"labels":[],"label_agreement":null},{"id":"W4411551997","doi":"10.1109/icse55347.2025.00152","title":"Synthesizing Document Database Queries Using Collection Abstractions","year":2025,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Database; Information retrieval; Programming language","score_opus":0.01922017920185965,"score_gpt":0.2998179507101469,"score_spread":0.28059777150828724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411551997","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":[0.039286852,0.0005186342,0.94210124,0.00022226505,0.000052832464,0.00034348885,0.0011726208,0.012138328,0.0041637137],"genre_scores_gemma":[0.2128293,0.0006155231,0.77855635,0.00019048803,0.00003535763,0.00037259187,0.0034686332,0.0016785354,0.0022532817],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9978325,0.00044862152,0.0002851563,0.00042841848,0.00087710825,0.00012817014],"domain_scores_gemma":[0.9970131,0.0017678072,0.00015866142,0.0004949111,0.0005116771,0.0000538078],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013912785,0.0010059611,0.0008042606,0.0011152204,0.0005393809,0.001761499,0.0015867437,0.0007151142,0.0027681526],"category_scores_gemma":[0.005931615,0.00047888895,0.0013854488,0.0013373386,0.00080595305,0.0024713168,0.0019194576,0.0010916725,0.0008547812],"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":[0.00073348486,0.00035594843,0.004177215,0.0037093493,0.00018008339,0.0016239439,0.0017980256,0.13102818,0.13862294,0.09251599,0.021796577,0.6034582],"study_design_scores_gemma":[0.00020659844,0.0004460927,0.0007265736,0.00016957089,0.00019243195,0.001217459,0.00060372736,0.64658153,0.21966091,0.0499864,0.08011269,0.00009599468],"about_ca_topic_score_codex":0.0015122225,"about_ca_topic_score_gemma":0.0021109139,"teacher_disagreement_score":0.0027681526,"about_ca_system_score_codex":0.0007235814,"about_ca_system_score_gemma":0.0011214985,"threshold_uncertainty_score":0.009260416},"labels":[],"label_agreement":null},{"id":"W4412819486","doi":"10.1007/978-3-031-89033-8_28","title":"NetCDF","year":2025,"lang":"en","type":"book-chapter","venue":"CMS/CAIMS books in mathematics","topic":"Advanced Database Systems and Queries","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":"NetCDF; Computer science; Programming language","score_opus":0.02099023536611967,"score_gpt":0.24978120208072488,"score_spread":0.22879096671460522,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412819486","genre_codex":"other","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005838333,0.00078203616,0.014422254,0.0007922959,0.0007413935,0.00014393005,0.025823481,0.034223773,0.922487],"genre_scores_gemma":[0.0015308912,0.0005363284,0.005121295,0.00038957558,0.00016439555,0.000085602805,0.026712755,0.0063560335,0.95910305],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9994783,0.000044424294,0.000025657657,0.00011776786,0.00026954812,0.00006437785],"domain_scores_gemma":[0.9989911,0.00013023384,0.000035356676,0.00029082038,0.0003522006,0.00020031091],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00067094585,0.0016362929,0.0010489094,0.004783621,0.0013976276,0.0052162716,0.0022021648,0.0013253518,0.7628246],"category_scores_gemma":[0.0019174553,0.00077169825,0.00084616046,0.0036770483,0.00036588655,0.004050762,0.002500752,0.0013074097,0.7676744],"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":[0.000045230794,0.00003604518,0.00011555012,0.00011431562,0.00000459057,0.000026822956,0.000023636661,0.000116436415,0.0007146822,0.0049056145,0.79379356,0.20010348],"study_design_scores_gemma":[0.000010800033,0.000006721382,0.00014938049,0.000035448913,0.000003553626,0.000055359993,0.0000128161755,0.00026497585,0.000490635,0.0020638832,0.9968983,0.000008125012],"about_ca_topic_score_codex":0.0046180994,"about_ca_topic_score_gemma":0.0062445635,"teacher_disagreement_score":0.7628246,"about_ca_system_score_codex":0.0011945019,"about_ca_system_score_gemma":0.0012228884,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W4412886783","doi":"10.18653/v1/2025.acl-long.141","title":"Position-aware Automatic Circuit Discovery","year":2025,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Azrieli Foundation; European Commission; Open Philanthropy Project","keywords":"Computer science; Position (finance); Artificial intelligence","score_opus":0.008868999516609459,"score_gpt":0.24652842059285243,"score_spread":0.23765942107624297,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412886783","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":[0.025074821,0.0008360193,0.9263264,0.0007866909,0.000090957794,0.0003699214,0.009395701,0.033556443,0.0035630614],"genre_scores_gemma":[0.16054337,0.00047689697,0.8106635,0.00043493373,0.000058466285,0.0003990533,0.022175878,0.0022492898,0.0029986496],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99774617,0.00033737283,0.00020733384,0.00075327506,0.0007913196,0.00016451917],"domain_scores_gemma":[0.9947319,0.002474453,0.00032432686,0.0016091834,0.00074968126,0.00011045509],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012820917,0.0010977022,0.0010601499,0.0034644492,0.0009054228,0.0026703824,0.0031223095,0.0014592557,0.0075967577],"category_scores_gemma":[0.010251229,0.0008149306,0.002721415,0.0027029198,0.0008315425,0.0058930633,0.0031506198,0.0016605747,0.0028684596],"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":[0.00042176442,0.00022833192,0.012613494,0.0020847635,0.00023581552,0.00076934625,0.0008790493,0.03718103,0.054533176,0.083920375,0.05830456,0.7488284],"study_design_scores_gemma":[0.000116347845,0.0001295912,0.002197894,0.00014566688,0.00016321885,0.0010255218,0.00044186632,0.68388444,0.066423155,0.18559968,0.05979445,0.00007815576],"about_ca_topic_score_codex":0.0023595619,"about_ca_topic_score_gemma":0.0059899553,"teacher_disagreement_score":0.0075967577,"about_ca_system_score_codex":0.0015601298,"about_ca_system_score_gemma":0.002058202,"threshold_uncertainty_score":0.025413692},"labels":[],"label_agreement":null},{"id":"W4413361263","doi":"10.1109/icde65448.2025.00363","title":"LineageX: A Column Lineage Extraction System for SQL","year":2025,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Column (typography); Computer science; SQL; Extraction (chemistry); Lineage (genetic); Database; Chromatography; Chemistry; Computer network","score_opus":0.010876922970559939,"score_gpt":0.2927652775393659,"score_spread":0.28188835456880595,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413361263","genre_codex":"software","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":[0.0067100995,0.00028145063,0.39482683,0.00040628447,0.00008193536,0.00032618674,0.021853102,0.5696157,0.005898424],"genre_scores_gemma":[0.10711953,0.00089324923,0.6641602,0.0014906367,0.00009772273,0.0011447674,0.11118719,0.096580625,0.017326187],"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.998602,0.00022144514,0.00018246041,0.00029400742,0.0006021524,0.000098006996],"domain_scores_gemma":[0.99753857,0.00092104956,0.00020323753,0.00072440354,0.00049553614,0.000117289484],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023858766,0.0013730689,0.00058878947,0.001837221,0.00089476956,0.0029022663,0.0023483336,0.0008466993,0.01790504],"category_scores_gemma":[0.008958633,0.0013253613,0.0011298438,0.0017750256,0.0008224569,0.005965682,0.004140351,0.0019948627,0.008499336],"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":[0.001585162,0.00031680966,0.016660491,0.0018792481,0.00026890042,0.00094095385,0.003314572,0.00988421,0.035546925,0.0434266,0.50279593,0.38338023],"study_design_scores_gemma":[0.0003159255,0.00022340963,0.0073373527,0.00042772695,0.000110259316,0.0011115341,0.0007795331,0.21105726,0.09741912,0.061671797,0.6191935,0.00035252172],"about_ca_topic_score_codex":0.00497253,"about_ca_topic_score_gemma":0.006759749,"teacher_disagreement_score":0.01790504,"about_ca_system_score_codex":0.0008898859,"about_ca_system_score_gemma":0.0024400302,"threshold_uncertainty_score":0.059898257},"labels":[],"label_agreement":null},{"id":"W4413374215","doi":"10.1007/978-3-031-99872-0_19","title":"SProBench: Stream Processing Benchmark for High Performance Computing Infrastructure","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Benchmark (surveying); Stream processing; Distributed computing; Parallel computing; Cartography","score_opus":0.009209012185325566,"score_gpt":0.2398295776841203,"score_spread":0.23062056549879473,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413374215","genre_codex":"software","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":[0.19776183,0.0049131922,0.17676601,0.0029268456,0.0034028066,0.001423986,0.13450105,0.3634075,0.11489682],"genre_scores_gemma":[0.3735774,0.0017769231,0.2742167,0.0010694186,0.00031252543,0.0011102227,0.28763044,0.020142063,0.040164266],"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9979157,0.00026827774,0.00017596634,0.00025664826,0.0011131294,0.0002703401],"domain_scores_gemma":[0.9974837,0.00052557146,0.000106903375,0.000440251,0.0011892366,0.00025439393],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015357499,0.0017931218,0.0006394184,0.0016477564,0.00078311446,0.0013228196,0.0037470881,0.00086848857,0.011188556],"category_scores_gemma":[0.005411595,0.00063298,0.0006290526,0.0034164349,0.00049475883,0.0020954132,0.0009519604,0.001909686,0.0037038603],"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":[0.0017035118,0.0004984931,0.0024448084,0.0010873682,0.00018363363,0.00016418636,0.00015334708,0.050166745,0.015989862,0.011930208,0.80156916,0.114108674],"study_design_scores_gemma":[0.0013292871,0.0008612113,0.008469539,0.00016823004,0.00019693385,0.00029116345,0.00026346228,0.61477315,0.102626815,0.023497544,0.24735476,0.00016790195],"about_ca_topic_score_codex":0.01616269,"about_ca_topic_score_gemma":0.017769335,"teacher_disagreement_score":0.01616269,"about_ca_system_score_codex":0.0015341436,"about_ca_system_score_gemma":0.0030556023,"threshold_uncertainty_score":0.03742951},"labels":[],"label_agreement":null},{"id":"W4413755882","doi":"10.14778/3718057.3718059","title":"Esc: An Early-Stopping Checker for Budget-Aware Index Tuning","year":2025,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Index (typography); Computer science; Model checking; Programming language","score_opus":0.012348128414331278,"score_gpt":0.2604888289779635,"score_spread":0.24814070056363222,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413755882","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":[0.036647473,0.00095936557,0.814797,0.0006746485,0.00047024767,0.0006062952,0.0008159691,0.13952267,0.005506308],"genre_scores_gemma":[0.4110975,0.00035084446,0.5666103,0.0014201789,0.00024197936,0.00062825694,0.001977284,0.012243309,0.0054303664],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9873346,0.0032466992,0.0014453285,0.0020580387,0.0048595313,0.0010557793],"domain_scores_gemma":[0.96046424,0.02015448,0.0029209065,0.010937893,0.0042704944,0.0012520466],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010851969,0.0025709574,0.0018344189,0.0021824194,0.001272061,0.0036020246,0.004858888,0.0021700314,0.005727821],"category_scores_gemma":[0.04916378,0.001762623,0.0016063956,0.0011142121,0.0020391964,0.0057983524,0.0048013697,0.0037943888,0.0027932434],"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":[0.004822856,0.0013500348,0.030307353,0.0014256157,0.0005556486,0.0012316897,0.0012997763,0.13935988,0.074634865,0.042417638,0.076159716,0.626435],"study_design_scores_gemma":[0.000377676,0.00035977576,0.0018411516,0.00011742317,0.00014444605,0.00028554862,0.0001237082,0.9223467,0.03544196,0.019661762,0.019150874,0.00014886123],"about_ca_topic_score_codex":0.0029524066,"about_ca_topic_score_gemma":0.004335444,"teacher_disagreement_score":0.010851969,"about_ca_system_score_codex":0.001251427,"about_ca_system_score_gemma":0.003908501,"threshold_uncertainty_score":0.057391346},"labels":[],"label_agreement":null},{"id":"W4413825196","doi":"10.14778/3734839.3734849","title":"Accio: Bolt-on Query Federation","year":2025,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Russian federation; Computer science; Information retrieval; Geography; Regional science","score_opus":0.005557855411297835,"score_gpt":0.22850257909836866,"score_spread":0.22294472368707083,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413825196","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":[0.05730551,0.0013946624,0.6682981,0.0013443186,0.0008509272,0.0007828317,0.0017771561,0.25133365,0.016912818],"genre_scores_gemma":[0.44472638,0.0008120393,0.503323,0.002480467,0.0005184979,0.0006457047,0.014135332,0.020002188,0.013356431],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9879736,0.001866802,0.0012577946,0.001974084,0.005442995,0.0014846796],"domain_scores_gemma":[0.98047054,0.0023233488,0.0007606718,0.012701196,0.002629614,0.0011145874],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008981935,0.0021707045,0.0014732827,0.0020218925,0.002007473,0.0057345545,0.0071431478,0.0018272758,0.004903167],"category_scores_gemma":[0.016406188,0.0017041408,0.0024825353,0.0023686502,0.0019281555,0.008869699,0.011173242,0.0038999913,0.0026012708],"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":[0.0066275317,0.0019931062,0.038925882,0.0019040265,0.0016029689,0.0017666542,0.0053013754,0.042513434,0.114623606,0.07070595,0.24891013,0.4651253],"study_design_scores_gemma":[0.00076314696,0.0011264768,0.009831591,0.00020293635,0.0005944353,0.0019586745,0.0016232625,0.54405665,0.10960177,0.036879253,0.29274583,0.0006160698],"about_ca_topic_score_codex":0.012532781,"about_ca_topic_score_gemma":0.008611553,"teacher_disagreement_score":0.012532781,"about_ca_system_score_codex":0.0019733207,"about_ca_system_score_gemma":0.004500308,"threshold_uncertainty_score":0.047501564},"labels":[],"label_agreement":null},{"id":"W4413907849","doi":"10.5530/irc.2.1.7","title":"Comparative Analysis of Relational and Non-Relational Database Models: A Case Study on Travel Booking Systems","year":2025,"lang":"en","type":"article","venue":"Information Research Communications","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Relational database; Relational model; Computer science; Entity–relationship model; Database; Database design; Information retrieval","score_opus":0.25064401892497823,"score_gpt":0.44456075221250213,"score_spread":0.1939167332875239,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413907849","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":[0.9777208,0.0008968335,0.008078925,0.0007281226,0.00002357399,0.00035438885,0.00042752796,0.00014795148,0.011621936],"genre_scores_gemma":[0.9845823,0.00061598263,0.012734977,0.00007088223,0.000008810713,0.000070296366,0.0003961034,0.000033032502,0.0014876539],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99534756,0.002346999,0.00029191232,0.0003320632,0.0013390236,0.0003425008],"domain_scores_gemma":[0.98525697,0.010089365,0.0006542662,0.0009826738,0.0025252718,0.0004913845],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0042935354,0.00030375196,0.00036415533,0.001468654,0.0012052722,0.0031422505,0.0012055064,0.0009770632,0.0021020554],"category_scores_gemma":[0.011468954,0.00022649548,0.00053556025,0.0028113078,0.0007478826,0.0030639295,0.0008536116,0.0006927107,0.0003722622],"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":[0.002735331,0.0051264395,0.3462815,0.0053218026,0.0004948957,0.018383505,0.0415496,0.1534215,0.017652506,0.07741546,0.021623028,0.30999443],"study_design_scores_gemma":[0.00034839136,0.0063172258,0.18672638,0.0011647302,0.0005143066,0.008627973,0.15166463,0.49246913,0.025847608,0.01419571,0.111817986,0.00030595934],"about_ca_topic_score_codex":0.015964523,"about_ca_topic_score_gemma":0.017320462,"teacher_disagreement_score":0.015964523,"about_ca_system_score_codex":0.0026976578,"about_ca_system_score_gemma":0.001376256,"threshold_uncertainty_score":0.03174317},"labels":[],"label_agreement":null},{"id":"W4414497721","doi":"10.5120/ijca2025925604","title":"A Survey of Query Refinement Techniques From Neural Architectures to Practical Applications","year":2025,"lang":"en","type":"article","venue":"International Journal of Computer Applications","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Query optimization; Artificial neural network; Query language; Database query; Query expansion","score_opus":0.021249173264323736,"score_gpt":0.355831128757543,"score_spread":0.3345819554932193,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414497721","genre_codex":"methods","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009784845,0.17712645,0.7969557,0.0018872934,0.00025960943,0.0003155729,0.0005022749,0.0022857299,0.010882599],"genre_scores_gemma":[0.1800584,0.2652794,0.5369764,0.0016098309,0.0010155259,0.00054031535,0.0021041352,0.00051133096,0.0119045945],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99860555,0.0003730039,0.00018881756,0.00024007076,0.00050326536,0.00008930115],"domain_scores_gemma":[0.9977602,0.0012197299,0.00009447989,0.00034205202,0.00054513285,0.000038459733],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024919405,0.0012213006,0.0010614966,0.001994521,0.00036495953,0.0016028044,0.002099623,0.0010665207,0.0043897787],"category_scores_gemma":[0.007159402,0.0006500723,0.001099099,0.0029919127,0.00062687165,0.003128722,0.0013048446,0.0016330191,0.0015974309],"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":[0.00014336173,0.00010554211,0.0010887104,0.0021821368,0.0001105146,0.00009128857,0.00021713946,0.026944397,0.0053293724,0.02951933,0.011447358,0.92282087],"study_design_scores_gemma":[0.000094655734,0.000678966,0.0029216476,0.0014721099,0.00035983243,0.001472545,0.0004954169,0.6110444,0.020741716,0.10148673,0.2590343,0.00019775661],"about_ca_topic_score_codex":0.0058972263,"about_ca_topic_score_gemma":0.005028015,"teacher_disagreement_score":0.0058972263,"about_ca_system_score_codex":0.0011513721,"about_ca_system_score_gemma":0.0014099268,"threshold_uncertainty_score":0.014685333},"labels":[],"label_agreement":null},{"id":"W4414687920","doi":"10.1109/ccwc62904.2025.10903878","title":"An LLM-Based Framework for Synthetic Data Generation","year":2025,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Key (lock); Synthetic data; Differential privacy; Scarcity; Information privacy; Identification (biology)","score_opus":0.06413203143772486,"score_gpt":0.3591671951627064,"score_spread":0.2950351637249815,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414687920","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":[0.0010820063,0.00005222067,0.9955049,0.00020672297,0.00002987782,0.00009652242,0.0003423985,0.0017993937,0.00088602846],"genre_scores_gemma":[0.08820868,0.00014438095,0.9059401,0.00032601337,0.000056240893,0.00056602864,0.0023803043,0.00069588324,0.0016823505],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9959292,0.0016934288,0.00027275068,0.00057557056,0.0013483705,0.00018075234],"domain_scores_gemma":[0.9927434,0.0038459075,0.00037182862,0.0018872842,0.00087169785,0.00027989017],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008014677,0.00075499143,0.0006356215,0.0014567696,0.00078052847,0.0027935887,0.0033675982,0.0014223205,0.0059559345],"category_scores_gemma":[0.023597458,0.000615052,0.0016140928,0.0013296454,0.0017725443,0.0028480415,0.005385766,0.002694706,0.0017298327],"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":[0.0003433205,0.00020705555,0.0025256004,0.00033017315,0.000112301095,0.0005455097,0.00059748814,0.44514737,0.0090743685,0.382232,0.019089576,0.13979535],"study_design_scores_gemma":[0.000029454905,0.000031880132,0.000089951674,0.000022877806,0.0000064303986,0.00009854718,0.000036856185,0.9005049,0.0025018337,0.08443444,0.012224442,0.000018417613],"about_ca_topic_score_codex":0.003105323,"about_ca_topic_score_gemma":0.0046190135,"teacher_disagreement_score":0.008014677,"about_ca_system_score_codex":0.0014482912,"about_ca_system_score_gemma":0.0023124008,"threshold_uncertainty_score":0.042386174},"labels":[],"label_agreement":null},{"id":"W4414856476","doi":"10.1109/tsmc.2025.3612434","title":"A Spanning Tree-Induced Method to Derive Weights From Fuzzy Preference Relations: A Monte Carlo Simulation-Based Investigation","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Natural Science Foundation of China","keywords":"Spanning tree; Monte Carlo method; Minimum spanning tree; Logarithm; Equivalence (formal languages); Weight; Fuzzy logic","score_opus":0.03463362853336261,"score_gpt":0.2768043526713014,"score_spread":0.24217072413793878,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414856476","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":[0.009340287,0.000046664947,0.98994935,0.000037388574,0.00000649773,0.00002901015,0.000017990063,0.000036089878,0.00053674745],"genre_scores_gemma":[0.25999117,0.00018529354,0.73860276,0.000058178393,0.00002430613,0.00018272745,0.0001484108,0.00006222689,0.00074493885],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986161,0.0007750081,0.000055148386,0.0001463875,0.0003446475,0.000062793],"domain_scores_gemma":[0.99218833,0.0063077607,0.00035656322,0.00044062064,0.00059177453,0.000114973074],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033296566,0.0005667569,0.0006940726,0.0014030829,0.0004180697,0.0007714829,0.0011171518,0.00071747095,0.0023161506],"category_scores_gemma":[0.013267308,0.0003736608,0.001086617,0.0015413793,0.0007191861,0.0022990152,0.000880545,0.0011819032,0.00021481173],"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":[0.00007658734,0.00007883784,0.0017656296,0.00011807521,0.00009283894,0.00008997709,0.00019558085,0.77208954,0.0021354544,0.14889143,0.00068784214,0.073778085],"study_design_scores_gemma":[0.0000041507433,0.00001197674,0.00007570017,0.000004191528,0.0000041131157,0.000017825832,0.0000066273114,0.98526603,0.0002003252,0.014233541,0.0001705645,0.000004942154],"about_ca_topic_score_codex":0.0026981477,"about_ca_topic_score_gemma":0.0028441213,"teacher_disagreement_score":0.0033296566,"about_ca_system_score_codex":0.0007436759,"about_ca_system_score_gemma":0.0012148636,"threshold_uncertainty_score":0.01760906},"labels":[],"label_agreement":null},{"id":"W4414940134","doi":"10.59350/0mtak-78e86","title":"A Julia Package for the Data Retriever","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Software; Labrador Retriever; Software package; R package","score_opus":0.0793849882461397,"score_gpt":0.3253732437131759,"score_spread":0.24598825546703618,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414940134","genre_codex":"software","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":"software","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007864648,0.00040017467,0.36824316,0.0003611662,0.0004330441,0.00042140007,0.026313342,0.5907263,0.0123149],"genre_scores_gemma":[0.011643647,0.0008392837,0.36501387,0.0016794135,0.00053589564,0.001797087,0.113975465,0.47501075,0.029504558],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99483985,0.0007467747,0.00088221376,0.00082164846,0.0021258784,0.0005835711],"domain_scores_gemma":[0.98834085,0.0033484548,0.0006272506,0.0036287836,0.0034934983,0.0005611837],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005073977,0.0031248648,0.0027901318,0.0036958053,0.0013311545,0.006432239,0.005952446,0.0020442838,0.15360847],"category_scores_gemma":[0.023879392,0.00385173,0.0044350075,0.0033473375,0.0010677213,0.0060694134,0.006084263,0.0068857465,0.24375914],"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":[0.0007865101,0.0001322533,0.0010925174,0.0011069062,0.0002545377,0.00037659908,0.00036122647,0.001393884,0.007704012,0.015265754,0.8602984,0.11122748],"study_design_scores_gemma":[0.0004576167,0.00007875916,0.0010884656,0.00024626643,0.00010768428,0.00075872696,0.000116376075,0.012875744,0.020497423,0.023082698,0.94040436,0.0002859319],"about_ca_topic_score_codex":0.002515947,"about_ca_topic_score_gemma":0.0019811343,"teacher_disagreement_score":0.15360847,"about_ca_system_score_codex":0.0014959538,"about_ca_system_score_gemma":0.002623106,"threshold_uncertainty_score":0.51387155},"labels":[],"label_agreement":null},{"id":"W4415736396","doi":"10.1007/979-8-8688-2007-6_2","title":"Modeling Product and Cart State with Signals","year":2025,"lang":"en","type":"book-chapter","venue":"Apress pocket guides.","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brampton Civic Hospital","funders":"","keywords":"Cart; Product (mathematics); State (computer science); Service (business); Product-service system; Key (lock)","score_opus":0.020405632667433334,"score_gpt":0.23836818119446393,"score_spread":0.2179625485270306,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415736396","genre_codex":"methods","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":[0.020460162,0.0004356477,0.92407167,0.00047158689,0.00012211734,0.000072894356,0.00060047983,0.0017889914,0.051976457],"genre_scores_gemma":[0.5580332,0.0020597125,0.35309622,0.00044381773,0.00016543659,0.000350997,0.0015874289,0.00093060266,0.08333251],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99966526,0.00007693523,0.000013932757,0.00009247542,0.00011281956,0.00003848275],"domain_scores_gemma":[0.9996258,0.00019463315,0.000031557585,0.00006306838,0.00006805915,0.000016794844],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042425122,0.00062649685,0.00039078694,0.0004968262,0.00048604317,0.0025833345,0.0012636213,0.0010005516,0.010989077],"category_scores_gemma":[0.0015835117,0.00051981275,0.00072508445,0.00058740296,0.0010377389,0.0034683894,0.0010187203,0.0013918226,0.002689338],"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":[0.000080142294,0.00007348143,0.000973891,0.00010731252,0.000021684766,0.00016278627,0.00042566052,0.4296262,0.004342265,0.5256929,0.0049209804,0.033572603],"study_design_scores_gemma":[0.000010276579,0.00003073039,0.00016189307,0.000027763042,0.000015424708,0.000042344363,0.000052750303,0.88871837,0.001953277,0.08680881,0.022157973,0.000020375104],"about_ca_topic_score_codex":0.0077735893,"about_ca_topic_score_gemma":0.007066545,"teacher_disagreement_score":0.010989077,"about_ca_system_score_codex":0.0009659054,"about_ca_system_score_gemma":0.0007350123,"threshold_uncertainty_score":0.03676212},"labels":[],"label_agreement":null},{"id":"W4416037522","doi":"10.18653/v1/2025.emnlp-industry.33","title":"QuackIR: Retrieval in DuckDB and Other Relational Database Management Systems","year":2025,"lang":"","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Relational database; Data retrieval; Entity–relationship model; Database design; Information system; Data management; Relational database management system; Relational model","score_opus":0.024007297687297296,"score_gpt":0.27773186318960824,"score_spread":0.25372456550231093,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416037522","genre_codex":"software","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":[0.025100328,0.0065878113,0.35548618,0.002247427,0.0007986055,0.0022212646,0.026669374,0.5480757,0.03281335],"genre_scores_gemma":[0.14651865,0.0017421768,0.71617854,0.0027279544,0.00015665466,0.00093773886,0.08365966,0.025532952,0.022545598],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9897947,0.0019252434,0.0015322308,0.0018124614,0.0041970373,0.0007383578],"domain_scores_gemma":[0.9904785,0.0025927403,0.00044054206,0.0037913157,0.0020214315,0.0006755113],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011027827,0.0014966839,0.0015793985,0.003547857,0.0023881225,0.005896016,0.007637214,0.0022327194,0.017016979],"category_scores_gemma":[0.022948176,0.0018182322,0.0012891485,0.005130216,0.0015636106,0.011099647,0.007125314,0.002703402,0.014258464],"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":[0.0032786955,0.000999105,0.0047617108,0.003500497,0.0004250375,0.00078048866,0.0018302058,0.01095066,0.020951014,0.044867024,0.540956,0.36669955],"study_design_scores_gemma":[0.001196408,0.00072597404,0.0055010677,0.00048175963,0.00022422202,0.0015266723,0.0009990587,0.21023041,0.06494093,0.034973487,0.67845744,0.0007425946],"about_ca_topic_score_codex":0.06272438,"about_ca_topic_score_gemma":0.051532142,"teacher_disagreement_score":0.06272438,"about_ca_system_score_codex":0.00354283,"about_ca_system_score_gemma":0.0044140425,"threshold_uncertainty_score":0.12471855},"labels":[],"label_agreement":null},{"id":"W4416285692","doi":"10.1186/s40537-025-01307-2","title":"UniqueNOSD: a novel framework for NoSQL over SQL databases","year":2025,"lang":"en","type":"article","venue":"Journal Of Big Data","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada; University of Windsor","keywords":"NoSQL; SQL; Scalability; Relational database; Relational database management system; Redundancy (engineering); Consistency (knowledge bases); View; Query by Example","score_opus":0.1547059754666002,"score_gpt":0.37866323701805993,"score_spread":0.22395726155145973,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416285692","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":[0.0035547176,0.0010925046,0.9321506,0.0007908146,0.0006082603,0.0006480769,0.0032774666,0.05198342,0.0058940444],"genre_scores_gemma":[0.10331229,0.0017171226,0.8634985,0.0014376921,0.0005670653,0.001483666,0.013333925,0.005351747,0.009297982],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9960912,0.00062036904,0.0006467776,0.0005323749,0.0018143427,0.00029484142],"domain_scores_gemma":[0.99701357,0.00079039705,0.00022899105,0.0010259389,0.0007229253,0.00021810153],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0055143526,0.0009923521,0.0013159654,0.0018324964,0.0010831774,0.0048559215,0.005019292,0.0010760896,0.010841073],"category_scores_gemma":[0.009844989,0.001022452,0.0014791539,0.0024959191,0.0014032718,0.005651874,0.00554741,0.0029902847,0.0032251794],"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":[0.0011274235,0.00052513933,0.0058067455,0.0024549302,0.00039496276,0.0010473484,0.0006259618,0.025114318,0.01682076,0.28884187,0.2013106,0.45592996],"study_design_scores_gemma":[0.00044806418,0.00029720174,0.00089501933,0.00038991528,0.00017690458,0.00094272604,0.0002133612,0.32063252,0.024190797,0.15125342,0.5002908,0.00026935973],"about_ca_topic_score_codex":0.0036906798,"about_ca_topic_score_gemma":0.0049671093,"teacher_disagreement_score":0.010841073,"about_ca_system_score_codex":0.0014400245,"about_ca_system_score_gemma":0.004106447,"threshold_uncertainty_score":0.036266983},"labels":[],"label_agreement":null},{"id":"W4416799466","doi":"10.1109/icmic66299.2025.11257817","title":"A Structure-Based Method for Data Migration Between Heterogeneous DBMSs in Defense Systems","year":2025,"lang":"","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nexen (Canada)","funders":"","keywords":"Data migration; Maintainability; Consistency (knowledge bases); Table (database); Oracle; Process (computing); Key (lock); Data integrity; Data structure; Data access","score_opus":0.05154697758812195,"score_gpt":0.3505071340859986,"score_spread":0.29896015649787666,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416799466","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":[0.00658806,0.00013152855,0.98907894,0.00016860968,0.000084748965,0.00015675885,0.00005404638,0.0026446334,0.001092695],"genre_scores_gemma":[0.09729585,0.00016192048,0.89900786,0.00013677347,0.0000431435,0.00021591365,0.00026370087,0.00036818,0.002506611],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99801815,0.0004097082,0.00019703718,0.00032699943,0.0009285019,0.00011961718],"domain_scores_gemma":[0.99683654,0.00059168873,0.0002919389,0.0012768471,0.00088363164,0.000119306824],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019609837,0.00049791165,0.0004479572,0.0015663069,0.0011327217,0.0015603089,0.001806171,0.0009076025,0.0017927608],"category_scores_gemma":[0.0063112145,0.00058973976,0.0006691649,0.0011217373,0.00082919287,0.0033179307,0.0021303196,0.0013136757,0.00079584634],"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":[0.00030884377,0.00020709059,0.006140572,0.00041033395,0.00010527429,0.0005032947,0.002220795,0.026785737,0.05382538,0.12423283,0.012064205,0.7731957],"study_design_scores_gemma":[0.00019535245,0.0006077961,0.003431501,0.0002508435,0.0001781604,0.0018286954,0.00089784263,0.6077023,0.12200651,0.087157756,0.1755174,0.00022583203],"about_ca_topic_score_codex":0.0017949186,"about_ca_topic_score_gemma":0.0019946413,"teacher_disagreement_score":0.0019609837,"about_ca_system_score_codex":0.0008919317,"about_ca_system_score_gemma":0.0019203293,"threshold_uncertainty_score":0.010370791},"labels":[],"label_agreement":null},{"id":"W4416890273","doi":"10.1016/j.sysarc.2025.103659","title":"Reconfigurable acceleration for database systems: Taxonomy, techniques, and research challenges","year":2025,"lang":"en","type":"article","venue":"Journal of Systems Architecture","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Acceleration; Key (lock); Database application; Hardware acceleration","score_opus":0.08471486437881295,"score_gpt":0.33418972092458527,"score_spread":0.2494748565457723,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416890273","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":[0.025381878,0.68839407,0.2437717,0.0064484985,0.0010180539,0.0002988257,0.00038756352,0.00207052,0.032228865],"genre_scores_gemma":[0.14430161,0.59326106,0.25022787,0.0013621936,0.0019138675,0.00030038808,0.00084412104,0.00028851806,0.007500455],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986425,0.00021529796,0.0001454491,0.00024363206,0.0006129456,0.00014008717],"domain_scores_gemma":[0.99806315,0.00089247886,0.0001571273,0.0002905749,0.0005026017,0.00009402223],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012951333,0.001012062,0.00096658384,0.003362115,0.0005276544,0.003762841,0.0021047846,0.0011497977,0.0021713017],"category_scores_gemma":[0.0027615186,0.0008465088,0.0007811167,0.0057731234,0.00092547707,0.004646938,0.0010149514,0.0021808208,0.0011977359],"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":[0.00013679353,0.00019519716,0.002777219,0.004302528,0.000086456705,0.0001987889,0.00049303967,0.016749837,0.010360033,0.13685021,0.012068402,0.8157815],"study_design_scores_gemma":[0.000072888244,0.0011549772,0.004645647,0.0038726297,0.00018595262,0.00279784,0.0011238301,0.13857593,0.013858343,0.13660708,0.696891,0.00021389547],"about_ca_topic_score_codex":0.0017408743,"about_ca_topic_score_gemma":0.001438047,"teacher_disagreement_score":0.003762841,"about_ca_system_score_codex":0.0011232975,"about_ca_system_score_gemma":0.0014095039,"threshold_uncertainty_score":0.008150101},"labels":[],"label_agreement":null},{"id":"W4416942877","doi":"10.1109/bigdata66926.2025.11402455","title":"Relation-Stratified Sampling for Shapley Values Estimation in Relational Databases","year":2025,"lang":"","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Tuple; Estimator; Joins; Sampling (signal processing); RSS; Relational database; Variance (accounting); Stratification (seeds); Sample (material)","score_opus":0.08141308089082669,"score_gpt":0.35213014326630215,"score_spread":0.27071706237547544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416942877","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":[0.010191098,0.00014525588,0.98851043,0.00007179326,0.000015696358,0.00007622264,0.00008775699,0.00026564003,0.00063607126],"genre_scores_gemma":[0.4825645,0.00029286422,0.51478285,0.00018259094,0.0000843823,0.00043338304,0.00063211937,0.00016744113,0.00085989584],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99513656,0.0025786767,0.0002093553,0.00088635925,0.0009629678,0.00022617243],"domain_scores_gemma":[0.98580825,0.01002807,0.0007620252,0.002050477,0.0010642951,0.000287024],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008103428,0.0010089052,0.0014527778,0.0016278744,0.0008022586,0.002530666,0.0023087899,0.0009776922,0.0026743247],"category_scores_gemma":[0.037720736,0.0007076508,0.0009935764,0.002040032,0.0013206386,0.0035466957,0.002018771,0.0020452742,0.00044941696],"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":[0.00033097784,0.00017338981,0.0070993374,0.00018275737,0.00020287714,0.000087993285,0.00040003948,0.5709029,0.0034795848,0.2529249,0.0025630353,0.16165224],"study_design_scores_gemma":[0.000017222856,0.000037506627,0.000321359,0.000014096998,0.000011761791,0.000023184972,0.00002638669,0.9041534,0.00093652616,0.09372383,0.00072063005,0.00001400148],"about_ca_topic_score_codex":0.0030463676,"about_ca_topic_score_gemma":0.0031775197,"teacher_disagreement_score":0.008103428,"about_ca_system_score_codex":0.0018410656,"about_ca_system_score_gemma":0.002079757,"threshold_uncertainty_score":0.04285556},"labels":[],"label_agreement":null},{"id":"W46528900","doi":"10.1007/1-4020-5392-4_3","title":"Database Models and Data Modelling","year":2007,"lang":"en","type":"book-chapter","venue":"˜The œGeojournal library","topic":"Advanced Database Systems and Queries","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":"Database; Computer science","score_opus":0.11208703712196075,"score_gpt":0.27525263846077397,"score_spread":0.16316560133881322,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W46528900","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":[0.002001351,0.039114885,0.84963673,0.0063363183,0.0023537509,0.00021456346,0.0020609894,0.0033338424,0.09494766],"genre_scores_gemma":[0.110372104,0.08242773,0.4826247,0.0040761824,0.0027027125,0.000935383,0.010486779,0.0029220271,0.30345237],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9971698,0.0006373823,0.00037542704,0.0004982953,0.0012129738,0.00010621397],"domain_scores_gemma":[0.99733573,0.0011188467,0.00009958177,0.00092419627,0.00044528866,0.000076368815],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002807326,0.001784653,0.0021305974,0.0023360737,0.0010026657,0.010547209,0.0034800724,0.00200838,0.017087303],"category_scores_gemma":[0.008787865,0.0015669739,0.0016244936,0.0057782386,0.0025374843,0.011312725,0.0027147725,0.0035436098,0.014306934],"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":[0.000029393483,0.000052872314,0.00031245264,0.00062951556,0.00004683579,0.00013674932,0.00046897228,0.010233464,0.0005919456,0.7143392,0.08403397,0.18912469],"study_design_scores_gemma":[0.00001087064,0.000020319858,0.000129584,0.00025487845,0.00004354626,0.00030556435,0.00012997512,0.029241273,0.000614118,0.54576457,0.42345542,0.000029807647],"about_ca_topic_score_codex":0.005115209,"about_ca_topic_score_gemma":0.002406138,"teacher_disagreement_score":0.017087303,"about_ca_system_score_codex":0.0021031047,"about_ca_system_score_gemma":0.001908601,"threshold_uncertainty_score":0.05716276},"labels":[],"label_agreement":null},{"id":"W54133306","doi":"","title":"Bi-Level Mapping: Combining Schema and Data Level Heterogeneity in Peer Data Sharing Systems.","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Schema (genetic algorithms); Data sharing; Data mapping; Data mining; Theoretical computer science; Information retrieval; Database","score_opus":0.3371969095604573,"score_gpt":0.36494078980268324,"score_spread":0.02774388024222596,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W54133306","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":[0.05688538,0.000485406,0.93571746,0.0009389653,0.00007120253,0.00029352968,0.00007841448,0.0008407894,0.0046888804],"genre_scores_gemma":[0.66536784,0.0003495299,0.33048692,0.00025201062,0.000077683646,0.00029223695,0.00020546003,0.00012442614,0.0028438529],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9911589,0.0041740704,0.0007602098,0.0006046799,0.0029252851,0.00037679402],"domain_scores_gemma":[0.9911822,0.0039481265,0.0005939707,0.002779046,0.001109597,0.00038703633],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008661509,0.0004171054,0.00067642087,0.0011852426,0.0011213982,0.0034967763,0.0019592068,0.0014625124,0.0010839852],"category_scores_gemma":[0.01717567,0.0005984517,0.000610501,0.0019311457,0.0019829548,0.009739323,0.0049682595,0.0014776967,0.0002922609],"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":[0.00045541135,0.0002491339,0.017618526,0.0005054813,0.00027543522,0.0019064099,0.0051236125,0.08144211,0.01898441,0.6155511,0.0059469645,0.25194147],"study_design_scores_gemma":[0.00007500955,0.00027527905,0.0022136145,0.00010882791,0.00016599084,0.0019123706,0.0015210642,0.5854947,0.014374497,0.35145482,0.04229434,0.00010957355],"about_ca_topic_score_codex":0.0016563634,"about_ca_topic_score_gemma":0.0015050791,"teacher_disagreement_score":0.008661509,"about_ca_system_score_codex":0.0011259693,"about_ca_system_score_gemma":0.0015111032,"threshold_uncertainty_score":0.045807004},"labels":[],"label_agreement":null},{"id":"W55051199","doi":"","title":"True Online TD(lambda)","year":2014,"lang":"en","type":"article","venue":"International Conference on Machine Learning","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":30,"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":"Lambda; Computer science; Physics; Optics","score_opus":0.03161988976831424,"score_gpt":0.3009143998948404,"score_spread":0.26929451012652617,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W55051199","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":[0.022519708,0.00040863475,0.8910832,0.0027487907,0.0017644345,0.00016110518,0.0038317237,0.03509402,0.04238834],"genre_scores_gemma":[0.46900886,0.00029585836,0.42298886,0.002712505,0.000688547,0.00032017907,0.0055858144,0.007177689,0.09122171],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9961008,0.00073516916,0.00023244802,0.0010399333,0.0011932802,0.000698378],"domain_scores_gemma":[0.98953235,0.0032768834,0.00026179902,0.0042032804,0.0022335504,0.00049211644],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029384298,0.0011328894,0.0011608734,0.0009524667,0.0014356066,0.0045142714,0.0037050731,0.0022419451,0.06546439],"category_scores_gemma":[0.01425935,0.00077606144,0.0011587434,0.0009846404,0.0014219093,0.007520533,0.0055102827,0.0036968463,0.021425331],"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":[0.003096503,0.00070796016,0.0043180618,0.000904103,0.00017300586,0.0006922617,0.00047761365,0.010856082,0.016599013,0.16922939,0.17950068,0.6134454],"study_design_scores_gemma":[0.0004066948,0.0003696866,0.0015964255,0.00012478464,0.00020577,0.0012451689,0.00046633082,0.22782761,0.03627081,0.6288717,0.10247521,0.00013989858],"about_ca_topic_score_codex":0.003407289,"about_ca_topic_score_gemma":0.005920179,"teacher_disagreement_score":0.06546439,"about_ca_system_score_codex":0.0014766222,"about_ca_system_score_gemma":0.003981268,"threshold_uncertainty_score":0.21900022},"labels":[],"label_agreement":null},{"id":"W56576261","doi":"","title":"Information Integration: a Vision for Integration Independence and Linking Open Data.","year":2010,"lang":"en","type":"article","venue":"AMW","topic":"Advanced Database Systems and Queries","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 Toronto","funders":"","keywords":"Independence (probability theory); Data integration; Information integration; Computer science; Data mining; Mathematics","score_opus":0.02859230865770166,"score_gpt":0.3279443309987999,"score_spread":0.2993520223410982,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W56576261","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":[0.0031958898,0.0043397285,0.96833426,0.006921926,0.0005762235,0.00015240339,0.00072996377,0.0029732147,0.012776302],"genre_scores_gemma":[0.07426142,0.0058357106,0.9020404,0.0031497558,0.0015994094,0.00041839477,0.0040048794,0.000876766,0.007813204],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98125595,0.005705584,0.00197581,0.0030946801,0.007162922,0.00080499076],"domain_scores_gemma":[0.97051245,0.008166273,0.0017033451,0.013632656,0.004365088,0.0016201156],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.021827081,0.0011812476,0.0020188678,0.008940527,0.002575585,0.017975854,0.006198301,0.0037628603,0.0045114756],"category_scores_gemma":[0.039234288,0.0015265071,0.0024809155,0.011241752,0.007448595,0.041302737,0.01496391,0.006801332,0.0042290585],"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":[0.00012849753,0.0001361407,0.0013797944,0.0005926476,0.00022108843,0.00017237244,0.0015264342,0.0016849029,0.0027551528,0.73986673,0.031650767,0.21988548],"study_design_scores_gemma":[0.000030650135,0.00004777023,0.00047395565,0.0003426835,0.00013596486,0.00025396177,0.00048641206,0.009758129,0.0030166619,0.81833696,0.16705391,0.000062860665],"about_ca_topic_score_codex":0.0027642946,"about_ca_topic_score_gemma":0.0014562295,"teacher_disagreement_score":0.021827081,"about_ca_system_score_codex":0.0017869694,"about_ca_system_score_gemma":0.005455672,"threshold_uncertainty_score":0.11543405},"labels":[],"label_agreement":null},{"id":"W59453251","doi":"10.1007/978-3-540-79980-1_19","title":"Constant Complements, Reversibility and Universal View Updates","year":2008,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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":"Mount Allison University","funders":"","keywords":"Complement (music); Sketch; Constant (computer programming); Computer science; Theoretical computer science; Physical constant; Algebraic number; Algorithm; Mathematics; Programming language","score_opus":0.020424082124550092,"score_gpt":0.24687557727130363,"score_spread":0.22645149514675353,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W59453251","genre_codex":"methods","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":[0.11159731,0.009647357,0.62162995,0.004013873,0.0014042023,0.00017195893,0.0010024075,0.001969869,0.24856307],"genre_scores_gemma":[0.8107563,0.0045819,0.1199329,0.0009767609,0.0010354826,0.00017080056,0.0009657344,0.00089471426,0.06068535],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99732804,0.00061442034,0.00022721611,0.0007208762,0.0007169952,0.00039237115],"domain_scores_gemma":[0.99356574,0.003344624,0.00034637807,0.0019399723,0.0005846184,0.00021871214],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026035209,0.00086623227,0.0012858197,0.0015863299,0.0021213212,0.00661356,0.0017328869,0.0016530534,0.009946997],"category_scores_gemma":[0.012057687,0.0012920838,0.0013069871,0.0026488502,0.0067212414,0.025326224,0.00428401,0.005547454,0.0011826695],"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":[0.000060003928,0.00001653741,0.00008410172,0.00005570082,0.0000089975565,0.00006594669,0.0002525234,0.0005472509,0.00048009257,0.9797332,0.0019409577,0.01675468],"study_design_scores_gemma":[0.00001914989,0.000012571709,0.00006138176,0.000018424102,0.000020032101,0.00015280826,0.00007879823,0.0015340876,0.0010754465,0.9875864,0.009425501,0.000015452393],"about_ca_topic_score_codex":0.0019931744,"about_ca_topic_score_gemma":0.00143976,"teacher_disagreement_score":0.009946997,"about_ca_system_score_codex":0.0014898855,"about_ca_system_score_gemma":0.00122774,"threshold_uncertainty_score":0.03327602},"labels":[],"label_agreement":null},{"id":"W601341005","doi":"10.4018/ijaeis.2015070103","title":"New Design Approach to Handle Spatial Vagueness in Spatial OLAP Datacubes","year":2015,"lang":"en","type":"article","venue":"International Journal of Agricultural and Environmental Information Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Centre de Géomatique du Québec","funders":"","keywords":"Vagueness; Online analytical processing; Computer science; Spatial analysis; Metadata; Data mining; Data science; Information retrieval; Fuzzy logic; Geography; Data warehouse; Artificial intelligence; World Wide Web","score_opus":0.021950130857757898,"score_gpt":0.21718246831694232,"score_spread":0.19523233745918442,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W601341005","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":[0.0027837276,0.000081050464,0.99515593,0.00013835408,0.000033383265,0.00011773805,0.000052100553,0.0004639462,0.0011738024],"genre_scores_gemma":[0.08459489,0.00023044324,0.9119874,0.00019104472,0.000058211645,0.00047808667,0.00030947433,0.00016606915,0.0019843716],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99609464,0.0012464677,0.00048310988,0.00047935534,0.0014826267,0.00021378254],"domain_scores_gemma":[0.99647266,0.00087570027,0.00028216574,0.0007829719,0.0013861804,0.00020039082],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003912095,0.0007506369,0.0008644892,0.0012562494,0.001075633,0.0031423757,0.0022549927,0.0010632682,0.0035119473],"category_scores_gemma":[0.0063619814,0.0006734687,0.0012833867,0.0017499202,0.0010840399,0.0041827364,0.0037117852,0.0014688707,0.00092852954],"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":[0.00059303624,0.00039236984,0.0046706717,0.001108134,0.00026239312,0.0010727516,0.0033084457,0.23312101,0.05210479,0.30551407,0.014064959,0.38378742],"study_design_scores_gemma":[0.000086089545,0.00028805586,0.00046587258,0.000102912556,0.000100448655,0.00062036514,0.00067711796,0.8319796,0.018640326,0.06818416,0.078774326,0.000080725156],"about_ca_topic_score_codex":0.0013111613,"about_ca_topic_score_gemma":0.0013944953,"teacher_disagreement_score":0.003912095,"about_ca_system_score_codex":0.00086098106,"about_ca_system_score_gemma":0.0013888804,"threshold_uncertainty_score":0.020689368},"labels":[],"label_agreement":null},{"id":"W622520872","doi":"","title":"9th International Database Engineering & Applications Symposium (IDEAS 2005) : proceedings : July 25-27, 2005, Montreal, Canada","year":2005,"lang":"en","type":"book","venue":"IEEE Computer Society eBooks","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Library science; Database; History; Computer science","score_opus":0.006956762094309596,"score_gpt":0.20082162944601895,"score_spread":0.19386486735170935,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W622520872","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018012429,0.074437216,0.20613036,0.028041884,0.038586654,0.0021056538,0.037203286,0.040795125,0.55468744],"genre_scores_gemma":[0.0069919173,0.011181558,0.023806764,0.0010448531,0.0012285647,0.0001308462,0.014105257,0.0015502189,0.93996006],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988833,0.000094843126,0.000040749608,0.00016050246,0.0006574433,0.00016316671],"domain_scores_gemma":[0.9964414,0.00021943869,0.000052690855,0.00025397402,0.0024454521,0.0005870256],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002665831,0.0016354737,0.0020185346,0.0019249072,0.0024146584,0.007784281,0.002555087,0.0012899308,0.20449997],"category_scores_gemma":[0.002689204,0.00087802607,0.00092510844,0.002604025,0.00090517825,0.0030997866,0.0020027165,0.0021634374,0.1095755],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006401841,0.00006654913,0.00028926955,0.00012548214,0.000017006552,0.000035141675,0.00006763911,0.00013852605,0.0010619335,0.0014346694,0.9085985,0.088101335],"study_design_scores_gemma":[0.000041580297,0.000054328193,0.0020305235,0.00013311722,0.00006507482,0.0001379597,0.00015190015,0.0021227107,0.0019498427,0.0016761208,0.9916039,0.000032975953],"about_ca_topic_score_codex":0.19632089,"about_ca_topic_score_gemma":0.36994243,"teacher_disagreement_score":0.8036791,"about_ca_system_score_codex":0.005095939,"about_ca_system_score_gemma":0.010653289,"threshold_uncertainty_score":0.68412054},"labels":[],"label_agreement":null},{"id":"W625246740","doi":"","title":"On the XML Data Stream and Xpath Queries","year":2008,"lang":"en","type":"article","venue":"Journal of the Association for Information Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg","funders":"","keywords":"XPath; Computer science; Streaming XML; Efficient XML Interchange; XML database; Information retrieval; XML; XML Encryption; XML validation; XML Schema Editor; XML Signature; Focus (optics); Database; World Wide Web","score_opus":0.03119640806529936,"score_gpt":0.24420769330226075,"score_spread":0.2130112852369614,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W625246740","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":[0.014083059,0.0024116354,0.97221226,0.0020500573,0.00024142908,0.00015148542,0.00043612492,0.0014672694,0.0069466955],"genre_scores_gemma":[0.18581632,0.0076997997,0.78229535,0.0013568362,0.0011413106,0.00029670497,0.0019165411,0.00084454246,0.018632583],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9965963,0.0008855038,0.0003086217,0.00057017506,0.0014447968,0.00019456714],"domain_scores_gemma":[0.9942973,0.0036309818,0.00028952135,0.00076454814,0.00083422347,0.00018339796],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0040966207,0.0009167193,0.001189225,0.002117902,0.0012978944,0.00384774,0.0016090116,0.0014282968,0.0038605898],"category_scores_gemma":[0.013741959,0.0006933087,0.0010184243,0.004580182,0.0018397463,0.01185688,0.0024983778,0.0024242694,0.0014124634],"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":[0.0013433605,0.00017423098,0.0026945856,0.00048289105,0.00007576362,0.00093967805,0.0007960613,0.06555073,0.0058084005,0.52894366,0.028629538,0.3645611],"study_design_scores_gemma":[0.000106161955,0.00012190429,0.000640952,0.00011039402,0.00004745679,0.00085014495,0.0002982345,0.53656906,0.0056686434,0.41590184,0.039641406,0.00004374114],"about_ca_topic_score_codex":0.0052386452,"about_ca_topic_score_gemma":0.0030128977,"teacher_disagreement_score":0.0052386452,"about_ca_system_score_codex":0.001120785,"about_ca_system_score_gemma":0.0010539362,"threshold_uncertainty_score":0.021665275},"labels":[],"label_agreement":null},{"id":"W653879595","doi":"","title":"PODS '08 : proceedings of the twenty-seventh ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, Vancouver, BC, Canada, June 9-11, 2008","year":2008,"lang":"en","type":"book","venue":"ACM eBooks","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Library science; Database; Computer science; History","score_opus":0.021065978697032684,"score_gpt":0.22178605822803701,"score_spread":0.20072007953100432,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W653879595","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0073260902,0.08380606,0.3524198,0.014303389,0.06875262,0.0011011381,0.022691881,0.051601537,0.39799753],"genre_scores_gemma":[0.00802281,0.032713722,0.048083156,0.002021551,0.0035219574,0.00020795122,0.02477748,0.004964862,0.8756866],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99923146,0.0000749684,0.000047765196,0.00009798511,0.00049363554,0.000054145916],"domain_scores_gemma":[0.99788254,0.0004159513,0.000068059526,0.00032185964,0.00088910945,0.00042253238],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015707308,0.0013209103,0.0015603653,0.0013617786,0.00092957675,0.0055883266,0.0017513301,0.0008095418,0.10617257],"category_scores_gemma":[0.0032149816,0.0010509474,0.0006850469,0.0025690931,0.00063609815,0.0038117697,0.0016047583,0.0033168162,0.0747472],"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":[0.00005030526,0.000064858286,0.00013032199,0.00020106779,0.000008135118,0.000025233947,0.000036686684,0.00023228397,0.00088968634,0.0026068848,0.8924722,0.10328228],"study_design_scores_gemma":[0.000031770593,0.000038271188,0.00065523386,0.00011005701,0.000017248894,0.00019788471,0.00003043091,0.0016059249,0.00076822285,0.0035739143,0.9929577,0.000013381833],"about_ca_topic_score_codex":0.004704421,"about_ca_topic_score_gemma":0.014707433,"teacher_disagreement_score":0.10617257,"about_ca_system_score_codex":0.001190909,"about_ca_system_score_gemma":0.003217209,"threshold_uncertainty_score":0.3551826},"labels":[],"label_agreement":null},{"id":"W6912459065","doi":"10.5281/zenodo.2652489","title":"Polyhedral Compilation for Multi-dimensional Stream Processing: Addendum","year":2019,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Addendum; George (robot); Algebra over a field","score_opus":0.052352686442658176,"score_gpt":0.27428503326030473,"score_spread":0.22193234681764656,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6912459065","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":[0.0055909045,0.005218589,0.8610366,0.0050434736,0.043464217,0.000410364,0.0047845147,0.030715251,0.04373608],"genre_scores_gemma":[0.10558285,0.00811189,0.6183833,0.0048856596,0.026015287,0.0012330024,0.029647043,0.04755074,0.15859026],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9966493,0.00043274136,0.00025972197,0.0005768198,0.0017378961,0.00034344525],"domain_scores_gemma":[0.99458426,0.0014168984,0.00014991828,0.0011461275,0.0023109482,0.0003919434],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013475489,0.0017261197,0.0011805997,0.0012858821,0.00068543846,0.0022410045,0.0016119451,0.00071085186,0.08553306],"category_scores_gemma":[0.00745434,0.0009584794,0.0016192943,0.0020641456,0.00075154233,0.0023558135,0.0037030848,0.002607274,0.043057956],"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":[0.00047941625,0.00022393225,0.0003550776,0.00090310466,0.00011435725,0.00044056558,0.00016457868,0.01295782,0.010691302,0.050083496,0.61518514,0.30840126],"study_design_scores_gemma":[0.00018129715,0.0001940112,0.00060745125,0.00018316502,0.000086796725,0.0008288827,0.000058057947,0.045582015,0.025669621,0.048174098,0.8782725,0.000162025],"about_ca_topic_score_codex":0.0012836783,"about_ca_topic_score_gemma":0.0011432334,"teacher_disagreement_score":0.08553306,"about_ca_system_score_codex":0.0011970721,"about_ca_system_score_gemma":0.001265402,"threshold_uncertainty_score":0.28613657},"labels":[],"label_agreement":null},{"id":"W6912906530","doi":"10.5281/zenodo.8411193","title":"Plan de gestion des données pour Optimisation d'un procédé industriel d'extrusion","year":2023,"lang":"fr","type":"article","venue":"Bibliothèque et Archives nationales du Québec (Québec government)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Cégep de Sherbrooke","funders":"","keywords":"Plan (archaeology); Context (archaeology); Work (physics)","score_opus":0.05578212190576315,"score_gpt":0.23907406164869233,"score_spread":0.18329193974292918,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6912906530","genre_codex":"methods","genre_gemma":"protocol","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"protocol","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05778759,0.00047386767,0.92040944,0.0005000278,0.00007429551,0.00061538507,0.0018258995,0.007485419,0.010828051],"genre_scores_gemma":[0.27313486,0.0006051262,0.7062661,0.00009885076,0.00001566342,0.0007734952,0.0027573418,0.00075985544,0.015588661],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99872357,0.00017745179,0.000066660206,0.00021934093,0.00069849746,0.00011442701],"domain_scores_gemma":[0.99842465,0.0008431437,0.00007839294,0.00018380112,0.00041178745,0.000058182788],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017223506,0.0019367252,0.0010665293,0.0014876222,0.0012684943,0.0025039632,0.001101376,0.0018404181,0.01027489],"category_scores_gemma":[0.0037563378,0.000983514,0.0015280516,0.0011670624,0.00095077255,0.0012043741,0.0011838028,0.0012036035,0.0018147108],"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":[0.0009964311,0.0002037112,0.005710267,0.00087332085,0.00011395407,0.0007713394,0.0016887905,0.6119216,0.07641936,0.010970124,0.0077868165,0.28254429],"study_design_scores_gemma":[0.00018010147,0.0005542793,0.008670516,0.00020411596,0.00008941641,0.00027935207,0.0010869964,0.85668594,0.072056256,0.008693932,0.05133575,0.00016335273],"about_ca_topic_score_codex":0.0674746,"about_ca_topic_score_gemma":0.057394862,"teacher_disagreement_score":0.0674746,"about_ca_system_score_codex":0.0017373313,"about_ca_system_score_gemma":0.0046596304,"threshold_uncertainty_score":0.13416374},"labels":[],"label_agreement":null},{"id":"W69211128","doi":"","title":"Generic Approach to Internationalization of Websites","year":2004,"lang":"en","type":"article","venue":"IASTED Conference on Software Engineering and Applications","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Acadia University","funders":"","keywords":"Computer science; Internationalization; Software; Architecture; World Wide Web; Software engineering; Software architecture; Database; Programming language","score_opus":0.019818693340325603,"score_gpt":0.23289884819678305,"score_spread":0.21308015485645745,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W69211128","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":[0.013870551,0.0007148815,0.87436116,0.00085287617,0.00031962732,0.00071061426,0.00092464214,0.0077178497,0.10052774],"genre_scores_gemma":[0.16304088,0.0016403917,0.79768115,0.0007044161,0.00024144894,0.00093995663,0.004393436,0.0024696516,0.028888667],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99346066,0.0019425086,0.0009434288,0.0013806362,0.0016476874,0.00062509434],"domain_scores_gemma":[0.9947961,0.0004654014,0.00043575888,0.003119149,0.00089750224,0.00028607188],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0044271694,0.0009544693,0.0009970627,0.005875652,0.0021926777,0.009137264,0.0026635688,0.0017826528,0.008473424],"category_scores_gemma":[0.007435869,0.0008700486,0.0024629098,0.0075558894,0.00403971,0.010429918,0.0075158756,0.0030783857,0.0034148004],"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":[0.00004019551,0.000067986424,0.0018836652,0.00026425283,0.000057229943,0.00027043582,0.0024795546,0.0039760023,0.0029426657,0.85346913,0.012463097,0.12208576],"study_design_scores_gemma":[0.000032590902,0.00008859633,0.0021149924,0.0003252441,0.00012900394,0.0011238522,0.0015125313,0.01933456,0.0080977,0.23946688,0.72767913,0.00009494217],"about_ca_topic_score_codex":0.002895291,"about_ca_topic_score_gemma":0.003054144,"teacher_disagreement_score":0.009137264,"about_ca_system_score_codex":0.0025430843,"about_ca_system_score_gemma":0.0025338372,"threshold_uncertainty_score":0.02834642},"labels":[],"label_agreement":null},{"id":"W6924480477","doi":"10.15468/dl.dpf2nr","title":"Occurrence Download","year":2024,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Download; Matching (statistics); Range (aeronautics); Metadata","score_opus":0.013126178761845044,"score_gpt":0.22495170928002253,"score_spread":0.21182553051817749,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6924480477","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00004667562,0.0000268661,0.00005201756,0.00004231216,0.000011418767,0.000006375777,0.99880445,0.0004165844,0.00059330417],"genre_scores_gemma":[0.00016674414,0.000031657313,0.00021654736,0.000044402284,0.0000030650401,0.00004129038,0.99900204,0.00012303893,0.00037122803],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988483,0.00015943231,0.00016359928,0.00038387292,0.00027557157,0.00016924253],"domain_scores_gemma":[0.9973182,0.0007825191,0.00024243323,0.00069840584,0.00066076074,0.00029761327],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0011312669,0.0019199161,0.001513496,0.0050745984,0.0009864292,0.0024919417,0.0029957457,0.0020750011,0.12813455],"category_scores_gemma":[0.006503909,0.0008911582,0.0011771573,0.009064164,0.0004580875,0.0022341795,0.0023081296,0.002111351,0.1731209],"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":[0.000027537675,0.000012153918,0.0003425271,0.00041813537,0.000013082958,0.000013641202,0.000018925537,0.00013379852,0.00010195487,0.00039156905,0.9972398,0.0012869039],"study_design_scores_gemma":[0.000085615604,0.000008574369,0.0019053671,0.00017337978,0.00001454213,0.000043255666,0.00007259473,0.0002350426,0.00022680091,0.0008900292,0.9963271,0.000017670574],"about_ca_topic_score_codex":0.021310605,"about_ca_topic_score_gemma":0.03319362,"teacher_disagreement_score":0.87186545,"about_ca_system_score_codex":0.0017603952,"about_ca_system_score_gemma":0.0025614554,"threshold_uncertainty_score":0.42865276},"labels":[],"label_agreement":null},{"id":"W6925273490","doi":"10.17632/s662r5mkxx","title":"Why Resident Identification Matters","year":2023,"lang":"en","type":"dataset","venue":"Mendeley Data","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Identification (biology); Data collection; Descriptive statistics; Descriptive research; Survey research; Population","score_opus":0.061719075031185025,"score_gpt":0.317832689814207,"score_spread":0.25611361478302197,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6925273490","genre_codex":"empirical","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6722956,0.0075228065,0.0034933558,0.20812476,0.0028949117,0.00042050294,0.046246648,0.00020244201,0.058798995],"genre_scores_gemma":[0.94712,0.004071222,0.001456846,0.023541663,0.0012172862,0.00048169307,0.013898538,0.000103872255,0.008108859],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9933982,0.0028928118,0.0007167529,0.0008096261,0.0011645159,0.0010179381],"domain_scores_gemma":[0.97186655,0.012033248,0.0063960324,0.0020306834,0.0052845455,0.0023889062],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00742697,0.00013370274,0.00030715772,0.0010792849,0.0012931371,0.0014507662,0.0008724419,0.00091802346,0.011483008],"category_scores_gemma":[0.062261466,0.00027872898,0.0003196214,0.003083566,0.00059849734,0.0024465432,0.0013956126,0.0010586894,0.0028196885],"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":[0.00018043634,0.00012256426,0.6764829,0.0007382568,0.00007082167,0.00031436354,0.0057001896,0.0001067917,0.000116021925,0.0034614368,0.23672426,0.07598196],"study_design_scores_gemma":[0.000046733432,0.0001366136,0.80317056,0.0021163356,0.00009124056,0.00093590625,0.026626766,0.00058309897,0.0003085804,0.003172769,0.16276541,0.00004595141],"about_ca_topic_score_codex":0.02328186,"about_ca_topic_score_gemma":0.035806887,"teacher_disagreement_score":0.02328186,"about_ca_system_score_codex":0.0012000735,"about_ca_system_score_gemma":0.003085739,"threshold_uncertainty_score":0.046292722},"labels":[],"label_agreement":null},{"id":"W6930897667","doi":"10.5281/zenodo.165284","title":"Figure 79 In Guide To The Parasites Of Fishes Of Canada Part V: Nematoda","year":2016,"lang":"en","type":"other","venue":"INFM-OAR (INFN Catania)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Taxonomy (biology); Helminths; Aquatic animal; Morphology (biology); Host (biology)","score_opus":0.007026230658481822,"score_gpt":0.24709845796684743,"score_spread":0.2400722273083656,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6930897667","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0020179986,0.032349605,0.008639891,0.0020836475,0.0042760223,0.0010522611,0.112002514,0.0051230486,0.83245516],"genre_scores_gemma":[0.0074642063,0.025987174,0.0180853,0.0015979011,0.0004848129,0.00035547963,0.057765193,0.0012879146,0.886972],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997645,0.000009124438,0.000013631712,0.000038732494,0.00012231531,0.000051762425],"domain_scores_gemma":[0.9994697,0.000039314713,0.000042270993,0.000047404512,0.0003025364,0.00009876303],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00028079667,0.0014915329,0.00091371953,0.0073287115,0.0026613849,0.0014176179,0.0020175406,0.0009360116,0.3779097],"category_scores_gemma":[0.0007701787,0.00073601,0.0006138766,0.0059454837,0.0010271834,0.0016733882,0.0015869718,0.0013589743,0.25115937],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023094408,0.000018233499,0.00073738745,0.00040465538,0.000006847207,0.00008564067,0.00014208506,0.000114154514,0.0013444335,0.0014829804,0.83652675,0.15911382],"study_design_scores_gemma":[0.0000016362161,0.000004704078,0.0025862665,0.00010169598,0.0000040289106,0.000095160896,0.000055164845,0.000020312327,0.00012519238,0.00023783362,0.9967625,0.0000055065952],"about_ca_topic_score_codex":0.45119295,"about_ca_topic_score_gemma":0.7503499,"teacher_disagreement_score":0.548807,"about_ca_system_score_codex":0.004004325,"about_ca_system_score_gemma":0.004842116,"threshold_uncertainty_score":0.8971334},"labels":[],"label_agreement":null},{"id":"W6931064573","doi":"10.5281/zenodo.15732260","title":"Fig. 2 in Methods for estimating and modelling spruce budworm development rates at constant temperatures","year":2021,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Natural Resources Canada; Canadian Forest Service","funders":"","keywords":"Spruce budworm; Constant (computer programming); Choristoneura fumiferana; Larva; Instar","score_opus":0.04995082548137678,"score_gpt":0.3155411337029902,"score_spread":0.2655903082216134,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6931064573","genre_codex":"methods","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":[0.00085822237,0.00031720632,0.9227166,0.0002298967,0.00041181964,0.0003628175,0.03647414,0.028723354,0.009905923],"genre_scores_gemma":[0.018652739,0.0006132267,0.8695473,0.00041986883,0.00018934114,0.002527407,0.05271674,0.014210685,0.041122712],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991277,0.0002606172,0.000075650045,0.00020702007,0.00027524933,0.00005376192],"domain_scores_gemma":[0.9977197,0.0012352021,0.00010639353,0.0005915,0.00028984153,0.0000572456],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024083985,0.002119937,0.00069264864,0.0016367261,0.00073983235,0.0015869976,0.004015229,0.0024664903,0.21682689],"category_scores_gemma":[0.0074210595,0.0016051334,0.0017712793,0.0011969489,0.00038469804,0.0011918315,0.001505325,0.0015286773,0.1280473],"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":[0.00034810218,0.0002132304,0.0051937387,0.001753713,0.000554667,0.00040778838,0.00020746049,0.08497407,0.015441879,0.04425566,0.53938353,0.30726615],"study_design_scores_gemma":[0.00021969723,0.00009312393,0.004837972,0.00025226682,0.00016642286,0.0005521213,0.000053924938,0.23170356,0.014510025,0.041880492,0.70556045,0.0001698641],"about_ca_topic_score_codex":0.007066846,"about_ca_topic_score_gemma":0.01092813,"teacher_disagreement_score":0.21682689,"about_ca_system_score_codex":0.00067549513,"about_ca_system_score_gemma":0.0009812098,"threshold_uncertainty_score":0.7253582},"labels":[],"label_agreement":null},{"id":"W6931278345","doi":"10.5281/zenodo.4167675","title":"[@123MOVIES]!! .HD!! The Kid Detective (2020) FULL MOVIE FREE ONLINE STREAMING kjw","year":2020,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Download; Sign (mathematics); Action (physics); Text messaging; Legal action; Online video","score_opus":0.03184361030933329,"score_gpt":0.2366253513328716,"score_spread":0.2047817410235383,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6931278345","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0004323796,0.00013204274,0.0005977763,0.00037578118,0.0007519269,0.00010750818,0.0038698132,0.0053380397,0.9883946],"genre_scores_gemma":[0.0016608369,0.0001569251,0.00044883433,0.0003704605,0.00012215979,0.000057958507,0.002509144,0.002680838,0.9919927],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99985206,0.000010641576,0.000004616998,0.00002809372,0.000063161046,0.00004132263],"domain_scores_gemma":[0.9993443,0.000042431027,0.000014664429,0.00007278167,0.00027741244,0.0002483204],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00020032763,0.00078580255,0.0004516773,0.00079452107,0.0019556577,0.0032812282,0.0009103154,0.0011333142,0.9393684],"category_scores_gemma":[0.0011175793,0.00047982065,0.0005211239,0.00064408814,0.00028556123,0.0029248486,0.0027339542,0.0012887323,0.89548814],"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":[0.000017798198,0.000010909172,0.000046335,0.00004452052,0.0000010248261,0.00002069058,0.00004924843,0.0000075621415,0.00019271998,0.00048052892,0.9831843,0.01594443],"study_design_scores_gemma":[0.000007131976,0.000008782401,0.0003957972,0.000034979366,0.0000013815053,0.000044630575,0.000092272945,0.000029702147,0.0001533684,0.00012051129,0.9991054,0.000006065837],"about_ca_topic_score_codex":0.0067879064,"about_ca_topic_score_gemma":0.017055761,"teacher_disagreement_score":0.060631573,"about_ca_system_score_codex":0.00062022393,"about_ca_system_score_gemma":0.00037174832,"threshold_uncertainty_score":0.0864836},"labels":[],"label_agreement":null},{"id":"W6946947667","doi":"10.34943/ef599c2e-32a7-4a70-a97b-a1c346717847","title":"Bullseye Hydrophone Deployed 2014-05-24","year":2014,"lang":"en","type":"dataset","venue":"Ocean Networks Canada Society","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Hydrophone; Underwater; Data logger; Waveform; Seafloor spreading; Sound (geography); Ocean bottom","score_opus":0.004448095507230505,"score_gpt":0.18720931778509928,"score_spread":0.18276122227786878,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6946947667","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010860119,0.0000794844,0.00033545456,0.00010747073,0.00007351716,0.00003091095,0.99509627,0.001178916,0.0020119261],"genre_scores_gemma":[0.0012891202,0.00003970603,0.00048032773,0.000030865045,0.000008879778,0.000044514974,0.99689865,0.00009857053,0.0011093512],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99883825,0.00011034788,0.00011674292,0.00029801176,0.00046739096,0.00016931961],"domain_scores_gemma":[0.9981072,0.00017420165,0.000101824044,0.0004206193,0.0010354449,0.00016067075],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009771214,0.0017052403,0.0011100624,0.0025059422,0.0008071797,0.0014291791,0.0023161045,0.0012016749,0.017413309],"category_scores_gemma":[0.0036594414,0.00047944897,0.00065512885,0.0038193078,0.0005141772,0.0014675334,0.0016247259,0.0013611121,0.03737239],"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":[0.00007318325,0.00002457216,0.0016477511,0.00023525122,0.000025931502,0.000043013966,0.000041306877,0.0005977961,0.00035998807,0.0004645792,0.99279153,0.003695063],"study_design_scores_gemma":[0.00013499797,0.000027422999,0.012636554,0.0001711153,0.000022829454,0.00008888035,0.00025038494,0.0017430081,0.0010284851,0.0010449555,0.9827976,0.000053671352],"about_ca_topic_score_codex":0.096674584,"about_ca_topic_score_gemma":0.17658079,"teacher_disagreement_score":0.096674584,"about_ca_system_score_codex":0.0017457935,"about_ca_system_score_gemma":0.0027571202,"threshold_uncertainty_score":0.19222379},"labels":[],"label_agreement":null},{"id":"W6949614347","doi":"10.5281/zenodo.14480814","title":"Characterizing Spatial Heterogeneity of Hydraulic Conductivity using Borehole NMR in a Complex Groundwater Flow System","year":2025,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Hydraulic conductivity; Groundwater flow; Borehole; Groundwater; Flow (mathematics); Groundwater model; Spatial heterogeneity; Spatial variability","score_opus":0.05700859848897952,"score_gpt":0.2753845796595763,"score_spread":0.21837598117059678,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6949614347","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.026255807,0.00009890168,0.0010137189,0.00012318706,0.00002853953,0.00003239129,0.969368,0.0016443052,0.0014352584],"genre_scores_gemma":[0.021414798,0.000062298146,0.0017024709,0.00003946343,0.000008403307,0.00006961536,0.9760944,0.000065834916,0.00054262945],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.99958235,0.000049429982,0.000045286197,0.00016112074,0.00009634033,0.00006552657],"domain_scores_gemma":[0.9990545,0.00032974375,0.000080792845,0.00025784297,0.00020505246,0.00007214265],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00070658704,0.001095798,0.00073414703,0.0022409481,0.00039128048,0.0007927642,0.0014619979,0.0011921552,0.0078002703],"category_scores_gemma":[0.0017684207,0.0003677857,0.0007155376,0.0027169886,0.00036367172,0.0005743809,0.0007230982,0.0005653293,0.0057342607],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00079036184,0.00044427297,0.032643497,0.001945135,0.00023512564,0.00056051253,0.00021891223,0.050735515,0.0053904736,0.0026037395,0.86673135,0.037701204],"study_design_scores_gemma":[0.0019079781,0.00056423474,0.18697216,0.00070692913,0.00036195942,0.0013446982,0.0011189516,0.12461952,0.025236698,0.013849874,0.64286065,0.0004564099],"about_ca_topic_score_codex":0.022800867,"about_ca_topic_score_gemma":0.03645064,"teacher_disagreement_score":0.022800867,"about_ca_system_score_codex":0.00095233234,"about_ca_system_score_gemma":0.00090178946,"threshold_uncertainty_score":0.045336306},"labels":[],"label_agreement":null},{"id":"W6950449746","doi":"10.5281/zenodo.8411192","title":"Plan de gestion des données pour Optimisation d'un procédé industriel d'extrusion","year":2023,"lang":"fr","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Cégep de Sherbrooke","funders":"","keywords":"Plan (archaeology); Context (archaeology); Work (physics)","score_opus":0.17864372978290535,"score_gpt":0.2623048771648191,"score_spread":0.08366114738191374,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6950449746","genre_codex":"methods","genre_gemma":"protocol","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"protocol","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03547599,0.000426051,0.9495866,0.00035211904,0.00006989542,0.0003414876,0.0012350425,0.005561458,0.0069513456],"genre_scores_gemma":[0.2566991,0.00069679855,0.725468,0.00009926964,0.000022983653,0.0007331369,0.0027214307,0.00085216435,0.0127070835],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986834,0.0002194721,0.000071153765,0.0002474161,0.00067310163,0.00010544315],"domain_scores_gemma":[0.99838865,0.0009725604,0.00007223778,0.00019629189,0.00031524253,0.00005504504],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015224222,0.0018778284,0.0009869989,0.0012422837,0.00097637606,0.0023238068,0.0009884584,0.001968198,0.010164053],"category_scores_gemma":[0.0037177538,0.00086210534,0.0015544085,0.000963344,0.00093226065,0.0012802265,0.0012155824,0.0013335884,0.0019009545],"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":[0.0013316857,0.00024482392,0.0046479735,0.0009655154,0.00013153398,0.00094144983,0.0016951334,0.5815256,0.08022401,0.018279307,0.008904194,0.30110887],"study_design_scores_gemma":[0.00023718258,0.0005782937,0.005419689,0.00018195568,0.00008117316,0.0004243559,0.00088786596,0.83936834,0.07791408,0.013669309,0.061083093,0.00015464867],"about_ca_topic_score_codex":0.019989023,"about_ca_topic_score_gemma":0.013894008,"teacher_disagreement_score":0.019989023,"about_ca_system_score_codex":0.0009977458,"about_ca_system_score_gemma":0.0025107467,"threshold_uncertainty_score":0.03974533},"labels":[],"label_agreement":null},{"id":"W6979726906","doi":"","title":"Addressing Our Many Solitudes: Building a Web Archives Community of Practice in Canada","year":2018,"lang":"en","type":"other","venue":"University of North Texas Digital Library (University of North Texas)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Presentation (obstetrics); The Internet; Web site; Internet research; Web standards; Web technology","score_opus":0.01760903747678949,"score_gpt":0.208728726655615,"score_spread":0.19111968917882552,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6979726906","genre_codex":"commentary","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":[0.26583168,0.0075090528,0.014077233,0.5203493,0.004653446,0.0015206325,0.0011054283,0.0014894322,0.18346378],"genre_scores_gemma":[0.76420724,0.004060948,0.030431619,0.043353446,0.00030706162,0.0005215479,0.00062254356,0.00086793065,0.15562765],"study_design_codex":"not_applicable","study_design_gemma":"qualitative","domain_scores_codex":[0.9847928,0.0032749735,0.00045563717,0.0011475701,0.0055746804,0.0047542914],"domain_scores_gemma":[0.9358797,0.0034655414,0.0011224638,0.0014465716,0.020215118,0.037870597],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.014236452,0.0004015857,0.00052160496,0.0026382052,0.06791975,0.018699447,0.0052733086,0.004480553,0.018926853],"category_scores_gemma":[0.021563023,0.0008541588,0.00068853126,0.0038059328,0.013981647,0.0069153947,0.019448617,0.0063683605,0.0019430924],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":true,"study_design_scores_codex":[0.00018772253,0.00058174616,0.022672653,0.0004610999,0.00005549602,0.0026781068,0.27991995,0.00064560556,0.0021681339,0.047483027,0.38021508,0.26293135],"study_design_scores_gemma":[0.000044963188,0.00007812555,0.010446874,0.00042221465,0.000025393714,0.0003440394,0.2998667,0.0006566574,0.00061753707,0.005139984,0.6822101,0.00014749894],"about_ca_topic_score_codex":0.9786527,"about_ca_topic_score_gemma":0.9947195,"teacher_disagreement_score":0.98130053,"about_ca_system_score_codex":0.14033228,"about_ca_system_score_gemma":0.5502475,"threshold_uncertainty_score":0.9970927},"labels":[],"label_agreement":null},{"id":"W6984899827","doi":"","title":"Cleveland, Ohio","year":2009,"lang":"en","type":"other","venue":"OhioLink ETD Center (Ohio Library and Information Network)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Pearl; Work (physics); Quarter (Canadian coin); Square (algebra)","score_opus":0.007940468061787422,"score_gpt":0.20095915139746906,"score_spread":0.19301868333568165,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6984899827","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000794028,0.002746495,0.0007521543,0.0027366248,0.0032131039,0.00015920609,0.008212663,0.000819234,0.9805664],"genre_scores_gemma":[0.003789929,0.0026701326,0.001083972,0.0008010031,0.00060510525,0.00017313508,0.0038523441,0.0006045245,0.98641986],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99870455,0.00013254957,0.000068813235,0.0005356179,0.00040773198,0.00015071231],"domain_scores_gemma":[0.99829024,0.0002624639,0.00011305939,0.0002312651,0.00052499364,0.00057792215],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009757673,0.0020073499,0.0010564055,0.0018696665,0.0028892648,0.005427422,0.0013450512,0.0027191718,0.84963995],"category_scores_gemma":[0.0024785013,0.0006803948,0.00081649807,0.002887621,0.0007319326,0.0030676734,0.0021156059,0.002009574,0.56784403],"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":[0.00008949359,0.00011511385,0.00071124715,0.00013138982,0.000013228256,0.0002524551,0.000079779784,0.00006569544,0.00033341258,0.0047258856,0.88529116,0.108191155],"study_design_scores_gemma":[0.000035003337,0.000021078922,0.0010860655,0.0000843617,0.0000060910497,0.00008963041,0.0000696153,0.000041085565,0.00007184753,0.00043807342,0.99804676,0.000010438098],"about_ca_topic_score_codex":0.0111927455,"about_ca_topic_score_gemma":0.026010137,"teacher_disagreement_score":0.84963995,"about_ca_system_score_codex":0.0016620884,"about_ca_system_score_gemma":0.0024647731,"threshold_uncertainty_score":0.21447039},"labels":[],"label_agreement":null},{"id":"W6986254854","doi":"","title":"Optimistic concurrency control in McXML","year":2003,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"XML validation; Timestamp-based concurrency control; XML database; Non-lock concurrency control; Streaming XML; Efficient XML Interchange; XML Encryption; Optimistic concurrency control; Multiversion concurrency control","score_opus":0.013116304849615021,"score_gpt":0.24519223889096783,"score_spread":0.23207593404135282,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6986254854","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":[0.03304477,0.0016103938,0.94712037,0.0011027926,0.00023006319,0.00034912207,0.00017016407,0.007900805,0.008471507],"genre_scores_gemma":[0.5704669,0.0009235047,0.41548038,0.0009471372,0.0003092458,0.0005709155,0.00045342403,0.0008063793,0.010042189],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9867181,0.00305324,0.001179313,0.0011609553,0.0068752365,0.0010130737],"domain_scores_gemma":[0.98752636,0.0038455445,0.0010743489,0.0056198444,0.001481803,0.00045213837],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011284334,0.0006072049,0.00073515653,0.0011022498,0.0015586703,0.0048841843,0.0038247288,0.0009325885,0.00275108],"category_scores_gemma":[0.017493142,0.0010788348,0.0007617841,0.0010610542,0.002180852,0.0077975844,0.0058150506,0.0026241927,0.0006406087],"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":[0.0013284018,0.00032110588,0.0074172234,0.0006638973,0.00017919739,0.0010797313,0.0033341968,0.07748556,0.026941763,0.5614326,0.015184664,0.30463168],"study_design_scores_gemma":[0.00044792474,0.00031707616,0.0012783032,0.00025350673,0.00020690261,0.00094670977,0.00041553003,0.56938946,0.07290776,0.24296415,0.11062169,0.00025102135],"about_ca_topic_score_codex":0.0038072818,"about_ca_topic_score_gemma":0.0032471549,"teacher_disagreement_score":0.011284334,"about_ca_system_score_codex":0.0018978429,"about_ca_system_score_gemma":0.0029155766,"threshold_uncertainty_score":0.059678018},"labels":[],"label_agreement":null},{"id":"W6991580861","doi":"","title":"High-level static optimizations for efficient differentiable programming in MLIR","year":2023,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Set (abstract data type); Differentiable function; Software; Computation","score_opus":0.02831003003903301,"score_gpt":0.2656391563452175,"score_spread":0.2373291263061845,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6991580861","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":[0.020698868,0.00043058436,0.9298713,0.00031680614,0.00012222645,0.00012098694,0.0003490845,0.039545387,0.0085447775],"genre_scores_gemma":[0.1991322,0.00029227833,0.7813999,0.00045755223,0.000088414745,0.00025398898,0.001030012,0.011509688,0.005835872],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99855155,0.00033369238,0.00012792219,0.00026604658,0.000524695,0.00019601952],"domain_scores_gemma":[0.99791807,0.0009088663,0.00018767522,0.0006407896,0.0002818435,0.000062757965],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012658571,0.0013840167,0.00061396847,0.0008098543,0.00059340434,0.0020831006,0.0023058555,0.0007150017,0.009099425],"category_scores_gemma":[0.005794439,0.0007368687,0.001027735,0.0007887742,0.0013404526,0.002907306,0.0025073064,0.0031912618,0.004727404],"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":[0.00075171894,0.00045274547,0.0074067255,0.0008119641,0.00011649148,0.0005713309,0.0009352733,0.10775659,0.057196457,0.14950131,0.035944726,0.6385546],"study_design_scores_gemma":[0.00014444983,0.00030198984,0.001413597,0.0001718174,0.000073460695,0.0003080126,0.00020587831,0.7512694,0.09118354,0.09278187,0.062046397,0.00009960078],"about_ca_topic_score_codex":0.0014089275,"about_ca_topic_score_gemma":0.0037868426,"teacher_disagreement_score":0.009099425,"about_ca_system_score_codex":0.0010416687,"about_ca_system_score_gemma":0.001818537,"threshold_uncertainty_score":0.030440629},"labels":[],"label_agreement":null},{"id":"W6999720786","doi":"","title":"Data indexing and update in XML database","year":2003,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"XML database; XML Schema Editor; Efficient XML Interchange; Streaming XML; XML validation; XML Encryption; Document Structure Description; XML Signature","score_opus":0.028861390271067468,"score_gpt":0.27139120857913507,"score_spread":0.2425298183080676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6999720786","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":[0.022631159,0.0086799655,0.7189737,0.0061866487,0.0020867249,0.0012557484,0.010354068,0.062755175,0.16707684],"genre_scores_gemma":[0.13707858,0.010884436,0.44848898,0.0021918798,0.0011361854,0.0010277245,0.026627097,0.0067687393,0.36579636],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978727,0.00052442984,0.00039106494,0.00019683456,0.0008674642,0.00014760347],"domain_scores_gemma":[0.9962529,0.0011636628,0.00017783344,0.001627573,0.0005835913,0.00019450733],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003674949,0.00046737638,0.00075097353,0.0031915894,0.0010591641,0.0047221417,0.0015523518,0.00120099,0.02564138],"category_scores_gemma":[0.00957288,0.0006820328,0.0006152956,0.0046758824,0.00091508316,0.008068034,0.0028289412,0.0013237611,0.018753342],"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":[0.0003186256,0.0001672764,0.002646647,0.00057125685,0.00005032703,0.0005056246,0.0010294765,0.003118503,0.008147019,0.09705267,0.2245708,0.6618218],"study_design_scores_gemma":[0.00010040732,0.00011452898,0.0018779814,0.0003691983,0.0000635219,0.00086678326,0.00042021726,0.03105905,0.015743786,0.042832218,0.9064882,0.00006408339],"about_ca_topic_score_codex":0.005167005,"about_ca_topic_score_gemma":0.004858697,"teacher_disagreement_score":0.02564138,"about_ca_system_score_codex":0.0013038502,"about_ca_system_score_gemma":0.0015479648,"threshold_uncertainty_score":0.08577895},"labels":[],"label_agreement":null},{"id":"W7008984277","doi":"","title":"Designing an Integrated Database for Human Spaceflight Data Management","year":2023,"lang":"en","type":"dissertation","venue":"elib (German Aerospace Center)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"NoSQL; Metis; Spaceflight; Aerospace; Data management; Human spaceflight; Web application; Data exchange","score_opus":0.05318843941157964,"score_gpt":0.35613316419687335,"score_spread":0.3029447247852937,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7008984277","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":[0.020612463,0.0012513853,0.9622209,0.00074730144,0.00014738418,0.001256259,0.0011984558,0.0071001663,0.005465607],"genre_scores_gemma":[0.10967549,0.0008859363,0.87710804,0.0004545156,0.000073307965,0.0006499736,0.004997348,0.0004510009,0.0057043917],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99691916,0.0005666644,0.00056874176,0.00069684023,0.0010349313,0.00021374006],"domain_scores_gemma":[0.9973863,0.00050529017,0.0001289129,0.0006799419,0.0010789571,0.0002206598],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0064220023,0.0003797209,0.0006860217,0.0011400268,0.0010128244,0.004754074,0.0024805581,0.00093193154,0.0028668586],"category_scores_gemma":[0.0057537616,0.0005252868,0.00058861554,0.0018181405,0.00040835675,0.004651133,0.0020597607,0.0010352322,0.0014747201],"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":[0.0012454683,0.0011347297,0.015649144,0.0013595079,0.0002910108,0.00089809374,0.0028041257,0.021758959,0.075781286,0.07030263,0.04000079,0.7687744],"study_design_scores_gemma":[0.00053554017,0.0011415686,0.008528207,0.0005156969,0.00046682637,0.0019022217,0.002365374,0.27922925,0.12403056,0.032987162,0.5480926,0.00020497164],"about_ca_topic_score_codex":0.0026984478,"about_ca_topic_score_gemma":0.0018239495,"teacher_disagreement_score":0.0064220023,"about_ca_system_score_codex":0.0009881477,"about_ca_system_score_gemma":0.0023049465,"threshold_uncertainty_score":0.033963203},"labels":[],"label_agreement":null},{"id":"W7017636539","doi":"","title":"Automatic Conflict Resolution to Integrate Relational Schema","year":2001,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Data integration; Interoperability; Semantic interoperability; Relational database; Schema (genetic algorithms); Database schema; USable; XML; IDEF1X; Semantic heterogeneity","score_opus":0.037493545086923784,"score_gpt":0.27851456727531815,"score_spread":0.24102102218839436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7017636539","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":[0.007216503,0.00014144785,0.981612,0.00016861965,0.00005582206,0.00025426905,0.00015016118,0.006724317,0.0036768694],"genre_scores_gemma":[0.06768572,0.00013963813,0.9272669,0.00015278744,0.000023209606,0.000192545,0.00088521006,0.00081243797,0.0028415658],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9925541,0.002019442,0.00079729763,0.0011199208,0.0032142634,0.00029509232],"domain_scores_gemma":[0.98926204,0.003005293,0.0007091575,0.004077387,0.002774333,0.00017179559],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006613604,0.00077249,0.00087902683,0.0020206075,0.0009556491,0.003817445,0.0024827195,0.0009144346,0.0051704873],"category_scores_gemma":[0.020630563,0.00096362404,0.001558959,0.0019236837,0.0010987378,0.0057577947,0.0050565787,0.00206853,0.0023813],"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":[0.00031615308,0.00030295635,0.004504582,0.00054879603,0.00020732697,0.00063113286,0.0031362216,0.023790887,0.025313716,0.26191148,0.016557194,0.66277957],"study_design_scores_gemma":[0.00013494966,0.00018899066,0.00097563444,0.0002283013,0.0002074842,0.0009545752,0.00115709,0.530995,0.098609895,0.20002218,0.16638234,0.00014350543],"about_ca_topic_score_codex":0.0019149256,"about_ca_topic_score_gemma":0.002126017,"teacher_disagreement_score":0.006613604,"about_ca_system_score_codex":0.0010768905,"about_ca_system_score_gemma":0.0018238106,"threshold_uncertainty_score":0.034976482},"labels":[],"label_agreement":null},{"id":"W7026405797","doi":"","title":"Analyse numérique des mécanismes de rupture critiques des semelles en remblai cimenté excavées à la base en plusieurs séquences","year":2020,"lang":"fr","type":"other","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"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":"Natural Sciences and Engineering Research Council of Canada","keywords":"Medium term; Western europe; Prospection; Telmatology","score_opus":0.013748302418991788,"score_gpt":0.2550112358438476,"score_spread":0.24126293342485583,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7026405797","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":[0.9020976,0.0007312458,0.07225666,0.00066847145,0.000061278566,0.000047075042,0.0013354685,0.00068777567,0.02211436],"genre_scores_gemma":[0.9634591,0.0001723966,0.027850904,0.000019357847,0.000015005576,0.000046509653,0.000646135,0.00013582024,0.007654712],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992155,0.00017795518,0.000042991127,0.00017240903,0.0003125165,0.00007857769],"domain_scores_gemma":[0.99050856,0.0071242205,0.0006029413,0.0005372043,0.0010866843,0.00014048831],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016458239,0.00047142303,0.00054753514,0.0030168118,0.0008603602,0.0023524617,0.0010125064,0.0018036067,0.007405986],"category_scores_gemma":[0.015581424,0.00047260796,0.00067067734,0.0016490316,0.001072107,0.0014453242,0.0007902303,0.00068980904,0.0007684588],"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":[0.00040579817,0.0000809422,0.07323277,0.00038672873,0.00016163441,0.00082381873,0.0016012327,0.78873867,0.011981503,0.025983198,0.0036270176,0.092976674],"study_design_scores_gemma":[0.000030516814,0.00006710202,0.031835534,0.000064656306,0.000054293625,0.0002726528,0.0010431387,0.94168097,0.006339679,0.010431581,0.008137477,0.00004239718],"about_ca_topic_score_codex":0.055436373,"about_ca_topic_score_gemma":0.06268173,"teacher_disagreement_score":0.055436373,"about_ca_system_score_codex":0.0025752725,"about_ca_system_score_gemma":0.0013828968,"threshold_uncertainty_score":0.110227406},"labels":[],"label_agreement":null},{"id":"W7034946618","doi":"","title":"Ο ποιητής Λεονάρδος Ντελλαπόρτας ως πρεσβευτής της Βενετίας εις Τυνησίαν κατ’ ανέκδοτα βενετικά έγγραφα (1389)","year":2015,"lang":"fr","type":"other","venue":"University of Thessaly Institutional Repository (University of Thessaly)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Nomination; Archivist; Passer; Nova scotia","score_opus":0.02087885649589103,"score_gpt":0.18795107908674388,"score_spread":0.16707222259085286,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7034946618","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02356502,0.01695921,0.006431695,0.041418545,0.0019982366,0.00005120566,0.00036894772,0.00011689702,0.9090902],"genre_scores_gemma":[0.41169506,0.011179041,0.0031312876,0.0066005774,0.0011028962,0.00014489832,0.00020956255,0.00024090144,0.5656957],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988186,0.00036118427,0.000036654248,0.00025911652,0.0003297165,0.00019475253],"domain_scores_gemma":[0.9993482,0.00025651275,0.000076123455,0.000055072516,0.00018422204,0.000079939826],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014390456,0.0006866467,0.00026111238,0.0009883087,0.004817128,0.005604336,0.00071778346,0.0022946824,0.02325285],"category_scores_gemma":[0.0025876039,0.00039222607,0.00026423406,0.0009112413,0.01214221,0.0049236435,0.0020377967,0.004175196,0.006960868],"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":[0.000096951895,0.000033098277,0.0011799975,0.0002448481,0.000014380423,0.0002798331,0.054920707,0.00009979774,0.0012937866,0.78266454,0.110970706,0.048201416],"study_design_scores_gemma":[0.000009632822,0.000016513697,0.0017303847,0.00020440048,0.000005797876,0.00014086918,0.0097176,0.000054762284,0.00049138267,0.034538046,0.953076,0.000014575718],"about_ca_topic_score_codex":0.02730734,"about_ca_topic_score_gemma":0.042730574,"teacher_disagreement_score":0.02730734,"about_ca_system_score_codex":0.0067138188,"about_ca_system_score_gemma":0.0034569437,"threshold_uncertainty_score":0.07778853},"labels":[],"label_agreement":null},{"id":"W7037727786","doi":"","title":"Evolution of an international research collaborative in HIV and rehabilitation:Community engaged process, lessons learned, and recommendations","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Human immunodeficiency virus (HIV); Context (archaeology); Rehabilitation; Sustainability; Capacity building; Knowledge transfer; Health care","score_opus":0.08796354896184268,"score_gpt":0.42749682387301474,"score_spread":0.3395332749111721,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7037727786","genre_codex":"commentary","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":[0.013201357,0.018763527,0.027624529,0.911612,0.008867621,0.0022851005,0.00019100687,0.0004375849,0.01701727],"genre_scores_gemma":[0.43095058,0.03882127,0.31463385,0.17855841,0.0036361834,0.0100670755,0.0014985353,0.0007792763,0.021054843],"study_design_codex":"design_other","study_design_gemma":"qualitative","domain_scores_codex":[0.7532435,0.1847872,0.014401532,0.011925534,0.019204803,0.016437422],"domain_scores_gemma":[0.55757767,0.1248941,0.015578779,0.02702722,0.09827859,0.17664358],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.2708101,0.001723385,0.0015378754,0.006960848,0.024642296,0.03852356,0.012005552,0.016899941,0.010519075],"category_scores_gemma":[0.1855652,0.0015908782,0.0024832059,0.007802326,0.023723412,0.047530502,0.041468572,0.026793033,0.0025755737],"study_design_candidate":"qualitative","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":[0.00027376055,0.002008147,0.025131417,0.006550133,0.00030903498,0.0025614977,0.15088263,0.0008417579,0.0012956827,0.1189168,0.17865513,0.512574],"study_design_scores_gemma":[0.00029017686,0.0007036479,0.009932588,0.018832488,0.00021330238,0.001629621,0.33353394,0.0013008416,0.00086010183,0.08030677,0.5521214,0.00027519139],"about_ca_topic_score_codex":0.027110884,"about_ca_topic_score_gemma":0.048540458,"teacher_disagreement_score":0.2708101,"about_ca_system_score_codex":0.028021166,"about_ca_system_score_gemma":0.1892347,"threshold_uncertainty_score":0.89922094},"labels":[],"label_agreement":null},{"id":"W7037850949","doi":"","title":"Evaporator Scaling at a Zero-effluent BCTMP Mill","year":2022,"lang":"","type":"dissertation","venue":"TSpace","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Effluent; Mill; Piping; Pulp mill; Boiler feedwater; Pulp (tooth); Scaling; Solubility; Work (physics)","score_opus":0.02352555013441746,"score_gpt":0.3435730075499767,"score_spread":0.32004745741555923,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7037850949","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":[0.98724616,0.00007788813,0.004436106,0.00009961778,0.000012654258,0.00011940961,0.00017803759,0.0003713518,0.007458747],"genre_scores_gemma":[0.9833354,0.000087174594,0.0068302182,0.000050381434,0.0000062837457,0.00004105011,0.00016265715,0.000059542213,0.009427194],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99930847,0.00004428166,0.000027909027,0.00011284674,0.00041231472,0.00009417151],"domain_scores_gemma":[0.9995376,0.0000773385,0.000042247706,0.000041800646,0.00024016446,0.000060788847],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004477032,0.00019642728,0.00044375175,0.0004444331,0.001603028,0.0012222101,0.0005440823,0.00040176357,0.0031531893],"category_scores_gemma":[0.0005054746,0.000185251,0.000266772,0.00058487034,0.00050217105,0.00054810947,0.0005260196,0.0007683753,0.0009503124],"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":[0.000638524,0.0004635373,0.014886775,0.00016644794,0.000015793947,0.0010384861,0.0009155545,0.006141899,0.927317,0.0008734124,0.0014993307,0.0460432],"study_design_scores_gemma":[0.00006580819,0.0006164598,0.03889469,0.000024234334,0.000028150524,0.00022392468,0.001138769,0.022112317,0.9248884,0.00031311426,0.01164634,0.000047826597],"about_ca_topic_score_codex":0.012932317,"about_ca_topic_score_gemma":0.023087373,"teacher_disagreement_score":0.012932317,"about_ca_system_score_codex":0.0017051647,"about_ca_system_score_gemma":0.0014381113,"threshold_uncertainty_score":0.0257141},"labels":[],"label_agreement":null},{"id":"W7043783051","doi":"","title":"Structured Query Language (SQL) and Th ree-Valued Logic (3VL)","year":2015,"lang":"tr","type":"article","venue":"DergiPark (Istanbul University)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Stantec (Canada)","funders":"","keywords":"Query language; Query expansion; RDF query language; Query optimization; Object Query Language; Natural language; Feature (linguistics)","score_opus":0.023485075288201356,"score_gpt":0.23104342204026587,"score_spread":0.20755834675206453,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7043783051","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":[0.015886087,0.0022943388,0.96646065,0.0017288694,0.00021918943,0.00010331148,0.000853864,0.0020737313,0.01038001],"genre_scores_gemma":[0.34562805,0.0027545106,0.6351022,0.0013568104,0.00042113053,0.00025659747,0.002804069,0.00038957587,0.011287114],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9973448,0.00085020706,0.0003083067,0.00045031894,0.0008366319,0.00020976664],"domain_scores_gemma":[0.99811614,0.0010101901,0.00021588644,0.00027000942,0.00029649783,0.00009139228],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002300166,0.0006748983,0.00070197735,0.0013674176,0.00057605637,0.0044643516,0.0014605381,0.0009813817,0.004658726],"category_scores_gemma":[0.0045332257,0.0004566159,0.0016308492,0.0020184808,0.0016882947,0.0064867786,0.002150411,0.0023237085,0.0012419731],"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":[0.00035222585,0.00011427837,0.0007178571,0.00037889992,0.000068378926,0.00031048595,0.00036860607,0.006568786,0.004776511,0.86510503,0.0070684273,0.11417039],"study_design_scores_gemma":[0.00011184743,0.00016783261,0.00066739315,0.0002006685,0.00012179833,0.00048337615,0.00025595055,0.09590173,0.008327018,0.8480261,0.04565515,0.000081090155],"about_ca_topic_score_codex":0.0026059414,"about_ca_topic_score_gemma":0.001649655,"teacher_disagreement_score":0.004658726,"about_ca_system_score_codex":0.0013482036,"about_ca_system_score_gemma":0.0020707962,"threshold_uncertainty_score":0.015585005},"labels":[],"label_agreement":null},{"id":"W7065667458","doi":"","title":"An Efficient, Extensible, Hardware-aware Indexing Kernel","year":2013,"lang":"en","type":"dissertation","venue":"Library and Archives Canada (Government of Canada)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Search engine indexing; Kernel (algebra); Context (archaeology); Scalability; Overhead (engineering); Query expansion; Data structure; Kernel method; Query optimization; Range query (database)","score_opus":0.0036779578072562414,"score_gpt":0.16732596363361207,"score_spread":0.16364800582635583,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7065667458","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":[0.031112295,0.0006818884,0.9458535,0.00030261473,0.00017126324,0.00028765044,0.00034695462,0.01563387,0.0056099202],"genre_scores_gemma":[0.21907158,0.00081135763,0.7693977,0.0002662184,0.00015878741,0.00022369839,0.0017751228,0.0008705925,0.0074250144],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99858224,0.00007691442,0.0001448508,0.00019285471,0.0008274889,0.0001756612],"domain_scores_gemma":[0.9982863,0.00022981598,0.00012637101,0.0008016893,0.0004642362,0.0000915664],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007985686,0.0006078873,0.0007359217,0.0010052588,0.00068575726,0.0027338683,0.0027241483,0.0006060029,0.0021207873],"category_scores_gemma":[0.003135602,0.00040225527,0.0006355273,0.0016700713,0.00063480966,0.0040569804,0.0021007925,0.0015752488,0.0021025944],"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":[0.00075453555,0.0005621271,0.0038913367,0.00042072896,0.00009381512,0.000337064,0.00057694805,0.052590296,0.1411639,0.07358558,0.03427823,0.69174546],"study_design_scores_gemma":[0.000090763715,0.00042251538,0.0013615487,0.000044604094,0.000066300185,0.0005741834,0.00019599222,0.8002366,0.1022728,0.021640716,0.0729917,0.000102310805],"about_ca_topic_score_codex":0.0020468049,"about_ca_topic_score_gemma":0.0017804184,"teacher_disagreement_score":0.0027338683,"about_ca_system_score_codex":0.00080098107,"about_ca_system_score_gemma":0.0019843462,"threshold_uncertainty_score":0.007094741},"labels":[],"label_agreement":null},{"id":"W70671613","doi":"10.5220/0001237501990205","title":"RULE-BASED QUERY TREE EVALUATION OVER FRAGMENTED XML DOCUMENTS","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Computer science; Redundancy (engineering); Document Structure Description; Information retrieval; XML; XML validation; Efficient XML Interchange; Streaming XML; Database; Source document; World Wide Web","score_opus":0.011211652524484625,"score_gpt":0.2676665806872853,"score_spread":0.2564549281628007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W70671613","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":[0.13955913,0.0012936213,0.8484153,0.00029826528,0.000062572944,0.0003935345,0.00056951074,0.0045767124,0.0048313863],"genre_scores_gemma":[0.56736684,0.0004932697,0.42574197,0.00016374285,0.000067846326,0.00018855496,0.0020056302,0.00050672924,0.0034655356],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9952454,0.0012362915,0.00041358246,0.0005305213,0.0023180267,0.00025620326],"domain_scores_gemma":[0.99013126,0.0056919563,0.0005259151,0.00080680585,0.0025436091,0.0003004569],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036226113,0.0005984035,0.0014101214,0.0020372227,0.00057773455,0.0021257044,0.0016755658,0.00097054965,0.0027415492],"category_scores_gemma":[0.013777122,0.00033805193,0.0006181102,0.001934749,0.0005654516,0.002397498,0.00093560736,0.00073787145,0.0008332474],"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":[0.002271714,0.00041614397,0.0069995495,0.00067097286,0.00024529864,0.0010489046,0.00091385806,0.20767367,0.058319774,0.022615295,0.008083129,0.69074166],"study_design_scores_gemma":[0.00010019537,0.00020514122,0.0012010048,0.000041033996,0.00006368016,0.00023941937,0.00017407618,0.96507704,0.01890604,0.010390163,0.003574144,0.000028158176],"about_ca_topic_score_codex":0.0051129675,"about_ca_topic_score_gemma":0.0051088,"teacher_disagreement_score":0.0051129675,"about_ca_system_score_codex":0.0011054324,"about_ca_system_score_gemma":0.0013292498,"threshold_uncertainty_score":0.019158423},"labels":[],"label_agreement":null},{"id":"W7072215710","doi":"","title":"The United States and Canada: Outlook for Bilateral Relations in 2021","year":2020,"lang":"en","type":"article","venue":"eYLS (Yale Law School)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Industrial relations; Relation (database); Government (linguistics); Labor relations","score_opus":0.013582065469224138,"score_gpt":0.22854177290392994,"score_spread":0.2149597074347058,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7072215710","genre_codex":"commentary","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":[0.014610557,0.045470737,0.0007174108,0.6539512,0.005551896,0.00012174265,0.0059035406,0.00019693842,0.273476],"genre_scores_gemma":[0.30628967,0.07608072,0.0038173038,0.33084396,0.0022061646,0.00022134552,0.005249381,0.0001895094,0.27510196],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9888748,0.0005257639,0.00019528976,0.00035379897,0.0056373184,0.0044129975],"domain_scores_gemma":[0.98962724,0.0009488707,0.0002805544,0.000104502615,0.005884547,0.0031542676],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006018961,0.00073073275,0.0006370841,0.002723805,0.01568086,0.0133473715,0.002306628,0.018181775,0.018322466],"category_scores_gemma":[0.0110457465,0.0005257159,0.0011282461,0.004120652,0.0028745898,0.0044185543,0.0030534586,0.009173856,0.001410744],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000564542,0.00004187501,0.002537727,0.00014776217,0.000024433213,0.00041571946,0.0007983767,0.0009122689,0.00018821655,0.13081536,0.83452696,0.029534863],"study_design_scores_gemma":[0.000028139006,0.000013510296,0.008748004,0.0004459687,0.00003435722,0.00009164355,0.004474423,0.0005595741,0.00021996141,0.013060963,0.97221947,0.00010404301],"about_ca_topic_score_codex":0.9782516,"about_ca_topic_score_gemma":0.98960894,"teacher_disagreement_score":0.086931966,"about_ca_system_score_codex":0.086931966,"about_ca_system_score_gemma":0.25896308,"threshold_uncertainty_score":0.6307385},"labels":[],"label_agreement":null},{"id":"W7095909336","doi":"","title":"DEPARTEMENT D&amp;apos;INFORMATIQUE ET DE GENIE LOGICIEL","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Software; Context (archaeology); Work (physics); Automation","score_opus":0.0798518932505752,"score_gpt":0.3510367384253851,"score_spread":0.2711848451748099,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7095909336","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.034027796,0.10156019,0.10426011,0.18626219,0.028875202,0.00054553844,0.0065205945,0.0047638314,0.5331846],"genre_scores_gemma":[0.108908705,0.046944905,0.049874466,0.004209796,0.013935108,0.00034262333,0.0021603163,0.0014502738,0.77217376],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9945076,0.0009200006,0.00025633682,0.0014202395,0.0021746154,0.00072119216],"domain_scores_gemma":[0.9860832,0.005732198,0.00053898105,0.0008899725,0.003776816,0.0029788804],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004363832,0.0017708997,0.001947122,0.004608756,0.0026377975,0.006897848,0.0020241453,0.0028324474,0.109171286],"category_scores_gemma":[0.010577952,0.0009306077,0.0013350275,0.0026758385,0.0029600735,0.0036841088,0.0030678369,0.008213867,0.045840446],"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":[0.00073471793,0.0004689939,0.005091957,0.0013054286,0.00014556762,0.000641175,0.0016874478,0.0042313742,0.003985859,0.21417029,0.40589538,0.36164182],"study_design_scores_gemma":[0.00010818232,0.00016471531,0.005151447,0.00029295933,0.000036374306,0.000829812,0.0003915962,0.0057728067,0.00564709,0.027929982,0.9535994,0.00007564454],"about_ca_topic_score_codex":0.021930926,"about_ca_topic_score_gemma":0.0119918715,"teacher_disagreement_score":0.8908287,"about_ca_system_score_codex":0.012855709,"about_ca_system_score_gemma":0.008947054,"threshold_uncertainty_score":0.36521435},"labels":[],"label_agreement":null},{"id":"W7097026846","doi":"","title":"Schema Management","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"IBM; Schema (genetic algorithms); Data management; Data integration; Conceptual schema; Context (archaeology); Information system; Management system","score_opus":0.01877771089336534,"score_gpt":0.20756386419559797,"score_spread":0.18878615330223264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7097026846","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":[0.00777416,0.005263988,0.6125345,0.0049551693,0.002420442,0.0030784484,0.05861835,0.11041742,0.19493756],"genre_scores_gemma":[0.062922426,0.006947549,0.5218473,0.0063002408,0.0010823992,0.0018049167,0.23426418,0.020108357,0.14472261],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9929986,0.0011088933,0.0013706691,0.0011667759,0.0028785404,0.00047650427],"domain_scores_gemma":[0.9832302,0.0020302178,0.0010307075,0.007885827,0.0048034587,0.0010194969],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0103642475,0.0012601989,0.001373883,0.008401629,0.0022856144,0.012634516,0.005033906,0.001965271,0.04852917],"category_scores_gemma":[0.022498323,0.0011410922,0.0020098255,0.010532982,0.0010728462,0.011435462,0.008632022,0.0041216933,0.03932816],"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":[0.00034298885,0.00025587162,0.0042712106,0.0011223457,0.00024809,0.00060602976,0.0023070036,0.002091402,0.009772914,0.14004527,0.4642063,0.37473056],"study_design_scores_gemma":[0.00003032277,0.000024360035,0.00052214286,0.00015120723,0.00004806591,0.00039487693,0.0002601972,0.0028935613,0.0044376273,0.014706345,0.9764891,0.00004214889],"about_ca_topic_score_codex":0.004312683,"about_ca_topic_score_gemma":0.0034895227,"teacher_disagreement_score":0.04852917,"about_ca_system_score_codex":0.002192586,"about_ca_system_score_gemma":0.0051745824,"threshold_uncertainty_score":0.16234624},"labels":[],"label_agreement":null},{"id":"W7097236449","doi":"","title":"Bases, (Kyoto, Japan), August 1986. [37] M. J. Carey, D. J. DeWitt, and S. L. Vandenberg, &amp;quot;A data model and a query language for EXODUS,&amp;quot;","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"SQL; Query language; Datalog; Deductive database; Deductive method; Data model (GIS); Deductive reasoning; Relational database","score_opus":0.05365334606060552,"score_gpt":0.31852005233544906,"score_spread":0.26486670627484354,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7097236449","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011885256,0.14230302,0.17264014,0.010621082,0.008785613,0.0007671524,0.035860874,0.010689872,0.60644704],"genre_scores_gemma":[0.018437315,0.038829632,0.07843468,0.000850203,0.000821686,0.00039699159,0.023887794,0.0017079103,0.8366337],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990349,0.00013920659,0.00014439995,0.00020509811,0.00039791208,0.00007864123],"domain_scores_gemma":[0.99868315,0.00019934848,0.000060697334,0.00035708214,0.00059790775,0.00010177413],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0017499845,0.0013984146,0.0013678513,0.0019060784,0.0014446285,0.0025591492,0.0012436635,0.001347721,0.12620294],"category_scores_gemma":[0.0030792726,0.0014888104,0.000666789,0.0033177084,0.0006267016,0.003751935,0.0015869287,0.0018250175,0.17220898],"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":[0.0002619192,0.00013719403,0.0014227337,0.00068965467,0.00006829346,0.0003234073,0.0003094798,0.0012789347,0.0033810681,0.015490361,0.53441435,0.4422227],"study_design_scores_gemma":[0.000029851692,0.0000541171,0.0024408381,0.00023102769,0.000047744237,0.00040395846,0.00024732715,0.002248822,0.0016320557,0.007002385,0.98563844,0.000023310173],"about_ca_topic_score_codex":0.014116587,"about_ca_topic_score_gemma":0.032644678,"teacher_disagreement_score":0.87379706,"about_ca_system_score_codex":0.0013073961,"about_ca_system_score_gemma":0.001844337,"threshold_uncertainty_score":0.4221909},"labels":[],"label_agreement":null},{"id":"W7097479410","doi":"","title":"Performance and Tuning Guide: Volume 2- Query Optimization, Query Tuning and Abstract Plans","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"License; Software; Order (exchange); Volume (thermodynamics); Subject (documents)","score_opus":0.017731056807982665,"score_gpt":0.22025521706260354,"score_spread":0.20252416025462086,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7097479410","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":[0.0054704216,0.002971264,0.44128624,0.0023440209,0.00041083604,0.0018038814,0.019226296,0.4355486,0.090938434],"genre_scores_gemma":[0.07661677,0.0037261292,0.6368237,0.0022685833,0.0005225622,0.002624207,0.06385776,0.09495006,0.11861023],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99222976,0.0017462216,0.00056660414,0.00061885733,0.0043884246,0.00045022593],"domain_scores_gemma":[0.9925288,0.0025681152,0.00024393892,0.0020338397,0.0023055589,0.0003197618],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006538642,0.002306471,0.001623668,0.00224892,0.001026059,0.0065284874,0.0032675704,0.0011689072,0.08954353],"category_scores_gemma":[0.02037482,0.0019198896,0.0009883252,0.002875742,0.00047670782,0.0045344434,0.002016125,0.0024370318,0.09498234],"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":[0.0005932586,0.00020817026,0.00073890237,0.0003232315,0.00006585042,0.000057483703,0.00013248093,0.0097781345,0.0070201447,0.0059367744,0.60787153,0.36727396],"study_design_scores_gemma":[0.00044822035,0.00035054455,0.0030486188,0.00021744188,0.0000968935,0.00045410125,0.00021333928,0.20998763,0.029291272,0.019213626,0.7364609,0.00021747919],"about_ca_topic_score_codex":0.009478444,"about_ca_topic_score_gemma":0.0075581847,"teacher_disagreement_score":0.08954353,"about_ca_system_score_codex":0.0018225645,"about_ca_system_score_gemma":0.0043447264,"threshold_uncertainty_score":0.29955292},"labels":[],"label_agreement":null},{"id":"W7097710758","doi":"","title":"Implementing Q u e l Processing Using Views in Semistructured Databases","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Legislation; Order (exchange); The Internet; Reproduction; Subject (documents)","score_opus":0.053262917349366404,"score_gpt":0.330317378178419,"score_spread":0.2770544608290526,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7097710758","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":[0.07605746,0.00041251178,0.88134515,0.0008246566,0.0001156197,0.0003418796,0.0011458274,0.031686593,0.008070279],"genre_scores_gemma":[0.4177041,0.00034202286,0.5724407,0.00027295342,0.00005916389,0.0001551698,0.0023178617,0.0012514918,0.0054566176],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99668616,0.001192741,0.0003581941,0.00037760512,0.0011336853,0.00025160078],"domain_scores_gemma":[0.99247956,0.003113064,0.00029957193,0.00303754,0.0006772893,0.00039295046],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004278298,0.00042275141,0.00058631424,0.0012357339,0.0008813168,0.005284679,0.0020617985,0.0011966161,0.0035424414],"category_scores_gemma":[0.0115957875,0.00070263597,0.0010958737,0.0017261377,0.0013213821,0.006476946,0.0047785523,0.0010806394,0.00134937],"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":[0.0025167298,0.00079670554,0.013220776,0.0006063601,0.0002626402,0.0013151235,0.007244094,0.046759725,0.03958377,0.1212019,0.030725421,0.73576677],"study_design_scores_gemma":[0.00034742392,0.00070554175,0.002552518,0.0002546374,0.00018174162,0.0006733274,0.0040236744,0.6940334,0.06961164,0.15580142,0.071627565,0.00018706742],"about_ca_topic_score_codex":0.009012061,"about_ca_topic_score_gemma":0.012512421,"teacher_disagreement_score":0.009012061,"about_ca_system_score_codex":0.00087328156,"about_ca_system_score_gemma":0.0018597912,"threshold_uncertainty_score":0.022626102},"labels":[],"label_agreement":null},{"id":"W7097772734","doi":"","title":"University of New Brunswick CS6795- Semantic Web Techniques","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"RuleML; Serialization; Markup language; XML; HTML; Semantic Web; XHTML; Document type definition","score_opus":0.025571820225391246,"score_gpt":0.2154359556872816,"score_spread":0.18986413546189035,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7097772734","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018331098,0.0050163306,0.05277748,0.0058797994,0.001628363,0.00028291013,0.012419255,0.007069432,0.91309327],"genre_scores_gemma":[0.009582178,0.0070028235,0.04243772,0.0010288964,0.00020761041,0.0002907428,0.019487265,0.0028494075,0.9171133],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9974132,0.00033481666,0.00025660955,0.00078992284,0.00091600284,0.0002894647],"domain_scores_gemma":[0.9953667,0.0011959631,0.00014974916,0.0012676504,0.0016656213,0.00035433596],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0021739905,0.0019889248,0.0018241397,0.003766736,0.0027928543,0.0070704375,0.0025602253,0.0021066412,0.52885437],"category_scores_gemma":[0.008100865,0.0011162381,0.001169821,0.0092205405,0.0015819495,0.0071929195,0.003469886,0.0035212913,0.3712219],"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":[0.00014638412,0.000090217756,0.0007057431,0.00066759245,0.00003392953,0.0005160154,0.00033126332,0.0016908452,0.002471777,0.12051862,0.42990947,0.4429181],"study_design_scores_gemma":[0.000016368405,0.000008451687,0.0002543358,0.0002311286,0.000010189919,0.000096618045,0.00008692328,0.0009106169,0.00056184287,0.012548603,0.9852557,0.000019268295],"about_ca_topic_score_codex":0.13038118,"about_ca_topic_score_gemma":0.13720217,"teacher_disagreement_score":0.47114563,"about_ca_system_score_codex":0.007909296,"about_ca_system_score_gemma":0.008549272,"threshold_uncertainty_score":0.67203206},"labels":[],"label_agreement":null},{"id":"W7098019193","doi":"","title":"Sizing Multiple Buffer Pools for","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Buffer (optical fiber); Sizing; Task (project management); Greedy algorithm; Key (lock); Benchmark (surveying); Object (grammar)","score_opus":0.025004046116742274,"score_gpt":0.2579585943084479,"score_spread":0.23295454819170563,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7098019193","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":[0.16733171,0.0024941526,0.79897773,0.0012830744,0.00049324543,0.0012958228,0.0013790147,0.007301244,0.019443955],"genre_scores_gemma":[0.5613279,0.0006304467,0.42435777,0.00031444288,0.00008837151,0.0006028721,0.0015601452,0.00064935413,0.010468753],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987866,0.0001920436,0.000129791,0.00042723716,0.00024150875,0.00022284694],"domain_scores_gemma":[0.9979352,0.0005703944,0.00023549648,0.000532034,0.0005218285,0.00020504904],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001178323,0.0012836116,0.0009872505,0.0015781191,0.001008299,0.0033003404,0.003103613,0.00083346816,0.013897249],"category_scores_gemma":[0.0035038947,0.00071827037,0.00076725916,0.0016488417,0.00046078948,0.004700284,0.002374826,0.00084388175,0.0029859503],"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":[0.0016415527,0.00061171514,0.010760923,0.00086187135,0.00020072167,0.0006762725,0.000773602,0.15291104,0.19346379,0.03812499,0.028808024,0.57116556],"study_design_scores_gemma":[0.00019966291,0.00091418135,0.0036245543,0.00016531892,0.00025426483,0.0008532529,0.00081468106,0.739752,0.15242717,0.027716016,0.07311684,0.00016210203],"about_ca_topic_score_codex":0.002590536,"about_ca_topic_score_gemma":0.0035890345,"teacher_disagreement_score":0.013897249,"about_ca_system_score_codex":0.0013299172,"about_ca_system_score_gemma":0.0025197398,"threshold_uncertainty_score":0.046490908},"labels":[],"label_agreement":null},{"id":"W7109234313","doi":"10.1145/3769790","title":"Enjima: A Resource-Adaptive Stream Processing System","year":2025,"lang":"en","type":"article","venue":"Proceedings of the ACM on Management of Data","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Latency (audio); Stream processing; Dataflow; Pipeline (software); Workload; Throughput; Scheduling (production processes); Memory management; Response time","score_opus":0.04016599984991381,"score_gpt":0.2851652727165403,"score_spread":0.24499927286662648,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7109234313","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":[0.15901548,0.0029681362,0.6372416,0.0008712966,0.0010364422,0.0013617548,0.0048879576,0.1549608,0.037656486],"genre_scores_gemma":[0.55822974,0.0017159504,0.39401466,0.0018437959,0.00029138455,0.000789406,0.013376077,0.0021225605,0.027616378],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994066,0.00006310135,0.00007282425,0.00016331478,0.00020781737,0.00008643699],"domain_scores_gemma":[0.99925345,0.00012658782,0.00004956985,0.00022217468,0.0002260452,0.000122119],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00076643267,0.00077401305,0.00072972686,0.0006554783,0.00043531114,0.0013254497,0.0022992678,0.00045972795,0.005636983],"category_scores_gemma":[0.002095441,0.00047219006,0.00035451917,0.0007648136,0.00031964213,0.0020742153,0.0019439962,0.0012730701,0.0020235423],"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":[0.0059674974,0.0013586523,0.013496904,0.0007785579,0.00039809884,0.0012566103,0.00057847524,0.040858362,0.16677803,0.019065615,0.17896205,0.57050115],"study_design_scores_gemma":[0.0012017295,0.001188355,0.0076957024,0.000101035446,0.00030008276,0.0010137429,0.0001854237,0.75293,0.079643734,0.010506722,0.14499003,0.00024348372],"about_ca_topic_score_codex":0.002021376,"about_ca_topic_score_gemma":0.0023582892,"teacher_disagreement_score":0.005636983,"about_ca_system_score_codex":0.0007095376,"about_ca_system_score_gemma":0.0014190922,"threshold_uncertainty_score":0.018857598},"labels":[],"label_agreement":null},{"id":"W7117687674","doi":"10.1145/3786785","title":"Finding Smallest Witnesses for Conjunctive Queries","year":2025,"lang":"en","type":"article","venue":"ACM Transactions on Database Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Conjunctive query; Rewriting; Property (philosophy); Logarithm; Class (philosophy); Time complexity; Polynomial; Constant (computer programming)","score_opus":0.03221601730685047,"score_gpt":0.2997566851307163,"score_spread":0.2675406678238658,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7117687674","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":[0.14949176,0.0013273705,0.831946,0.003451832,0.00016503505,0.0005278337,0.0032598241,0.0046539293,0.0051764078],"genre_scores_gemma":[0.5633989,0.00084292056,0.42470145,0.0008864978,0.00020757102,0.0003641118,0.0052617057,0.0009452009,0.0033915383],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99349135,0.00095906446,0.00067256,0.002473644,0.0016640885,0.00073924754],"domain_scores_gemma":[0.96483773,0.02394155,0.0017078595,0.0071653477,0.0015717903,0.0007756352],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004470903,0.0015855831,0.0020711855,0.0010066187,0.0015611709,0.005324111,0.0038870473,0.002000483,0.007540354],"category_scores_gemma":[0.03845896,0.0013682396,0.002752077,0.0021589776,0.0022270032,0.018925123,0.004916113,0.0041498817,0.0012536395],"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":[0.0031803239,0.0008722564,0.01611427,0.0038825856,0.0007940118,0.0013272882,0.0045129675,0.1840881,0.046349373,0.34435418,0.0237843,0.37074032],"study_design_scores_gemma":[0.0003026444,0.00027633534,0.0010954109,0.00016886451,0.00030233513,0.0008534955,0.001087873,0.47465667,0.025843604,0.48551613,0.0098130815,0.00008360172],"about_ca_topic_score_codex":0.0024345268,"about_ca_topic_score_gemma":0.0031557204,"teacher_disagreement_score":0.007540354,"about_ca_system_score_codex":0.002093408,"about_ca_system_score_gemma":0.002685674,"threshold_uncertainty_score":0.025224984},"labels":[],"label_agreement":null},{"id":"W7118911591","doi":"10.14778/3773731.3773734","title":"Sampling-Based Predictive Database Buffer Management","year":2025,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Workload; Buffer (optical fiber); Sample (material); Volume (thermodynamics); Set (abstract data type); Data access; Data set","score_opus":0.011922581415300254,"score_gpt":0.25314774292857595,"score_spread":0.2412251615132757,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7118911591","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":[0.0561664,0.00080797856,0.9361778,0.00024318635,0.0000679452,0.00011999775,0.00022918588,0.0051614773,0.0010259446],"genre_scores_gemma":[0.811875,0.00039915755,0.18593371,0.00016624008,0.00007657797,0.00014501695,0.00041457536,0.00016723853,0.0008225798],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99833316,0.00033625044,0.000113882365,0.00042741274,0.000635663,0.0001536907],"domain_scores_gemma":[0.9936219,0.002890103,0.0006984888,0.0015268025,0.0010330498,0.00022972531],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022302936,0.000932616,0.0010646497,0.0011170055,0.00074629387,0.0015019322,0.0035878804,0.0005593653,0.00087274547],"category_scores_gemma":[0.010212601,0.00063342357,0.00042499823,0.0015037553,0.0006811727,0.0024954134,0.0012122084,0.0010553066,0.000274573],"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":[0.0007493925,0.00041613824,0.021423591,0.00021765233,0.00018496762,0.00016446153,0.00063037267,0.55010074,0.029962884,0.009059271,0.0059006494,0.38118982],"study_design_scores_gemma":[0.000016182517,0.00006211455,0.00066717155,0.0000078735175,0.00002574723,0.000060290477,0.00006205949,0.9892351,0.0068400507,0.0021517673,0.00085353333,0.000018065923],"about_ca_topic_score_codex":0.008015106,"about_ca_topic_score_gemma":0.012139035,"teacher_disagreement_score":0.008015106,"about_ca_system_score_codex":0.0012624977,"about_ca_system_score_gemma":0.002369787,"threshold_uncertainty_score":0.015936911},"labels":[],"label_agreement":null},{"id":"W7132862348","doi":"","title":"DTDMatch: dynamically matching streaming documents to DTDs","year":2005,"lang":"","type":"dissertation","venue":"TSpace","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Library and Archives Canada","funders":"","keywords":"Document type definition; XML; Set (abstract data type); Document Structure Description; XML validation; Matching (statistics); Sequence (biology); Identification (biology)","score_opus":0.014771449820254343,"score_gpt":0.34476637793684345,"score_spread":0.3299949281165891,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7132862348","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":[0.034470297,0.0018911072,0.8713571,0.0007220424,0.0006979419,0.00058491016,0.003693976,0.081389986,0.0051927124],"genre_scores_gemma":[0.1339611,0.0009433712,0.8431456,0.00062113494,0.00017320394,0.00026844547,0.008106866,0.0050809886,0.007699282],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99679214,0.00050228,0.0004046181,0.0007808513,0.0013489919,0.00017106535],"domain_scores_gemma":[0.9920854,0.0027512298,0.0006310827,0.0031992989,0.001009238,0.00032372965],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029761656,0.00083015463,0.0014915371,0.0031512743,0.0012999468,0.0034558729,0.003042807,0.0015983224,0.0054298164],"category_scores_gemma":[0.01473721,0.0009914463,0.0008744802,0.0033923797,0.0011397722,0.0053384937,0.003359684,0.0014833036,0.0027951766],"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":[0.0017746005,0.00023810806,0.0071186507,0.0009241349,0.00020415934,0.00079316006,0.0012720132,0.015351919,0.03983412,0.026082225,0.06415226,0.84225464],"study_design_scores_gemma":[0.00034710442,0.00039440938,0.0034073119,0.00024572274,0.00016264671,0.0019649395,0.0007210996,0.39900935,0.16133954,0.044414602,0.38768935,0.0003039739],"about_ca_topic_score_codex":0.006759886,"about_ca_topic_score_gemma":0.0055666165,"teacher_disagreement_score":0.006759886,"about_ca_system_score_codex":0.0019439731,"about_ca_system_score_gemma":0.0021119004,"threshold_uncertainty_score":0.018164515},"labels":[],"label_agreement":null},{"id":"W7132886178","doi":"","title":"Iterative improvement of database configurations","year":2006,"lang":"","type":"dissertation","venue":"TSpace","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bank of Canada; Library and Archives Canada","funders":"","keywords":"Iterative and incremental development; Process (computing); Class (philosophy); Control (management); Iterative method; Big data; Recommender system; Materialized view","score_opus":0.01938271900128443,"score_gpt":0.3331789206777541,"score_spread":0.3137962016764697,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7132886178","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":[0.10119235,0.0010279489,0.8827025,0.00052766706,0.000067017456,0.00066581566,0.000119192955,0.005957938,0.0077395453],"genre_scores_gemma":[0.44528106,0.00043423357,0.55007964,0.00015403281,0.00005264391,0.00037638968,0.0003802909,0.00036066017,0.0028810934],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99060225,0.0036032526,0.0005523399,0.001717074,0.0026762446,0.0008488355],"domain_scores_gemma":[0.97568786,0.01147921,0.001573546,0.0061035026,0.004612177,0.00054363697],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007073139,0.0017398503,0.0017860798,0.0020016027,0.001333967,0.0031933086,0.004303571,0.001771672,0.003508038],"category_scores_gemma":[0.04072747,0.0012222606,0.0011202584,0.0015057499,0.0011232386,0.0042071473,0.004753289,0.0019857113,0.0016558178],"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":[0.00056579243,0.000726864,0.011636455,0.00041831506,0.00023095672,0.0002197634,0.0018886954,0.2003215,0.020881748,0.0138954995,0.0057441886,0.7434703],"study_design_scores_gemma":[0.00012426339,0.0005160757,0.0029638363,0.000093579394,0.00014285193,0.0002666045,0.00061721745,0.9484997,0.018769585,0.01899545,0.0089133205,0.00009759798],"about_ca_topic_score_codex":0.0037745186,"about_ca_topic_score_gemma":0.0052257273,"teacher_disagreement_score":0.007073139,"about_ca_system_score_codex":0.0013145198,"about_ca_system_score_gemma":0.0024224883,"threshold_uncertainty_score":0.037406743},"labels":[],"label_agreement":null},{"id":"W7132937022","doi":"","title":"Dynamic, Hardware-Conscious Tuning of Concurrent Multithreaded Analytical Database Queries","year":2024,"lang":"","type":"dissertation","venue":"TSpace","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Query optimization; Hash function; Online aggregation; Execution time; Sargable; Profiling (computer programming); Query language; Query plan; Hash table","score_opus":0.031074463796688975,"score_gpt":0.3672445027240642,"score_spread":0.33617003892737524,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7132937022","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":[0.5827561,0.0009124448,0.39742926,0.00041932712,0.00015697302,0.00019729596,0.00014592557,0.011659996,0.0063226265],"genre_scores_gemma":[0.9449408,0.000106530664,0.053548843,0.000097663644,0.000030802086,0.00005695594,0.00009316695,0.00039695788,0.00072835287],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979253,0.00034272287,0.00011161021,0.0004993834,0.0008455791,0.00027541062],"domain_scores_gemma":[0.9972505,0.0011481816,0.0002359403,0.0008513383,0.0003270026,0.00018689618],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020062288,0.0006856799,0.0005813049,0.00041440263,0.0005487229,0.0016818085,0.0022704815,0.0004479034,0.00092397956],"category_scores_gemma":[0.006276561,0.00048967573,0.00033185838,0.0004411152,0.0007387956,0.0017166679,0.0015181248,0.0011016793,0.00021332136],"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":[0.0023562186,0.00092388707,0.028582053,0.00036471823,0.00016436017,0.00038555256,0.0011550412,0.3207405,0.2840734,0.021285512,0.0056861932,0.33428255],"study_design_scores_gemma":[0.00007482848,0.00016018767,0.0026777107,0.000009706014,0.00002939646,0.00007295356,0.00010992614,0.9396415,0.049682606,0.0039933706,0.0035180324,0.000029890101],"about_ca_topic_score_codex":0.002415945,"about_ca_topic_score_gemma":0.0022623783,"teacher_disagreement_score":0.002415945,"about_ca_system_score_codex":0.00084022176,"about_ca_system_score_gemma":0.0014467811,"threshold_uncertainty_score":0.010610104},"labels":[],"label_agreement":null},{"id":"W7132962253","doi":"","title":"A rule mechanism for peer-to-peer data management","year":2003,"lang":"","type":"dissertation","venue":"TSpace","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Toronto","keywords":"Mechanism (biology); Distributed database; Rule-based system; Exception handling; Data modeling; Data exchange; Database design; Active database; Data integration; Database testing","score_opus":0.05489080790830721,"score_gpt":0.3744753405451732,"score_spread":0.319584532636866,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7132962253","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":[0.0017976011,0.00033249485,0.9906222,0.00032461053,0.00020393445,0.00043753418,0.00011897149,0.0035221966,0.002640524],"genre_scores_gemma":[0.068353444,0.00080551446,0.9197503,0.0004324343,0.00038561109,0.0008837001,0.0005852164,0.00041129315,0.008392589],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.98801804,0.0023445827,0.0019670557,0.0019612173,0.0052052,0.0005039515],"domain_scores_gemma":[0.986432,0.004930713,0.00077850214,0.0044163275,0.0027649235,0.0006775629],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013143364,0.00082679244,0.0016750698,0.00223498,0.0026465796,0.00785616,0.0077276984,0.003272245,0.003834148],"category_scores_gemma":[0.019104637,0.0010965075,0.0017353013,0.0025213729,0.0032947797,0.011038847,0.0035513295,0.0038849912,0.0034980457],"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":[0.0002825647,0.00039870935,0.0010951194,0.0007518918,0.00022044055,0.0011053523,0.0013594126,0.021984717,0.014495442,0.61860687,0.019924669,0.31977478],"study_design_scores_gemma":[0.00038510156,0.00066619075,0.0006523909,0.0003717622,0.0003570539,0.0029328333,0.00030886437,0.27905038,0.036268167,0.3582936,0.32034162,0.00037213133],"about_ca_topic_score_codex":0.002057818,"about_ca_topic_score_gemma":0.0013236433,"teacher_disagreement_score":0.013143364,"about_ca_system_score_codex":0.0012031858,"about_ca_system_score_gemma":0.00304891,"threshold_uncertainty_score":0.069509566},"labels":[],"label_agreement":null},{"id":"W7161825175","doi":"10.82308/33799","title":"A page based storage manager for a native XML database /","year":2005,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"XML database; Efficient XML Interchange; Streaming XML; XML validation; XML Signature; XML; XML Encryption; XML framework","score_opus":0.017500664601564093,"score_gpt":0.2892408166450095,"score_spread":0.2717401520434454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7161825175","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":[0.032135453,0.0029428788,0.8314629,0.0011584909,0.0011722926,0.0014823613,0.0029263317,0.09361788,0.033101413],"genre_scores_gemma":[0.22322457,0.0015773174,0.68495363,0.001671542,0.000646961,0.0011849137,0.0060241655,0.0046319896,0.076084904],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99809116,0.00022440455,0.0003114583,0.00042080713,0.00080595526,0.00014612453],"domain_scores_gemma":[0.9970798,0.0003247428,0.00018829979,0.0013257102,0.00086753984,0.00021389236],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001720521,0.00067510677,0.00075972266,0.0013169046,0.0011221771,0.0046772673,0.002357816,0.0010266091,0.0131199565],"category_scores_gemma":[0.0032277114,0.0007737483,0.00058313005,0.0011380162,0.00068308855,0.0046490845,0.0020326425,0.0017528782,0.008650661],"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":[0.0014506262,0.00064066733,0.0069576716,0.0015111864,0.00024760372,0.0011753171,0.0026138716,0.006688958,0.14064115,0.13537435,0.15623395,0.5464646],"study_design_scores_gemma":[0.00029290657,0.00073498,0.0037222686,0.0001655781,0.00035818186,0.0030465815,0.0004844527,0.08116615,0.2626622,0.02302232,0.6240727,0.00027165125],"about_ca_topic_score_codex":0.0016489241,"about_ca_topic_score_gemma":0.0012851274,"teacher_disagreement_score":0.0131199565,"about_ca_system_score_codex":0.0010391135,"about_ca_system_score_gemma":0.0021765926,"threshold_uncertainty_score":0.043890655},"labels":[],"label_agreement":null},{"id":"W74024549","doi":"","title":"Making DB2Products Self-Managing: Strategies and Experiences.","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"IBM; Unix; Computer science; Watson; Key (lock); Center (category theory); Operating system; Research center; Software engineering; Software; Engineering management; Artificial intelligence","score_opus":0.017978282136510548,"score_gpt":0.25935939477448455,"score_spread":0.24138111263797402,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W74024549","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":[0.5628159,0.012232304,0.12905358,0.049333632,0.0015038116,0.00041737716,0.0002375948,0.0015787502,0.24282706],"genre_scores_gemma":[0.8643664,0.0066616647,0.09006892,0.004470347,0.00032807095,0.00018829902,0.00047823077,0.00083322247,0.032604847],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9899687,0.006254193,0.00023433458,0.00055061386,0.0020536769,0.00093845057],"domain_scores_gemma":[0.9895873,0.0043268013,0.0003881583,0.0014587943,0.0015403172,0.002698637],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.017500192,0.00062389113,0.00025759274,0.000729357,0.003875275,0.0097938785,0.0025052284,0.0022701456,0.0028950777],"category_scores_gemma":[0.025154263,0.00044089975,0.00039933508,0.0011269265,0.003457277,0.014729596,0.0063347155,0.00316256,0.0010682275],"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":[0.00033037746,0.0017842058,0.011890276,0.0006486746,0.000074546806,0.0019281601,0.26254013,0.0018340962,0.006116386,0.11560902,0.108123355,0.4891208],"study_design_scores_gemma":[0.000059130765,0.0004930833,0.002158226,0.00030473535,0.000038520375,0.0016301053,0.11081613,0.0039542885,0.0052566174,0.02649063,0.84869117,0.000107266584],"about_ca_topic_score_codex":0.0023756193,"about_ca_topic_score_gemma":0.0037331567,"teacher_disagreement_score":0.017500192,"about_ca_system_score_codex":0.0015472472,"about_ca_system_score_gemma":0.0022275967,"threshold_uncertainty_score":0.09255099},"labels":[],"label_agreement":null},{"id":"W74688787","doi":"10.1007/3-540-44503-x_18","title":"A Semi-monad for Semi-structured Data (ICDT Version)","year":2001,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bell (Canada); Glycemic Index Laboratories","funders":"","keywords":"Computer science; XML; Monad (category theory); XML Schema Editor; Streaming XML; XML validation; Programming language; Construct (python library); XML Encryption; XML Schema (W3C); Information retrieval; Efficient XML Interchange; XML database; Algebra over a field; Database; World Wide Web; Mathematics; Discrete mathematics; Functor; Pure mathematics","score_opus":0.03064829008049793,"score_gpt":0.27062425106218585,"score_spread":0.2399759609816879,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W74688787","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":[0.0016060675,0.0005694036,0.98164314,0.00034588334,0.00064146944,0.00009044008,0.0015348789,0.008849553,0.0047191377],"genre_scores_gemma":[0.06628778,0.0009809369,0.88421595,0.0008499273,0.00089995743,0.0005077854,0.008324349,0.005546873,0.032386396],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99733317,0.00044872132,0.0005049058,0.00052258576,0.0009117896,0.0002788593],"domain_scores_gemma":[0.9970413,0.00067708106,0.00013839931,0.0013751815,0.00058392895,0.0001840899],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034825453,0.00093516347,0.0011589421,0.0018180825,0.0012435687,0.0052480195,0.0019011843,0.0012501666,0.020939777],"category_scores_gemma":[0.0056002615,0.0015881025,0.0026077565,0.0034466397,0.0017505792,0.008081585,0.0036146427,0.004289442,0.009132547],"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":[0.00050203403,0.00013951203,0.000681231,0.000643746,0.000083698156,0.00029108766,0.00069742516,0.0049747205,0.0075488216,0.57282615,0.10076087,0.31085062],"study_design_scores_gemma":[0.00013577654,0.00016406071,0.00072230544,0.00026597054,0.00015143686,0.001063977,0.00015055445,0.049712937,0.015604108,0.47423112,0.4576504,0.00014723778],"about_ca_topic_score_codex":0.0029080634,"about_ca_topic_score_gemma":0.002846072,"teacher_disagreement_score":0.020939777,"about_ca_system_score_codex":0.0015106285,"about_ca_system_score_gemma":0.0021628179,"threshold_uncertainty_score":0.07005048},"labels":[],"label_agreement":null},{"id":"W79233526","doi":"","title":"Distributed query processing using composite semijoins.","year":2001,"lang":"en","type":"article","venue":"Scholarship at UWindsor (University of Windsor)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Composite number; Artificial intelligence; Algorithm","score_opus":0.02750438321188143,"score_gpt":0.23939234668252032,"score_spread":0.2118879634706389,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W79233526","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":[0.006506262,0.00030352297,0.989199,0.00009829621,0.0000520965,0.00016604364,0.000089691624,0.001651265,0.0019337656],"genre_scores_gemma":[0.14020468,0.0003565019,0.8544297,0.00011489769,0.000101490405,0.00030556787,0.00068489666,0.0003489683,0.003453319],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9966942,0.0008269092,0.00023383799,0.0005083585,0.0015726886,0.00016404333],"domain_scores_gemma":[0.99639624,0.0015479504,0.00027603042,0.0010175246,0.00059309526,0.00016920971],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031072504,0.0008154888,0.0011063736,0.0010397275,0.0010682106,0.0020119892,0.0019239427,0.0007192581,0.0034077957],"category_scores_gemma":[0.004704229,0.00054670125,0.0012739762,0.0013269748,0.00088561117,0.0025511503,0.0025796192,0.0012358633,0.0018871526],"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":[0.0017538032,0.00046303408,0.002240209,0.0010318935,0.00037663578,0.00055098097,0.0014206191,0.12880181,0.09184467,0.09494451,0.019708727,0.65686303],"study_design_scores_gemma":[0.00023334606,0.0006123107,0.0007554257,0.000056209476,0.00011155991,0.00081670634,0.0003350925,0.7965305,0.042463228,0.110696465,0.047315147,0.00007406777],"about_ca_topic_score_codex":0.0011687657,"about_ca_topic_score_gemma":0.0015807465,"teacher_disagreement_score":0.0034077957,"about_ca_system_score_codex":0.0004550202,"about_ca_system_score_gemma":0.0011006293,"threshold_uncertainty_score":0.016432881},"labels":[],"label_agreement":null},{"id":"W82412099","doi":"10.47164/ijngc.v1i2.17","title":"Searching Complex Data Without an Index.","year":2010,"lang":"en","type":"article","venue":"INTERNATIONAL JOURNAL OF NEXT-GENERATION COMPUTING","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Leverage (statistics); Information retrieval; Focus (optics); Index (typography); Relational database; Software; Data mining; Domain (mathematical analysis); Computation; Semi-structured data; World Wide Web; Machine learning; Programming language","score_opus":0.19191990482773225,"score_gpt":0.38935293094972134,"score_spread":0.1974330261219891,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W82412099","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":[0.022237644,0.0011941567,0.9459221,0.00061662274,0.00015362616,0.00030643836,0.0016644526,0.013718071,0.0141868815],"genre_scores_gemma":[0.23515712,0.0010271504,0.74430215,0.00057361636,0.00013617892,0.0003747652,0.004780795,0.0016468704,0.012001348],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99775165,0.00038829146,0.00026595747,0.0003862332,0.0010670742,0.00014090317],"domain_scores_gemma":[0.99351305,0.0030644096,0.00032919756,0.0021434424,0.00072944135,0.0002204482],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019201072,0.00065375917,0.0010598813,0.0022406997,0.001002812,0.004131458,0.001869414,0.0009220932,0.00929281],"category_scores_gemma":[0.0143606,0.0004311479,0.0006035014,0.003943357,0.0011619837,0.0066357357,0.0034062394,0.0007507638,0.00459486],"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":[0.001263695,0.00037817436,0.00857124,0.0016719261,0.00027144238,0.0010079932,0.0030121158,0.018601218,0.04481234,0.21434943,0.06206001,0.6440004],"study_design_scores_gemma":[0.00016409688,0.0003791619,0.0035885612,0.0003197367,0.00025964947,0.0024130403,0.0009653831,0.4798698,0.072214775,0.19804949,0.24159537,0.00018093573],"about_ca_topic_score_codex":0.0034052834,"about_ca_topic_score_gemma":0.004387243,"teacher_disagreement_score":0.00929281,"about_ca_system_score_codex":0.0007472336,"about_ca_system_score_gemma":0.0011996833,"threshold_uncertainty_score":0.031087577},"labels":[],"label_agreement":null},{"id":"W85188112","doi":"","title":"Indexing XML Data with ToXin.","year":2001,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":73,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Search engine indexing; Path expression; XML; Path (computing); Information retrieval; Data mining; Database index; XML database; Data structure; Query language; Database; World Wide Web; Computer network; Programming language","score_opus":0.038508694260878294,"score_gpt":0.273025936182309,"score_spread":0.23451724192143072,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W85188112","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":[0.016729994,0.0015096361,0.94507354,0.0005104601,0.00017247122,0.00060518424,0.0033377837,0.026534704,0.0055261706],"genre_scores_gemma":[0.12941237,0.001698637,0.83680767,0.0005196292,0.00012890575,0.0007193737,0.02069797,0.0012805755,0.008734787],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9970673,0.0005366018,0.0005089513,0.0002740919,0.0014442863,0.00016881866],"domain_scores_gemma":[0.9945773,0.0015281963,0.00055054115,0.0022353742,0.0009079495,0.00020072452],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032915368,0.0005790251,0.0008940592,0.0029627357,0.001042179,0.0032350696,0.0016947405,0.0008055665,0.0039191474],"category_scores_gemma":[0.009406891,0.0006483275,0.00085521635,0.005051325,0.0010431733,0.006611652,0.00442804,0.0010099699,0.0028884697],"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":[0.0012151524,0.00027416612,0.00650486,0.0010752992,0.00022329015,0.00053805485,0.0015904015,0.015556443,0.043570396,0.18649241,0.067772016,0.6751875],"study_design_scores_gemma":[0.00046210902,0.0007580239,0.003596656,0.00027398058,0.00020371452,0.0019972736,0.0007601783,0.32504946,0.0921394,0.16452901,0.4099813,0.00024895676],"about_ca_topic_score_codex":0.003042509,"about_ca_topic_score_gemma":0.0026803545,"teacher_disagreement_score":0.0039191474,"about_ca_system_score_codex":0.0013231202,"about_ca_system_score_gemma":0.0022449724,"threshold_uncertainty_score":0.017407477},"labels":[],"label_agreement":null},{"id":"W89277058","doi":"","title":"RA: An XML Schema Reduction Algorithm.","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"XML Schema Editor; Document Structure Description; Computer science; XML validation; Efficient XML Interchange; XML Schema (W3C); RELAX NG; Streaming XML; XML database; Information retrieval; XML Encryption; XML; Programming language; Database; World Wide Web","score_opus":0.008531778415264613,"score_gpt":0.23480484889657832,"score_spread":0.2262730704813137,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W89277058","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":[0.003264868,0.00071368855,0.9163293,0.00042838982,0.00020800444,0.00031898607,0.0024477579,0.07206221,0.004226727],"genre_scores_gemma":[0.019393148,0.00023629627,0.96466833,0.00025041832,0.00004628842,0.0003187021,0.0069961282,0.0027953903,0.0052953605],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99835193,0.00046883352,0.00013983861,0.00039951666,0.0005240431,0.00011587336],"domain_scores_gemma":[0.9980867,0.0006595049,0.00009861009,0.00062603183,0.00046933204,0.00005980515],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018556338,0.0014628049,0.0007703585,0.0033464518,0.0010362965,0.0023033768,0.0028477951,0.0018237812,0.018870816],"category_scores_gemma":[0.0063355165,0.00095714343,0.0015618949,0.0035928702,0.00070182653,0.0034281868,0.0022041972,0.0022846633,0.021815147],"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":[0.0004619422,0.0002055692,0.0010142468,0.0006184967,0.00016834839,0.00016811656,0.00031579655,0.009122888,0.012458502,0.022986453,0.1751413,0.7773384],"study_design_scores_gemma":[0.00044401764,0.00027862657,0.0015791035,0.0002852231,0.00022318967,0.0012230916,0.00054734456,0.517474,0.059843745,0.094607964,0.3233708,0.00012285229],"about_ca_topic_score_codex":0.0019630634,"about_ca_topic_score_gemma":0.0029260821,"teacher_disagreement_score":0.018870816,"about_ca_system_score_codex":0.000679418,"about_ca_system_score_gemma":0.001487739,"threshold_uncertainty_score":0.06312913},"labels":[],"label_agreement":null},{"id":"W90148240","doi":"10.1007/978-3-642-32597-7_37","title":"Alternative Query Optimization for Workload Management","year":2012,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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":"IBM (Canada); York University","funders":"","keywords":"Computer science; Workload; Query plan; Query optimization; Sargable; Query expansion; Throughput; Web query classification; Database; Query language; Resource (disambiguation); Web search query; Online aggregation; Distributed computing; Information retrieval; Search engine; Operating system; Computer network","score_opus":0.018893835191774972,"score_gpt":0.25643931941265463,"score_spread":0.23754548422087965,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W90148240","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":[0.024449786,0.0017104705,0.96218437,0.000553061,0.00035343936,0.00019125629,0.0003065006,0.0029711945,0.0072800345],"genre_scores_gemma":[0.44877294,0.0008677448,0.53517985,0.0003599864,0.00073570904,0.00033233443,0.0011627056,0.00086188246,0.011726818],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99436116,0.0012568067,0.00032974922,0.000686397,0.002647666,0.00071815],"domain_scores_gemma":[0.9958664,0.0012905332,0.00018895284,0.0014239199,0.0010196833,0.00021048536],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027224596,0.0016358958,0.0020117192,0.0014052866,0.0010684207,0.0031361964,0.004127738,0.00097512885,0.008837509],"category_scores_gemma":[0.006885,0.000572882,0.0011945998,0.0032712468,0.00085187115,0.0033176942,0.0019254871,0.0019892883,0.0016524453],"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":[0.0024185209,0.000806384,0.0015587099,0.000551213,0.00025353098,0.00020879686,0.00040301916,0.1506213,0.039139934,0.09349472,0.034469258,0.6760747],"study_design_scores_gemma":[0.000100387115,0.00022747609,0.0004850942,0.000018389444,0.00008458773,0.0001364252,0.000079439786,0.9420602,0.007002762,0.042703085,0.0070640286,0.000038237085],"about_ca_topic_score_codex":0.0022860167,"about_ca_topic_score_gemma":0.003039148,"teacher_disagreement_score":0.008837509,"about_ca_system_score_codex":0.0015136999,"about_ca_system_score_gemma":0.0017626549,"threshold_uncertainty_score":0.02956444},"labels":[],"label_agreement":null},{"id":"W91360576","doi":"","title":"Redundance of Trees.","year":2004,"lang":"en","type":"article","venue":"Ars Combinatoria","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Mathematics; Combinatorics","score_opus":0.010498553171263064,"score_gpt":0.23781660960231296,"score_spread":0.2273180564310499,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W91360576","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":[0.20035318,0.017293977,0.48935404,0.007264229,0.0011832273,0.00013795382,0.004859361,0.0025329369,0.27702108],"genre_scores_gemma":[0.86312824,0.00322053,0.07830131,0.0012606359,0.0012617473,0.000113523354,0.004429528,0.00047932475,0.047805063],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9978683,0.00042824514,0.00019196917,0.00047316623,0.00076923706,0.00026898077],"domain_scores_gemma":[0.9944729,0.0025511023,0.0005289935,0.0013229499,0.00078103447,0.0003429853],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014596629,0.00051768654,0.0010971841,0.0044110348,0.0018906478,0.0029327634,0.0012865412,0.0009299531,0.0132189905],"category_scores_gemma":[0.009140352,0.00062288414,0.001117898,0.0035120572,0.0019894294,0.0066086715,0.0027075345,0.0022723295,0.0029786895],"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":[0.00007955713,0.000030098669,0.001123901,0.00020286217,0.00003620945,0.00026710064,0.00042564597,0.0010591847,0.001102761,0.9400371,0.010755551,0.044879973],"study_design_scores_gemma":[0.000011794245,0.000022512491,0.0007633468,0.000047181074,0.000037053833,0.00073032005,0.00010937065,0.004775791,0.0009682535,0.9668032,0.025716722,0.000014531],"about_ca_topic_score_codex":0.0010130714,"about_ca_topic_score_gemma":0.0015763051,"teacher_disagreement_score":0.0132189905,"about_ca_system_score_codex":0.0014733158,"about_ca_system_score_gemma":0.00065773644,"threshold_uncertainty_score":0.044221938},"labels":[],"label_agreement":null},{"id":"W93368330","doi":"10.1007/978-3-642-15684-7_1","title":"Distributed XML Query Processing","year":2010,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Database Systems and Queries","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 Waterloo","funders":"","keywords":"Computer science; Streaming XML; XML database; Efficient XML Interchange; XML; Scalability; Variety (cybernetics); XML Signature; Database; XML Schema Editor; XML Encryption; XML validation; XML framework; Information retrieval; World Wide Web","score_opus":0.013018505649926492,"score_gpt":0.24554325006313757,"score_spread":0.23252474441321108,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W93368330","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":[0.006352706,0.0013409029,0.9231259,0.0005430931,0.00031522656,0.00019419119,0.0006669602,0.015874641,0.051586244],"genre_scores_gemma":[0.1435339,0.0023449257,0.66875625,0.0005779827,0.0004128947,0.00035335854,0.00778039,0.0031019582,0.17313837],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99891365,0.0001512294,0.000083245,0.0002469403,0.00052889803,0.00007595521],"domain_scores_gemma":[0.9993272,0.00015099694,0.000016797001,0.0003336584,0.00014369615,0.000027777976],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010334753,0.00095932494,0.001024,0.0010333138,0.00094921666,0.0023371375,0.002367725,0.0007597317,0.023572287],"category_scores_gemma":[0.0014378635,0.00071080716,0.0006955754,0.0020282017,0.00059830653,0.002838122,0.0016955417,0.0013178901,0.011024571],"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":[0.00038210483,0.00023302922,0.000473305,0.00032358646,0.0000699161,0.00018388775,0.00034663023,0.009088912,0.028840147,0.10461252,0.090648934,0.7647971],"study_design_scores_gemma":[0.00017461492,0.00018721337,0.001321602,0.00011829873,0.0001363103,0.0011756489,0.000252173,0.26172686,0.08250714,0.18959361,0.4627255,0.00008108353],"about_ca_topic_score_codex":0.0018417045,"about_ca_topic_score_gemma":0.0018741558,"teacher_disagreement_score":0.023572287,"about_ca_system_score_codex":0.000789551,"about_ca_system_score_gemma":0.0007653597,"threshold_uncertainty_score":0.07885718},"labels":[],"label_agreement":null},{"id":"W944015242","doi":"","title":"UDM：两个领域里的最佳选择——Analysis Service的新模型结合了关系型（Relational）和OLAP（联机分析处理）报告的优点","year":2004,"lang":"zh","type":"article","venue":"Windows & Net Magazine：国际中文版","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Online analytical processing; Computer science; Service (business); Relational database; Database; Data science; Data warehouse; Business","score_opus":0.01617371826844966,"score_gpt":0.24390013859812637,"score_spread":0.22772642032967672,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W944015242","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":[0.07611415,0.0019749275,0.7016721,0.010513608,0.00062695827,0.00075562915,0.0009017816,0.008093632,0.19934721],"genre_scores_gemma":[0.6180373,0.0009802101,0.32988682,0.002461494,0.00039926224,0.00044078715,0.00086103234,0.0007247315,0.046208374],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9959065,0.0014051342,0.00042829636,0.00067420496,0.0012801508,0.0003056805],"domain_scores_gemma":[0.9966539,0.0007391419,0.0002443804,0.00062318286,0.0014440538,0.00029534436],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00490792,0.00038201615,0.0005349434,0.0017942257,0.001704493,0.009528541,0.0010874262,0.0010637819,0.004913965],"category_scores_gemma":[0.0070744553,0.00046396154,0.0005245411,0.002792149,0.0020921205,0.008321757,0.0029876174,0.0016788874,0.0025475442],"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":[0.0002605718,0.00018669873,0.0063801697,0.00025694823,0.00006987708,0.00018872555,0.0036335501,0.0036303687,0.009375558,0.62885463,0.020331258,0.32683164],"study_design_scores_gemma":[0.0000968486,0.00015083204,0.0068296674,0.0002160831,0.00012883582,0.00050399214,0.0050871656,0.072077714,0.03366717,0.25223038,0.628851,0.0001603663],"about_ca_topic_score_codex":0.011348113,"about_ca_topic_score_gemma":0.0047204588,"teacher_disagreement_score":0.011348113,"about_ca_system_score_codex":0.0036506134,"about_ca_system_score_gemma":0.005295529,"threshold_uncertainty_score":0.026487231},"labels":[],"label_agreement":null},{"id":"W99269297","doi":"","title":"Globalizing Internet Websites.","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Acadia University","funders":"","keywords":"The Internet; World Wide Web; Computer science; XML; Internationalization; Java; Reusability; Business; Programming language; Software","score_opus":0.010897313127743103,"score_gpt":0.23750589872480096,"score_spread":0.22660858559705785,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W99269297","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":[0.030693997,0.00803104,0.119918436,0.008759581,0.001233183,0.0008573487,0.0020210848,0.01112998,0.81735533],"genre_scores_gemma":[0.36928636,0.023586709,0.3295529,0.0062189633,0.0010732336,0.0006334703,0.015157966,0.0048202104,0.2496702],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99819785,0.00052107207,0.00010436926,0.00021780071,0.00076348754,0.0001954639],"domain_scores_gemma":[0.99749845,0.0005281475,0.0002738482,0.00094403914,0.000462669,0.00029278622],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022534293,0.00057989877,0.0002730031,0.0030126597,0.0012407913,0.0074798865,0.00085705053,0.0011494637,0.019983515],"category_scores_gemma":[0.0064872396,0.00023764413,0.0005244921,0.004655702,0.0013070019,0.0074961605,0.0049501793,0.0012149776,0.006584736],"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":[0.000026021431,0.0000788553,0.0041976045,0.0004976295,0.00002397648,0.00031456928,0.002921712,0.0007610501,0.0032884418,0.2009712,0.09647104,0.690448],"study_design_scores_gemma":[0.000007688271,0.000035829875,0.0031144267,0.0002596337,0.000025677155,0.0006966677,0.0017518384,0.00094257557,0.002372009,0.03161614,0.95915836,0.000019250163],"about_ca_topic_score_codex":0.0013814337,"about_ca_topic_score_gemma":0.002670752,"teacher_disagreement_score":0.019983515,"about_ca_system_score_codex":0.0008903294,"about_ca_system_score_gemma":0.0014910464,"threshold_uncertainty_score":0.0668515},"labels":[],"label_agreement":null}]}