{"meta":{"query_hash":"17ba044f3be7","filters":{"venue":"Journal of Computational Science"},"cohort_total":29,"direct_labels_cover":0,"predictions_cover":29,"exported":29,"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/17ba044f3be7","api":"https://metacan.xera.ac/api/v1/cohort?venue=Journal+of+Computational+Science"},"results":[{"id":"W2022139216","doi":"10.1016/j.jocs.2014.04.009","title":"High performance computing theory and applications – Proceedings of SHARCNET Research Day 2012 (Guelph, Ontario)","year":2014,"lang":"en","type":"article","venue":"Journal of Computational Science","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Trent University; Perimeter Institute; University of Waterloo; Wilfrid Laurier University","funders":"","keywords":"Stochastic differential equation; Applied mathematics; Stochastic control; Optimal control; Computer science; Mathematics; Variation (astronomy); Variational principle; State space; Mathematical optimization; Mathematical analysis; Statistics; Physics","score_opus":0.03079851343778521,"score_gpt":0.27587276950170636,"score_spread":0.24507425606392114,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2022139216","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4427523,0.0001675222,0.5543354,0.00015342566,0.00005663345,0.00009960091,0.00000571936,0.0000033703345,0.0024260243],"genre_scores_gemma":[0.98465174,0.000010882768,0.015098543,0.000036080688,0.00014601978,0.0000058023847,0.0000011410871,0.0000045187926,0.00004528526],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989022,0.0000040560026,0.00054417667,0.00018797521,0.00017729787,0.00018429446],"domain_scores_gemma":[0.9981503,0.00033673565,0.0005772046,0.00006159286,0.00078491797,0.00008924902],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0051262877,0.00006316335,0.00020832093,0.00034401103,0.0003294604,0.00007229094,0.000411137,0.00002864526,0.000020708443],"category_scores_gemma":[0.00024221545,0.00006233682,0.000027021966,0.000724192,0.00047308527,0.00048231432,0.00009690892,0.0001954391,0.000013766309],"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":[0.0000091726,0.0000415255,0.004762639,0.000018165565,0.0000040743594,2.856896e-8,0.00044134815,0.0014878655,0.00010647574,0.9877161,0.0000216128,0.0053909975],"study_design_scores_gemma":[0.00016746868,0.000106230495,0.28128442,0.000027075546,0.000002330233,0.000011361546,0.000051181,0.005464601,0.00005186136,0.71037084,0.0023978725,0.00006474289],"about_ca_topic_score_codex":0.00009346269,"about_ca_topic_score_gemma":0.0000109710145,"teacher_disagreement_score":0.5418994,"about_ca_system_score_codex":0.00008913711,"about_ca_system_score_gemma":0.00016092113,"threshold_uncertainty_score":0.25420216},"labels":[],"label_agreement":null},{"id":"W2033655691","doi":"10.1016/j.jocs.2014.02.012","title":"Solution of large generalized <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" altimg=\"si4.gif\" overflow=\"scroll\"> <mml:msub> <mml:mi mathvariant=\"script\">H</mml:mi> <mml:mo>∞</mml:mo> </mml:msub> </mml:math> algebraic Riccati equations","year":2014,"lang":"en","type":"article","venue":"Journal of Computational Science","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","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":"Scroll; Computer science; Algorithm; Artificial intelligence; Philosophy; Theology","score_opus":0.019692982539419125,"score_gpt":0.2576172042473329,"score_spread":0.2379242217079138,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2033655691","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8472994,0.00010243959,0.14665306,0.0006893297,0.0009991921,0.000033514592,0.00003628082,0.000027883716,0.0041589127],"genre_scores_gemma":[0.9905515,0.000030076648,0.0077254334,0.0004943645,0.0009903837,0.000031843403,0.00007040783,0.00004611456,0.000059916067],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99677575,0.00013401498,0.00086761307,0.00041408517,0.001235337,0.0005731798],"domain_scores_gemma":[0.9974864,0.00036165264,0.0012161222,0.000302937,0.00030780325,0.0003250526],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0013622029,0.00022798596,0.00019683865,0.00022569683,0.00086578226,0.00032569817,0.0006426229,0.00017382081,0.0009266329],"category_scores_gemma":[0.00017239411,0.00028460578,0.0004398645,0.00062570546,0.00043476967,0.0009388674,0.00024762776,0.00044330422,0.0001609225],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009672312,0.00017059478,0.000019540787,0.000030903913,0.00010366816,0.000007518467,0.00034693308,0.07376933,0.0034818004,0.9153361,0.004149863,0.0024870634],"study_design_scores_gemma":[0.00088224834,0.0002860902,0.00032049863,0.0001433744,0.0001252784,0.00013356733,0.00015597897,0.9629029,0.019160679,0.014642177,0.000979942,0.000267266],"about_ca_topic_score_codex":0.0001589523,"about_ca_topic_score_gemma":0.000018350194,"teacher_disagreement_score":0.9006939,"about_ca_system_score_codex":0.000019077315,"about_ca_system_score_gemma":0.00069285725,"threshold_uncertainty_score":0.99998665},"labels":[],"label_agreement":null},{"id":"W2046201795","doi":"10.1016/j.jocs.2013.10.008","title":"EigenBlock algorithm for change detection – An application of adaptive dictionary learning techniques","year":2013,"lang":"en","type":"article","venue":"Journal of Computational Science","topic":"Anomaly Detection Techniques and Applications","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 Saskatchewan; York University; Statistics Canada","funders":"","keywords":"Computer science; Dictionary learning; Change detection; Algorithm; Artificial intelligence; Machine learning; Pattern recognition (psychology); Sparse approximation","score_opus":0.02018068831839023,"score_gpt":0.2893790152961578,"score_spread":0.2691983269777676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2046201795","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010733741,0.000027330405,0.98836035,0.00021768294,0.00007193541,0.00044139172,0.0000018097826,0.00007963131,0.0000661258],"genre_scores_gemma":[0.5605764,0.0000049025616,0.43917164,0.000041101746,0.0000965969,0.0000995198,7.572217e-7,0.000003354327,0.000005768003],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99878824,0.000033003525,0.00040449103,0.00020817925,0.00042439433,0.00014171342],"domain_scores_gemma":[0.99735075,0.0000996059,0.00063588016,0.00013481856,0.0016753214,0.00010361859],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006698594,0.00008496282,0.00013135665,0.00036257206,0.00033260084,0.0000789715,0.00060682243,0.000043296164,0.0000034310663],"category_scores_gemma":[0.000026158634,0.00007732613,0.00007648513,0.0009365127,0.00015524746,0.0020106798,0.00006623456,0.00012849219,0.0000026767734],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000032427845,0.000075318734,0.00006507976,0.0000028714203,0.0000048801685,1.0121623e-7,0.00013881814,0.0012691463,0.015233452,0.008038288,0.0000107168435,0.9751581],"study_design_scores_gemma":[0.000108079046,0.00089988,0.011951452,0.000012561771,0.000005653036,0.00007502553,0.00006791405,0.88574344,0.04769282,0.052387055,0.0009500292,0.000106080064],"about_ca_topic_score_codex":0.00004322152,"about_ca_topic_score_gemma":9.103299e-7,"teacher_disagreement_score":0.975052,"about_ca_system_score_codex":0.00009581959,"about_ca_system_score_gemma":0.00012774703,"threshold_uncertainty_score":0.3153268},"labels":[],"label_agreement":null},{"id":"W2068919549","doi":"10.1016/j.jocs.2010.12.002","title":"Examining random and designed tests to detect code mistakes in scientific software","year":2010,"lang":"en","type":"article","venue":"Journal of Computational Science","topic":"Software Engineering Research","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":"University of Ottawa; Royal Military College of Canada","funders":"","keywords":"Computer science; Mistake; Code (set theory); Test (biology); Software; Code coverage; Software bug; Programming language; Reliability engineering; Engineering","score_opus":0.029649452150085878,"score_gpt":0.29610406219953816,"score_spread":0.2664546100494523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2068919549","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5413347,0.000029274928,0.45803666,0.00017155863,0.00034282572,0.00005805632,4.6345258e-7,0.000017358743,0.000009107466],"genre_scores_gemma":[0.63733196,2.2859045e-7,0.362595,0.00003226833,0.000027255544,0.0000014553659,6.8577954e-8,0.0000030203944,0.000008718481],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9979625,0.00003912951,0.00032967023,0.00030047548,0.0010596672,0.00030855442],"domain_scores_gemma":[0.9964742,0.0022744152,0.00011874211,0.00018555307,0.00065054063,0.00029654521],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038639975,0.00009137307,0.00015476867,0.00090292963,0.00023486368,0.0007517593,0.0012089731,0.00002727941,0.0000042974884],"category_scores_gemma":[0.006504796,0.000079881014,0.000023440098,0.0019881702,0.00032165964,0.00093712745,0.000117171076,0.0002892118,0.000005642393],"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":[0.00010003701,0.00012280687,0.10453639,0.000041786665,0.000014156256,0.0002246077,0.0046187546,0.3783693,0.27814865,0.0024618686,0.00050288084,0.23085876],"study_design_scores_gemma":[0.0013067896,0.00026252388,0.9265121,0.00010122571,0.0000022260842,0.0005141432,0.000035059475,0.058527295,0.0047145057,0.0074766567,0.00031280745,0.00023463558],"about_ca_topic_score_codex":0.0000033842637,"about_ca_topic_score_gemma":0.00001381896,"teacher_disagreement_score":0.82197577,"about_ca_system_score_codex":0.00006896375,"about_ca_system_score_gemma":0.0007540367,"threshold_uncertainty_score":0.7787318},"labels":[],"label_agreement":null},{"id":"W2085092676","doi":"10.1016/j.jocs.2012.08.017","title":"Efficient SIMD solution of multiple systems of stiff IVPs","year":2012,"lang":"en","type":"article","venue":"Journal of Computational Science","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":9,"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 Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"SIMD; Computer science; Parallel computing; Applied mathematics; Mathematics","score_opus":0.023765874126207582,"score_gpt":0.2824321634234131,"score_spread":0.25866628929720553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2085092676","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.31183523,0.00034803498,0.68711615,0.00006481908,0.0005110497,0.000055798017,0.0000045589313,0.000016736278,0.00004764747],"genre_scores_gemma":[0.7865113,0.0000022771521,0.21344104,0.000007544246,0.0000327884,5.959834e-7,3.065633e-7,0.000002028183,0.00000208948],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979473,0.00003859089,0.0005867674,0.00012999131,0.0010520393,0.00024531723],"domain_scores_gemma":[0.99738246,0.0003730592,0.0010156983,0.00023721899,0.0008940099,0.000097559],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014957186,0.00008303481,0.00021446738,0.00040028483,0.00009973751,0.000037421756,0.0013021132,0.000031460633,0.0000011502802],"category_scores_gemma":[0.00071166334,0.00006702103,0.00005731808,0.000880332,0.00052253634,0.0009744828,0.0003178345,0.00011734561,0.000003043051],"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":[0.0000076056845,0.00013766119,0.0015912135,0.000017702867,0.0000062267704,0.0000010435965,0.00029736073,0.93495804,0.014853383,0.043842297,0.00006904267,0.0042184284],"study_design_scores_gemma":[0.0003565542,0.00020034211,0.027669651,0.000092603856,0.0000064313517,0.00014548276,0.00013915739,0.9610035,0.006624449,0.0034919998,0.00015729341,0.00011256654],"about_ca_topic_score_codex":0.000008863139,"about_ca_topic_score_gemma":2.9108412e-7,"teacher_disagreement_score":0.4746761,"about_ca_system_score_codex":0.00012241356,"about_ca_system_score_gemma":0.00027540937,"threshold_uncertainty_score":0.27330384},"labels":[],"label_agreement":null},{"id":"W2521096743","doi":"10.1016/j.jocs.2016.09.004","title":"A self-updating model driven by a higher-order hidden Markov chain for temperature dynamics","year":2016,"lang":"en","type":"article","venue":"Journal of Computational Science","topic":"Climate variability and models","field":"Environmental Science","cited_by":14,"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","keywords":"Hidden Markov model; Markov chain; Computer science; Series (stratigraphy); Stochastic modelling; Mean reversion; Time series; Markov model; Applied mathematics; Econometrics; Mathematics; Statistics; Artificial intelligence; Machine learning","score_opus":0.008489747261169907,"score_gpt":0.24689219522281633,"score_spread":0.23840244796164642,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2521096743","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.78805524,0.000010690026,0.20291828,0.0074379407,0.00018847754,0.00020729004,0.00006777974,0.000019501069,0.001094809],"genre_scores_gemma":[0.78115195,0.0000052440264,0.21827254,0.00031607208,0.00004063944,0.000003759657,0.0000024806454,0.000006235135,0.0002010603],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99851596,0.000028407987,0.0003458831,0.00022559802,0.0006289408,0.00025520992],"domain_scores_gemma":[0.99906117,0.00026543587,0.00027066143,0.00009351912,0.00015822519,0.00015096948],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010597713,0.000102069556,0.00013993825,0.000056628876,0.0002557401,0.00007081496,0.0004514692,0.00004685987,0.000117179465],"category_scores_gemma":[0.00014072486,0.00006729044,0.000064967826,0.0003443035,0.00029690197,0.0007612177,0.00012560461,0.00009212553,0.000008366809],"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":[0.00013253804,0.0005208338,0.007770082,0.000035354362,0.00003543391,0.0000041719813,0.0009222634,0.851552,0.09461932,0.01831158,0.0080933785,0.01800304],"study_design_scores_gemma":[0.00058356294,0.00009651048,0.0021431867,0.000030441615,0.000010192757,0.000022678927,0.000025452617,0.9627737,0.00011306105,0.033693105,0.00037577457,0.00013236677],"about_ca_topic_score_codex":0.000004432601,"about_ca_topic_score_gemma":0.0000054419143,"teacher_disagreement_score":0.11122166,"about_ca_system_score_codex":0.000514806,"about_ca_system_score_gemma":0.00017177797,"threshold_uncertainty_score":0.27440244},"labels":[],"label_agreement":null},{"id":"W2560378075","doi":"10.1016/j.jocs.2016.11.006","title":"Recent advances in parallel techniques for scientific computing","year":2016,"lang":"en","type":"article","venue":"Journal of Computational Science","topic":"Neural Networks and Applications","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":"St. Francis Xavier University","funders":"","keywords":"Computer science; Scalability; Cluster analysis; Parallel computing; Pipeline (software); Kernel (algebra); Scale (ratio); Benchmark (surveying); Artificial neural network; Implementation; Artificial intelligence; Mathematics","score_opus":0.024172417896376294,"score_gpt":0.32487627625100995,"score_spread":0.30070385835463365,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2560378075","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012051777,0.0005378753,0.98119456,0.005582364,0.00033226836,0.00013366608,0.0000010214628,0.000019406349,0.00014707682],"genre_scores_gemma":[0.6093183,0.00015238363,0.39026773,0.00014480407,0.000091679765,0.0000039628612,1.7142604e-7,0.000002357358,0.000018583372],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99868745,0.000020688662,0.0003923297,0.0002282825,0.00044684226,0.00022439174],"domain_scores_gemma":[0.99839914,0.0003771114,0.00032380185,0.00012466157,0.0006859371,0.00008935216],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014457438,0.00006643418,0.00011425608,0.0002662154,0.0002637829,0.00020602503,0.0010379791,0.000014905043,0.000002529082],"category_scores_gemma":[0.00011072247,0.000042107225,0.000045124045,0.0011007406,0.00028671988,0.0015418807,0.00010678527,0.000058855087,0.000002196609],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005439716,0.000043219923,0.00023224585,0.0000020850562,8.475281e-7,0.0000012210505,0.000048658403,0.01806622,0.0016548401,0.08176186,0.0003455669,0.8978378],"study_design_scores_gemma":[0.0008115371,0.000259082,0.010197973,0.00024805457,0.0000027963385,0.00012702419,0.000014567703,0.26640555,0.002695351,0.54015213,0.17882209,0.00026387977],"about_ca_topic_score_codex":1.8075364e-7,"about_ca_topic_score_gemma":0.0000015871066,"teacher_disagreement_score":0.89757395,"about_ca_system_score_codex":0.000090317044,"about_ca_system_score_gemma":0.00031987723,"threshold_uncertainty_score":0.20288314},"labels":[],"label_agreement":null},{"id":"W2749237848","doi":"10.1016/j.jocs.2017.08.008","title":"On enhancing the object migration automaton using the Pursuit paradigm","year":2017,"lang":"en","type":"article","venue":"Journal of Computational Science","topic":"Optimization and Search Problems","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":"Carleton University","funders":"","keywords":"Computer science; Benchmark (surveying); Automaton; Field (mathematics); Theoretical computer science; Cellular automaton; Learning automata; Task (project management); Graph; Realization (probability); Object (grammar); Artificial intelligence; Distributed computing; Mathematics","score_opus":0.03582544266573404,"score_gpt":0.3362522927853283,"score_spread":0.30042685011959425,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2749237848","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.108481795,0.000026409069,0.8729142,0.017416263,0.00054283405,0.00010322972,3.041169e-7,0.000011971749,0.00050299487],"genre_scores_gemma":[0.96964943,0.000005854291,0.029583244,0.0006453589,0.000086794345,8.7954635e-7,9.328092e-8,0.0000025179472,0.000025847403],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99798524,0.000091777336,0.00030661255,0.00014157147,0.0012849427,0.00018985051],"domain_scores_gemma":[0.99815357,0.00038974584,0.0006186486,0.00034804948,0.0004108748,0.00007909692],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0032427597,0.000073063355,0.000089068206,0.00012024896,0.0023265427,0.0021283354,0.0029962289,0.000016590842,0.000006979161],"category_scores_gemma":[0.0004866488,0.00003763802,0.00006170686,0.00033454545,0.00039905857,0.0015923548,0.0001997769,0.00018920029,0.00000741131],"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":[0.0000044903813,0.000025435635,0.00011183535,0.0000015509598,0.0000059790887,0.0000036527158,0.00090113055,0.84356815,0.0009100028,0.14952037,0.00026443874,0.004682969],"study_design_scores_gemma":[0.00014338104,0.00007802875,0.013122561,0.000035774163,0.0000026912473,0.000108817396,0.000027948217,0.92896247,0.000684856,0.056484107,0.0002920054,0.000057336212],"about_ca_topic_score_codex":0.000014112839,"about_ca_topic_score_gemma":0.000008919567,"teacher_disagreement_score":0.8611676,"about_ca_system_score_codex":0.000091783375,"about_ca_system_score_gemma":0.0007388745,"threshold_uncertainty_score":0.9989723},"labels":[],"label_agreement":null},{"id":"W2807284373","doi":"10.1016/j.jocs.2018.04.020","title":"Optimization in distributed information systems","year":2018,"lang":"en","type":"article","venue":"Journal of Computational Science","topic":"Cloud Computing and Resource Management","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 Manitoba; St. Francis Xavier University","funders":"","keywords":"Computer science; Distributed computing","score_opus":0.008257279946239862,"score_gpt":0.23919143705270823,"score_spread":0.23093415710646836,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2807284373","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.074840866,0.000017616941,0.92289925,0.0006080119,0.0006558665,0.00005556506,5.070126e-7,0.00001717245,0.00090514275],"genre_scores_gemma":[0.9433084,6.5580195e-7,0.056462366,0.000120556775,0.00010055923,4.5151586e-7,6.623488e-7,0.0000010620747,0.000005244793],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99859035,0.000038112838,0.00044642927,0.00009325411,0.00067304453,0.00015878532],"domain_scores_gemma":[0.9985508,0.00006826935,0.00037481097,0.00010741065,0.00082611776,0.000072645715],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013813569,0.000058329762,0.000096220065,0.00046710734,0.000156288,0.00035706593,0.0008157785,0.000017069267,0.0000018873488],"category_scores_gemma":[0.00013300021,0.000047704994,0.000026376189,0.0015591664,0.00014470804,0.00055039517,0.000154027,0.00008030595,0.000011102106],"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":[0.0000031913635,0.000018912186,0.00021277538,0.0000028962368,0.000001939383,0.0000018529886,0.0003101474,0.9791146,0.000004618714,0.015899051,0.00018469045,0.0042453585],"study_design_scores_gemma":[0.00024621747,0.00010127862,0.010701539,0.000039702474,0.0000011394541,0.000056353478,0.000054200216,0.986171,0.000013491395,0.0013821508,0.0011760532,0.000056883957],"about_ca_topic_score_codex":0.000008925053,"about_ca_topic_score_gemma":3.4266142e-7,"teacher_disagreement_score":0.86846757,"about_ca_system_score_codex":0.00014342248,"about_ca_system_score_gemma":0.00022688051,"threshold_uncertainty_score":0.3443195},"labels":[],"label_agreement":null},{"id":"W2898639560","doi":"10.1016/j.jocs.2018.10.008","title":"Benchmarking the performance of plane-wave vs. localized orbital basis set methods in DFT modeling of metal surface: a case study for Fe-(110)","year":2018,"lang":"en","type":"article","venue":"Journal of Computational Science","topic":"Advanced Chemical Physics Studies","field":"Physics and Astronomy","cited_by":19,"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; Regroupement Québécois sur les Matériaux de Pointe","funders":"Qatar National Research Fund","keywords":"Basis set; Basis function; Basis (linear algebra); Plane wave; Atomic orbital; Benchmark (surveying); Gaussian; Wave function; Density functional theory; Plane (geometry); Space (punctuation); Computer science; Physics; Mathematics; Quantum mechanics; Geometry","score_opus":0.04874787825788341,"score_gpt":0.37269996058447075,"score_spread":0.32395208232658734,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2898639560","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7885165,0.000015522333,0.21117716,0.00002097671,0.0000696429,0.000118884076,0.000011813933,9.761087e-7,0.00006851105],"genre_scores_gemma":[0.89653605,3.629886e-7,0.10335036,0.0000060806333,0.0000988395,0.0000019897777,8.9972417e-7,0.000004117942,0.0000013037945],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987339,0.000051098807,0.0005449099,0.00012863977,0.00038019568,0.00016128765],"domain_scores_gemma":[0.9981104,0.0005760541,0.00048725767,0.00007693141,0.0007099191,0.000039436396],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012735185,0.00009429343,0.00029137018,0.000069284266,0.00017958139,0.000015216216,0.00021085392,0.00000967532,0.0000058893443],"category_scores_gemma":[0.00004133002,0.000064999884,0.00008406859,0.00042366987,0.00035413224,0.00028579342,0.00009517159,0.00012290082,1.2205108e-7],"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":[0.000107705026,0.0001726596,0.0069050044,0.000012962554,0.00007096055,0.000003996145,0.002168521,0.98395216,0.0043383897,0.00040891615,0.0000067462647,0.0018520034],"study_design_scores_gemma":[0.0007812863,0.00043364128,0.0006377632,0.00004391951,0.000040398132,0.000042953245,0.003518287,0.96643794,0.008571204,0.019401347,0.000002709432,0.00008853964],"about_ca_topic_score_codex":0.00006233372,"about_ca_topic_score_gemma":0.0000029184373,"teacher_disagreement_score":0.10801953,"about_ca_system_score_codex":0.00004180211,"about_ca_system_score_gemma":0.00016902415,"threshold_uncertainty_score":0.26506186},"labels":[],"label_agreement":null},{"id":"W2997080587","doi":"10.1016/j.jocs.2019.101063","title":"An efficient and high accuracy finite-difference scheme for the acoustic wave equation in 3D heterogeneous media","year":2019,"lang":"en","type":"article","venue":"Journal of Computational Science","topic":"Electromagnetic Simulation and Numerical Methods","field":"Engineering","cited_by":23,"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 Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Richardson extrapolation; Extrapolation; Acoustic wave equation; Wave equation; Scheme (mathematics); Stability (learning theory); Grid; Mathematics; Boundary (topology); Central differencing scheme; Finite difference method; Finite difference; Applied mathematics; Runge–Kutta methods; Mathematical analysis; Algorithm; Acoustic wave; Computer science; Numerical analysis; Finite difference coefficient; Geometry; Acoustics; Finite element method; Physics","score_opus":0.02574013335362535,"score_gpt":0.29536637398088944,"score_spread":0.2696262406272641,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2997080587","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5826105,0.00006584858,0.41703117,0.000058423368,0.00015517052,0.00006824971,7.308656e-7,0.0000046612763,0.0000052578157],"genre_scores_gemma":[0.92799556,0.0000071954432,0.071889944,0.00006121648,0.00003864169,0.0000016871908,6.4346455e-7,0.000003860358,0.0000012535401],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992442,0.000027088983,0.00022666452,0.00008126329,0.00029654245,0.00012422683],"domain_scores_gemma":[0.9966632,0.002980731,0.00008037652,0.000053725686,0.00015979602,0.00006214007],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063563796,0.00005747675,0.000094450304,0.00011094368,0.000054077667,0.00005316086,0.00013887357,0.000018533034,0.000020203042],"category_scores_gemma":[0.0005367025,0.000040067724,0.000017782313,0.00028547124,0.000067106426,0.00010277614,0.000010671025,0.000091425485,0.0000013131556],"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":[0.000011991958,0.000012989711,0.00021333076,0.0000048341985,0.0000020390773,4.744506e-7,0.00016334049,0.96910083,0.009987028,0.00024469406,8.400756e-7,0.020257607],"study_design_scores_gemma":[0.00029381175,0.00014015449,0.0784788,0.000011522519,0.0000036837362,0.000014235436,0.000015234418,0.91797346,0.0003600719,0.0026557567,0.0000057827206,0.000047510515],"about_ca_topic_score_codex":0.0000014348973,"about_ca_topic_score_gemma":6.8048263e-7,"teacher_disagreement_score":0.34538507,"about_ca_system_score_codex":0.000047373767,"about_ca_system_score_gemma":0.000063568485,"threshold_uncertainty_score":0.16339143},"labels":[],"label_agreement":null},{"id":"W3157883511","doi":"10.1016/j.jocs.2021.101375","title":"Calibration of single-cell model parameters based on membrane resistance improves the accuracy of cardiac tissue simulations","year":2021,"lang":"en","type":"article","venue":"Journal of Computational Science","topic":"Cardiac electrophysiology and arrhythmias","field":"Medicine","cited_by":2,"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 Calgary","funders":"Universidade Federal de Juiz de Fora; Fundação de Amparo à Pesquisa do Estado de Minas Gerais; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; University of Calgary","keywords":"Mean squared error; Calibration; Waveform; Biological system; Algorithm; Mathematics; Root mean square; Computer science; Statistics; Physics","score_opus":0.017769827680105574,"score_gpt":0.2842395353090677,"score_spread":0.2664697076289621,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3157883511","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9703633,0.00017038605,0.026971221,0.0019138493,0.00011762657,0.000096546755,0.000013386354,0.0000026392254,0.0003510418],"genre_scores_gemma":[0.98454744,0.0000072677612,0.0150852,0.00025507234,0.00004744159,5.2356785e-7,0.0000050511735,0.0000034641241,0.000048532],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988961,0.00006845059,0.00034262595,0.000102588645,0.0004966937,0.00009353862],"domain_scores_gemma":[0.99771327,0.0009753801,0.00039890292,0.00012237564,0.00074017793,0.000049894705],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000327987,0.000059572678,0.00021716085,0.00009653163,0.00009464375,0.0000118507,0.00008835478,0.00002572247,0.0000058376077],"category_scores_gemma":[0.00056666834,0.00004142357,0.00011780425,0.0004650248,0.0002880815,0.000161424,0.00001334717,0.00012096959,2.3360403e-7],"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":[0.00008953966,0.00005670758,0.000018563327,0.000014343984,0.000008091011,0.000002816071,0.000058334994,0.5918734,0.4072812,0.00025876384,0.00003529634,0.00030294567],"study_design_scores_gemma":[0.0003661435,0.00025649363,0.003217044,0.000077311575,0.000052760446,0.000015443262,0.00003024941,0.54112935,0.45205247,0.0027305111,0.000027551874,0.000044677436],"about_ca_topic_score_codex":0.0000011953745,"about_ca_topic_score_gemma":5.402819e-7,"teacher_disagreement_score":0.050744064,"about_ca_system_score_codex":0.000042630058,"about_ca_system_score_gemma":0.0010269111,"threshold_uncertainty_score":0.18216962},"labels":[],"label_agreement":null},{"id":"W4226064814","doi":"10.1016/j.jocs.2022.101656","title":"Efficiency of parallel anisotropic mesh adaptation for the solution of the bidomain model in cardiac tissue","year":2022,"lang":"en","type":"article","venue":"Journal of Computational Science","topic":"Cardiovascular Function and Risk Factors","field":"Medicine","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":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada; American University of Sharjah; Heart and Stroke Foundation of Canada; Compute Canada; Royal Society; Université Laval","keywords":"Polygon mesh; Computer science; Estimator; Anisotropy; Nonlinear system; Computational science; Anisotropic diffusion; Mathematical optimization; Applied mathematics; Physics; Mathematics; Artificial intelligence; Optics","score_opus":0.021897107436601306,"score_gpt":0.27863551243275514,"score_spread":0.25673840499615386,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4226064814","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5696812,0.00030288234,0.42837167,0.0009290397,0.0004167135,0.00025097234,0.0000074655964,0.0000014897975,0.000038538747],"genre_scores_gemma":[0.9950187,0.000019298333,0.004848274,0.000046265122,0.000032458127,0.0000040978484,9.1287853e-7,0.0000024331484,0.000027569487],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986313,0.00006441597,0.00030532098,0.000068906884,0.000850042,0.00008002848],"domain_scores_gemma":[0.9991246,0.00016114468,0.0002806346,0.000083339684,0.00032377083,0.000026530004],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014223544,0.000040001763,0.000155324,0.00013377814,0.00018807505,0.0000051782517,0.00016357268,0.000011117521,0.0000073777087],"category_scores_gemma":[0.00014731876,0.000022802094,0.00019433632,0.0005814915,0.00018597377,0.0000712559,0.000039874765,0.00010678133,1.1415368e-7],"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":[0.00007386659,0.000054464086,0.0019121085,0.0000074095483,0.000018348808,2.619974e-7,0.00057782466,0.9893409,0.0036588563,0.0017794946,0.00010323965,0.0024732158],"study_design_scores_gemma":[0.0010002735,0.00027614465,0.17537987,0.000020911326,0.00007026189,0.000043518507,0.0008592639,0.81866175,0.00074255397,0.0024491663,0.0004591311,0.000037129572],"about_ca_topic_score_codex":0.000022879127,"about_ca_topic_score_gemma":0.0000022449317,"teacher_disagreement_score":0.42533746,"about_ca_system_score_codex":0.0001236171,"about_ca_system_score_gemma":0.00068941433,"threshold_uncertainty_score":0.14465402},"labels":[],"label_agreement":null},{"id":"W4230704803","doi":"10.1016/j.jocs.2012.10.002","title":"Preface","year":2013,"lang":"en","type":"article","venue":"Journal of Computational Science","topic":"Numerical methods for differential equations","field":"Mathematics","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":"Nonlinear system; Reaction–diffusion system; Diffusion; Advection; Stability (learning theory); Mathematics; Term (time); Numerical analysis; Applied mathematics; Mathematical analysis; Computer science; Physics","score_opus":0.06876360092324377,"score_gpt":0.39818008782307013,"score_spread":0.3294164868998264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4230704803","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3617256,0.0000075450416,0.63647676,0.0007505003,0.00019098328,0.000059604103,3.3326089e-7,0.0000072606736,0.0007814379],"genre_scores_gemma":[0.51429653,3.317939e-7,0.4855675,0.00004279273,0.000039712486,8.2677445e-7,4.8240597e-8,0.0000022384556,0.000049987513],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9988432,0.000043522676,0.00031940656,0.000067333,0.0006064789,0.000120050274],"domain_scores_gemma":[0.99810565,0.00063516945,0.0002996672,0.000063084335,0.00077531504,0.00012111027],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006834818,0.000048287948,0.00011108473,0.00013138916,0.00010675863,0.00007779999,0.00030836195,0.00001281773,0.00025698257],"category_scores_gemma":[0.0014341942,0.00003481339,0.000053313783,0.00043181758,0.00018834589,0.00053607917,0.00003761803,0.00009708213,0.000044427798],"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":[0.000020196016,0.0007218528,0.0016124162,0.000042176944,0.0000681589,0.000005288553,0.0013990755,0.021642754,0.035553448,0.6322462,0.005093733,0.30159467],"study_design_scores_gemma":[0.00010947199,0.000055732453,0.019041676,0.000012377369,0.0000062284435,0.000032322383,0.000028587174,0.0051994044,0.00045901514,0.9748801,0.00013264932,0.00004244156],"about_ca_topic_score_codex":0.0000032483333,"about_ca_topic_score_gemma":1.4987992e-7,"teacher_disagreement_score":0.34263387,"about_ca_system_score_codex":0.00005466634,"about_ca_system_score_gemma":0.00019120018,"threshold_uncertainty_score":0.28137788},"labels":[],"label_agreement":null},{"id":"W4281779348","doi":"10.1016/j.jocs.2022.101745","title":"Computational science for a better future","year":2022,"lang":"en","type":"article","venue":"Journal of Computational Science","topic":"Scientific Computing and Data Management","field":"Decision Sciences","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":"International Council for Canadian Studies","keywords":"Computer science","score_opus":0.07914762414839015,"score_gpt":0.4064927710852509,"score_spread":0.32734514693686073,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281779348","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.48659706,0.00007929993,0.4926754,0.012350952,0.006782734,0.00026910214,0.0000700761,0.000021397545,0.0011539712],"genre_scores_gemma":[0.8927598,2.7601232e-7,0.105321586,0.0013165342,0.00039577918,0.0000050976187,0.0000043911496,0.000004722514,0.00019183647],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9899141,0.00010878235,0.0010095692,0.0006523425,0.007908915,0.00040626654],"domain_scores_gemma":[0.9938037,0.0014716386,0.0009592132,0.00037345343,0.0031392514,0.0002527751],"candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.02761681,0.00011773749,0.00023015121,0.0017480274,0.002794434,0.001183312,0.004083646,0.000011739176,0.00028330274],"category_scores_gemma":[0.002144392,0.00009150501,0.0001643215,0.005819649,0.0011104395,0.0014150309,0.0010750924,0.00022011895,0.000024361616],"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":[0.000038967395,0.00010563834,0.0007492672,0.0000016571465,0.000006196001,0.000006014852,0.0004589635,0.8890956,0.00016251598,0.022645444,0.03248909,0.054240633],"study_design_scores_gemma":[0.0006826301,0.00029373728,0.03744384,0.000006546179,0.00000963222,0.00023975618,0.0014312649,0.48926157,0.000031138574,0.35214794,0.118277974,0.00017398314],"about_ca_topic_score_codex":0.000001965988,"about_ca_topic_score_gemma":4.3536443e-7,"teacher_disagreement_score":0.4061627,"about_ca_system_score_codex":0.0003165989,"about_ca_system_score_gemma":0.0021133814,"threshold_uncertainty_score":0.99985355},"labels":[],"label_agreement":null},{"id":"W4311087681","doi":"10.1016/j.jocs.2022.101928","title":"A broad approach to expert detection using syntactic and semantic social networks analysis in the context of Global Software Development","year":2022,"lang":"en","type":"article","venue":"Journal of Computational Science","topic":"Software Engineering Research","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":"Western University","funders":"Fundação de Amparo à Pesquisa do Estado de Minas Gerais; Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Computer science; Ontology; Task (project management); Social network analysis; Data science; Context (archaeology); Social network (sociolinguistics); Software development; Software; Knowledge management; Software engineering; Artificial intelligence; World Wide Web; Social media","score_opus":0.024940242092239495,"score_gpt":0.30004047692677327,"score_spread":0.2751002348345338,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4311087681","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.45928168,0.000050880033,0.54048735,0.000072454655,0.000056588793,0.00004504917,2.8021813e-7,0.000003744064,0.0000019837828],"genre_scores_gemma":[0.9167544,4.24796e-7,0.08311849,0.00009884885,0.000022043278,0.0000037073614,1.6515816e-7,0.0000016042214,2.9247911e-7],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99804664,0.00011609736,0.0003100525,0.00016881165,0.0011755339,0.00018283862],"domain_scores_gemma":[0.99905723,0.00039188034,0.0001705851,0.00007852232,0.00023963318,0.00006212771],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002050754,0.00006476921,0.00016268584,0.00037422808,0.00037296303,0.00012273536,0.0008211144,0.000012814373,0.0000010859953],"category_scores_gemma":[0.00025640675,0.0000530034,0.00004840836,0.00446162,0.00008095035,0.0003095109,0.00028454512,0.00016943342,1.05811765e-7],"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":[0.000011020272,0.00006419187,0.0134051265,0.0000039923507,0.000029058545,0.0000051202496,0.0041514514,0.9652173,0.00005647481,0.00027081938,0.0000053403137,0.016780093],"study_design_scores_gemma":[0.00012600038,0.000048638587,0.3851799,0.0000056783833,0.000007637974,0.00015653811,0.000516571,0.61368614,0.00001714906,0.00019065627,0.000009642841,0.000055453318],"about_ca_topic_score_codex":0.000041549963,"about_ca_topic_score_gemma":0.000005463752,"teacher_disagreement_score":0.45747274,"about_ca_system_score_codex":0.00044443522,"about_ca_system_score_gemma":0.0004451382,"threshold_uncertainty_score":0.2868568},"labels":[],"label_agreement":null},{"id":"W4328136169","doi":"10.1016/j.jocs.2023.102002","title":"A link prediction method based on topological nearest-neighbors similarity in directed networks","year":2023,"lang":"en","type":"article","venue":"Journal of Computational Science","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","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":"Carleton University","funders":"Basic Public Welfare Research Program of Zhejiang Province; National Natural Science Foundation of China; Zhejiang Office of Philosophy and Social Science","keywords":"Similarity (geometry); Computer science; Link (geometry); Benchmark (surveying); Robustness (evolution); Field (mathematics); Data mining; Distance matrix; Node (physics); k-nearest neighbors algorithm; Enhanced Data Rates for GSM Evolution; Topology (electrical circuits); Artificial intelligence; Algorithm; Mathematics","score_opus":0.019146567164580464,"score_gpt":0.33489030719160146,"score_spread":0.315743740027021,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4328136169","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1977386,0.000007935931,0.7992863,0.00142074,0.00017564902,0.00009970223,0.00000559806,0.000075252785,0.0011902454],"genre_scores_gemma":[0.96622974,9.3772326e-7,0.033351548,0.000090132016,0.00030634645,0.0000029647777,0.000007163684,0.0000038476687,0.00000732257],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985748,0.00014396747,0.0003846538,0.00017126472,0.00051932014,0.00020600964],"domain_scores_gemma":[0.99864537,0.0006634957,0.00023295214,0.00008578756,0.00028029387,0.000092119495],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017780962,0.00008618573,0.00018641823,0.0004305032,0.00015290968,0.000070682596,0.00029061598,0.00002811688,0.00009407562],"category_scores_gemma":[0.00007994011,0.00007028757,0.000104618535,0.0022711179,0.00012349628,0.0001657517,0.00005002073,0.00030349987,0.000002790967],"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":[0.000020758687,0.00005688983,0.03563532,6.0766183e-7,0.000006145778,0.0000043268838,0.000022916458,0.94742346,0.000021989918,0.0032899186,0.0003836495,0.013133993],"study_design_scores_gemma":[0.00014968566,0.00007647585,0.26658306,0.000021226497,0.0000056487274,0.0000010863554,0.000009881716,0.69867057,0.000020494128,0.034280438,0.0001374523,0.000043994743],"about_ca_topic_score_codex":0.000021608936,"about_ca_topic_score_gemma":0.0000021848978,"teacher_disagreement_score":0.76849115,"about_ca_system_score_codex":0.000079671496,"about_ca_system_score_gemma":0.00020456106,"threshold_uncertainty_score":0.28662437},"labels":[],"label_agreement":null},{"id":"W4367057102","doi":"10.1016/j.jocs.2023.102034","title":"A unified forcing scheme for the single relaxation lattice Boltzmann method","year":2023,"lang":"en","type":"article","venue":"Journal of Computational Science","topic":"Lattice Boltzmann Simulation Studies","field":"Engineering","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 Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Lattice Boltzmann methods; Discretization; Forcing (mathematics); Boltzmann equation; Mathematics; Applied mathematics; Momentum (technical analysis); Body force; Statistical physics; Mathematical analysis; Mechanics; Physics","score_opus":0.05296929016269584,"score_gpt":0.3353661978949451,"score_spread":0.28239690773224924,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4367057102","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.111074544,0.00015729065,0.88594043,0.0013592243,0.00065945036,0.00015717818,0.0000029239723,0.00008755574,0.00056139997],"genre_scores_gemma":[0.88087225,0.00000780835,0.11878546,0.00008023318,0.00016988796,0.0000040702416,0.0000011347377,0.000010357124,0.00006878135],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99886465,0.00001787748,0.00034369377,0.00008681829,0.0005065606,0.00018040484],"domain_scores_gemma":[0.9971472,0.0018869397,0.00017678471,0.00007272098,0.00066733523,0.000049016235],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018904512,0.000074090894,0.0001169583,0.0002195183,0.0003470597,0.00009985471,0.00025279215,0.000020469222,0.0000038770763],"category_scores_gemma":[0.00061984133,0.000052826803,0.000064963686,0.0010591976,0.00008931658,0.0005327504,0.000037710808,0.000100657046,0.000012082219],"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":[0.000007504927,0.00000570108,0.00008076158,0.000011987411,0.000025931713,7.652341e-7,0.00050661043,0.98693305,0.0025172902,0.004550781,0.00088931434,0.0044703274],"study_design_scores_gemma":[0.0003107278,0.000038141017,0.02139864,0.000024053059,0.000021268463,0.00001698038,0.00029507297,0.95775044,0.00053514395,0.01621928,0.0033168022,0.00007345528],"about_ca_topic_score_codex":7.9461586e-7,"about_ca_topic_score_gemma":9.217138e-7,"teacher_disagreement_score":0.76979774,"about_ca_system_score_codex":0.0001046224,"about_ca_system_score_gemma":0.00008686837,"threshold_uncertainty_score":0.26693374},"labels":[],"label_agreement":null},{"id":"W4384157336","doi":"10.1016/j.jocs.2023.102102","title":"The computational planet","year":2023,"lang":"en","type":"article","venue":"Journal of Computational Science","topic":"Computational Physics and Python Applications","field":"Computer Science","cited_by":3,"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":"International Council for Canadian Studies","keywords":"Planet; Computer science; Astrobiology; Astronomy; Biology; Physics","score_opus":0.018295342137415495,"score_gpt":0.2943474346308674,"score_spread":0.27605209249345186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4384157336","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020110963,0.00013682409,0.9640475,0.01179911,0.0012301449,0.00013624385,0.00000715294,0.00010983191,0.0024222175],"genre_scores_gemma":[0.95640254,0.0000145466865,0.042871248,0.000436099,0.00017309409,0.0000037190086,0.0000097899565,0.000005168738,0.00008381965],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978794,0.000040393392,0.00043670816,0.00017876828,0.0012183624,0.00024639987],"domain_scores_gemma":[0.9970944,0.0013837506,0.00037139334,0.00017861996,0.0008266911,0.00014513744],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015678544,0.00008772375,0.00010585706,0.000264462,0.0005736036,0.00033051183,0.0016995309,0.00001575669,0.000007860309],"category_scores_gemma":[0.000101005906,0.00006165189,0.000060834016,0.0017049542,0.00033418927,0.0007121135,0.00022198816,0.00014763916,0.0001584837],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000023071486,0.000014665883,0.00003722256,8.184529e-7,0.0000064132755,0.0000031593656,0.00010693671,0.47895634,0.000038629292,0.497276,0.012791669,0.010765849],"study_design_scores_gemma":[0.00012362537,0.000033313085,0.024994072,0.0000039017386,0.0000015593482,0.00007768355,0.0000146171715,0.50819916,0.0000072611906,0.43717775,0.029307174,0.000059863938],"about_ca_topic_score_codex":0.0000029286832,"about_ca_topic_score_gemma":5.4629163e-7,"teacher_disagreement_score":0.9362916,"about_ca_system_score_codex":0.00011109773,"about_ca_system_score_gemma":0.0012327001,"threshold_uncertainty_score":0.44117534},"labels":[],"label_agreement":null},{"id":"W4385638295","doi":"10.1016/j.jocs.2023.102119","title":"A framework for the comparison of errors in agent-based models using machine learning","year":2023,"lang":"en","type":"article","venue":"Journal of Computational Science","topic":"Opinion Dynamics and Social Influence","field":"Physics and Astronomy","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":"University at Buffalo; Thompson Rivers University; George Mason University","keywords":"Soar; Computer science; Artificial intelligence; Machine learning; Classifier (UML); Perception; Decision tree; Psychology","score_opus":0.0837010296547493,"score_gpt":0.40563199685798157,"score_spread":0.3219309672032323,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385638295","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.49980938,0.000016796737,0.49979964,0.00022232582,0.000095353644,0.000038904178,0.0000041014455,0.0000013397564,0.000012164731],"genre_scores_gemma":[0.9724978,5.4853683e-7,0.027429223,0.00001981208,0.000045273075,8.958512e-7,0.0000014203877,0.0000026616356,0.0000023677208],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999249,0.000020935184,0.00027836955,0.000057490583,0.00028666557,0.00010754158],"domain_scores_gemma":[0.9989001,0.0004893049,0.00032543248,0.000031360538,0.00022368642,0.000030121526],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007160596,0.000040600382,0.00011348698,0.0001160337,0.00019045464,0.000033209093,0.00020858215,0.000010974444,0.0000056025397],"category_scores_gemma":[0.000044364395,0.000030141457,0.000066115885,0.00062097586,0.00012723224,0.00013634967,0.000023488155,0.0001435868,3.1311131e-7],"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":[0.0000070088663,0.00002255025,0.027276628,0.0000023267512,0.0000043231007,9.409319e-8,0.0004551059,0.92151374,0.0000915825,0.04960017,0.000002485087,0.0010239711],"study_design_scores_gemma":[0.00013377253,0.00002647477,0.0072566657,0.000036440557,0.0000032124724,1.3478356e-7,0.00039343967,0.8681478,0.00003892354,0.12391946,0.000015627991,0.00002804148],"about_ca_topic_score_codex":0.000057971974,"about_ca_topic_score_gemma":0.0000014948823,"teacher_disagreement_score":0.4726884,"about_ca_system_score_codex":0.000026800779,"about_ca_system_score_gemma":0.00026790606,"threshold_uncertainty_score":0.14648423},"labels":[],"label_agreement":null},{"id":"W4389538277","doi":"10.1016/j.jocs.2023.102196","title":"Mining actionable concepts in concept lattice using Interestingness Propagation","year":2023,"lang":"en","type":"article","venue":"Journal of Computational Science","topic":"Rough Sets and Fuzzy Logic","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":"Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Bottleneck; Data science; Theoretical computer science; Data mining; Information retrieval","score_opus":0.059392799072551135,"score_gpt":0.3523125265898065,"score_spread":0.29291972751725537,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389538277","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.70445204,0.000027178903,0.29390404,0.00047855335,0.00061749294,0.000060538438,3.9528746e-7,0.000027964143,0.00043181455],"genre_scores_gemma":[0.8535957,0.0000014259807,0.1462132,0.00010242995,0.00007391325,6.370711e-7,4.7622444e-7,0.0000026868818,0.000009548858],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983993,0.00006095346,0.00041476332,0.00019295918,0.00068176666,0.00025023468],"domain_scores_gemma":[0.9986537,0.00031265427,0.00037049584,0.00009091949,0.00048252905,0.00008971474],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014781442,0.000077071825,0.00013758028,0.000476987,0.00020871498,0.00024025011,0.00074105116,0.000024257572,0.0000057679554],"category_scores_gemma":[0.0002916066,0.00006531505,0.000036575828,0.002561838,0.00020297238,0.001772341,0.00015635326,0.00013113608,0.000008389557],"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":[0.000007394835,0.000038398968,0.0018042376,0.000007016707,0.000003854611,0.00005779022,0.0017801111,0.9524353,0.0010415969,0.015107862,0.00010660976,0.02760984],"study_design_scores_gemma":[0.00030244395,0.00007285083,0.032177825,0.000075906355,0.0000018115397,0.00016746177,0.00025352946,0.9516774,0.00022806201,0.014875198,0.0000794818,0.00008806695],"about_ca_topic_score_codex":0.000010713592,"about_ca_topic_score_gemma":0.0000013419256,"teacher_disagreement_score":0.14914365,"about_ca_system_score_codex":0.00016143915,"about_ca_system_score_gemma":0.0006397506,"threshold_uncertainty_score":0.26634705},"labels":[],"label_agreement":null},{"id":"W4394566534","doi":"10.1016/j.jocs.2024.102283","title":"Analyzing modularity maximization in approximation, heuristic, and graph neural network algorithms for community detection","year":2024,"lang":"en","type":"article","venue":"Journal of Computational Science","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","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":"Polytechnique Montréal; University of Toronto","funders":"","keywords":"Modularity (biology); Heuristic; Computer science; Maximization; Artificial neural network; Graph; Algorithm; Theoretical computer science; Artificial intelligence; Mathematical optimization; Mathematics","score_opus":0.020075415100593307,"score_gpt":0.30094373188961965,"score_spread":0.28086831678902635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394566534","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27361718,0.00009078937,0.72601026,0.00008330634,0.00008421587,0.000072323404,0.000002079576,0.000010148598,0.00002967313],"genre_scores_gemma":[0.9478218,0.000002404318,0.051951427,0.000010319162,0.00019744482,0.0000038880157,0.000006743028,0.000004192515,0.0000017996337],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99913967,0.00008473597,0.00034223447,0.00010508472,0.00019892832,0.0001293657],"domain_scores_gemma":[0.9991382,0.000273136,0.00016539119,0.000056778328,0.00031826456,0.00004827807],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016326085,0.000070284674,0.0001362766,0.00029572748,0.00031048394,0.00020778547,0.00015144148,0.00001376098,0.00000462777],"category_scores_gemma":[0.000028753666,0.00006474096,0.00006566782,0.0010668944,0.000113810645,0.00047785,0.000041314182,0.00022059918,1.3419815e-7],"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":[0.000010576112,0.0000428672,0.009503187,0.000014598688,0.000021908261,5.3107857e-7,0.00016506121,0.886949,0.00016961982,0.011271062,0.000050709146,0.09180089],"study_design_scores_gemma":[0.000082657556,0.000033306755,0.025871692,0.000029545005,0.000014651618,0.0000053994563,0.000027543643,0.6893895,0.00005675126,0.28442246,0.00002163302,0.000044873505],"about_ca_topic_score_codex":0.00004857325,"about_ca_topic_score_gemma":0.000010935343,"teacher_disagreement_score":0.6742046,"about_ca_system_score_codex":0.000052052812,"about_ca_system_score_gemma":0.00007629663,"threshold_uncertainty_score":0.26400596},"labels":[],"label_agreement":null},{"id":"W4400011934","doi":"10.1016/j.jocs.2024.102379","title":"Computation at the Cutting Edge of Science","year":2024,"lang":"en","type":"article","venue":"Journal of Computational Science","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"International Council for Canadian Studies","keywords":"Computer science; Computation; Enhanced Data Rates for GSM Evolution; Computational science; Parallel computing; Artificial intelligence; Algorithm","score_opus":0.11367585900270406,"score_gpt":0.44182465747841043,"score_spread":0.3281487984757064,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400011934","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.76429653,0.0003736217,0.22378522,0.002784882,0.0042501483,0.000093694245,0.0000070769474,0.00001661204,0.0043922323],"genre_scores_gemma":[0.9897573,0.000001988425,0.009640319,0.000100969526,0.00012522125,3.1469045e-7,5.853608e-7,0.0000030478977,0.00037027313],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9926826,0.000092791386,0.0010400367,0.00045536543,0.005469081,0.00026017427],"domain_scores_gemma":[0.9938591,0.002723096,0.0006548314,0.00032162367,0.0023027952,0.00013851852],"candidate_categories":["metaresearch","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.031422317,0.00008843129,0.00017328767,0.0012510554,0.00094990875,0.0013035573,0.002461126,0.000013142226,0.000080972095],"category_scores_gemma":[0.0042923447,0.000049014725,0.00011810642,0.007445261,0.0035982132,0.0014566233,0.00080044614,0.00014611814,0.00009323615],"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":[0.00001652634,0.00005615755,0.0009933746,0.000012050043,0.000012843553,0.000014804457,0.0021340242,0.6655016,0.004839943,0.02572327,0.022131925,0.27856347],"study_design_scores_gemma":[0.00016318983,0.000112070185,0.040259298,0.00012337476,0.000016050119,0.00023574829,0.0009995735,0.8316118,0.0014686029,0.10973666,0.015156561,0.000117082505],"about_ca_topic_score_codex":0.000005960422,"about_ca_topic_score_gemma":0.000001462059,"teacher_disagreement_score":0.2784464,"about_ca_system_score_codex":0.00020416485,"about_ca_system_score_gemma":0.0013071442,"threshold_uncertainty_score":0.9997332},"labels":[],"label_agreement":null},{"id":"W4402289221","doi":"10.1016/j.jocs.2024.102426","title":"DeepDetect: An innovative hybrid deep learning framework for anomaly detection in IoT networks","year":2024,"lang":"en","type":"article","venue":"Journal of Computational Science","topic":"Network Security and Intrusion Detection","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":"Brandon University","funders":"Eesti Teadusagentuur","keywords":"Anomaly detection; Internet of Things; Computer science; Deep learning; Anomaly (physics); Artificial intelligence; Computer architecture; Embedded system; Physics","score_opus":0.011812688111160407,"score_gpt":0.28446663342730966,"score_spread":0.2726539453161492,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402289221","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24308215,0.00026039834,0.7551497,0.0002257484,0.0011175356,0.000092491435,2.0971896e-7,0.00004380548,0.000027947488],"genre_scores_gemma":[0.86281943,0.000011908,0.13660206,0.00015268732,0.00039889038,0.0000046846717,4.5280234e-7,0.0000067564993,0.0000031315244],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981823,0.00010060875,0.0005238834,0.0003315812,0.0005600633,0.00030159438],"domain_scores_gemma":[0.9980676,0.00063035975,0.0002744905,0.000106573396,0.00080261787,0.000118318545],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023722374,0.00012132824,0.00016984656,0.00078258786,0.0003549761,0.0006019154,0.0006943659,0.00006001226,0.0000070587016],"category_scores_gemma":[0.00035866466,0.00011102981,0.00007186709,0.003582961,0.00014551858,0.0018671782,0.00008750299,0.0006459121,0.0000031312927],"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":[0.000027538525,0.000028567782,0.000055803175,0.0000065666177,0.0000059078834,0.000013724893,0.0005444701,0.62443084,0.0004126478,0.024353232,0.0000049776054,0.35011572],"study_design_scores_gemma":[0.00013844408,0.0005866614,0.0036160836,0.00009649919,0.0000027179874,0.00021607488,0.000026076963,0.8614986,0.0012147066,0.1317568,0.0007323572,0.00011495388],"about_ca_topic_score_codex":0.0000058383853,"about_ca_topic_score_gemma":0.000010406885,"teacher_disagreement_score":0.61973727,"about_ca_system_score_codex":0.00022276811,"about_ca_system_score_gemma":0.0002998647,"threshold_uncertainty_score":0.5804284},"labels":[],"label_agreement":null},{"id":"W4404512492","doi":"10.1016/j.jocs.2024.102463","title":"Comparative evaluation of sparse and minimal data point cloud registration: A study on Tibiofemoral Bones","year":2024,"lang":"en","type":"article","venue":"Journal of Computational Science","topic":"3D Shape Modeling and Analysis","field":"Engineering","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":"Kementerian Keuangan Republik Indonesia; Lembaga Pengelola Dana Pendidikan","keywords":"Point cloud; Computer science; Cloud computing; Orthodontics; Point (geometry); Artificial intelligence; Mathematics; Medicine; Geometry","score_opus":0.1598750192136956,"score_gpt":0.3889262294235912,"score_spread":0.22905121020989558,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404512492","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97117096,0.00041601234,0.027675062,0.00018862782,0.00021258646,0.000059245194,0.0000071250324,0.000010008107,0.0002603966],"genre_scores_gemma":[0.9971038,0.0000038637477,0.0027744023,0.0000061918154,0.00010107975,3.5249246e-7,0.0000033245526,0.0000026265689,0.000004321763],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986185,0.000040473784,0.00031764578,0.00012161018,0.00083836087,0.00006340193],"domain_scores_gemma":[0.9993813,0.00010064817,0.000083612125,0.000092924085,0.0002967334,0.00004476782],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021880337,0.00005968319,0.00014048371,0.00019759191,0.000053230135,0.000090214875,0.00018528684,0.000010663714,0.0000069538105],"category_scores_gemma":[0.000059223683,0.0000475609,0.000023262422,0.0003795058,0.00009671645,0.0003905254,0.000026559532,0.00008940948,0.0000022343368],"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":[0.0000105729605,0.0000565688,0.00021709174,0.000009083788,0.00004630037,0.0000044110184,0.001326867,0.9945161,0.00043838847,0.00017407729,0.00047957868,0.0027209765],"study_design_scores_gemma":[0.00018100973,0.0001591504,0.011043431,0.00006696004,0.000075943135,0.000026950513,0.00061235577,0.985786,0.00010332354,0.0018856311,0.000011912303,0.00004732316],"about_ca_topic_score_codex":0.0000029321398,"about_ca_topic_score_gemma":0.0000032142068,"teacher_disagreement_score":0.0259329,"about_ca_system_score_codex":0.000044667544,"about_ca_system_score_gemma":0.00020618629,"threshold_uncertainty_score":0.19394773},"labels":[],"label_agreement":null},{"id":"W4406602249","doi":"10.1016/j.jocs.2025.102525","title":"Bayesian approaches for revealing complex neural network dynamics in Parkinson’s disease","year":2025,"lang":"en","type":"article","venue":"Journal of Computational Science","topic":"Neurological disorders and treatments","field":"Medicine","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":"Wilfrid Laurier University; University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; Alliance de recherche numérique du Canada","keywords":"Parkinson's disease; Computer science; Dynamics (music); Bayesian probability; Artificial neural network; Artificial intelligence; Bayesian network; Disease; Machine learning; Medicine; Psychology","score_opus":0.048668912428379264,"score_gpt":0.3182661554392713,"score_spread":0.269597243010892,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406602249","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8618049,0.00030577023,0.121291384,0.015128878,0.00024345212,0.00036866628,0.000007098982,0.000008000115,0.00084185635],"genre_scores_gemma":[0.983529,0.000004489379,0.014881966,0.0015042507,0.000044677894,0.0000032962241,0.000005699854,0.0000022684062,0.00002439918],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99921846,0.000020140551,0.00025816358,0.00012100756,0.00022651516,0.00015569585],"domain_scores_gemma":[0.9994536,0.00015752994,0.00011347754,0.000044213542,0.000120592704,0.00011057663],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000313874,0.00005936088,0.00015349801,0.00012469094,0.00010897989,0.00002712951,0.00011088736,0.000013603237,0.0000037744426],"category_scores_gemma":[0.00013360634,0.000043544165,0.00006941649,0.00044216024,0.00012750186,0.000089286936,0.000023316861,0.0000855327,2.212832e-7],"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":[0.00055200973,0.00033043182,0.31377965,0.000035389738,0.000017499764,0.00005024687,0.000020773774,0.65337336,0.000006348091,0.015661906,0.0005285794,0.01564381],"study_design_scores_gemma":[0.000590193,0.00008837536,0.4482723,0.000030384892,0.00001378695,0.0000050586045,0.000012481669,0.4866783,2.696286e-7,0.06419396,0.00009443675,0.000020484342],"about_ca_topic_score_codex":0.0000017444785,"about_ca_topic_score_gemma":0.0000040190894,"teacher_disagreement_score":0.16669506,"about_ca_system_score_codex":0.00011898445,"about_ca_system_score_gemma":0.00024701134,"threshold_uncertainty_score":0.17756796},"labels":[],"label_agreement":null},{"id":"W4408704205","doi":"10.1016/j.jocs.2025.102575","title":"Physics-informed neural networks for microflows: Rarefied gas dynamics in cylinder arrays","year":2025,"lang":"en","type":"article","venue":"Journal of Computational Science","topic":"Lattice Boltzmann Simulation Studies","field":"Engineering","cited_by":13,"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":"Fonds de recherche du Québec – Nature et technologies; European Research Council","keywords":"Dynamics (music); Gas dynamics; Physics; Artificial neural network; Cylinder; Statistical physics; Computer science; Mechanics; Artificial intelligence; Mechanical engineering; Acoustics; Engineering","score_opus":0.014932877573920554,"score_gpt":0.2886436959321828,"score_spread":0.2737108183582623,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408704205","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24108583,0.00014022575,0.75656736,0.00038263682,0.0007252069,0.000120682394,0.0000029418222,0.000019877314,0.00095525687],"genre_scores_gemma":[0.98664737,0.000008122545,0.013070573,0.00015152116,0.00009598785,0.0000024747762,0.0000023484365,0.000005243546,0.000016388158],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99909,0.0000073118335,0.0003947501,0.0000785369,0.00023965193,0.0001897109],"domain_scores_gemma":[0.9989931,0.00041922648,0.00010385509,0.000050407998,0.00039297057,0.000040443316],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034481383,0.00008527623,0.00016407063,0.00020897202,0.00010496614,0.000067567074,0.00021193603,0.000025864707,0.0000015832646],"category_scores_gemma":[0.00008000675,0.00007659056,0.000060497267,0.00067216327,0.000105943305,0.00045832578,0.000028736598,0.00013582275,6.591263e-7],"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":[0.000015750216,0.000011364932,0.0015374143,0.000014804578,0.00001779503,7.8647207e-7,0.00012460728,0.9900709,0.000037645124,0.0031371485,0.00020193189,0.0048298775],"study_design_scores_gemma":[0.0006154779,0.000016577225,0.011470239,0.00003820057,0.000009086692,0.0000039533406,0.00012421474,0.9764812,0.00004045889,0.011035823,0.0000942851,0.00007051196],"about_ca_topic_score_codex":8.282335e-7,"about_ca_topic_score_gemma":0.00000855014,"teacher_disagreement_score":0.74556154,"about_ca_system_score_codex":0.00039338882,"about_ca_system_score_gemma":0.00017329364,"threshold_uncertainty_score":0.3123272},"labels":[],"label_agreement":null},{"id":"W4410566011","doi":"10.1016/j.jocs.2025.102593","title":"From simulations to surrogates: Neural networks enhancing burn wound healing predictions","year":2025,"lang":"en","type":"article","venue":"Journal of Computational Science","topic":"Infrared Thermography in Medicine","field":"Medicine","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":"Institute of Infection and Immunity","funders":"Nederlandse Brandwonden Stichting; Health~Holland","keywords":"Burn wound; Wound healing; Computer science; Medicine; Surgery","score_opus":0.013274065599196923,"score_gpt":0.32407906892411725,"score_spread":0.31080500332492034,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410566011","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6225133,0.0001486466,0.37270212,0.0031145737,0.0009794988,0.00013369172,0.0000058230526,0.00001759509,0.00038473812],"genre_scores_gemma":[0.9836572,0.000002874857,0.014109855,0.0015382869,0.00064551417,0.0000012613826,0.0000069703324,0.000005398769,0.000032670036],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983142,0.00003492927,0.00058007264,0.00016453852,0.00068188814,0.00022438793],"domain_scores_gemma":[0.9976956,0.0006318148,0.00020812482,0.000121187695,0.0011037226,0.00023952447],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00071999995,0.00009683668,0.00023235638,0.0007003842,0.00035922127,0.00006289191,0.00021821777,0.00003874559,0.000059307717],"category_scores_gemma":[0.0006061398,0.00008104594,0.000089795656,0.0019814787,0.00023927704,0.00026861372,0.000043613018,0.00032128446,0.0000018084312],"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":[0.00006432543,0.000052420924,0.006964956,0.00000540396,0.000040938055,0.0000093246,0.0005504945,0.9870674,0.0033148532,0.00034370398,0.0003357672,0.0012504329],"study_design_scores_gemma":[0.0008775182,0.00024379765,0.14862521,0.00046017882,0.00009286119,0.000091067,0.00037576072,0.8410235,0.00024079162,0.0077068997,0.00018472741,0.00007770161],"about_ca_topic_score_codex":0.000025726691,"about_ca_topic_score_gemma":0.0000068545614,"teacher_disagreement_score":0.36114386,"about_ca_system_score_codex":0.00018000774,"about_ca_system_score_gemma":0.0005616637,"threshold_uncertainty_score":0.33049574},"labels":[],"label_agreement":null},{"id":"W4415533517","doi":"10.1016/j.jocs.2025.102734","title":"A generalized colouring method for a parallelizable integer linear programming approach to polyomino tiling","year":2025,"lang":"en","type":"article","venue":"Journal of Computational Science","topic":"Color Science and Applications","field":"Physics and Astronomy","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 Guelph","funders":"","keywords":"Parallelizable manifold; Integer programming; Scalability; Integer (computer science); Overhead (engineering); Computation","score_opus":0.023497177055913778,"score_gpt":0.37262405190821596,"score_spread":0.3491268748523022,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415533517","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08625388,0.000011860014,0.9113048,0.0007837682,0.00008318961,0.00023374979,0.0000020369257,0.0000050657845,0.0013216652],"genre_scores_gemma":[0.45873684,8.859284e-8,0.54090333,0.0001179999,0.00007856907,0.000025024146,8.267637e-7,0.0000015962197,0.00013574645],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991074,0.000014770073,0.00028845356,0.00016356976,0.0002321875,0.00019357991],"domain_scores_gemma":[0.99907583,0.00014488347,0.00015463804,0.00006645963,0.0004614611,0.00009672611],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010127373,0.000064218264,0.00013339272,0.00020552495,0.00032677862,0.0001242388,0.00038261779,0.00001035693,0.0000070691735],"category_scores_gemma":[0.00003921937,0.000053244723,0.00008357606,0.0009310169,0.00006648543,0.00021209901,0.00006204213,0.000075932476,0.000001581384],"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":[0.000028486273,0.00016423654,0.0007342993,0.000007009688,0.000019750592,1.07777915e-7,0.0003916706,0.7428403,0.0029840518,0.20845148,0.00041635716,0.043962244],"study_design_scores_gemma":[0.0005839067,0.00007618211,0.0011695635,0.00004239758,0.000023627459,0.0000048947313,0.00048263022,0.9285614,0.0023021048,0.050507,0.016125416,0.00012087876],"about_ca_topic_score_codex":0.000016664242,"about_ca_topic_score_gemma":3.6028263e-7,"teacher_disagreement_score":0.37248296,"about_ca_system_score_codex":0.00004594453,"about_ca_system_score_gemma":0.0005621542,"threshold_uncertainty_score":0.251335},"labels":[],"label_agreement":null}]}