{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":29,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":29,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"query_hash":"17ba044f3be7","filters":{"venue":"Journal of Computational Science"}},"results":[{"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,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"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","retraction":null,"screen_n_in":null,"score":{"opus":0.02574013335362535,"gpt":0.2953663739808894,"spread":0.2696262406272641,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000635638,0.00005747675,0.0000944503,0.0001109437,0.00005407767,0.00005316086,0.0001388736,0.00001853303,0.00002020304],"category_scores_gemma":[0.0005367025,0.00004006772,0.00001778231,0.0002854712,0.00006710643,0.0001027761,0.00001067102,0.00009142549,0.000001313156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004737377,"about_ca_system_score_gemma":0.00006356848,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001434897,"about_ca_topic_score_gemma":6.804826e-7,"domain_scores_codex":[0.9992442,0.00002708898,0.0002266645,0.00008126329,0.0002965425,0.0001242268],"domain_scores_gemma":[0.9966632,0.002980731,0.00008037652,0.00005372569,0.000159796,0.00006214007],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001199196,0.00001298971,0.0002133308,0.000004834199,0.000002039077,4.744506e-7,0.0001633405,0.9691008,0.009987028,0.0002446941,8.400756e-7,0.02025761],"study_design_scores_gemma":[0.0002938118,0.0001401545,0.0784788,0.00001152252,0.000003683736,0.00001423544,0.00001523442,0.9179735,0.0003600719,0.002655757,0.000005782721,0.00004751052],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5826105,0.00006584858,0.4170312,0.00005842337,0.0001551705,0.00006824971,7.308656e-7,0.000004661276,0.000005257816],"genre_scores_gemma":[0.9279956,0.000007195443,0.07188994,0.00006121648,0.00003864169,0.000001687191,6.434645e-7,0.000003860358,0.00000125354],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3453851,"threshold_uncertainty_score":0.1633914,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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","retraction":null,"screen_n_in":null,"score":{"opus":0.02007541510059331,"gpt":0.3009437318896196,"spread":0.2808683167890264,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001632608,0.00007028467,0.0001362766,0.0002957275,0.0003104839,0.0002077855,0.0001514415,0.00001376098,0.00000462777],"category_scores_gemma":[0.00002875367,0.00006474096,0.00006566782,0.001066894,0.0001138106,0.00047785,0.00004131418,0.0002205992,1.341981e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005205281,"about_ca_system_score_gemma":0.00007629663,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004857325,"about_ca_topic_score_gemma":0.00001093534,"domain_scores_codex":[0.9991397,0.00008473597,0.0003422345,0.0001050847,0.0001989283,0.0001293657],"domain_scores_gemma":[0.9991382,0.000273136,0.0001653912,0.00005677833,0.0003182646,0.00004827807],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001057611,0.0000428672,0.009503187,0.00001459869,0.00002190826,5.310786e-7,0.0001650612,0.886949,0.0001696198,0.01127106,0.00005070915,0.09180089],"study_design_scores_gemma":[0.00008265756,0.00003330675,0.02587169,0.000029545,0.00001465162,0.000005399456,0.00002754364,0.6893895,0.00005675126,0.2844225,0.00002163302,0.0000448735],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2736172,0.00009078937,0.7260103,0.00008330634,0.00008421587,0.0000723234,0.000002079576,0.0000101486,0.00002967313],"genre_scores_gemma":[0.9478218,0.000002404318,0.05195143,0.00001031916,0.0001974448,0.000003888016,0.000006743028,0.000004192515,0.000001799634],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6742046,"threshold_uncertainty_score":0.264006,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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","retraction":null,"screen_n_in":null,"score":{"opus":0.04874787825788341,"gpt":0.3726999605844707,"spread":0.3239520823265873,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001273519,0.00009429343,0.0002913702,0.00006928427,0.0001795814,0.00001521622,0.0002108539,0.00000967532,0.000005889344],"category_scores_gemma":[0.00004133002,0.00006499988,0.00008406859,0.0004236699,0.0003541322,0.0002857934,0.00009517159,0.0001229008,1.220511e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004180211,"about_ca_system_score_gemma":0.0001690241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006233372,"about_ca_topic_score_gemma":0.000002918437,"domain_scores_codex":[0.9987339,0.00005109881,0.0005449099,0.0001286398,0.0003801957,0.0001612877],"domain_scores_gemma":[0.9981104,0.0005760541,0.0004872577,0.00007693141,0.0007099191,0.0000394364],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000107705,0.0001726596,0.006905004,0.00001296255,0.00007096055,0.000003996145,0.002168521,0.9839522,0.00433839,0.0004089162,0.000006746265,0.001852003],"study_design_scores_gemma":[0.0007812863,0.0004336413,0.0006377632,0.00004391951,0.00004039813,0.00004295324,0.003518287,0.9664379,0.008571204,0.01940135,0.000002709432,0.00008853964],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7885165,0.00001552233,0.2111772,0.00002097671,0.0000696429,0.0001188841,0.00001181393,9.761087e-7,0.00006851105],"genre_scores_gemma":[0.8965361,3.629886e-7,0.1033504,0.000006080633,0.0000988395,0.000001989778,8.997242e-7,0.000004117942,0.000001303795],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1080195,"threshold_uncertainty_score":0.2650619,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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","retraction":null,"screen_n_in":null,"score":{"opus":0.01181268811116041,"gpt":0.2844666334273097,"spread":0.2726539453161492,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002372237,0.0001213282,0.0001698466,0.0007825879,0.0003549761,0.0006019154,0.0006943659,0.00006001226,0.000007058702],"category_scores_gemma":[0.0003586647,0.0001110298,0.00007186709,0.003582961,0.0001455186,0.001867178,0.00008750299,0.0006459121,0.000003131293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002227681,"about_ca_system_score_gemma":0.0002998647,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005838385,"about_ca_topic_score_gemma":0.00001040688,"domain_scores_codex":[0.9981823,0.0001006087,0.0005238834,0.0003315812,0.0005600633,0.0003015944],"domain_scores_gemma":[0.9980676,0.0006303597,0.0002744905,0.0001065734,0.0008026179,0.0001183185],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002753852,0.00002856778,0.00005580318,0.000006566618,0.000005907883,0.00001372489,0.0005444701,0.6244308,0.0004126478,0.02435323,0.000004977605,0.3501157],"study_design_scores_gemma":[0.0001384441,0.0005866614,0.003616084,0.00009649919,0.000002717987,0.0002160749,0.00002607696,0.8614986,0.001214707,0.1317568,0.0007323572,0.0001149539],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2430822,0.0002603983,0.7551497,0.0002257484,0.001117536,0.00009249143,2.09719e-7,0.00004380548,0.00002794749],"genre_scores_gemma":[0.8628194,0.000011908,0.1366021,0.0001526873,0.0003988904,0.000004684672,4.528023e-7,0.000006756499,0.000003131524],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6197373,"threshold_uncertainty_score":0.5804284,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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","retraction":null,"screen_n_in":null,"score":{"opus":0.02964945215008588,"gpt":0.2961040621995382,"spread":0.2664546100494523,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003863998,0.00009137307,0.0001547687,0.0009029296,0.0002348637,0.0007517593,0.001208973,0.00002727941,0.000004297488],"category_scores_gemma":[0.006504796,0.00007988101,0.0000234401,0.00198817,0.0003216596,0.0009371275,0.0001171711,0.0002892118,0.000005642393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006896375,"about_ca_system_score_gemma":0.0007540367,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003384264,"about_ca_topic_score_gemma":0.00001381896,"domain_scores_codex":[0.9979625,0.00003912951,0.0003296702,0.0003004755,0.001059667,0.0003085544],"domain_scores_gemma":[0.9964742,0.002274415,0.0001187421,0.0001855531,0.0006505406,0.0002965452],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.000100037,0.0001228069,0.1045364,0.00004178666,0.00001415626,0.0002246077,0.004618755,0.3783693,0.2781487,0.002461869,0.0005028808,0.2308588],"study_design_scores_gemma":[0.00130679,0.0002625239,0.9265121,0.0001012257,0.000002226084,0.0005141432,0.00003505947,0.05852729,0.004714506,0.007476657,0.0003128074,0.0002346356],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5413347,0.00002927493,0.4580367,0.0001715586,0.0003428257,0.00005805632,4.634526e-7,0.00001735874,0.000009107466],"genre_scores_gemma":[0.637332,2.285905e-7,0.362595,0.00003226833,0.00002725554,0.000001455366,6.857795e-8,0.000003020394,0.000008718481],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8219758,"threshold_uncertainty_score":0.7787318,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"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","retraction":null,"screen_n_in":null,"score":{"opus":0.008489747261169907,"gpt":0.2468921952228163,"spread":0.2384024479616464,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001059771,0.0001020696,0.0001399382,0.00005662888,0.0002557401,0.00007081496,0.0004514692,0.00004685987,0.0001171795],"category_scores_gemma":[0.0001407249,0.00006729044,0.00006496783,0.0003443035,0.000296902,0.0007612177,0.0001256046,0.00009212553,0.000008366809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000514806,"about_ca_system_score_gemma":0.000171778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004432601,"about_ca_topic_score_gemma":0.000005441914,"domain_scores_codex":[0.998516,0.00002840799,0.0003458831,0.000225598,0.0006289408,0.0002552099],"domain_scores_gemma":[0.9990612,0.0002654359,0.0002706614,0.00009351912,0.0001582252,0.0001509695],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000132538,0.0005208338,0.007770082,0.00003535436,0.00003543391,0.000004171981,0.0009222634,0.851552,0.09461932,0.01831158,0.008093379,0.01800304],"study_design_scores_gemma":[0.0005835629,0.00009651048,0.002143187,0.00003044162,0.00001019276,0.00002267893,0.00002545262,0.9627737,0.000113061,0.0336931,0.0003757746,0.0001323668],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7880552,0.00001069003,0.2029183,0.007437941,0.0001884775,0.00020729,0.00006777974,0.00001950107,0.001094809],"genre_scores_gemma":[0.781152,0.000005244026,0.2182725,0.0003160721,0.00004063944,0.000003759657,0.000002480645,0.000006235135,0.0002010603],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1112217,"threshold_uncertainty_score":0.2744024,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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","retraction":null,"screen_n_in":null,"score":{"opus":0.01493287757392055,"gpt":0.2886436959321828,"spread":0.2737108183582623,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003448138,0.00008527623,0.0001640706,0.000208972,0.0001049661,0.00006756707,0.000211936,0.00002586471,0.000001583265],"category_scores_gemma":[0.00008000675,0.00007659056,0.00006049727,0.0006721633,0.0001059433,0.0004583258,0.0000287366,0.0001358227,6.591263e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003933888,"about_ca_system_score_gemma":0.0001732936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":8.282335e-7,"about_ca_topic_score_gemma":0.00000855014,"domain_scores_codex":[0.99909,0.000007311834,0.0003947501,0.0000785369,0.0002396519,0.0001897109],"domain_scores_gemma":[0.9989931,0.0004192265,0.0001038551,0.000050408,0.0003929706,0.00004044332],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001575022,0.00001136493,0.001537414,0.00001480458,0.00001779503,7.864721e-7,0.0001246073,0.9900709,0.00003764512,0.003137148,0.0002019319,0.004829878],"study_design_scores_gemma":[0.0006154779,0.00001657723,0.01147024,0.00003820057,0.000009086692,0.000003953341,0.0001242147,0.9764812,0.00004045889,0.01103582,0.0000942851,0.00007051196],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2410858,0.0001402257,0.7565674,0.0003826368,0.0007252069,0.0001206824,0.000002941822,0.00001987731,0.0009552569],"genre_scores_gemma":[0.9866474,0.000008122545,0.01307057,0.0001515212,0.00009598785,0.000002474776,0.000002348437,0.000005243546,0.00001638816],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7455615,"threshold_uncertainty_score":0.3123272,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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","retraction":null,"screen_n_in":null,"score":{"opus":0.01914656716458046,"gpt":0.3348903071916015,"spread":0.315743740027021,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001778096,0.00008618573,0.0001864182,0.0004305032,0.0001529097,0.0000706826,0.000290616,0.00002811688,0.00009407562],"category_scores_gemma":[0.00007994011,0.00007028757,0.0001046185,0.002271118,0.0001234963,0.0001657517,0.00005002073,0.0003034999,0.000002790967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000796715,"about_ca_system_score_gemma":0.0002045611,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002160894,"about_ca_topic_score_gemma":0.000002184898,"domain_scores_codex":[0.9985748,0.0001439675,0.0003846538,0.0001712647,0.0005193201,0.0002060096],"domain_scores_gemma":[0.9986454,0.0006634957,0.0002329521,0.00008578756,0.0002802939,0.0000921195],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002075869,0.00005688983,0.03563532,6.076618e-7,0.000006145778,0.000004326884,0.00002291646,0.9474235,0.00002198992,0.003289919,0.0003836495,0.01313399],"study_design_scores_gemma":[0.0001496857,0.00007647585,0.2665831,0.0000212265,0.000005648727,0.000001086355,0.000009881716,0.6986706,0.00002049413,0.03428044,0.0001374523,0.00004399474],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1977386,0.000007935931,0.7992863,0.00142074,0.000175649,0.00009970223,0.00000559806,0.00007525278,0.001190245],"genre_scores_gemma":[0.9662297,9.377233e-7,0.03335155,0.00009013202,0.0003063465,0.000002964778,0.000007163684,0.000003847669,0.00000732257],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7684911,"threshold_uncertainty_score":0.2866244,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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","retraction":null,"screen_n_in":null,"score":{"opus":0.0249402420922395,"gpt":0.3000404769267733,"spread":0.2751002348345338,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002050754,0.00006476921,0.0001626858,0.0003742281,0.000372963,0.0001227354,0.0008211144,0.00001281437,0.000001085995],"category_scores_gemma":[0.0002564068,0.0000530034,0.00004840836,0.00446162,0.00008095035,0.0003095109,0.0002845451,0.0001694334,1.058118e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004444352,"about_ca_system_score_gemma":0.0004451382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004154996,"about_ca_topic_score_gemma":0.000005463752,"domain_scores_codex":[0.9980466,0.0001160974,0.0003100525,0.0001688116,0.001175534,0.0001828386],"domain_scores_gemma":[0.9990572,0.0003918803,0.0001705851,0.00007852232,0.0002396332,0.00006212771],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001102027,0.00006419187,0.01340513,0.000003992351,0.00002905854,0.00000512025,0.004151451,0.9652173,0.00005647481,0.0002708194,0.000005340314,0.01678009],"study_design_scores_gemma":[0.0001260004,0.00004863859,0.3851799,0.000005678383,0.000007637974,0.0001565381,0.000516571,0.6136861,0.00001714906,0.0001906563,0.000009642841,0.00005545332],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4592817,0.00005088003,0.5404873,0.00007245466,0.00005658879,0.00004504917,2.802181e-7,0.000003744064,0.000001983783],"genre_scores_gemma":[0.9167544,4.24796e-7,0.08311849,0.00009884885,0.00002204328,0.000003707361,1.651582e-7,0.000001604221,2.924791e-7],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4574727,"threshold_uncertainty_score":0.2868568,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"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","retraction":null,"screen_n_in":null,"score":{"opus":0.02189710743660131,"gpt":0.2786355124327551,"spread":0.2567384049961539,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001422354,0.00004000176,0.000155324,0.0001337781,0.000188075,0.000005178252,0.0001635727,0.00001111752,0.000007377709],"category_scores_gemma":[0.0001473188,0.00002280209,0.0001943363,0.0005814915,0.0001859738,0.0000712559,0.00003987477,0.0001067813,1.141537e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001236171,"about_ca_system_score_gemma":0.0006894143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002287913,"about_ca_topic_score_gemma":0.000002244932,"domain_scores_codex":[0.9986313,0.00006441597,0.000305321,0.00006890688,0.000850042,0.00008002848],"domain_scores_gemma":[0.9991246,0.0001611447,0.0002806346,0.00008333968,0.0003237708,0.00002653],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007386659,0.00005446409,0.001912109,0.000007409548,0.00001834881,2.619974e-7,0.0005778247,0.9893409,0.003658856,0.001779495,0.0001032396,0.002473216],"study_design_scores_gemma":[0.001000274,0.0002761447,0.1753799,0.00002091133,0.00007026189,0.00004351851,0.0008592639,0.8186617,0.000742554,0.002449166,0.0004591311,0.00003712957],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5696812,0.0003028823,0.4283717,0.0009290397,0.0004167135,0.0002509723,0.000007465596,0.000001489797,0.00003853875],"genre_scores_gemma":[0.9950187,0.00001929833,0.004848274,0.00004626512,0.00003245813,0.000004097848,9.128785e-7,0.000002433148,0.00002756949],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4253375,"threshold_uncertainty_score":0.144654,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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","retraction":null,"screen_n_in":null,"score":{"opus":0.03582544266573404,"gpt":0.3362522927853283,"spread":0.3004268501195942,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00324276,0.00007306335,0.00008906821,0.000120249,0.002326543,0.002128335,0.002996229,0.00001659084,0.000006979161],"category_scores_gemma":[0.0004866488,0.00003763802,0.00006170686,0.0003345454,0.0003990586,0.001592355,0.0001997769,0.0001892003,0.00000741131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009178337,"about_ca_system_score_gemma":0.0007388745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001411284,"about_ca_topic_score_gemma":0.000008919567,"domain_scores_codex":[0.9979852,0.00009177734,0.0003066126,0.0001415715,0.001284943,0.0001898505],"domain_scores_gemma":[0.9981536,0.0003897458,0.0006186486,0.0003480495,0.0004108748,0.00007909692],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004490381,0.00002543563,0.0001118353,0.00000155096,0.000005979089,0.000003652716,0.0009011306,0.8435681,0.0009100028,0.1495204,0.0002644387,0.004682969],"study_design_scores_gemma":[0.000143381,0.00007802875,0.01312256,0.00003577416,0.000002691247,0.0001088174,0.00002794822,0.9289625,0.000684856,0.05648411,0.0002920054,0.00005733621],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1084818,0.00002640907,0.8729142,0.01741626,0.0005428341,0.0001032297,3.041169e-7,0.00001197175,0.0005029949],"genre_scores_gemma":[0.9696494,0.000005854291,0.02958324,0.0006453589,0.00008679435,8.795463e-7,9.328092e-8,0.000002517947,0.0000258474],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8611676,"threshold_uncertainty_score":0.9989723,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"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","retraction":null,"screen_n_in":null,"score":{"opus":0.02376587412620758,"gpt":0.2824321634234131,"spread":0.2586662892972055,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001495719,0.00008303481,0.0002144674,0.0004002848,0.00009973751,0.00003742176,0.001302113,0.00003146063,0.00000115028],"category_scores_gemma":[0.0007116633,0.00006702103,0.00005731808,0.000880332,0.0005225363,0.0009744828,0.0003178345,0.0001173456,0.000003043051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001224136,"about_ca_system_score_gemma":0.0002754094,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008863139,"about_ca_topic_score_gemma":2.910841e-7,"domain_scores_codex":[0.9979473,0.00003859089,0.0005867674,0.0001299913,0.001052039,0.0002453172],"domain_scores_gemma":[0.9973825,0.0003730592,0.001015698,0.000237219,0.0008940099,0.000097559],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000007605684,0.0001376612,0.001591214,0.00001770287,0.00000622677,0.000001043597,0.0002973607,0.934958,0.01485338,0.0438423,0.00006904267,0.004218428],"study_design_scores_gemma":[0.0003565542,0.0002003421,0.02766965,0.00009260386,0.000006431352,0.0001454828,0.0001391574,0.9610035,0.006624449,0.003492,0.0001572934,0.0001125665],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3118352,0.000348035,0.6871161,0.00006481908,0.0005110497,0.00005579802,0.000004558931,0.00001673628,0.00004764747],"genre_scores_gemma":[0.7865113,0.000002277152,0.213441,0.000007544246,0.0000327884,5.959834e-7,3.065633e-7,0.000002028183,0.00000208948],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4746761,"threshold_uncertainty_score":0.2733038,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba; St. Francis Xavier University","funders":"","keywords":"Computer science; Distributed computing","retraction":null,"screen_n_in":null,"score":{"opus":0.008257279946239862,"gpt":0.2391914370527082,"spread":0.2309341571064684,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001381357,0.00005832976,0.00009622006,0.0004671073,0.000156288,0.0003570659,0.0008157785,0.00001706927,0.000001887349],"category_scores_gemma":[0.0001330002,0.00004770499,0.00002637619,0.001559166,0.000144708,0.0005503952,0.000154027,0.00008030595,0.00001110211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001434225,"about_ca_system_score_gemma":0.0002268805,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008925053,"about_ca_topic_score_gemma":3.426614e-7,"domain_scores_codex":[0.9985904,0.00003811284,0.0004464293,0.00009325411,0.0006730445,0.0001587853],"domain_scores_gemma":[0.9985508,0.00006826935,0.000374811,0.0001074106,0.0008261178,0.00007264571],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003191363,0.00001891219,0.0002127754,0.000002896237,0.000001939383,0.000001852989,0.0003101474,0.9791146,0.000004618714,0.01589905,0.0001846904,0.004245359],"study_design_scores_gemma":[0.0002462175,0.0001012786,0.01070154,0.00003970247,0.000001139454,0.00005635348,0.00005420022,0.986171,0.0000134914,0.001382151,0.001176053,0.00005688396],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07484087,0.00001761694,0.9228992,0.0006080119,0.0006558665,0.00005556506,5.070126e-7,0.00001717245,0.0009051427],"genre_scores_gemma":[0.9433084,6.55802e-7,0.05646237,0.0001205568,0.0001005592,4.515159e-7,6.623488e-7,0.000001062075,0.000005244793],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8684676,"threshold_uncertainty_score":0.3443195,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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","retraction":null,"screen_n_in":null,"score":{"opus":0.02018068831839023,"gpt":0.2893790152961578,"spread":0.2691983269777676,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006698594,0.00008496282,0.0001313566,0.0003625721,0.0003326008,0.0000789715,0.0006068224,0.00004329616,0.000003431066],"category_scores_gemma":[0.00002615863,0.00007732613,0.00007648513,0.0009365127,0.0001552475,0.00201068,0.00006623456,0.0001284922,0.000002676773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009581959,"about_ca_system_score_gemma":0.000127747,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004322152,"about_ca_topic_score_gemma":9.103299e-7,"domain_scores_codex":[0.9987882,0.00003300353,0.000404491,0.0002081792,0.0004243943,0.0001417134],"domain_scores_gemma":[0.9973508,0.0000996059,0.0006358802,0.0001348186,0.001675321,0.0001036186],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003242784,0.00007531873,0.00006507976,0.00000287142,0.000004880168,1.012162e-7,0.0001388181,0.001269146,0.01523345,0.008038288,0.00001071684,0.9751581],"study_design_scores_gemma":[0.000108079,0.00089988,0.01195145,0.00001256177,0.000005653036,0.00007502553,0.00006791405,0.8857434,0.04769282,0.05238706,0.0009500292,0.0001060801],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01073374,0.0000273304,0.9883603,0.0002176829,0.00007193541,0.0004413917,0.000001809783,0.00007963131,0.0000661258],"genre_scores_gemma":[0.5605764,0.000004902562,0.4391716,0.00004110175,0.0000965969,0.0000995198,7.572217e-7,0.000003354327,0.000005768003],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.975052,"threshold_uncertainty_score":0.3153268,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"International Council for Canadian Studies","keywords":"Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.07914762414839015,"gpt":0.4064927710852509,"spread":0.3273451469368607,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.02761681,0.0001177375,0.0002301512,0.001748027,0.002794434,0.001183312,0.004083646,0.00001173918,0.0002833027],"category_scores_gemma":[0.002144392,0.00009150501,0.0001643215,0.005819649,0.00111044,0.001415031,0.001075092,0.0002201189,0.00002436162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003165989,"about_ca_system_score_gemma":0.002113381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001965988,"about_ca_topic_score_gemma":4.353644e-7,"domain_scores_codex":[0.9899141,0.0001087823,0.001009569,0.0006523425,0.007908915,0.0004062665],"domain_scores_gemma":[0.9938037,0.001471639,0.0009592132,0.0003734534,0.003139251,0.0002527751],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000389674,0.0001056383,0.0007492672,0.000001657147,0.000006196001,0.000006014852,0.0004589635,0.8890956,0.000162516,0.02264544,0.03248909,0.05424063],"study_design_scores_gemma":[0.0006826301,0.0002937373,0.03744384,0.000006546179,0.00000963222,0.0002397562,0.001431265,0.4892616,0.00003113857,0.3521479,0.118278,0.0001739831],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4865971,0.00007929993,0.4926754,0.01235095,0.006782734,0.0002691021,0.0000700761,0.00002139755,0.001153971],"genre_scores_gemma":[0.8927598,2.760123e-7,0.1053216,0.001316534,0.0003957792,0.000005097619,0.00000439115,0.000004722514,0.0001918365],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4061627,"threshold_uncertainty_score":0.9998536,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"Scroll; Computer science; Algorithm; Artificial intelligence; Philosophy; Theology","retraction":null,"screen_n_in":null,"score":{"opus":0.01969298253941913,"gpt":0.2576172042473329,"spread":0.2379242217079138,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001362203,0.000227986,0.0001968386,0.0002256968,0.0008657823,0.0003256982,0.0006426229,0.0001738208,0.0009266329],"category_scores_gemma":[0.0001723941,0.0002846058,0.0004398645,0.0006257055,0.0004347697,0.0009388674,0.0002476278,0.0004433042,0.0001609225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001907732,"about_ca_system_score_gemma":0.0006928573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001589523,"about_ca_topic_score_gemma":0.00001835019,"domain_scores_codex":[0.9967757,0.000134015,0.0008676131,0.0004140852,0.001235337,0.0005731798],"domain_scores_gemma":[0.9974864,0.0003616526,0.001216122,0.000302937,0.0003078032,0.0003250526],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009672312,0.0001705948,0.00001954079,0.00003090391,0.0001036682,0.000007518467,0.0003469331,0.07376933,0.0034818,0.9153361,0.004149863,0.002487063],"study_design_scores_gemma":[0.0008822483,0.0002860902,0.0003204986,0.0001433744,0.0001252784,0.0001335673,0.000155979,0.9629029,0.01916068,0.01464218,0.000979942,0.000267266],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8472994,0.0001024396,0.1466531,0.0006893297,0.0009991921,0.00003351459,0.00003628082,0.00002788372,0.004158913],"genre_scores_gemma":[0.9905515,0.00003007665,0.007725433,0.0004943645,0.0009903837,0.0000318434,0.00007040783,0.00004611456,0.00005991607],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9006939,"threshold_uncertainty_score":0.9999866,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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","retraction":null,"screen_n_in":null,"score":{"opus":0.1136758590027041,"gpt":0.4418246574784104,"spread":0.3281487984757064,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.03142232,0.00008843129,0.0001732877,0.001251055,0.0009499087,0.001303557,0.002461126,0.00001314223,0.0000809721],"category_scores_gemma":[0.004292345,0.00004901472,0.0001181064,0.007445261,0.003598213,0.001456623,0.0008004461,0.0001461181,0.00009323615],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002041649,"about_ca_system_score_gemma":0.001307144,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005960422,"about_ca_topic_score_gemma":0.000001462059,"domain_scores_codex":[0.9926826,0.00009279139,0.001040037,0.0004553654,0.005469081,0.0002601743],"domain_scores_gemma":[0.9938591,0.002723096,0.0006548314,0.0003216237,0.002302795,0.0001385185],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001652634,0.00005615755,0.0009933746,0.00001205004,0.00001284355,0.00001480446,0.002134024,0.6655016,0.004839943,0.02572327,0.02213193,0.2785635],"study_design_scores_gemma":[0.0001631898,0.0001120702,0.0402593,0.0001233748,0.00001605012,0.0002357483,0.0009995735,0.8316118,0.001468603,0.1097367,0.01515656,0.0001170825],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7642965,0.0003736217,0.2237852,0.002784882,0.004250148,0.00009369425,0.000007076947,0.00001661204,0.004392232],"genre_scores_gemma":[0.9897573,0.000001988425,0.009640319,0.0001009695,0.0001252213,3.146905e-7,5.853608e-7,0.000003047898,0.0003702731],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2784464,"threshold_uncertainty_score":0.9997332,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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","retraction":null,"screen_n_in":null,"score":{"opus":0.01327406559919692,"gpt":0.3240790689241173,"spread":0.3108050033249203,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072,0.00009683668,0.0002323564,0.0007003842,0.0003592213,0.00006289191,0.0002182178,0.00003874559,0.00005930772],"category_scores_gemma":[0.0006061398,0.00008104594,0.00008979566,0.001981479,0.000239277,0.0002686137,0.00004361302,0.0003212845,0.000001808431],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001800077,"about_ca_system_score_gemma":0.0005616637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002572669,"about_ca_topic_score_gemma":0.000006854561,"domain_scores_codex":[0.9983142,0.00003492927,0.0005800726,0.0001645385,0.0006818881,0.0002243879],"domain_scores_gemma":[0.9976956,0.0006318148,0.0002081248,0.0001211877,0.001103723,0.0002395245],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006432543,0.00005242092,0.006964956,0.00000540396,0.00004093806,0.0000093246,0.0005504945,0.9870674,0.003314853,0.000343704,0.0003357672,0.001250433],"study_design_scores_gemma":[0.0008775182,0.0002437977,0.1486252,0.0004601788,0.00009286119,0.000091067,0.0003757607,0.8410235,0.0002407916,0.0077069,0.0001847274,0.00007770161],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6225133,0.0001486466,0.3727021,0.003114574,0.0009794988,0.0001336917,0.000005823053,0.00001759509,0.0003847381],"genre_scores_gemma":[0.9836572,0.000002874857,0.01410985,0.001538287,0.0006455142,0.000001261383,0.000006970332,0.000005398769,0.00003267004],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3611439,"threshold_uncertainty_score":0.3304957,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"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","retraction":null,"screen_n_in":null,"score":{"opus":0.05296929016269584,"gpt":0.3353661978949451,"spread":0.2823969077322492,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001890451,0.00007409089,0.0001169583,0.0002195183,0.0003470597,0.00009985471,0.0002527921,0.00002046922,0.000003877076],"category_scores_gemma":[0.0006198413,0.0000528268,0.00006496369,0.001059198,0.00008931658,0.0005327504,0.00003771081,0.000100657,0.00001208222],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001046224,"about_ca_system_score_gemma":0.00008686837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":7.946159e-7,"about_ca_topic_score_gemma":9.217138e-7,"domain_scores_codex":[0.9988647,0.00001787748,0.0003436938,0.00008681829,0.0005065606,0.0001804048],"domain_scores_gemma":[0.9971472,0.00188694,0.0001767847,0.00007272098,0.0006673352,0.00004901623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000007504927,0.00000570108,0.00008076158,0.00001198741,0.00002593171,7.652341e-7,0.0005066104,0.9869331,0.00251729,0.004550781,0.0008893143,0.004470327],"study_design_scores_gemma":[0.0003107278,0.00003814102,0.02139864,0.00002405306,0.00002126846,0.00001698038,0.000295073,0.9577504,0.0005351439,0.01621928,0.003316802,0.00007345528],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1110745,0.0001572906,0.8859404,0.001359224,0.0006594504,0.0001571782,0.000002923972,0.00008755574,0.0005614],"genre_scores_gemma":[0.8808722,0.00000780835,0.1187855,0.00008023318,0.000169888,0.000004070242,0.000001134738,0.00001035712,0.00006878135],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7697977,"threshold_uncertainty_score":0.2669337,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"International Council for Canadian Studies","keywords":"Planet; Computer science; Astrobiology; Astronomy; Biology; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.01829534213741549,"gpt":0.2943474346308674,"spread":0.2760520924934519,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001567854,0.00008772375,0.0001058571,0.000264462,0.0005736036,0.0003305118,0.001699531,0.00001575669,0.000007860309],"category_scores_gemma":[0.0001010059,0.00006165189,0.00006083402,0.001704954,0.0003341893,0.0007121135,0.0002219882,0.0001476392,0.0001584837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001110977,"about_ca_system_score_gemma":0.0012327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002928683,"about_ca_topic_score_gemma":5.462916e-7,"domain_scores_codex":[0.9978794,0.00004039339,0.0004367082,0.0001787683,0.001218362,0.0002463999],"domain_scores_gemma":[0.9970944,0.001383751,0.0003713933,0.00017862,0.0008266911,0.0001451374],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002307149,0.00001466588,0.00003722256,8.184529e-7,0.000006413276,0.000003159366,0.0001069367,0.4789563,0.00003862929,0.497276,0.01279167,0.01076585],"study_design_scores_gemma":[0.0001236254,0.00003331308,0.02499407,0.000003901739,0.000001559348,0.00007768355,0.00001461717,0.5081992,0.000007261191,0.4371777,0.02930717,0.00005986394],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02011096,0.0001368241,0.9640475,0.01179911,0.001230145,0.0001362438,0.00000715294,0.0001098319,0.002422218],"genre_scores_gemma":[0.9564025,0.00001454669,0.04287125,0.000436099,0.0001730941,0.000003719009,0.000009789956,0.000005168738,0.00008381965],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9362916,"threshold_uncertainty_score":0.4411753,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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","retraction":null,"screen_n_in":null,"score":{"opus":0.1598750192136956,"gpt":0.3889262294235912,"spread":0.2290512102098956,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002188034,0.00005968319,0.0001404837,0.0001975919,0.00005323013,0.00009021487,0.0001852868,0.00001066371,0.00000695381],"category_scores_gemma":[0.00005922368,0.0000475609,0.00002326242,0.0003795058,0.00009671645,0.0003905254,0.00002655953,0.00008940948,0.000002234337],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004466754,"about_ca_system_score_gemma":0.0002061863,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000293214,"about_ca_topic_score_gemma":0.000003214207,"domain_scores_codex":[0.9986185,0.00004047378,0.0003176458,0.0001216102,0.0008383609,0.00006340193],"domain_scores_gemma":[0.9993813,0.0001006482,0.00008361213,0.00009292409,0.0002967334,0.00004476782],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001057296,0.0000565688,0.0002170917,0.000009083788,0.00004630037,0.000004411018,0.001326867,0.9945161,0.0004383885,0.0001740773,0.0004795787,0.002720976],"study_design_scores_gemma":[0.0001810097,0.0001591504,0.01104343,0.00006696004,0.00007594314,0.00002695051,0.0006123558,0.985786,0.0001033235,0.001885631,0.0000119123,0.00004732316],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.971171,0.0004160123,0.02767506,0.0001886278,0.0002125865,0.00005924519,0.000007125032,0.00001000811,0.0002603966],"genre_scores_gemma":[0.9971038,0.000003863748,0.002774402,0.000006191815,0.0001010797,3.524925e-7,0.000003324553,0.000002626569,0.000004321763],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0259329,"threshold_uncertainty_score":0.1939477,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"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","retraction":null,"screen_n_in":null,"score":{"opus":0.01776982768010557,"gpt":0.2842395353090677,"spread":0.2664697076289621,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000327987,0.00005957268,0.0002171609,0.00009653163,0.00009464375,0.0000118507,0.00008835478,0.00002572247,0.000005837608],"category_scores_gemma":[0.0005666683,0.00004142357,0.0001178043,0.0004650248,0.0002880815,0.000161424,0.00001334717,0.0001209696,2.33604e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004263006,"about_ca_system_score_gemma":0.001026911,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001195374,"about_ca_topic_score_gemma":5.402819e-7,"domain_scores_codex":[0.9988961,0.00006845059,0.0003426259,0.0001025886,0.0004966937,0.00009353862],"domain_scores_gemma":[0.9977133,0.0009753801,0.0003989029,0.0001223756,0.0007401779,0.0000498947],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008953966,0.00005670758,0.00001856333,0.00001434398,0.000008091011,0.000002816071,0.00005833499,0.5918734,0.4072812,0.0002587638,0.00003529634,0.0003029457],"study_design_scores_gemma":[0.0003661435,0.0002564936,0.003217044,0.00007731158,0.00005276045,0.00001544326,0.00003024941,0.5411294,0.4520525,0.002730511,0.00002755187,0.00004467744],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9703633,0.000170386,0.02697122,0.001913849,0.0001176266,0.00009654676,0.00001338635,0.000002639225,0.0003510418],"genre_scores_gemma":[0.9845474,0.000007267761,0.0150852,0.0002550723,0.00004744159,5.235678e-7,0.000005051174,0.000003464124,0.000048532],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05074406,"threshold_uncertainty_score":0.1821696,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"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","retraction":null,"screen_n_in":null,"score":{"opus":0.05939279907255113,"gpt":0.3523125265898065,"spread":0.2929197275172554,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001478144,0.00007707183,0.0001375803,0.000476987,0.000208715,0.0002402501,0.0007410512,0.00002425757,0.000005767955],"category_scores_gemma":[0.0002916066,0.00006531505,0.00003657583,0.002561838,0.0002029724,0.001772341,0.0001563533,0.0001311361,0.000008389557],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001614392,"about_ca_system_score_gemma":0.0006397506,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001071359,"about_ca_topic_score_gemma":0.000001341926,"domain_scores_codex":[0.9983993,0.00006095346,0.0004147633,0.0001929592,0.0006817667,0.0002502347],"domain_scores_gemma":[0.9986537,0.0003126543,0.0003704958,0.00009091949,0.0004825291,0.00008971474],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000007394835,0.00003839897,0.001804238,0.000007016707,0.000003854611,0.00005779022,0.001780111,0.9524353,0.001041597,0.01510786,0.0001066098,0.02760984],"study_design_scores_gemma":[0.000302444,0.00007285083,0.03217782,0.00007590636,0.00000181154,0.0001674618,0.0002535295,0.9516774,0.000228062,0.0148752,0.0000794818,0.00008806695],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.704452,0.0000271789,0.293904,0.0004785534,0.0006174929,0.00006053844,3.952875e-7,0.00002796414,0.0004318146],"genre_scores_gemma":[0.8535957,0.000001425981,0.1462132,0.0001024299,0.00007391325,6.370711e-7,4.762244e-7,0.000002686882,0.000009548858],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1491437,"threshold_uncertainty_score":0.2663471,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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","retraction":null,"screen_n_in":null,"score":{"opus":0.02417241789637629,"gpt":0.32487627625101,"spread":0.3007038583546336,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001445744,0.00006643418,0.0001142561,0.0002662154,0.0002637829,0.000206025,0.001037979,0.00001490504,0.000002529082],"category_scores_gemma":[0.0001107225,0.00004210723,0.00004512404,0.001100741,0.0002867199,0.001541881,0.0001067853,0.00005885509,0.000002196609],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009031704,"about_ca_system_score_gemma":0.0003198772,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":1.807536e-7,"about_ca_topic_score_gemma":0.000001587107,"domain_scores_codex":[0.9986874,0.00002068866,0.0003923297,0.0002282825,0.0004468423,0.0002243917],"domain_scores_gemma":[0.9983991,0.0003771114,0.0003238019,0.0001246616,0.0006859371,0.00008935216],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000005439716,0.00004321992,0.0002322458,0.000002085056,8.475281e-7,0.000001221051,0.0000486584,0.01806622,0.00165484,0.08176186,0.0003455669,0.8978378],"study_design_scores_gemma":[0.0008115371,0.000259082,0.01019797,0.0002480546,0.000002796339,0.0001270242,0.0000145677,0.2664056,0.002695351,0.5401521,0.1788221,0.0002638798],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01205178,0.0005378753,0.9811946,0.005582364,0.0003322684,0.0001336661,0.000001021463,0.00001940635,0.0001470768],"genre_scores_gemma":[0.6093183,0.0001523836,0.3902677,0.0001448041,0.00009167977,0.000003962861,1.71426e-7,0.000002357358,0.00001858337],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8975739,"threshold_uncertainty_score":0.2028831,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"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","retraction":null,"screen_n_in":null,"score":{"opus":0.04866891242837926,"gpt":0.3182661554392713,"spread":0.269597243010892,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000313874,0.00005936088,0.000153498,0.0001246909,0.0001089799,0.00002712951,0.0001108874,0.00001360324,0.000003774443],"category_scores_gemma":[0.0001336063,0.00004354417,0.00006941649,0.0004421602,0.0001275019,0.00008928694,0.00002331686,0.0000855327,2.212832e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001189844,"about_ca_system_score_gemma":0.0002470113,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001744478,"about_ca_topic_score_gemma":0.000004019089,"domain_scores_codex":[0.9992185,0.00002014055,0.0002581636,0.0001210076,0.0002265152,0.0001556958],"domain_scores_gemma":[0.9994536,0.0001575299,0.0001134775,0.00004421354,0.0001205927,0.0001105766],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005520097,0.0003304318,0.3137797,0.00003538974,0.00001749976,0.00005024687,0.00002077377,0.6533734,0.000006348091,0.01566191,0.0005285794,0.01564381],"study_design_scores_gemma":[0.000590193,0.00008837536,0.4482723,0.00003038489,0.00001378695,0.000005058605,0.00001248167,0.4866783,2.696286e-7,0.06419396,0.00009443675,0.00002048434],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8618049,0.0003057702,0.1212914,0.01512888,0.0002434521,0.0003686663,0.000007098982,0.000008000115,0.0008418564],"genre_scores_gemma":[0.983529,0.000004489379,0.01488197,0.001504251,0.00004467789,0.000003296224,0.000005699854,0.000002268406,0.00002439918],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1666951,"threshold_uncertainty_score":0.177568,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Guelph","funders":"","keywords":"Parallelizable manifold; Integer programming; Scalability; Integer (computer science); Overhead (engineering); Computation","retraction":null,"screen_n_in":null,"score":{"opus":0.02349717705591378,"gpt":0.372624051908216,"spread":0.3491268748523022,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001012737,0.00006421826,0.0001333927,0.0002055249,0.0003267786,0.0001242388,0.0003826178,0.00001035693,0.000007069174],"category_scores_gemma":[0.00003921937,0.00005324472,0.00008357606,0.0009310169,0.00006648543,0.000212099,0.00006204213,0.00007593248,0.000001581384],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004594453,"about_ca_system_score_gemma":0.0005621542,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001666424,"about_ca_topic_score_gemma":3.602826e-7,"domain_scores_codex":[0.9991074,0.00001477007,0.0002884536,0.0001635698,0.0002321875,0.0001935799],"domain_scores_gemma":[0.9990758,0.0001448835,0.000154638,0.00006645963,0.0004614611,0.00009672611],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002848627,0.0001642365,0.0007342993,0.000007009688,0.00001975059,1.077779e-7,0.0003916706,0.7428403,0.002984052,0.2084515,0.0004163572,0.04396224],"study_design_scores_gemma":[0.0005839067,0.00007618211,0.001169564,0.00004239758,0.00002362746,0.000004894731,0.0004826302,0.9285614,0.002302105,0.050507,0.01612542,0.0001208788],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08625388,0.00001186001,0.9113048,0.0007837682,0.00008318961,0.0002337498,0.000002036926,0.000005065785,0.001321665],"genre_scores_gemma":[0.4587368,8.859284e-8,0.5409033,0.0001179999,0.00007856907,0.00002502415,8.267637e-7,0.00000159622,0.0001357464],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.372483,"threshold_uncertainty_score":0.251335,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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","retraction":null,"screen_n_in":null,"score":{"opus":0.06876360092324377,"gpt":0.3981800878230701,"spread":0.3294164868998264,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006834818,0.00004828795,0.0001110847,0.0001313892,0.0001067586,0.00007779999,0.000308362,0.00001281773,0.0002569826],"category_scores_gemma":[0.001434194,0.00003481339,0.00005331378,0.0004318176,0.0001883459,0.0005360792,0.00003761803,0.00009708213,0.0000444278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005466634,"about_ca_system_score_gemma":0.0001912002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003248333,"about_ca_topic_score_gemma":1.498799e-7,"domain_scores_codex":[0.9988432,0.00004352268,0.0003194066,0.000067333,0.0006064789,0.0001200503],"domain_scores_gemma":[0.9981056,0.0006351694,0.0002996672,0.00006308434,0.000775315,0.0001211103],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002019602,0.0007218528,0.001612416,0.00004217694,0.0000681589,0.000005288553,0.001399075,0.02164275,0.03555345,0.6322462,0.005093733,0.3015947],"study_design_scores_gemma":[0.000109472,0.00005573245,0.01904168,0.00001237737,0.000006228443,0.00003232238,0.00002858717,0.005199404,0.0004590151,0.9748801,0.0001326493,0.00004244156],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3617256,0.000007545042,0.6364768,0.0007505003,0.0001909833,0.0000596041,3.332609e-7,0.000007260674,0.0007814379],"genre_scores_gemma":[0.5142965,3.317939e-7,0.4855675,0.00004279273,0.00003971249,8.267745e-7,4.82406e-8,0.000002238456,0.00004998751],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.3426339,"threshold_uncertainty_score":0.2813779,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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","retraction":null,"screen_n_in":null,"score":{"opus":0.0837010296547493,"gpt":0.4056319968579816,"spread":0.3219309672032323,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007160596,0.00004060038,0.000113487,0.0001160337,0.0001904546,0.00003320909,0.0002085821,0.00001097444,0.00000560254],"category_scores_gemma":[0.00004436439,0.00003014146,0.00006611588,0.0006209759,0.0001272322,0.0001363497,0.00002348816,0.0001435868,3.131113e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002680078,"about_ca_system_score_gemma":0.0002679061,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005797197,"about_ca_topic_score_gemma":0.000001494882,"domain_scores_codex":[0.999249,0.00002093518,0.0002783696,0.00005749058,0.0002866656,0.0001075416],"domain_scores_gemma":[0.9989001,0.0004893049,0.0003254325,0.00003136054,0.0002236864,0.00003012153],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000007008866,0.00002255025,0.02727663,0.000002326751,0.000004323101,9.409319e-8,0.0004551059,0.9215137,0.0000915825,0.04960017,0.000002485087,0.001023971],"study_design_scores_gemma":[0.0001337725,0.00002647477,0.007256666,0.00003644056,0.000003212472,1.347836e-7,0.0003934397,0.8681478,0.00003892354,0.1239195,0.00001562799,0.00002804148],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4998094,0.00001679674,0.4997996,0.0002223258,0.00009535364,0.00003890418,0.000004101445,0.000001339756,0.00001216473],"genre_scores_gemma":[0.9724978,5.485368e-7,0.02742922,0.00001981208,0.00004527307,8.958512e-7,0.000001420388,0.000002661636,0.000002367721],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4726884,"threshold_uncertainty_score":0.1464842,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"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,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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","retraction":null,"screen_n_in":null,"score":{"opus":0.03079851343778521,"gpt":0.2758727695017064,"spread":0.2450742560639211,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005126288,0.00006316335,0.0002083209,0.000344011,0.0003294604,0.00007229094,0.000411137,0.00002864526,0.00002070844],"category_scores_gemma":[0.0002422155,0.00006233682,0.00002702197,0.000724192,0.0004730853,0.0004823143,0.00009690892,0.0001954391,0.00001376631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008913711,"about_ca_system_score_gemma":0.0001609211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009346269,"about_ca_topic_score_gemma":0.00001097101,"domain_scores_codex":[0.9989022,0.000004056003,0.0005441767,0.0001879752,0.0001772979,0.0001842945],"domain_scores_gemma":[0.9981503,0.0003367357,0.0005772046,0.00006159286,0.000784918,0.00008924902],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000091726,0.0000415255,0.004762639,0.00001816557,0.000004074359,2.856896e-8,0.0004413482,0.001487865,0.0001064757,0.9877161,0.0000216128,0.005390998],"study_design_scores_gemma":[0.0001674687,0.0001062305,0.2812844,0.00002707555,0.000002330233,0.00001136155,0.000051181,0.005464601,0.00005186136,0.7103708,0.002397873,0.00006474289],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4427523,0.0001675222,0.5543354,0.0001534257,0.00005663345,0.00009960091,0.00000571936,0.000003370335,0.002426024],"genre_scores_gemma":[0.9846517,0.00001088277,0.01509854,0.00003608069,0.0001460198,0.000005802385,0.000001141087,0.000004518793,0.00004528526],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5418994,"threshold_uncertainty_score":0.2542022,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}