{"meta":{"query_hash":"2112e0aa723d","filters":{"venue":"International Journal of Mathematical Modelling and Numerical Optimisation"},"cohort_total":8,"direct_labels_cover":0,"predictions_cover":8,"exported":8,"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/2112e0aa723d","api":"https://metacan.xera.ac/api/v1/cohort?venue=International+Journal+of+Mathematical+Modelling+and+Numerical+Optimisation"},"results":[{"id":"W2020141331","doi":"10.1504/ijmmno.2014.059940","title":"Transmission of news shocks in a small open economy DSGE model","year":2014,"lang":"en","type":"article","venue":"International Journal of Mathematical Modelling and Numerical Optimisation","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","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":"Dynamic stochastic general equilibrium; Economics; Small open economy; Aggregate (composite); Bayes estimator; Econometrics; Bayesian probability; Variance (accounting); Aggregate data; Markov chain Monte Carlo; Bayesian vector autoregression; Interest rate; Monetary economics; Macroeconomics; Monetary policy; Statistics","score_opus":0.10825978878896159,"score_gpt":0.27058691178044164,"score_spread":0.16232712299148006,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2020141331","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":[0.6571172,0.0012144934,0.31269586,0.0025080387,0.00018335828,0.00013354198,0.002962051,0.00047460475,0.022710852],"genre_scores_gemma":[0.9804205,0.00072821864,0.009681487,0.00013400501,0.00006471018,0.00009098641,0.0010861629,0.000047038073,0.007746933],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996718,0.00012569147,0.000018548884,0.00007156176,0.00006053781,0.000051758518],"domain_scores_gemma":[0.9984571,0.0009085792,0.000272993,0.00006291126,0.00019006236,0.00010825276],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010222562,0.00062699325,0.0010583557,0.00095049856,0.0005346266,0.0021749414,0.0011323096,0.0013937484,0.0027106612],"category_scores_gemma":[0.004960385,0.00052063534,0.0006301026,0.0007173564,0.0010103423,0.001297151,0.000749294,0.0011958446,0.00031696077],"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":[0.000101636266,0.000028246772,0.005436598,0.00003604396,0.00009587123,0.00036892842,0.00012380385,0.91759545,0.0006744519,0.07068179,0.0012754021,0.0035817716],"study_design_scores_gemma":[0.000034873512,0.000015448133,0.0017562165,0.00000884967,0.000042404143,0.0000452456,0.000054497454,0.9832613,0.00015852277,0.013395772,0.0011985148,0.00002825086],"about_ca_topic_score_codex":0.10665894,"about_ca_topic_score_gemma":0.037880477,"teacher_disagreement_score":0.10665894,"about_ca_system_score_codex":0.0015465557,"about_ca_system_score_gemma":0.0014456257,"threshold_uncertainty_score":0.21207625},"labels":[],"label_agreement":null},{"id":"W2058621231","doi":"10.1504/ijmmno.2014.065404","title":"Coupling a chaotically encoded firefly algorithm with ranking to a physics-based mathematical model for robust optimisation of a gas turbine energy system","year":2014,"lang":"en","type":"article","venue":"International Journal of Mathematical Modelling and Numerical Optimisation","topic":"Metaheuristic Optimization Algorithms Research","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":"Firefly algorithm; Chaotic; Computer science; Particle swarm optimization; Energy (signal processing); Chaos theory; Algorithm; Firefly protocol; Ranking (information retrieval); Mathematical optimization; Mathematics; Artificial intelligence","score_opus":0.035475518875267203,"score_gpt":0.2725561610619726,"score_spread":0.2370806421867054,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2058621231","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.045766644,0.0002684311,0.94832104,0.00015373298,0.000041420222,0.00005392805,0.000020365582,0.00016256156,0.0052119833],"genre_scores_gemma":[0.869045,0.0002745202,0.12703101,0.00005741768,0.00002681999,0.00014529715,0.000041974115,0.000045635352,0.0033323253],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998628,0.00005037089,0.000006060642,0.000020164896,0.000045813733,0.0000148625795],"domain_scores_gemma":[0.99979895,0.00011060665,0.000036395948,0.000014606045,0.000031786494,0.000007693888],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004830707,0.0005642268,0.00067841413,0.00035558842,0.00027975772,0.00070276286,0.00062681607,0.0008859121,0.0007984624],"category_scores_gemma":[0.0009121238,0.00027153932,0.0006452337,0.0003202366,0.0005227988,0.00047477664,0.00044255733,0.0005411088,0.00014187583],"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":[0.000008732531,0.000007636453,0.00009546646,0.000017686622,0.000009907859,0.000016599062,0.000010996461,0.99235356,0.0011846112,0.0031455944,0.00005791057,0.0030913113],"study_design_scores_gemma":[0.0000014944003,0.00000943777,0.000021123873,0.0000010430845,0.0000016494434,0.0000033817605,0.0000012047693,0.9994399,0.000114220275,0.00033166457,0.00007350974,0.000001412066],"about_ca_topic_score_codex":0.0031827863,"about_ca_topic_score_gemma":0.0020138887,"teacher_disagreement_score":0.0031827863,"about_ca_system_score_codex":0.0004977555,"about_ca_system_score_gemma":0.0006850619,"threshold_uncertainty_score":0.006328523},"labels":[],"label_agreement":null},{"id":"W2061702552","doi":"10.1504/ijmmno.2012.049603","title":"Local complex dimensions of a fractal string","year":2012,"lang":"en","type":"article","venue":"International Journal of Mathematical Modelling and Numerical Optimisation","topic":"Mathematical Dynamics and Fractals","field":"Mathematics","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":"Acadia University","funders":"Natural Sciences and Engineering Research Council of Canada; Institut national de recherche en informatique et en automatique (INRIA)","keywords":"Fractal; Mathematics; Multifractal system; Set (abstract data type); Fractal dimension on networks; Pure mathematics; Neighbourhood (mathematics); Statistical physics; Fractal dimension; Mathematical analysis; Fractal analysis; Computer science; Physics","score_opus":0.07755726752123687,"score_gpt":0.32922759288993847,"score_spread":0.2516703253687016,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2061702552","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":[0.8556443,0.001065229,0.10697764,0.0007260646,0.00012684031,0.000030596257,0.00012282582,0.0002224695,0.035083946],"genre_scores_gemma":[0.9888832,0.00033936964,0.005371915,0.0000812075,0.00007477689,0.000027605993,0.00007110929,0.000056661538,0.005094129],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9997737,0.000047924706,0.0000107397445,0.000061896804,0.000066129796,0.000039638748],"domain_scores_gemma":[0.99907047,0.00032733145,0.00017915598,0.0001098247,0.00014012556,0.00017313215],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006343038,0.00046575905,0.00056709757,0.0019324006,0.00076407177,0.0024147467,0.0007091515,0.0009395123,0.0037176847],"category_scores_gemma":[0.0025786737,0.00030054414,0.0004114531,0.0007546987,0.002333489,0.0027142651,0.0014392526,0.0009856448,0.0005189122],"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":[0.000051304953,0.00005449319,0.0018487644,0.00011156928,0.000024853145,0.0005533679,0.00051692035,0.035566658,0.01781159,0.93764675,0.0008807085,0.004932813],"study_design_scores_gemma":[0.000054298023,0.00017948679,0.0053441254,0.00008995732,0.000029794883,0.0010025923,0.00043817225,0.24692261,0.00524049,0.7360058,0.004586736,0.00010593408],"about_ca_topic_score_codex":0.0002875249,"about_ca_topic_score_gemma":0.00013345474,"teacher_disagreement_score":0.0037176847,"about_ca_system_score_codex":0.0008372056,"about_ca_system_score_gemma":0.0002105112,"threshold_uncertainty_score":0.012436926},"labels":[],"label_agreement":null},{"id":"W2131649588","doi":"10.1504/ijmmno.2011.039429","title":"The recent developments in microwave design","year":2011,"lang":"en","type":"article","venue":"International Journal of Mathematical Modelling and Numerical Optimisation","topic":"Microwave Engineering and Waveguides","field":"Engineering","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":"Carleton University","funders":"","keywords":"Artificial neural network; Computer science; Extrapolation; Microwave; Artificial intelligence; Process (computing); Machine learning; Mathematics","score_opus":0.05038697656347413,"score_gpt":0.23689033089501788,"score_spread":0.18650335433154375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2131649588","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":[0.012277256,0.61235654,0.26450753,0.0083860075,0.0030838088,0.0000557138,0.000109910936,0.00032071615,0.09890249],"genre_scores_gemma":[0.15763839,0.6477522,0.12807198,0.0028053487,0.005621626,0.00013613232,0.00024807916,0.00016482917,0.057561398],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.999338,0.00019201095,0.000046193025,0.000104845014,0.0002850073,0.000033979162],"domain_scores_gemma":[0.9990711,0.000445174,0.00007855337,0.0000820972,0.00028424154,0.000038738646],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010658696,0.00046578347,0.0005826048,0.0007900557,0.0002370067,0.0012290599,0.000751141,0.0012705014,0.005158326],"category_scores_gemma":[0.0020231996,0.00034526654,0.0004323753,0.0015919101,0.0007174029,0.0017595709,0.00065757247,0.0012089233,0.0020339156],"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":[0.00012771282,0.000071939736,0.00067934557,0.0027517537,0.000061916406,0.0001562599,0.0001525076,0.017727854,0.008626086,0.09457946,0.010812985,0.86425227],"study_design_scores_gemma":[0.000018399816,0.00018476987,0.0012315278,0.0007820728,0.000063730404,0.0006992387,0.00012765649,0.043625668,0.0068163923,0.058755703,0.88764054,0.000054354317],"about_ca_topic_score_codex":0.00043645647,"about_ca_topic_score_gemma":0.00055469584,"teacher_disagreement_score":0.005158326,"about_ca_system_score_codex":0.0006643814,"about_ca_system_score_gemma":0.0004788079,"threshold_uncertainty_score":0.01725638},"labels":[],"label_agreement":null},{"id":"W2147593270","doi":"10.1504/ijmmno.2014.065405","title":"Implementation of a fast non-dominated sorting firefly algorithm and a vehicle simulation model for multi-objective component sizing of a power-split PHEV powertrain: a comparative numerical study","year":2014,"lang":"en","type":"article","venue":"International Journal of Mathematical Modelling and Numerical Optimisation","topic":"Electric Vehicles and Infrastructure","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":"University of Waterloo","funders":"","keywords":"Firefly algorithm; Sizing; Metaheuristic; Powertrain; Sorting; Component (thermodynamics); Computer science; Mathematical optimization; Genetic algorithm; Automotive industry; Multi-objective optimization; Local search (optimization); Algorithm; Particle swarm optimization; Engineering; Mathematics; Machine learning","score_opus":0.029829461218748243,"score_gpt":0.3169682697173184,"score_spread":0.28713880849857015,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147593270","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3910781,0.0008541964,0.57471746,0.00060060766,0.0002468939,0.00031822332,0.0003110119,0.0010167939,0.030856686],"genre_scores_gemma":[0.91723454,0.000290008,0.07895695,0.000040866707,0.000016318125,0.00019259172,0.00014688933,0.000055502816,0.0030663437],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997842,0.00009469357,0.0000128289685,0.000022491053,0.000052573385,0.0000332291],"domain_scores_gemma":[0.99936527,0.00041645853,0.0000530268,0.000033918575,0.00010199061,0.00002942432],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008957637,0.00085079717,0.000995875,0.00079650787,0.00058584835,0.0010255387,0.0009044506,0.0017944265,0.003080999],"category_scores_gemma":[0.0012317349,0.00043839563,0.0011245073,0.000649853,0.0004336007,0.00067015406,0.00059061445,0.0009797576,0.00029676096],"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":[0.00003994599,0.000042591764,0.00040705522,0.00003585933,0.000014714858,0.000037618513,0.000018320306,0.9941036,0.0006850442,0.0010004739,0.00009103841,0.003523687],"study_design_scores_gemma":[0.000004708378,0.000019057425,0.000052834905,0.0000019999427,0.0000029143653,0.000002580911,0.000005958019,0.9995888,0.0001567683,0.00006329755,0.00009908954,0.000001931852],"about_ca_topic_score_codex":0.02247152,"about_ca_topic_score_gemma":0.011291485,"teacher_disagreement_score":0.02247152,"about_ca_system_score_codex":0.000740343,"about_ca_system_score_gemma":0.001070873,"threshold_uncertainty_score":0.04468143},"labels":[],"label_agreement":null},{"id":"W2162184119","doi":"10.1504/ijmmno.2012.049605","title":"A collage-based approach to inverse problems for non-linear elliptic PDEs","year":2012,"lang":"en","type":"article","venue":"International Journal of Mathematical Modelling and Numerical Optimisation","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","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":"Natural Sciences and Engineering Research Council of Canada","keywords":"Applied mathematics; Inverse; Elliptic curve; Mathematics; Computer science; Mathematical analysis; Geometry","score_opus":0.06363590445075847,"score_gpt":0.3136062239266725,"score_spread":0.24997031947591403,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162184119","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0031250012,0.00018848604,0.99298096,0.00015310587,0.00005183979,0.000025493853,0.000012022191,0.00003298634,0.003429986],"genre_scores_gemma":[0.33976468,0.0014943613,0.6369047,0.00048440095,0.00031179798,0.0004233688,0.000119297816,0.00023686567,0.020260539],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994413,0.00017251773,0.00002159675,0.00007475737,0.00024429013,0.00004554629],"domain_scores_gemma":[0.99905497,0.0004942471,0.00010790404,0.00012103906,0.00016538461,0.000056466837],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011938136,0.0010760512,0.00089369726,0.0009663081,0.00078072335,0.0011321979,0.0011271192,0.0018455592,0.0026729119],"category_scores_gemma":[0.0036286816,0.00040324082,0.0010577822,0.00060266047,0.002687524,0.0017577215,0.0042322627,0.0025950961,0.0007625097],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005896578,0.00004409738,0.00034600994,0.0001943472,0.000036786634,0.00021136041,0.0004098331,0.27990463,0.011908747,0.6639877,0.0017056182,0.041192],"study_design_scores_gemma":[0.000013563483,0.00006637354,0.000065072934,0.000041037267,0.000009638361,0.000116186835,0.000057596964,0.902181,0.0025336177,0.08901305,0.0058773165,0.00002567285],"about_ca_topic_score_codex":0.0019335856,"about_ca_topic_score_gemma":0.0013622106,"teacher_disagreement_score":0.0026729119,"about_ca_system_score_codex":0.00058077247,"about_ca_system_score_gemma":0.00086018274,"threshold_uncertainty_score":0.00894177},"labels":[],"label_agreement":null},{"id":"W2164634985","doi":"10.1504/ijmmno.2012.044711","title":"GATE: a genetic algorithm designed for expensive cost functions","year":2012,"lang":"en","type":"article","venue":"International Journal of Mathematical Modelling and Numerical Optimisation","topic":"Advanced Multi-Objective Optimization Algorithms","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":"Polytechnique Montréal","funders":"","keywords":"Convergence (economics); Computer science; Algorithm; Heuristic; Genetic algorithm; Local search (optimization); Mathematical optimization; Gaussian; Function (biology); Mathematics","score_opus":0.03710974873704519,"score_gpt":0.2977458013577234,"score_spread":0.2606360526206782,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2164634985","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0042820894,0.000118901284,0.99121475,0.000056694964,0.0000794772,0.00007174382,0.00005069779,0.00059058046,0.0035350427],"genre_scores_gemma":[0.13641858,0.00037438463,0.85542816,0.00019814949,0.00006557243,0.00043762673,0.0002563098,0.0004175865,0.0064036925],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997434,0.00006561261,0.000009961624,0.000042376505,0.00010608913,0.00003249457],"domain_scores_gemma":[0.9996649,0.00020443885,0.000023615847,0.000029204817,0.00006073754,0.000017085977],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050455856,0.00079482584,0.0008156053,0.0007682633,0.00040468745,0.00066156563,0.0012508348,0.0012577573,0.003504929],"category_scores_gemma":[0.0019041126,0.00032866886,0.00056749146,0.0008956173,0.00057137804,0.00068096304,0.00074638205,0.0009998488,0.0006715578],"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":[0.000097182514,0.000056838668,0.0005800151,0.0001619297,0.00006733068,0.00013595595,0.00006798313,0.6832242,0.006935417,0.080553435,0.006105126,0.2220147],"study_design_scores_gemma":[0.000027904494,0.00005323698,0.00008181596,0.000014989183,0.000017559378,0.000070742906,0.0000072814887,0.978312,0.0018366349,0.011114981,0.008451829,0.000011044481],"about_ca_topic_score_codex":0.0031651468,"about_ca_topic_score_gemma":0.0032215852,"teacher_disagreement_score":0.003504929,"about_ca_system_score_codex":0.0006014428,"about_ca_system_score_gemma":0.0011048906,"threshold_uncertainty_score":0.011725187},"labels":[],"label_agreement":null},{"id":"W2610954229","doi":"10.1504/ijmmno.2018.088992","title":"Tuning Runge-Kutta parameters on a family of ordinary differential equations","year":2018,"lang":"en","type":"article","venue":"International Journal of Mathematical Modelling and Numerical Optimisation","topic":"Numerical methods for differential equations","field":"Mathematics","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":"Polytechnique Montréal; Group for Research in Decision Analysis","funders":"","keywords":"Runge–Kutta methods; Ode; Ordinary differential equation; Euler method; Mathematics; Nonlinear system; L-stability; Numerical methods for ordinary differential equations; Applied mathematics; Class (philosophy); Differential equation; Set (abstract data type); Backward Euler method; Explicit and implicit methods; Euler equations; Mathematical analysis; Differential algebraic equation; Computer science; Artificial intelligence","score_opus":0.12771740427071235,"score_gpt":0.3670674458068171,"score_spread":0.23935004153610476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2610954229","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08433636,0.00069559575,0.906006,0.000119533695,0.000058213976,0.00023579066,0.000088362074,0.0010841758,0.0073759463],"genre_scores_gemma":[0.62720096,0.00048823375,0.36855015,0.000050657884,0.000013589456,0.0005850536,0.00014892717,0.00024887192,0.0027135923],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99940705,0.00023442863,0.00003754881,0.00007814538,0.00019089437,0.000051990795],"domain_scores_gemma":[0.9984674,0.00089709373,0.00016844644,0.00014698031,0.00028455566,0.000035464305],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016496071,0.000910583,0.00095851556,0.00059700664,0.000530302,0.00084353966,0.0008317969,0.0010670089,0.0016128777],"category_scores_gemma":[0.005668244,0.0004045428,0.00061210844,0.00041828817,0.0007663004,0.0007293681,0.0008345163,0.0011800886,0.00059143495],"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":[0.00009776279,0.00008131538,0.0011575794,0.00025350243,0.000045866578,0.00009818493,0.00019738573,0.93127525,0.013094539,0.0062708715,0.000738451,0.046689186],"study_design_scores_gemma":[0.00001239965,0.00004824958,0.00028025365,0.0000298548,0.000008090142,0.000028993692,0.000019322733,0.9924004,0.0042045563,0.0011265252,0.0018270292,0.000014259515],"about_ca_topic_score_codex":0.0024564236,"about_ca_topic_score_gemma":0.0022431742,"teacher_disagreement_score":0.0024564236,"about_ca_system_score_codex":0.00050211797,"about_ca_system_score_gemma":0.001063568,"threshold_uncertainty_score":0.008724034},"labels":[],"label_agreement":null}]}