{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":46,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":46,"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","author_layer_release":"2026-06-26"},"query_hash":"658a2f5ef7f4","filters":{"venue":"Computational Economics"}},"results":[{"id":"W1572681426","doi":"10.1023/a:1026146100090","title":"Traders' Long-Run Wealth in an Artificial Financial Market","year":2003,"lang":"en","type":"article","venue":"Computational Economics","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":69,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Intertek (Canada)","funders":"","keywords":"Contrarian; Economics; Volatility (finance); Trend following; Trading strategy; Financial economics; Population; Distribution (mathematics); Financial market; Stock market; Context (archaeology); Finance","authors":[{"name":"Marco Raberto","is_ca":false},{"name":"Silvano Cincotti","is_ca":false},{"name":"Sergio M. Focardi","is_ca":true},{"name":"Michele Marchesi","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03641578466481869,"gpt":0.2268789311927527,"spread":0.190463146527934,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001501055,0.0002071237,0.0005589832,0.0005140885,0.0005431048,0.002013572,0.0006888437,0.001315762,0.002934143],"category_scores_gemma":[0.01079367,0.0003203517,0.0003014372,0.000412111,0.00129592,0.005108754,0.001190455,0.001062542,0.0001330311],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000399455,"about_ca_system_score_gemma":0.0004230693,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00118075,"about_ca_topic_score_gemma":0.001182943,"domain_scores_codex":[0.9998423,0.00006997125,0.00001375866,0.00003051109,0.00002390865,0.00001955617],"domain_scores_gemma":[0.99635,0.002654697,0.0004076945,0.0001271986,0.0001555414,0.0003047351],"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":[0.000439871,0.0001650446,0.01394755,0.00008805114,0.0001456102,0.0009398886,0.0005174998,0.6238048,0.003146018,0.3471828,0.0009792786,0.00864352],"study_design_scores_gemma":[0.00003073811,0.00003021899,0.001249655,0.000005238158,0.00001826802,0.00005050421,0.00005551035,0.9021158,0.0002031274,0.0960917,0.0001341776,0.00001505209],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9474966,0.0001482307,0.04787152,0.00115533,0.00004409429,0.00000713929,0.00005636056,0.00004339336,0.003177453],"genre_scores_gemma":[0.9965054,0.0000871764,0.002041523,0.00003416952,0.00001978572,0.000005011591,0.00001770527,0.000007349418,0.001281803],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002934143,"threshold_uncertainty_score":0.009815633,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1980163634","doi":"10.1023/a:1008713823410","title":"Explaining the Persistence of Commodity Prices","year":2000,"lang":"en","type":"article","venue":"Computational Economics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":44,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Montréal","funders":"Social Sciences and Humanities Research Council of Canada; Johns Hopkins University","keywords":"Heteroscedasticity; Economics; Econometrics; Rational expectations; Incentive; Production (economics); Commodity; Microeconomics; Persistence (discontinuity); Finance","authors":[{"name":"Serena Ng","is_ca":false},{"name":"Francisco J. Ruge‐Murcia","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04385446549105314,"gpt":0.2169523053526353,"spread":0.1730978398615822,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006771787,0.0002714741,0.0004543573,0.0008731289,0.0003837488,0.002076251,0.0007743735,0.001096198,0.003056137],"category_scores_gemma":[0.009698662,0.0003465246,0.0004747076,0.001019068,0.0009986588,0.004125069,0.0008824256,0.001424065,0.0002602564],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005465213,"about_ca_system_score_gemma":0.0005785784,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002878648,"about_ca_topic_score_gemma":0.001949906,"domain_scores_codex":[0.999855,0.00004868556,0.000008875308,0.00003259967,0.00002486017,0.00002996582],"domain_scores_gemma":[0.9960676,0.003086681,0.0003200895,0.0002909408,0.0001236723,0.0001108001],"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":[0.00008779138,0.00006588088,0.02428453,0.0001203426,0.0000975919,0.0002480187,0.0003892089,0.3816699,0.002293643,0.5526257,0.004575917,0.03354145],"study_design_scores_gemma":[0.000009414287,0.000004900617,0.002063858,0.000007833777,0.000008203679,0.00003431529,0.00005161869,0.6127604,0.0002057641,0.3839696,0.0008757578,0.000008344494],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7413195,0.001736134,0.2378908,0.006317386,0.0001773063,0.00001779545,0.0005734367,0.0004988738,0.01146879],"genre_scores_gemma":[0.992049,0.0005264439,0.006359669,0.00005659525,0.00007694642,0.000006645831,0.0001398533,0.00004479782,0.000740013],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003056137,"threshold_uncertainty_score":0.01022381,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4296047353","doi":"10.1007/s10614-022-10312-z","title":"Comparing Out-of-Sample Performance of Machine Learning Methods to Forecast U.S. GDP Growth","year":2022,"lang":"en","type":"article","venue":"Computational Economics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":41,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Predictive power; Lasso (programming language); Computer science; Boosting (machine learning); Artificial intelligence; Econometrics; Machine learning; Index (typography); Sample (material); Mathematics","authors":[{"name":"Ba Chu","is_ca":true},{"name":"Shafiullah Qureshi","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1281132991159381,"gpt":0.2801778171902609,"spread":0.1520645180743228,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006094075,0.0008850591,0.0005735513,0.0008947874,0.0003315001,0.0009407287,0.0005951452,0.001033921,0.001361443],"category_scores_gemma":[0.02541973,0.0002645726,0.0005025903,0.0005492972,0.0003498446,0.001633507,0.0007105877,0.00119289,0.0005387422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006537383,"about_ca_system_score_gemma":0.0007559122,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01445184,"about_ca_topic_score_gemma":0.01042101,"domain_scores_codex":[0.9990942,0.0005441695,0.00007494981,0.000130555,0.00009382988,0.00006226904],"domain_scores_gemma":[0.9713566,0.02491262,0.0005992746,0.00112146,0.001651125,0.0003589866],"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":[0.006293685,0.001246822,0.1052806,0.0002896082,0.0009848388,0.00008565608,0.0001933318,0.7264196,0.001320858,0.002369742,0.0116387,0.1438766],"study_design_scores_gemma":[0.0001475719,0.0003365786,0.01689937,0.0000280904,0.0000658627,0.00001956088,0.00008613486,0.9790397,0.001372032,0.001343245,0.0006416147,0.00002023382],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9793776,0.001766185,0.01242811,0.001149066,0.0003184096,0.00004005271,0.001128739,0.0004729061,0.003318988],"genre_scores_gemma":[0.9913887,0.0003533526,0.004333438,0.0001387758,0.0001322234,0.00002242112,0.002633778,0.00005623209,0.0009410182],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01445184,"threshold_uncertainty_score":0.03222889,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2036531676","doi":"10.1007/s10614-010-9200-8","title":"A Benders Decomposition Method for Solving Stochastic Complementarity Problems with an Application in Energy","year":2010,"lang":"en","type":"article","venue":"Computational Economics","topic":"Electric Power System Optimization","field":"Engineering","cited_by":41,"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":"Complementarity (molecular biology); Variational inequality; Mixed complementarity problem; Mathematical optimization; Mathematics; Benders' decomposition; Linear complementarity problem; Convergence (economics); Applied mathematics; Complementarity theory; Mathematical economics; Economics","authors":[{"name":"Steven A. Gabriel","is_ca":false},{"name":"J. David Fuller","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.00907199003721107,"gpt":0.2468367389626839,"spread":0.2377647489254729,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001857845,0.001809736,0.001591995,0.0009530676,0.0007414822,0.0009597351,0.00126498,0.002028912,0.007191878],"category_scores_gemma":[0.003410667,0.001129648,0.002149191,0.001339814,0.001087171,0.001398412,0.00157205,0.003763222,0.001536552],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005447213,"about_ca_system_score_gemma":0.001460976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003200908,"about_ca_topic_score_gemma":0.003601426,"domain_scores_codex":[0.9993467,0.0003146406,0.00002903334,0.00008632669,0.0001785307,0.0000446753],"domain_scores_gemma":[0.9988523,0.0007553405,0.00006737759,0.00008053036,0.0001730978,0.00007132676],"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":[0.0001101742,0.000159488,0.000282207,0.0002403926,0.0001368388,0.0001200542,0.0001144906,0.7096623,0.004759233,0.1701312,0.00655689,0.1077267],"study_design_scores_gemma":[0.00001504548,0.00003422016,0.00005228202,0.00001598359,0.0000150328,0.00001909746,0.000009036363,0.9635599,0.0005282146,0.03266764,0.003069361,0.0000140811],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001088476,0.0001188801,0.9971285,0.00008955359,0.00006445845,0.00002436243,0.00003679554,0.00007987836,0.001369011],"genre_scores_gemma":[0.04093977,0.0005234066,0.9486601,0.0001970559,0.0001537248,0.0003333492,0.0001911188,0.0003159692,0.008685545],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007191878,"threshold_uncertainty_score":0.02405918,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3118392031","doi":"10.1007/s10614-020-10083-5","title":"Nowcasting US GDP Using Tree-Based Ensemble Models and Dynamic Factors","year":2021,"lang":"en","type":"article","venue":"Computational Economics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":38,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Nowcasting; Dynamic factor; Gradient boosting; Random forest; Decision tree; Econometrics; Financial crisis; Computer science; Boosting (machine learning); Tree (set theory); Machine learning; Quarter (Canadian coin); Dimension (graph theory); Artificial intelligence; Economics; Mathematics; Geography; Macroeconomics","authors":[{"name":"Barış Soybilgen","is_ca":false},{"name":"Ege Yazgan","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06119604146959807,"gpt":0.2418194471311544,"spread":0.1806234056615563,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001347483,0.0006528165,0.00121498,0.0009989376,0.0004717483,0.001241417,0.0008125323,0.001244718,0.001606124],"category_scores_gemma":[0.005207107,0.0005024777,0.001273775,0.001451673,0.0002837061,0.002258981,0.0005677522,0.001896337,0.0004357433],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005530237,"about_ca_system_score_gemma":0.0007447621,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02471783,"about_ca_topic_score_gemma":0.02654665,"domain_scores_codex":[0.9997424,0.00008106396,0.000018427,0.00007739945,0.00003971599,0.0000409273],"domain_scores_gemma":[0.9983932,0.0009835581,0.0001014607,0.0001698797,0.0002734242,0.00007853954],"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":[0.00006730013,0.00003547604,0.003002974,0.00001481924,0.00008746531,0.00003394895,0.00003031647,0.9647657,0.0003720672,0.002928217,0.00103585,0.02762592],"study_design_scores_gemma":[0.000001726557,0.000002272754,0.0002359734,0.000001365975,0.000005069901,0.000001859947,0.000002743806,0.9983735,0.00004729313,0.001264751,0.00006052068,0.00000278853],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.529882,0.001125989,0.4615095,0.001069976,0.0007036557,0.00003252909,0.001235779,0.00105599,0.003384691],"genre_scores_gemma":[0.965186,0.0004480108,0.03112657,0.00007815962,0.0001841537,0.00002451148,0.001378224,0.00009071855,0.001483621],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02471783,"threshold_uncertainty_score":0.0491479,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2120293688","doi":"10.1007/s10614-006-9053-3","title":"Revisiting Individual Evolutionary Learning in the Cobweb Model – An Illustration of the Virtual Spite-Effect","year":2006,"lang":"en","type":"article","venue":"Computational Economics","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":36,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University","funders":"","keywords":"Cournot competition; Mathematical economics; Outcome (game theory); Convergence (economics); Context (archaeology); Economics; Nash equilibrium; Computer science; Oligopoly; General equilibrium theory; Microeconomics; Mathematical optimization; Mathematics","authors":[{"name":"Jasmina Arifovic","is_ca":true},{"name":"Michael K. Maschek","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02598662927457989,"gpt":0.2107474150154607,"spread":0.1847607857408808,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002143275,0.0003627315,0.0008923592,0.0004639945,0.0007674891,0.002464036,0.00225737,0.002499515,0.004906814],"category_scores_gemma":[0.01323456,0.0003085074,0.0006541537,0.0006367684,0.002673436,0.004838507,0.002101771,0.002248097,0.0005167045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007089941,"about_ca_system_score_gemma":0.0008137801,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002570947,"about_ca_topic_score_gemma":0.002102834,"domain_scores_codex":[0.9993221,0.0003838391,0.00001775726,0.0001108669,0.00009553081,0.00007001586],"domain_scores_gemma":[0.9956617,0.00298156,0.0002852059,0.0005584873,0.0002739912,0.0002390783],"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":[0.0000579799,0.00005606592,0.001463879,0.00005177778,0.00005273967,0.000217794,0.0003478524,0.2006586,0.0008901366,0.7802132,0.0009428919,0.01504702],"study_design_scores_gemma":[0.00001458974,0.00002193771,0.0002569441,0.000009659801,0.00001026431,0.00006003701,0.00004895519,0.5735562,0.0001632171,0.4247556,0.001089974,0.00001259943],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2115149,0.0008158259,0.7500767,0.004201991,0.0001832571,0.00003059294,0.00005688595,0.000235616,0.03288416],"genre_scores_gemma":[0.9642519,0.0003376954,0.03026494,0.0002264049,0.00006514263,0.00002523435,0.00002051143,0.00006992965,0.004738224],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004906814,"threshold_uncertainty_score":0.01641488,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1969535442","doi":"10.1007/s10614-005-2519-x","title":"Dantzig—Wolfe Decomposition of Variational Inequalities","year":2005,"lang":"en","type":"article","venue":"Computational Economics","topic":"Optimization and Variational Analysis","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematical optimization; Convergence (economics); Variational inequality; Decomposition; Mathematical economics; Mathematics; Computer science; Economics","authors":[{"name":"J. David Fuller","is_ca":true},{"name":"William Chung","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01517045414452262,"gpt":0.2525010091423522,"spread":0.2373305549978296,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002492722,0.001396694,0.001429922,0.001769264,0.0006638074,0.002792529,0.001314927,0.001412246,0.006410497],"category_scores_gemma":[0.004920666,0.0006973018,0.001107375,0.001399574,0.002070793,0.003103632,0.00198929,0.004199848,0.0009646156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001956831,"about_ca_system_score_gemma":0.001869335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001926377,"about_ca_topic_score_gemma":0.00175108,"domain_scores_codex":[0.9991266,0.0004045499,0.00003379677,0.0001042679,0.0002396691,0.00009111824],"domain_scores_gemma":[0.9989746,0.000496986,0.00008433317,0.0001181513,0.0002262577,0.0000996835],"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":[0.000006887171,0.00001233352,0.00004353702,0.00002302058,0.00001106396,0.00001188233,0.00002456749,0.008381386,0.0001796242,0.9833177,0.001303101,0.006684879],"study_design_scores_gemma":[0.000005277251,0.000004585008,0.00005241862,0.00001247851,0.000004229115,0.00001230999,0.00001189213,0.08845884,0.00008763569,0.9089923,0.002354043,0.000004010405],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006662538,0.001672876,0.9633126,0.001468298,0.0002397804,0.00004252521,0.0001377092,0.00004160498,0.02642208],"genre_scores_gemma":[0.4665799,0.007292027,0.4442535,0.0009854884,0.001220872,0.0006607394,0.00065575,0.0003217749,0.07802992],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006410497,"threshold_uncertainty_score":0.02144527,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2134549012","doi":"10.1007/s10614-012-9333-z","title":"Using Economic Theory to Guide Numerical Analysis: Solving for Equilibria in Models of Asymmetric First-Price Auctions","year":2012,"lang":"en","type":"article","venue":"Computational Economics","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":32,"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":"Common value auction; Polynomial; Mathematical optimization; Computer science; Combinatorial auction; Inverse; Mathematical economics; Quality (philosophy); Applied mathematics; Mathematics; Economics; Microeconomics","authors":[{"name":"Timothy P. Hubbard","is_ca":false},{"name":"René Kirkegaard","is_ca":true},{"name":"Harry J. Paarsch","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1633597457172882,"gpt":0.4059405145745929,"spread":0.2425807688573047,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004969632,0.001051528,0.001429679,0.001608246,0.001552672,0.003068299,0.002117305,0.003204146,0.005576691],"category_scores_gemma":[0.03749281,0.001256103,0.001117709,0.001433271,0.001948502,0.004452728,0.002290711,0.003042824,0.0008645798],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001376304,"about_ca_system_score_gemma":0.003210386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004453557,"about_ca_topic_score_gemma":0.005016171,"domain_scores_codex":[0.9989313,0.0006006978,0.00006823367,0.00009741656,0.0002383602,0.00006391983],"domain_scores_gemma":[0.9860724,0.01153045,0.0006957753,0.0006181488,0.0008214068,0.0002617856],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005838995,0.0001094891,0.0006636383,0.0001424005,0.0000484875,0.0000844243,0.000164495,0.8236174,0.0005423907,0.1467921,0.001806426,0.02597044],"study_design_scores_gemma":[0.00001677449,0.00000371074,0.00001823495,0.00001144736,0.000004429974,0.000006381169,0.0000116759,0.9489496,0.0001356975,0.05057556,0.0002624132,0.000004215685],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01459267,0.0001424369,0.9800551,0.0006694541,0.00006179998,0.00006869136,0.00003626532,0.0002441056,0.004129452],"genre_scores_gemma":[0.2702301,0.0002788096,0.7263752,0.0001886706,0.00008243178,0.0003669883,0.0001090263,0.0002268847,0.002141991],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005576691,"threshold_uncertainty_score":0.02628219,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3012922890","doi":"10.1007/s10614-021-10119-4","title":"Reinforcement Learning in Economics and Finance","year":2021,"lang":"en","type":"preprint","venue":"Computational Economics","topic":"Advanced Bandit Algorithms Research","field":"Decision Sciences","cited_by":30,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Centre National de la Recherche Scientifique; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; AXA Research Fund","keywords":"Reinforcement learning; Action (physics); Computer science; Set (abstract data type); Artificial intelligence; Time horizon; Q-learning; Behavioral economics; Order (exchange); Reinforcement; Process (computing); Term (time); Temporal difference learning; Economics; Microeconomics; Psychology; Finance; Social psychology","authors":[{"name":"Arthur Charpentier","is_ca":true},{"name":"Romuald Élie","is_ca":false},{"name":"Carl Remlinger","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.08548769842633776,"gpt":0.3792800501201351,"spread":0.2937923516937974,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002257501,0.0009146516,0.001415114,0.001108617,0.0005877785,0.003401731,0.0009371436,0.002649575,0.006425094],"category_scores_gemma":[0.0150124,0.0005567176,0.0004838814,0.002041675,0.002331882,0.004218115,0.001205385,0.00388472,0.0006554861],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002353121,"about_ca_system_score_gemma":0.001461619,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004296629,"about_ca_topic_score_gemma":0.002037437,"domain_scores_codex":[0.9989754,0.000674414,0.00002974766,0.00009446757,0.0001746251,0.00005138469],"domain_scores_gemma":[0.9926292,0.006344863,0.0002292497,0.0002298429,0.0003840298,0.0001829567],"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":[0.00003007976,0.00005038781,0.0004041971,0.0001628656,0.00003879617,0.00002692106,0.00005564528,0.02925777,0.0001527088,0.9350365,0.005855975,0.0289281],"study_design_scores_gemma":[0.0000144937,0.000005002183,0.0001548376,0.00002445683,0.000005568632,0.000008293582,0.00001455749,0.1022112,0.00006551688,0.8942791,0.003212111,0.000004923856],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0373807,0.04771404,0.8397238,0.03443277,0.001700306,0.0000632796,0.0002719231,0.0003319548,0.03838134],"genre_scores_gemma":[0.7888808,0.02758426,0.140045,0.001739656,0.004592985,0.0002552595,0.0003296433,0.0002075534,0.03636479],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006425094,"threshold_uncertainty_score":0.02149403,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2112115577","doi":"10.1007/s10614-005-6413-3","title":"Solving Finite Mixture Models: Efficient Computation in Economics Under Serial and Parallel Execution","year":2005,"lang":"en","type":"article","venue":"Computational Economics","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":24,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Queen's University","funders":"","keywords":"Computation; Computer science; Task (project management); Class (philosophy); Parallel computing; Code (set theory); Carry (investment); Function (biology); Cost efficiency; Mathematical optimization; Algorithm; Mathematics; Programming language; Artificial intelligence","authors":[{"name":"Christopher Ferrall","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02437650390906206,"gpt":0.223490563991701,"spread":0.1991140600826389,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002279859,0.001014343,0.001471946,0.0009020928,0.001093726,0.002151002,0.002517963,0.002003724,0.007648273],"category_scores_gemma":[0.01464011,0.001106082,0.001243298,0.001527144,0.001229895,0.003098125,0.002021189,0.002321494,0.001327826],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001305329,"about_ca_system_score_gemma":0.002480196,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01440425,"about_ca_topic_score_gemma":0.01811591,"domain_scores_codex":[0.9992023,0.0002955993,0.00005644238,0.0001652063,0.0001904434,0.0000900288],"domain_scores_gemma":[0.9937438,0.005002543,0.0002213422,0.0004715854,0.0003886825,0.0001721183],"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":[0.0001584645,0.0001059593,0.001183632,0.00010791,0.00006634635,0.00009108914,0.00009414514,0.8849418,0.0007351134,0.04768011,0.002565397,0.06227009],"study_design_scores_gemma":[0.00001165016,0.000002738698,0.00003731599,0.00000186302,0.000004742264,0.000005169468,0.000005522248,0.9818581,0.0001718658,0.017698,0.0002005882,0.000002452634],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01829834,0.000170823,0.9771296,0.0004965169,0.00007201727,0.00004571074,0.00008755725,0.001032566,0.00266684],"genre_scores_gemma":[0.2892696,0.0002757626,0.7038906,0.0002401386,0.0001809135,0.0003040884,0.0003557227,0.0005201957,0.004962984],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01440425,"threshold_uncertainty_score":0.02864081,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2073571177","doi":"10.1007/s10614-013-9396-5","title":"Capturing the Regime-Switching and Memory Properties of Interest Rates","year":2013,"lang":"en","type":"article","venue":"Computational Economics","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":18,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"","keywords":"Mean reversion; Markov chain; Inference; Volatility (finance); Measure (data warehouse); Computer science; Mathematics; Statistics; Econometrics; Algorithm; Artificial intelligence; Data mining","authors":[{"name":"Xiaojing Xi","is_ca":true},{"name":"Rogemar Mamon","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06547354741863756,"gpt":0.2111885835876019,"spread":0.1457150361689644,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001497405,0.0004191803,0.000735712,0.0008146333,0.0002878329,0.001814093,0.0009017203,0.001159263,0.001972013],"category_scores_gemma":[0.01663144,0.0004429553,0.0007713109,0.000724476,0.0006335196,0.002891387,0.000988103,0.001386458,0.0002233789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004468758,"about_ca_system_score_gemma":0.0007328336,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002142769,"about_ca_topic_score_gemma":0.001872048,"domain_scores_codex":[0.9997237,0.0001185734,0.00001899998,0.00005737732,0.00003906925,0.00004227395],"domain_scores_gemma":[0.9935532,0.005148273,0.0005489148,0.0004329409,0.0001764885,0.000140195],"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":[0.0001029689,0.0001111329,0.008953626,0.0001554593,0.00013517,0.0001687041,0.0001920831,0.5799016,0.002425337,0.360817,0.001769669,0.04526721],"study_design_scores_gemma":[0.000006255721,0.000006988398,0.0004537599,0.000006295857,0.000007992679,0.00001939203,0.000008923623,0.9066179,0.0001531569,0.09251461,0.0001999914,0.000004792706],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3213415,0.0009171728,0.670294,0.0009988027,0.000131313,0.00003903314,0.0002500229,0.0002734843,0.005754651],"genre_scores_gemma":[0.971054,0.0006396163,0.02589148,0.00007708343,0.0001421053,0.00003471276,0.0001835081,0.00004849297,0.001929048],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002142769,"threshold_uncertainty_score":0.007919133,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3173485134","doi":"10.1007/s10614-021-10111-y","title":"A Two-Dimensional Sentiment Analysis of Online Public Opinion and Future Financial Performance of Publicly Listed Companies","year":2021,"lang":"en","type":"article","venue":"Computational Economics","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Valence (chemistry); Sentiment analysis; Arousal; Quarter (Canadian coin); Lexicon; Psychology; Stock price; Stock (firearms); Business; Computer science; Social psychology; Artificial intelligence; History; Chemistry","authors":[{"name":"Meng‐Feng Yen","is_ca":false},{"name":"Yu‐Pei Huang","is_ca":false},{"name":"Liang Yu","is_ca":false},{"name":"Yueh‐Ling Chen","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02363227815902713,"gpt":0.2568372105926714,"spread":0.2332049324336443,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007066914,0.0002508029,0.0002799357,0.001461411,0.0004222631,0.001055968,0.0002318155,0.0003991874,0.001565014],"category_scores_gemma":[0.002401903,0.0001031771,0.0005415375,0.00110769,0.0001606928,0.0007978947,0.0004399878,0.0004025009,0.0004468288],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004201993,"about_ca_system_score_gemma":0.0002960293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003599756,"about_ca_topic_score_gemma":0.004125118,"domain_scores_codex":[0.9996315,0.0001227701,0.00002585605,0.0000676327,0.0001008146,0.00005140673],"domain_scores_gemma":[0.9987282,0.0005597686,0.0002012127,0.00006675283,0.0003317199,0.0001123245],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001675698,0.002087463,0.6952434,0.000216457,0.0007159734,0.0004903396,0.0009461969,0.01014385,0.03808002,0.003136443,0.01561483,0.2316494],"study_design_scores_gemma":[0.00004409149,0.000494004,0.7319588,0.00002476828,0.0002049683,0.0001727775,0.001487742,0.2572207,0.004583177,0.001555731,0.002205021,0.00004813496],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908823,0.00006321821,0.00485047,0.0002245065,0.00003395127,0.00003465493,0.001207773,0.00005999203,0.002643207],"genre_scores_gemma":[0.9941053,0.00004327511,0.003476051,0.00002764732,0.00005197437,0.00002554261,0.0015504,0.000004995641,0.0007146647],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003599756,"threshold_uncertainty_score":0.007157624,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2059050789","doi":"10.1007/s10614-006-9069-8","title":"Cutting the hedge","year":2007,"lang":"en","type":"article","venue":"Computational Economics","topic":"Biotechnology and Related Fields","field":"Medicine","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 Calgary","funders":"","keywords":"Hedge; Econometrics; Mathematics; Environmental science; Economics; Biology; Botany","authors":[{"name":"Giovanni Barone‐Adesi","is_ca":false},{"name":"Robert J. Elliott","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01087117260703808,"gpt":0.2510198327084015,"spread":0.2401486601013634,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003814884,0.0006516759,0.001063179,0.00154929,0.001859767,0.006659099,0.001000454,0.004744677,0.0255826],"category_scores_gemma":[0.02050262,0.0004796373,0.0006286141,0.001068941,0.005363952,0.0102766,0.002930062,0.005837503,0.00391756],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00201242,"about_ca_system_score_gemma":0.002294425,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001153129,"about_ca_topic_score_gemma":0.001478823,"domain_scores_codex":[0.9976575,0.0008825985,0.00008975187,0.0004353391,0.0007390082,0.0001956965],"domain_scores_gemma":[0.992489,0.004540098,0.000428327,0.001364875,0.0007671287,0.0004106069],"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":[0.00004929165,0.00001832717,0.0003000898,0.00005079371,0.00002617825,0.00003667806,0.000116162,0.0007252324,0.0001421978,0.9386316,0.02649159,0.03341183],"study_design_scores_gemma":[0.00001263739,0.00001375378,0.0001827444,0.00008698061,0.00001162455,0.00004891773,0.0001147556,0.001471328,0.0001525923,0.9483982,0.04949789,0.000008438127],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.03133897,0.0329527,0.1417891,0.2271743,0.007014866,0.00006878496,0.0004991322,0.0004687168,0.5586934],"genre_scores_gemma":[0.7725843,0.01274405,0.03277054,0.04440042,0.005199885,0.0001476147,0.0002993129,0.0004588132,0.131395],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0255826,"threshold_uncertainty_score":0.08558226,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2075052734","doi":"10.1007/s10614-006-9029-3","title":"Minding the Gap: Central Bank Estimates of the Unemployment Natural Rate","year":2006,"lang":"en","type":"article","venue":"Computational Economics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":15,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Bank of Canada","funders":"","keywords":"Natural rate of unemployment; Unemployment; Economics; Unemployment rate; Econometrics; Central bank; Ex-ante; Natural (archaeology); Empirical evidence; Macroeconomics; Monetary policy; Geography","authors":[{"name":"Sharon Kozicki","is_ca":true},{"name":"Peter A. Tinsley","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04486670021594546,"gpt":0.2167924872184925,"spread":0.171925787002547,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003589325,0.0002959574,0.000629063,0.001076257,0.0006293137,0.002116945,0.000768122,0.001186718,0.00175879],"category_scores_gemma":[0.03247732,0.0004197029,0.0003678698,0.001705785,0.0008298564,0.00237048,0.0009438377,0.001348446,0.0003255894],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007130071,"about_ca_system_score_gemma":0.001080257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02557935,"about_ca_topic_score_gemma":0.01747454,"domain_scores_codex":[0.9994429,0.0003607588,0.00002466221,0.00007491136,0.00005975382,0.0000369546],"domain_scores_gemma":[0.9903009,0.007279183,0.0007598727,0.0007157737,0.0006882672,0.0002560542],"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":[0.001721651,0.0001710119,0.1418677,0.0001813047,0.0005385182,0.000237526,0.001619098,0.6068757,0.0006916613,0.1315633,0.03743229,0.07710023],"study_design_scores_gemma":[0.0001405428,0.00002251583,0.03763067,0.00007491174,0.00007171439,0.00005174081,0.0005013163,0.8562545,0.0006057764,0.1015331,0.003068279,0.0000449927],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9413401,0.001625014,0.04245665,0.006254332,0.0002849177,0.00001193771,0.00111988,0.0004578758,0.006449301],"genre_scores_gemma":[0.9949008,0.0001452327,0.004016254,0.00007676376,0.00005529392,0.000007326481,0.0004160579,0.00004797427,0.0003343371],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02557935,"threshold_uncertainty_score":0.05086088,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2112276205","doi":"10.1023/a:1022238914245","title":"Macroeconomic Effects of Sectoral Shocks in Germany, The U.K. and, The U.S. A VAR-GARCH-M Approach","year":2003,"lang":"en","type":"article","venue":"Computational Economics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":14,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"York University","keywords":"Volatility (finance); Econometrics; Economics; Volatility clustering; Bayesian vector autoregression; Autoregressive conditional heteroskedasticity; Bayes estimator; Bayesian probability; Estimation; Markov chain Monte Carlo; Aggregate (composite); Statistics; Mathematics","authors":[{"name":"Gianluigi Pelloni","is_ca":false},{"name":"Wolfgang Polasek","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02653506066643293,"gpt":0.2059695240719207,"spread":0.1794344634054878,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002952081,0.0001593647,0.0002154234,0.0004745552,0.0002037218,0.001170019,0.0001757816,0.000389495,0.001342947],"category_scores_gemma":[0.001174394,0.0001336969,0.0002391124,0.001861784,0.000251719,0.0004627228,0.0004623774,0.0005341646,0.0002656046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001851356,"about_ca_system_score_gemma":0.0008917536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1937913,"about_ca_topic_score_gemma":0.1763867,"domain_scores_codex":[0.9998598,0.00002887639,0.0000152588,0.00002755423,0.00001582469,0.00005268242],"domain_scores_gemma":[0.9996946,0.00007453674,0.0001151475,0.00002273175,0.00004970509,0.00004337513],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002322173,0.000235642,0.6132164,0.0002764469,0.0005383035,0.0008758208,0.0007095258,0.2562177,0.002042721,0.0342923,0.03853135,0.05074156],"study_design_scores_gemma":[0.00005902946,0.0000786087,0.9372196,0.00005948234,0.0002349505,0.0001004782,0.001012708,0.04806058,0.001267617,0.004250552,0.007609732,0.00004671334],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9900282,0.0007420428,0.0003285582,0.00139148,0.00003788061,0.000002821836,0.00529187,0.00005267535,0.002124443],"genre_scores_gemma":[0.9985173,0.0003148163,0.00005434941,0.0000391897,0.000006361076,8.904324e-7,0.000703412,0.000003534211,0.0003601904],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1937913,"threshold_uncertainty_score":0.3853266,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2164609856","doi":"10.1023/a:1020922214711","title":"Axelrod Meets Cournot: Oligopoly and the Evolutionary Metaphor","year":2002,"lang":"en","type":"article","venue":"Computational Economics","topic":"Game Theory and Applications","field":"Decision Sciences","cited_by":14,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Economic and Social Research Council; Nuffield Foundation; York University","keywords":"Cournot competition; Duopoly; Microeconomics; Economics; Outcome (game theory); Champion; Mathematical economics; Simple (philosophy); Profit (economics); Evolutionary dynamics; Econometrics","authors":[{"name":"Huw David Dixon","is_ca":false},{"name":"Steven E. Wallis","is_ca":false},{"name":"Scott Moss","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.08778315319928906,"gpt":0.3098910073109915,"spread":0.2221078541117024,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001208895,0.0005111987,0.0009041689,0.0007297359,0.001099683,0.004362094,0.0006453337,0.002709616,0.005024262],"category_scores_gemma":[0.004835471,0.0003555335,0.0005651488,0.00146517,0.004658735,0.007974588,0.001412007,0.002309599,0.0005712308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001247907,"about_ca_system_score_gemma":0.001131988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001199449,"about_ca_topic_score_gemma":0.001150288,"domain_scores_codex":[0.9990491,0.0005905465,0.00002400367,0.0001213412,0.0001575467,0.00005734036],"domain_scores_gemma":[0.9983023,0.001180202,0.000135898,0.000136933,0.000106619,0.0001379719],"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":[0.000009341466,0.000005615605,0.00007409322,0.00002334682,0.000005685691,0.00003238681,0.00007829686,0.00390028,0.00007549552,0.9913636,0.0006932085,0.003738554],"study_design_scores_gemma":[0.000003489072,0.000002940022,0.0000306896,0.000006301947,0.000001697763,0.00002001241,0.00002260066,0.006364004,0.00001786914,0.9917766,0.001750488,0.000003309934],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1035204,0.01562202,0.6761792,0.02824337,0.000972286,0.00004441546,0.0001789177,0.0001650102,0.1750743],"genre_scores_gemma":[0.9350182,0.003949435,0.05055039,0.0007919644,0.0004391904,0.00005296654,0.00003827015,0.00003908407,0.009120436],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005024262,"threshold_uncertainty_score":0.01680779,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3026750406","doi":"10.1007/s10614-020-09993-1","title":"Technological Change and Catching-Up in the Indian Banking Sector: A Time-Dependent Nonparametric Frontier Approach","year":2020,"lang":"en","type":"article","venue":"Computational Economics","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Frontier; Convergence (economics); Estimator; Nonparametric statistics; Economics; Panel data; Stochastic frontier analysis; Econometrics; Financial system; Monetary economics; Macroeconomics; Mathematics; Statistics; Geography","authors":[{"name":"Sushanta Mallick","is_ca":false},{"name":"Aarti Rughoo","is_ca":false},{"name":"Nickolaos Tzeremes","is_ca":false},{"name":"Wei Xu","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1291047289669257,"gpt":0.3083563409778641,"spread":0.1792516120109384,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003281702,0.0002681347,0.0005892144,0.00190253,0.0003543914,0.001908043,0.0007141355,0.000580202,0.00215919],"category_scores_gemma":[0.009873533,0.0001689752,0.001238359,0.002131885,0.0008282026,0.000959859,0.001106707,0.001093987,0.000232347],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007989202,"about_ca_system_score_gemma":0.0005712737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01508047,"about_ca_topic_score_gemma":0.007942032,"domain_scores_codex":[0.998894,0.0004677805,0.00007616437,0.0001954175,0.0001499432,0.0002166952],"domain_scores_gemma":[0.9904038,0.006693543,0.001416806,0.0006412046,0.000613483,0.0002312057],"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":[0.0002811805,0.0002026063,0.4599559,0.0001780394,0.0006246086,0.0006755686,0.0007826725,0.4785368,0.001288769,0.01959566,0.001098014,0.03678034],"study_design_scores_gemma":[0.00001237379,0.0001831578,0.2936722,0.0000539103,0.0001510957,0.0001576935,0.001435368,0.6898075,0.001117963,0.01163669,0.001711461,0.00006056848],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9726423,0.0002799843,0.02410848,0.0002977645,0.00001017628,0.0000215965,0.0005583629,0.00004388559,0.002037346],"genre_scores_gemma":[0.9978122,0.00007169458,0.001290336,0.0000114329,0.000003858597,0.000008621909,0.0003083412,0.000003528914,0.0004900389],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01508047,"threshold_uncertainty_score":0.02998537,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4396797506","doi":"10.1007/s10614-024-10617-1","title":"Explaining Exchange Rate Forecasts with Macroeconomic Fundamentals Using Interpretive Machine Learning","year":2024,"lang":"en","type":"article","venue":"Computational Economics","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Exchange rate; Econometrics; Economics; Computer science; Machine learning; Artificial intelligence; Macroeconomics","authors":[{"name":"Davood Pirayesh Neghab","is_ca":true},{"name":"Mücahit Çevik","is_ca":true},{"name":"M.I.M. Wahab","is_ca":true},{"name":"Ayşe Bener","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1159999722831062,"gpt":0.3859591718129475,"spread":0.2699591995298413,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009213687,0.0004766969,0.0003058591,0.0006336062,0.0001845807,0.001072882,0.0004795237,0.0005901864,0.001386226],"category_scores_gemma":[0.006990314,0.0003250882,0.0003887691,0.0003960597,0.0003536587,0.001405407,0.0004206276,0.0009963955,0.0002501539],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003664421,"about_ca_system_score_gemma":0.000335045,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002996614,"about_ca_topic_score_gemma":0.002634044,"domain_scores_codex":[0.9998528,0.00007080461,0.000009957593,0.00002843661,0.0000258635,0.00001208069],"domain_scores_gemma":[0.9978278,0.001721879,0.0001799872,0.0001476492,0.00009617362,0.00002641409],"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":[0.00006272575,0.00009658738,0.008695128,0.00006138191,0.00008541334,0.0001313819,0.000136327,0.8905603,0.002019124,0.03580076,0.001328915,0.06102189],"study_design_scores_gemma":[0.000002959611,0.000002868553,0.0003937658,0.000003777647,0.000003744404,0.000003794277,0.000004739482,0.9871053,0.0001475867,0.01223796,0.00009149458,0.000002061312],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.320222,0.0006224094,0.6732673,0.00112125,0.0001348262,0.00003069359,0.0003062036,0.000586439,0.003708863],"genre_scores_gemma":[0.9606158,0.0002867075,0.03781911,0.00004715321,0.0001094541,0.00002331448,0.0002051114,0.00003028592,0.0008629346],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002996614,"threshold_uncertainty_score":0.005958378,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2163997726","doi":"10.1007/s10614-012-9352-9","title":"Bubble Formation and Heterogeneity of Traders: A Multi-Agent Perspective","year":2012,"lang":"en","type":"article","venue":"Computational Economics","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":9,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"Program for New Century Excellent Talents in University; National Natural Science Foundation of China","keywords":"Economics; Financial market; Rationality; Bubble; Perspective (graphical); Economic bubble; Financial economics; Microeconomics; Monetary economics; Finance; Computer science; Law; Political science","authors":[{"name":"Shupeng Chen","is_ca":false},{"name":"Ling‐Yun He","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0763517070736078,"gpt":0.2512982826589027,"spread":0.1749465755852949,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002557539,0.0004185853,0.001239225,0.001312966,0.0006925192,0.003729246,0.001746384,0.003014751,0.003221859],"category_scores_gemma":[0.0164459,0.0006544165,0.0007716196,0.0008552081,0.002168889,0.0067456,0.001594953,0.001546099,0.0001858361],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008360561,"about_ca_system_score_gemma":0.0005840325,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002166532,"about_ca_topic_score_gemma":0.001291178,"domain_scores_codex":[0.9992577,0.0003648256,0.00003651576,0.0001508539,0.00009795732,0.00009203643],"domain_scores_gemma":[0.9853575,0.01095381,0.001892901,0.0006297641,0.0003912898,0.0007748447],"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":[0.0001172685,0.0001185536,0.009732132,0.0001010601,0.000255722,0.0006502999,0.0005423061,0.2975546,0.001713248,0.6800678,0.00125786,0.007889165],"study_design_scores_gemma":[0.00003059686,0.00002832998,0.00207988,0.0000154642,0.00004132418,0.00007555993,0.0001513976,0.6779748,0.0001743668,0.3188927,0.0005061394,0.00002947965],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6164558,0.002766471,0.3491763,0.01171497,0.0001818175,0.00007181039,0.0002414633,0.0001206641,0.0192708],"genre_scores_gemma":[0.9896708,0.0006411811,0.007569233,0.0001355087,0.0002076241,0.00002211027,0.00003347627,0.00001723947,0.001702829],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003729246,"threshold_uncertainty_score":0.01352578,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2112283300","doi":"10.1023/a:1023995710308","title":"A New Demand-Supply Decomposition Method for a Class of Economic Equilibrium Models","year":2003,"lang":"en","type":"article","venue":"Computational Economics","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":9,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University; University of Waterloo","funders":"","keywords":"Decomposition; Mathematical optimization; Supply and demand; Linear programming; Commodity; Scale (ratio); Mathematical economics; Mathematics; Computer science; Economics; Microeconomics; Chemistry; Physics","authors":[{"name":"William Chung","is_ca":false},{"name":"J. David Fuller","is_ca":true},{"name":"Y.June Wu","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02806392295008844,"gpt":0.325994801831655,"spread":0.2979308788815666,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001968052,0.001280095,0.00164315,0.001237833,0.0007015299,0.001335693,0.001850333,0.001506057,0.00793991],"category_scores_gemma":[0.004347246,0.001010125,0.001714791,0.001285512,0.00062395,0.002148861,0.001907653,0.002735042,0.001439565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007840691,"about_ca_system_score_gemma":0.001885205,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004849018,"about_ca_topic_score_gemma":0.006222339,"domain_scores_codex":[0.9994789,0.0002573277,0.00002557495,0.00007943743,0.0001150908,0.00004372237],"domain_scores_gemma":[0.9986876,0.0007794615,0.00007779209,0.000124604,0.0002255471,0.0001050764],"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":[0.00008861037,0.0002210544,0.0006005326,0.000210829,0.0001631916,0.0001036319,0.0001092448,0.6639992,0.002077468,0.2025294,0.01174942,0.1181475],"study_design_scores_gemma":[0.00001357616,0.000006638542,0.00003051857,0.000008890927,0.000008013622,0.00001000794,0.000005514441,0.9702513,0.00008090369,0.02798028,0.001599588,0.000004881761],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001221014,0.00008699741,0.9971461,0.0001055079,0.00005184193,0.00002627429,0.0000818435,0.0000879791,0.001192377],"genre_scores_gemma":[0.05554324,0.0003976691,0.9359158,0.0001555617,0.000187283,0.0004172742,0.0004665617,0.000354755,0.006561778],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00793991,"threshold_uncertainty_score":0.02656162,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4386897094","doi":"10.1007/s10614-023-10459-3","title":"Deep Learning and American Options via Free Boundary Framework","year":2023,"lang":"en","type":"article","venue":"Computational Economics","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":8,"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; Cardiff University","keywords":"Boundary (topology); Free boundary problem; Function (biology); Singular boundary method; Boundary value problem; Computer science; Mixed boundary condition; Applied mathematics; Mathematical optimization; Mathematics; Mathematical analysis; Boundary element method; Engineering; Finite element method","authors":[{"name":"Chinonso Nwankwo","is_ca":true},{"name":"Nneka Umeorah","is_ca":false},{"name":"Tony Ware","is_ca":true},{"name":"Weizhong Dai","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01658216992105721,"gpt":0.2374716542151949,"spread":0.2208894842941377,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001964239,0.0007234749,0.001359627,0.0009672343,0.0006049385,0.001987853,0.001518517,0.002339093,0.004195427],"category_scores_gemma":[0.01064637,0.0006353057,0.0007470128,0.0008955478,0.002513487,0.005017369,0.002138504,0.003180657,0.0003187799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001469462,"about_ca_system_score_gemma":0.001057244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005756629,"about_ca_topic_score_gemma":0.004684427,"domain_scores_codex":[0.9994374,0.0003172085,0.00001869588,0.00008373833,0.00008076664,0.00006221598],"domain_scores_gemma":[0.9966247,0.002459619,0.0002445411,0.0001637097,0.0002125623,0.0002949552],"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":[0.00006030468,0.00004071656,0.0005187662,0.00004686556,0.00002882296,0.0000529535,0.00006063361,0.2865775,0.0002595925,0.7016151,0.001553829,0.009184848],"study_design_scores_gemma":[0.00000690835,0.000005151457,0.000070865,0.000008345492,0.000003582395,0.000006099872,0.000005805161,0.6575806,0.00004598144,0.3419637,0.0002976869,0.000005211052],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1417334,0.002922644,0.8394169,0.00485863,0.0002025918,0.00002346294,0.0002549888,0.0002686987,0.01031862],"genre_scores_gemma":[0.9368644,0.001415023,0.0459776,0.0004268663,0.0003092954,0.00007339953,0.0002928735,0.0001170653,0.01452353],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005756629,"threshold_uncertainty_score":0.01403511,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3120045999","doi":"10.1007/s10614-020-10082-6","title":"Finite Sample Lag Adjusted Critical Values of the ADF-GLS Test","year":2021,"lang":"en","type":"article","venue":"Computational Economics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":8,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Queen's University","funders":"","keywords":"Akaike information criterion; Mathematics; Lag; Sample (material); Econometrics; Inference; Statistics; Applied mathematics; Computer science","authors":[{"name":"Peter S. Sephton","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.09538382026477223,"gpt":0.2524697320356092,"spread":0.157085911770837,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02977199,0.0009161566,0.002412081,0.003584445,0.00119004,0.003350613,0.003021512,0.002454891,0.02249609],"category_scores_gemma":[0.2116804,0.0005039551,0.001591674,0.002402768,0.004665036,0.004978106,0.001489427,0.004142125,0.001417235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001251406,"about_ca_system_score_gemma":0.002392486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002185522,"about_ca_topic_score_gemma":0.001672313,"domain_scores_codex":[0.9846256,0.01085084,0.0004667252,0.002214456,0.001148867,0.0006935992],"domain_scores_gemma":[0.5631762,0.4127599,0.004750788,0.01238649,0.004958947,0.001967774],"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":[0.00505856,0.0006339923,0.07466776,0.001686081,0.003382606,0.002134539,0.001440068,0.1614782,0.002458261,0.4956808,0.04241863,0.2089605],"study_design_scores_gemma":[0.000775292,0.0009598655,0.03523792,0.0003960038,0.0006457884,0.0007401957,0.001102848,0.4129928,0.002494519,0.5349342,0.009506114,0.0002144546],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3690052,0.003398282,0.5930249,0.004763566,0.001610474,0.0003129515,0.003733003,0.002092653,0.02205911],"genre_scores_gemma":[0.960784,0.0002540523,0.03351539,0.0003762098,0.0003903358,0.0002472789,0.001333797,0.0002354993,0.002863522],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02977199,"threshold_uncertainty_score":0.1574513,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2025026146","doi":"10.1023/b:csem.0000026805.91428.af","title":"The Numerical Performance of Fast Bootstrap Procedures","year":2004,"lang":"en","type":"article","venue":"Computational Economics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":8,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Brock University","funders":"","keywords":"Fraction (chemistry); Computer science; Inference; Algorithm; Artificial intelligence","authors":[{"name":"Jean-François Lamarche","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0650092466734295,"gpt":0.3370920948479807,"spread":0.2720828481745513,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0182621,0.0009165643,0.001203508,0.001983057,0.001141144,0.002556904,0.001838559,0.002464548,0.004804289],"category_scores_gemma":[0.1930078,0.0006498992,0.0006378952,0.002521605,0.001665032,0.004221749,0.001859096,0.00230269,0.001315065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001018075,"about_ca_system_score_gemma":0.00221106,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003833825,"about_ca_topic_score_gemma":0.002648318,"domain_scores_codex":[0.9904985,0.006682281,0.0003115943,0.000414464,0.001829662,0.0002634001],"domain_scores_gemma":[0.770175,0.2061317,0.002630177,0.01144781,0.00866777,0.0009476366],"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":[0.002768288,0.0003096928,0.006941747,0.0005294565,0.0002947994,0.0002683989,0.0006079203,0.4567755,0.004890365,0.1965849,0.01352509,0.3165039],"study_design_scores_gemma":[0.0001640536,0.0001019757,0.001675204,0.0000657541,0.000035988,0.0001472858,0.00008262244,0.8914596,0.002169496,0.1018774,0.002182264,0.00003835297],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1400086,0.004680187,0.8406374,0.002709239,0.0004744853,0.00009311175,0.0004464397,0.001797084,0.009153428],"genre_scores_gemma":[0.6446077,0.001581557,0.3488628,0.0003270075,0.0003417519,0.0002133457,0.0007266384,0.000580066,0.002759287],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0182621,"threshold_uncertainty_score":0.09658039,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3027334546","doi":"10.1007/s10614-020-09990-4","title":"Does Capacity Utilization Predict Inflation? A Wavelet Based Evidence from United States","year":2020,"lang":"en","type":"article","venue":"Computational Economics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":7,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Queen's University","funders":"","keywords":"Inflation (cosmology); Wavelet; Econometrics; Economics; Environmental science; Computer science; Artificial intelligence","authors":[{"name":"Pejman Bahramian","is_ca":true},{"name":"Andisheh Saliminezhad","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1754834679410636,"gpt":0.2444700424082804,"spread":0.06898657446721682,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001111086,0.0001928451,0.0002887631,0.0008237741,0.0002090891,0.001038184,0.000482925,0.000517161,0.003406243],"category_scores_gemma":[0.0152458,0.0001711206,0.0003118805,0.00174761,0.0004011851,0.0009904226,0.0005996616,0.0008454855,0.0005627155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002853217,"about_ca_system_score_gemma":0.0003966213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01991734,"about_ca_topic_score_gemma":0.01019282,"domain_scores_codex":[0.999658,0.0001333756,0.00002968872,0.00005370588,0.00006335381,0.00006180271],"domain_scores_gemma":[0.9873532,0.007577702,0.002310963,0.0008390732,0.001405602,0.0005135112],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001361871,0.0003335302,0.9155635,0.0001228149,0.0005310826,0.0003372988,0.0004767636,0.02174135,0.0004943629,0.007297468,0.01413445,0.03760552],"study_design_scores_gemma":[0.00007991183,0.0001358107,0.9262521,0.0001128403,0.0003486795,0.000131975,0.001546923,0.05425283,0.000622467,0.01076612,0.005719105,0.00003117257],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9906834,0.0006048592,0.001419574,0.00235324,0.00004534744,0.000002861379,0.001727523,0.00002636756,0.00313683],"genre_scores_gemma":[0.9985791,0.0001885695,0.0001219964,0.00006423357,0.00002769671,0.000001855937,0.0007985783,0.000006069092,0.0002119448],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01991734,"threshold_uncertainty_score":0.03960282,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1552381488","doi":"10.1023/a:1014811703866","title":"Modeling Instrumental Rationality, Land Tenure and Conflict Resolution","year":2001,"lang":"en","type":"article","venue":"Computational Economics","topic":"Economic theories and models","field":"Economics, Econometrics and Finance","cited_by":5,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"International Institute for Sustainable Development","funders":"","keywords":"Rationality; Premise; Economics; Positive economics; Mathematical economics; Microeconomics; Neoclassical economics; Law and economics; Epistemology; Political science; Law; Philosophy","authors":[{"name":"Hans M. Amman","is_ca":false},{"name":"Anantha Kumar Duraiappah","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05183452758124187,"gpt":0.2275462495393429,"spread":0.175711721958101,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002455649,0.0005024183,0.001385874,0.0008509784,0.0006377259,0.002659931,0.002144765,0.002428396,0.006744204],"category_scores_gemma":[0.01603135,0.0005882473,0.0007455823,0.001522221,0.002146065,0.002931931,0.001546463,0.002068942,0.0003500728],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00165377,"about_ca_system_score_gemma":0.001779881,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01205649,"about_ca_topic_score_gemma":0.01144205,"domain_scores_codex":[0.9989144,0.0006546158,0.00003628982,0.000138701,0.00007617377,0.000179791],"domain_scores_gemma":[0.9872857,0.01085646,0.0009303963,0.0003826939,0.0002103559,0.000334535],"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":[0.00006708164,0.00009074414,0.003086484,0.00005338415,0.00006159574,0.000107366,0.0001331266,0.5856202,0.00009064415,0.4028706,0.001637399,0.006181389],"study_design_scores_gemma":[0.00003456012,0.000008378574,0.0003989081,0.000007814958,0.00001198253,0.0000185329,0.00006423081,0.6633637,0.00004151524,0.3353163,0.0007251782,0.000008845192],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4189466,0.002172161,0.5426953,0.008008965,0.0002251557,0.00006538285,0.0009419276,0.0002267817,0.02671774],"genre_scores_gemma":[0.9761464,0.0005211878,0.01657052,0.0001295981,0.00008955007,0.00006356291,0.0001879326,0.00002997476,0.006261346],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01205649,"threshold_uncertainty_score":0.02397263,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3196181599","doi":"10.1007/s10614-021-10179-6","title":"Optimal Pricing of Climate Risk","year":2021,"lang":"en","type":"article","venue":"Computational Economics","topic":"Climate Change Policy and Economics","field":"Economics, Econometrics and Finance","cited_by":5,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University; University of Waterloo","funders":"","keywords":"Scalability; Flexibility (engineering); Computer science; Climate change; Limiting; Sensitivity (control systems); Vectorization (mathematics); Computation; Risk analysis (engineering); Mathematical optimization; Parallel computing; Economics; Algorithm; Business; Mathematics; Engineering; Ecology","authors":[{"name":"Thomas F. Coleman","is_ca":true},{"name":"Nicole Sandra-Yaffa Dumont","is_ca":true},{"name":"Wanqi Li","is_ca":true},{"name":"Wenbin Liu","is_ca":false},{"name":"Alexey Rubtsov","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05540380247365082,"gpt":0.2449006682899143,"spread":0.1894968658162635,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001487528,0.0003692266,0.001012306,0.0007392442,0.0004893601,0.003231896,0.001158127,0.0021216,0.008153294],"category_scores_gemma":[0.01638017,0.0004807963,0.0006106534,0.0008630102,0.001608863,0.004789511,0.001185287,0.002050062,0.0003161007],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001583046,"about_ca_system_score_gemma":0.001472351,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003241428,"about_ca_topic_score_gemma":0.002165605,"domain_scores_codex":[0.9992208,0.000440852,0.0000294162,0.00009910986,0.00012229,0.00008746315],"domain_scores_gemma":[0.9943789,0.004517826,0.0002659,0.000333818,0.0002529905,0.0002506739],"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":[0.00004127041,0.00006070646,0.0006575684,0.00004385765,0.00002785078,0.00003681675,0.00004344362,0.1776275,0.0001655387,0.8113328,0.002928241,0.007034333],"study_design_scores_gemma":[0.00001537542,0.000004510568,0.0001874976,0.000006233245,0.000005809929,0.00001145584,0.00001745506,0.3487183,0.00004949218,0.6504118,0.0005656183,0.000006462354],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2941951,0.002615805,0.5996153,0.01867677,0.0008699844,0.00006600204,0.0005942427,0.000333525,0.08303337],"genre_scores_gemma":[0.9794826,0.0006563682,0.01386321,0.0001778071,0.0002790765,0.00002521059,0.0001104283,0.00004432947,0.005361013],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008153294,"threshold_uncertainty_score":0.02727544,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2070744509","doi":"10.1007/s10614-015-9485-8","title":"Economic Modeling Using Evolutionary Algorithms: The Influence of Mutation on the Premature Convergence Effect","year":2015,"lang":"en","type":"article","venue":"Computational Economics","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of the Fraser Valley","funders":"","keywords":"Premature convergence; Convergence (economics); Mutation; Binary number; Robustness (evolution); Encoding (memory); Computer science; Algorithm; Population; Range (aeronautics); Mathematical optimization; Mathematics; Artificial intelligence; Biology; Genetics; Economics; Arithmetic","authors":[{"name":"Michael K. Maschek","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04367278048033039,"gpt":0.2363265681070671,"spread":0.1926537876267367,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005054842,0.0005426891,0.001211527,0.0008409627,0.0006980328,0.001868876,0.001481439,0.002181129,0.00189426],"category_scores_gemma":[0.03801315,0.0005071389,0.0007817124,0.0006703323,0.001577623,0.003106156,0.001271653,0.002017183,0.0002337223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006067282,"about_ca_system_score_gemma":0.0009441269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002626411,"about_ca_topic_score_gemma":0.001591005,"domain_scores_codex":[0.998861,0.0007922393,0.00004060679,0.00009148735,0.0001547035,0.00006001764],"domain_scores_gemma":[0.9832364,0.0142171,0.0005853954,0.000633641,0.001055129,0.0002723801],"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":[0.00005560306,0.00004807246,0.002071826,0.00007540591,0.00008168243,0.0002180665,0.0001403153,0.895004,0.0007167276,0.08746527,0.0007526133,0.01337032],"study_design_scores_gemma":[0.000009569364,0.000009894327,0.0001559515,0.000009876321,0.000009516761,0.00002285167,0.000008424093,0.9820473,0.0001263507,0.01741088,0.0001839415,0.000005294143],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2353838,0.002069073,0.7450309,0.003351592,0.0002938451,0.0000656647,0.00005584595,0.0001578449,0.01359153],"genre_scores_gemma":[0.9419837,0.001131852,0.05254756,0.0002746652,0.0001646272,0.00009104854,0.00003393376,0.000128126,0.003644502],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005054842,"threshold_uncertainty_score":0.02673292,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2098457418","doi":"10.1007/s10614-012-9341-z","title":"A Generic Framework for a Combined Agent-based Market and Production Model","year":2012,"lang":"en","type":"article","venue":"Computational Economics","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Memorial University of Newfoundland; University of Calgary","funders":"","keywords":"Revenue; Production (economics); Negotiation; Double auction; Supply and demand; Computer science; A priori and a posteriori; Computational economics; Commodity; Economics; Von Neumann architecture; Order (exchange); Microeconomics; Limit (mathematics); Mathematical economics; Common value auction; Mathematics","authors":[{"name":"Bas Straatman","is_ca":true},{"name":"Danielle J. Marceau","is_ca":true},{"name":"Roger White","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05398082668317214,"gpt":0.2318570000701091,"spread":0.177876173386937,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001880761,0.0009830658,0.001611865,0.0009120717,0.0008645333,0.002709758,0.00350129,0.003305161,0.008905199],"category_scores_gemma":[0.003603037,0.0007333789,0.002194428,0.001437703,0.001350211,0.002885235,0.002693098,0.002126141,0.002051801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009723442,"about_ca_system_score_gemma":0.002084243,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003608381,"about_ca_topic_score_gemma":0.003802776,"domain_scores_codex":[0.9990749,0.0003584834,0.00008059457,0.0001716145,0.00022905,0.00008534088],"domain_scores_gemma":[0.9989828,0.0004475992,0.00009720683,0.0001737067,0.0001877408,0.0001109506],"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":[0.00001857507,0.00004630031,0.0003042769,0.0000748088,0.00007775583,0.0002122213,0.00006511214,0.3220619,0.0009331942,0.6655696,0.002107264,0.008528943],"study_design_scores_gemma":[0.0000239389,0.00001499695,0.00008515704,0.00001182793,0.00002612555,0.00006633011,0.00001107367,0.8258634,0.0001730979,0.1685501,0.005159832,0.00001400555],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001936945,0.0001308857,0.9925517,0.0004669617,0.00005331606,0.00003925061,0.0002028202,0.0001535289,0.004464621],"genre_scores_gemma":[0.2894702,0.001002059,0.6915464,0.0004185105,0.0003923885,0.0006607622,0.0006971022,0.0002835165,0.01552904],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008905199,"threshold_uncertainty_score":0.02979088,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4397034360","doi":"10.1007/s10614-024-10622-4","title":"Implementing a Hierarchical Deep Learning Approach for Simulating Multilevel Auction Data","year":2024,"lang":"en","type":"article","venue":"Computational Economics","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Center for Interuniversity Research and Analysis on Organizations; Polytechnique Montréal","funders":"","keywords":"Computer science; Artificial intelligence; Machine learning","authors":[{"name":"Igor Sadoune","is_ca":true},{"name":"Marcelin Joanis","is_ca":true},{"name":"Andrea Lodi","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2193451768061243,"gpt":0.4321025041571659,"spread":0.2127573273510416,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001650944,0.000396689,0.0008194623,0.0005835668,0.0006039542,0.001193305,0.002614904,0.001933894,0.006280369],"category_scores_gemma":[0.01016958,0.000827454,0.0007356492,0.0007745572,0.0007686715,0.001851129,0.001446296,0.00268095,0.0004413371],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00156647,"about_ca_system_score_gemma":0.001832399,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02391413,"about_ca_topic_score_gemma":0.03139695,"domain_scores_codex":[0.9995043,0.000188124,0.00002427628,0.00008802307,0.00009767697,0.0000975325],"domain_scores_gemma":[0.9953413,0.003273806,0.0002199081,0.0004861708,0.0004278201,0.0002509691],"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":[0.00005884136,0.00007094299,0.001361909,0.00001697547,0.00002750781,0.00003377025,0.00002862313,0.9816865,0.0003343785,0.01002627,0.0004965159,0.00585791],"study_design_scores_gemma":[0.000003539002,0.000002925663,0.00003187588,6.205568e-7,0.000001031034,0.000001562641,0.000001795319,0.9982979,0.00005761549,0.001575443,0.00002462526,0.000001154675],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3075829,0.0001047743,0.6830133,0.001048167,0.0001217006,0.0001187699,0.0005151955,0.00154976,0.005945487],"genre_scores_gemma":[0.8838768,0.00003253654,0.1129526,0.0002205021,0.00003115746,0.0001086474,0.0003475599,0.0001115796,0.002318525],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02391413,"threshold_uncertainty_score":0.04754984,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2064149127","doi":"10.1007/s10614-011-9313-8","title":"Computing Equilibrium Wealth Distributions in Models with Heterogeneous-Agents, Incomplete Markets and Idiosyncratic Risk","year":2012,"lang":"en","type":"article","venue":"Computational Economics","topic":"Economic theories and models","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Dow Chemical (Canada)","funders":"","keywords":"Incomplete markets; Markov process; Markov chain; Stationary distribution; Stochastic matrix; Mathematics; Aggregate (composite); Mathematical economics; Econometrics; Economics; Mathematical optimization; Applied mathematics; Microeconomics","authors":[{"name":"Muffasir Badshah","is_ca":true},{"name":"Paul M. Beaumont","is_ca":false},{"name":"Anuj Srivastava","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03039970818808732,"gpt":0.2202475433099989,"spread":0.1898478351219116,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002542256,0.0008245992,0.001554226,0.001309991,0.0008093787,0.002720117,0.001717508,0.002033939,0.003467011],"category_scores_gemma":[0.02252695,0.001287668,0.0008675208,0.001092023,0.001380631,0.004998882,0.00187814,0.001338233,0.0002676402],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001550693,"about_ca_system_score_gemma":0.001266534,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007405085,"about_ca_topic_score_gemma":0.007904247,"domain_scores_codex":[0.9994567,0.000254737,0.00003904432,0.0001154238,0.00005732667,0.00007677136],"domain_scores_gemma":[0.9882872,0.01028793,0.0005000465,0.0003498703,0.0002334676,0.0003414942],"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":[0.00008585659,0.00006561544,0.001779289,0.00003065922,0.00003282861,0.00007189455,0.0000543267,0.968277,0.00008439752,0.02362196,0.0002871091,0.005609063],"study_design_scores_gemma":[0.00001295244,0.000003564983,0.00006285289,0.000002394028,0.000003132527,0.000003910547,0.00001072238,0.9737828,0.00004599218,0.02603825,0.00003153381,0.000001939686],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5186899,0.0003725148,0.4752034,0.001148335,0.00005247639,0.00006549941,0.0002633847,0.0004377992,0.003766737],"genre_scores_gemma":[0.9275967,0.000173811,0.07037073,0.00006234684,0.00003786297,0.00006138106,0.0002762049,0.00006677036,0.001354117],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007405085,"threshold_uncertainty_score":0.01472396,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4225620916","doi":"10.1007/s10614-022-10252-8","title":"The Slicing Method: Determining Insensitivity Regions of Probability Weighting Functions","year":2022,"lang":"en","type":"article","venue":"Computational Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"CHIST-ERA; Xunta de Galicia; Natural Sciences and Engineering Research Council of Canada; Mitacs; Agencia Nacional de Investigación e Innovación","keywords":"Weighting; Heuristic; Rule of thumb; Computer science; Subadditivity; Slicing; Mathematical optimization; Class (philosophy); Mathematics; Algorithm; Artificial intelligence","authors":[{"name":"Martín Egozcue","is_ca":false},{"name":"Luis Fuentes García","is_ca":false},{"name":"Ričardas Zitikis","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1785096608880326,"gpt":0.3926388063783125,"spread":0.2141291454902799,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004864328,0.001303336,0.001337458,0.002697987,0.0005855411,0.001517392,0.001472187,0.0008909829,0.004286042],"category_scores_gemma":[0.02762898,0.001125854,0.001379914,0.001326365,0.001159473,0.002560878,0.001685851,0.001706816,0.0004757232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008352817,"about_ca_system_score_gemma":0.00178659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004690002,"about_ca_topic_score_gemma":0.003115193,"domain_scores_codex":[0.9989941,0.0005062807,0.00004683096,0.0001336679,0.000227154,0.00009206077],"domain_scores_gemma":[0.9835902,0.01365936,0.0005497741,0.000913131,0.0009458862,0.0003416776],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004576651,0.000123467,0.003144189,0.0004389714,0.0002423098,0.000261818,0.0004444887,0.5675729,0.01153988,0.1835824,0.004875876,0.2273161],"study_design_scores_gemma":[0.00001596466,0.00002387629,0.0004050599,0.00002861957,0.00002800957,0.00004593138,0.00001730079,0.9370164,0.002640743,0.05909849,0.0006624563,0.00001714712],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009853823,0.000151168,0.9886256,0.00003391827,0.000007659944,0.0000252266,0.00006838636,0.0002618646,0.0009723792],"genre_scores_gemma":[0.2785572,0.0004135453,0.718497,0.00009961016,0.00003728754,0.0001828316,0.0004460445,0.0006264591,0.001139873],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004864328,"threshold_uncertainty_score":0.02572536,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4400411810","doi":"10.1007/s10614-024-10663-9","title":"Bias Correction in the Least-Squares Monte Carlo Algorithm","year":2024,"lang":"en","type":"article","venue":"Computational Economics","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University; Wilfrid Laurier University; University of Ottawa","funders":"","keywords":"Monte Carlo method; Algorithm; Computer science; Least-squares function approximation; Mathematics; Statistics; Estimator","authors":[{"name":"François-Michel Boire","is_ca":true},{"name":"R. Mark Reesor","is_ca":true},{"name":"Lars Stentoft","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04166801103830703,"gpt":0.2376093718792449,"spread":0.1959413608409379,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006100077,0.0006518466,0.001542793,0.001057583,0.0007779236,0.001910305,0.001926377,0.002201278,0.004089411],"category_scores_gemma":[0.05038897,0.001005186,0.0007234222,0.001490165,0.001315368,0.002087506,0.001919562,0.002458088,0.001283629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001079199,"about_ca_system_score_gemma":0.002904989,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008515819,"about_ca_topic_score_gemma":0.006626297,"domain_scores_codex":[0.9965996,0.00200709,0.0001480096,0.0003507496,0.000735369,0.000159182],"domain_scores_gemma":[0.9781894,0.01796284,0.0005506007,0.001172185,0.001880466,0.0002445139],"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":[0.0002774324,0.00007643586,0.001944555,0.0001649219,0.0001372004,0.00008596972,0.0001144342,0.7879192,0.001951429,0.1064359,0.002600556,0.09829197],"study_design_scores_gemma":[0.00001620514,0.000009556356,0.0001250649,0.00001308862,0.000009184344,0.00001801455,0.00000377307,0.9754254,0.0005486115,0.02316758,0.0006532851,0.00001013612],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004259933,0.0002282266,0.9941877,0.0002429692,0.00006233023,0.00001815062,0.00002391853,0.0002756864,0.000701066],"genre_scores_gemma":[0.2583455,0.0005051406,0.7343557,0.0003292163,0.0002275753,0.0002266686,0.0002034476,0.0005497728,0.005256971],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008515819,"threshold_uncertainty_score":0.03226066,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3023418069","doi":"10.1007/s10614-020-09984-2","title":"Plant location decisions in the ethanol industry: a dynamic and spatial analysis","year":2020,"lang":"en","type":"article","venue":"Computational Economics","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","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 Saskatchewan; Government of Alberta","funders":"Agriculture and Agri-Food Canada","keywords":"Counterfactual thinking; Subsidy; Agriculture; Government (linguistics); Order (exchange); Environmental economics; Process (computing); Sizing; Ethanol fuel; Operations research; Computer science; Environmental resource management; Natural resource economics; Economics; Biofuel; Engineering; Geography; Chemistry","authors":[{"name":"Jason Wood","is_ca":true},{"name":"James Nolan","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04174553415954051,"gpt":0.2316685045028048,"spread":0.1899229703432643,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008955273,0.000232178,0.0005873675,0.0008646037,0.0003944801,0.001532521,0.0008532233,0.001013787,0.006960937],"category_scores_gemma":[0.003998542,0.0003779734,0.0008512314,0.00135653,0.0007894498,0.001828336,0.0009780257,0.0007484986,0.0003356161],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001734049,"about_ca_system_score_gemma":0.0009540601,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06343758,"about_ca_topic_score_gemma":0.05060223,"domain_scores_codex":[0.9997438,0.0001069487,0.000007730221,0.00005492549,0.00002312746,0.00006347839],"domain_scores_gemma":[0.9973341,0.002013328,0.0002762787,0.0000793806,0.0001588838,0.0001380984],"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":[0.0002157972,0.0001339268,0.02024831,0.00003977307,0.00007137945,0.0001719612,0.0001273059,0.9213979,0.0004903927,0.04623003,0.00160088,0.009272394],"study_design_scores_gemma":[0.00001890077,0.00003029632,0.005094608,0.000005482353,0.00003130444,0.00002533279,0.0002573552,0.9802576,0.0001244409,0.01363317,0.0005079132,0.0000136145],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9634572,0.0003554768,0.02926967,0.001360608,0.00001240039,0.00001732795,0.0004185162,0.00004032782,0.005068494],"genre_scores_gemma":[0.9946444,0.0001917618,0.001971445,0.0000266783,0.000009012015,0.000006348877,0.0001026366,0.000008586852,0.00303926],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06343758,"threshold_uncertainty_score":0.1261367,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4386349856","doi":"10.1007/s10614-023-10458-4","title":"Finite Sample Lag Adjusted Critical Values and Probability Values for the Fourier Wavelet Unit Root Test","year":2023,"lang":"en","type":"article","venue":"Computational Economics","topic":"Image and Signal Denoising Methods","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":"Queen's University","funders":"","keywords":"Unit root; Wavelet; Mathematics; Statistics; Augmented Dickey–Fuller test; Lag; Unit root test; Series (stratigraphy); Sample (material); Statistical hypothesis testing; Fourier series; Fourier transform; Sample size determination; Root (linguistics); Econometrics; Applied mathematics; Computer science; Mathematical analysis; Cointegration; Artificial intelligence","authors":[{"name":"Peter S. Sephton","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.07702739364224764,"gpt":0.3207901847743262,"spread":0.2437627911320786,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02787321,0.001086024,0.002026641,0.0052029,0.001035823,0.003715637,0.00292333,0.003040408,0.01331543],"category_scores_gemma":[0.2435953,0.0007031152,0.001727437,0.002742739,0.00726888,0.006775457,0.001912127,0.005603286,0.0006733965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001781665,"about_ca_system_score_gemma":0.002272435,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001101253,"about_ca_topic_score_gemma":0.0007267639,"domain_scores_codex":[0.9919167,0.004908402,0.0003194254,0.001110567,0.001217949,0.0005269765],"domain_scores_gemma":[0.5739223,0.3987723,0.006827065,0.01040352,0.007544807,0.002529959],"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":[0.0008952861,0.0002176178,0.009873228,0.0005116771,0.0004417168,0.0005905218,0.0005688067,0.07385903,0.002323708,0.8523549,0.00481773,0.05354572],"study_design_scores_gemma":[0.0001841628,0.0003240481,0.008762048,0.0002300156,0.0001566827,0.000335508,0.0003988243,0.2244292,0.002519552,0.759797,0.002728628,0.0001342606],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1248228,0.001498559,0.861428,0.001585431,0.0004326538,0.0001833807,0.0004835102,0.0004779176,0.009087712],"genre_scores_gemma":[0.89741,0.0008341562,0.09544747,0.0004609899,0.0005237539,0.000506255,0.0006803515,0.0003540352,0.003782963],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02787321,"threshold_uncertainty_score":0.1474093,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4413206736","doi":"10.1007/s10614-025-11077-x","title":"A Hidden Markov Modulated Deep Learning Model for Retail Forecasting with Interpretation","year":2025,"lang":"en","type":"article","venue":"Computational Economics","topic":"Forecasting Techniques and Applications","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Interpretation (philosophy); Artificial intelligence; Markov chain; Hidden Markov model; Computer science; Econometrics; Machine learning; Deep learning; Economics","authors":[{"name":"Davood Pirayesh Neghab","is_ca":true},{"name":"Mücahit Çevik","is_ca":true},{"name":"M.I.M. Wahab","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.09021920245593085,"gpt":0.3337881196480732,"spread":0.2435689171921424,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009304025,0.000428933,0.0009558522,0.0004673423,0.0003021484,0.001005768,0.001555706,0.001525318,0.00437671],"category_scores_gemma":[0.003295336,0.0005045357,0.0006458582,0.0007929636,0.0005327925,0.001724679,0.0007847429,0.002078143,0.0005949867],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001073574,"about_ca_system_score_gemma":0.0009505824,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0112881,"about_ca_topic_score_gemma":0.0112988,"domain_scores_codex":[0.9997936,0.00007393693,0.00001132719,0.00005409315,0.00003096495,0.00003614615],"domain_scores_gemma":[0.9989805,0.000698353,0.00007679297,0.00007026478,0.000132869,0.00004123491],"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":[0.00008989609,0.00006679446,0.0008185004,0.00004576898,0.00003801466,0.0000655711,0.00004319753,0.8983021,0.0006392321,0.05255042,0.002777209,0.04456336],"study_design_scores_gemma":[0.000001953226,0.000002597072,0.00003710913,0.000001876683,0.000002233796,0.000002176285,9.643071e-7,0.9928429,0.00003356145,0.006996569,0.00007637418,0.000001638005],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06303181,0.0009245061,0.92835,0.001811814,0.0001990614,0.00002867924,0.000483573,0.0005230543,0.004647399],"genre_scores_gemma":[0.918585,0.0006126753,0.06834047,0.0002993736,0.0001684381,0.00007836075,0.0004762578,0.00007843192,0.01136106],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0112881,"threshold_uncertainty_score":0.02244478,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4409557626","doi":"10.1007/s10614-025-10932-1","title":"Clean Energy Stock Market and Energy/Metals as Safe-Haven Assets: New Insights from Quantile-on-Quantile and Markov-Switching Approaches","year":2025,"lang":"en","type":"article","venue":"Computational Economics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Ontario Tech University","funders":"","keywords":"Quantile; Markov chain; Safe haven; Econometrics; Stock (firearms); Quantile regression; Financial economics; Business; Economics; Mathematics; Statistics; Engineering","authors":[{"name":"Wajih Khallouli","is_ca":false},{"name":"K. Smimou","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02889242201494416,"gpt":0.2225540626839598,"spread":0.1936616406690156,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003101205,0.0006728432,0.001697929,0.001035607,0.0005389506,0.002502386,0.002218942,0.001568943,0.006526149],"category_scores_gemma":[0.01090737,0.000596772,0.001720251,0.001062808,0.00189959,0.004112926,0.00166044,0.002895729,0.000250345],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001187329,"about_ca_system_score_gemma":0.001293967,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008429972,"about_ca_topic_score_gemma":0.005892524,"domain_scores_codex":[0.9994003,0.0002657052,0.0000231243,0.00009556134,0.00009902004,0.0001164028],"domain_scores_gemma":[0.9943689,0.004025564,0.0005972115,0.0003535255,0.0003224389,0.0003323878],"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":[0.00005369972,0.00007318758,0.003609946,0.00005623299,0.00009194025,0.0001061222,0.0001156869,0.367159,0.0003278923,0.6160675,0.001901829,0.01043699],"study_design_scores_gemma":[0.000007877069,0.000007656132,0.0006994178,0.000008667536,0.00001315214,0.00001432319,0.0000242455,0.8163396,0.00005568959,0.1824138,0.0004052792,0.00001030787],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1691686,0.003150193,0.8094676,0.004930708,0.0003001047,0.00004214511,0.0004174278,0.0002108274,0.01231239],"genre_scores_gemma":[0.9665539,0.002405041,0.02193564,0.0003295058,0.0004841805,0.00004199837,0.0002817601,0.0000853739,0.007882682],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008429972,"threshold_uncertainty_score":0.02183211,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4411037250","doi":"10.1007/s10614-025-11003-1","title":"Social and Individual Learning in the Minority Game","year":2025,"lang":"en","type":"article","venue":"Computational Economics","topic":"Evolutionary Game Theory and Cooperation","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Sociology; Psychology","authors":[{"name":"Bryce Morsky","is_ca":true},{"name":"Fuwei Zhuang","is_ca":true},{"name":"Zuojun Zhou","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03568753772248391,"gpt":0.3117014981224978,"spread":0.2760139604000139,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002424099,0.0003398214,0.0009202303,0.0005082319,0.0009620165,0.002370891,0.001183439,0.001367947,0.005062681],"category_scores_gemma":[0.01346783,0.0002189645,0.0004987448,0.0003469556,0.002644327,0.003962953,0.001629528,0.001331473,0.0002126794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001364542,"about_ca_system_score_gemma":0.001104375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004967574,"about_ca_topic_score_gemma":0.003500776,"domain_scores_codex":[0.998769,0.0008022505,0.00002749715,0.000120725,0.0001219544,0.0001585342],"domain_scores_gemma":[0.99064,0.007778607,0.0004724386,0.0002741878,0.0002311268,0.0006035466],"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":[0.0001040424,0.00009760286,0.002137981,0.00005516661,0.0000474834,0.0001136385,0.0004501187,0.08082608,0.0004664355,0.9047984,0.00125896,0.009644051],"study_design_scores_gemma":[0.00003516095,0.00003211795,0.0007626901,0.000009898721,0.00001416302,0.00003508331,0.0001937555,0.2965923,0.0001359949,0.7012786,0.0008970832,0.00001307308],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6973233,0.0005207974,0.2434495,0.006049289,0.00009143937,0.00009525371,0.0000983297,0.00004812587,0.05232396],"genre_scores_gemma":[0.9881042,0.0001364447,0.007042282,0.0001086645,0.00003583525,0.00004091296,0.00001615089,0.000009857354,0.004505728],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005062681,"threshold_uncertainty_score":0.0169363,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4410896380","doi":"10.1007/s10614-025-11005-z","title":"Hopf Bifurcation Analysis in a Business Cycle Model with Gamma-Type Distributed Time Delay","year":2025,"lang":"en","type":"article","venue":"Computational Economics","topic":"Complex Systems and Time Series Analysis","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":false},"ca_institutions":"University of Toronto","funders":"Natural Science Foundation of Inner Mongolia; National Natural Science Foundation of China","keywords":"Hopf bifurcation; Type (biology); Mathematics; Applied mathematics; Business cycle; Bifurcation; Control theory (sociology); Computer science; Economics; Physics; Biology; Nonlinear system; Artificial intelligence","authors":[{"name":"Yan Lu","is_ca":false},{"name":"Nan Liu","is_ca":false},{"name":"Haiying Liu","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01133869054132651,"gpt":0.2000754323920189,"spread":0.1887367418506924,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006240936,0.000432204,0.0008380972,0.001027629,0.0005013704,0.001063487,0.0005945836,0.001028307,0.002124195],"category_scores_gemma":[0.002627993,0.0002901896,0.0008674804,0.0004533864,0.0009539865,0.00107176,0.0009455573,0.0007468303,0.0001629923],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009546612,"about_ca_system_score_gemma":0.0008244115,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004893877,"about_ca_topic_score_gemma":0.001941909,"domain_scores_codex":[0.9998878,0.00004530617,0.000005215402,0.00002197907,0.00001839758,0.00002125246],"domain_scores_gemma":[0.9991928,0.0005269451,0.00009925009,0.0000222664,0.00009708772,0.00006170023],"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":[0.00008396097,0.00004110059,0.001617848,0.00009145187,0.00008309288,0.0002501954,0.0001622239,0.8406708,0.0028269,0.1464962,0.0008506739,0.006825618],"study_design_scores_gemma":[0.000004977758,0.000006075024,0.0001369064,0.000004570968,0.00000893354,0.00001389844,0.00001533607,0.9827482,0.00009397815,0.01684547,0.0001165758,0.000005000458],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4380541,0.001642073,0.5398604,0.001430576,0.0001515899,0.00006241768,0.0001479746,0.0002072567,0.0184436],"genre_scores_gemma":[0.9896678,0.0004184444,0.005293613,0.00005766682,0.00002832483,0.00002704935,0.00004309081,0.00002846573,0.004435579],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004893877,"threshold_uncertainty_score":0.009730756,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4407979027","doi":"10.1007/s10614-025-10864-w","title":"Augmented Graphical Ridge Estimation with Application in the Cryptocurrency Market","year":2025,"lang":"en","type":"article","venue":"Computational Economics","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"Iran National Science Foundation; University of Pretoria","keywords":"Cryptocurrency; Ridge; Graphical model; Estimation; Computer science; Econometrics; Artificial intelligence; Economics; Geology; Paleontology; World Wide Web","authors":[{"name":"Andriëtte Bekker","is_ca":false},{"name":"Azam Kheyri","is_ca":true},{"name":"‎M‎ohammad Arashi","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01426168017959838,"gpt":0.2329539577111924,"spread":0.218692277531594,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00425087,0.0005597131,0.001074585,0.0009295802,0.0003017356,0.0008489483,0.001222959,0.00103885,0.001624347],"category_scores_gemma":[0.01371317,0.0004562261,0.0008708261,0.0009958403,0.0007799817,0.0009469994,0.001279479,0.001485257,0.0002982697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003493903,"about_ca_system_score_gemma":0.001086473,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00573803,"about_ca_topic_score_gemma":0.006188017,"domain_scores_codex":[0.9986894,0.0008795101,0.00004108059,0.0001552182,0.0001454416,0.00008932194],"domain_scores_gemma":[0.993337,0.004972284,0.0004378642,0.0006241981,0.000491905,0.0001366968],"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":[0.0001616813,0.0001166869,0.006902403,0.00009428916,0.0001636642,0.0001817898,0.00007697786,0.8637062,0.001821296,0.03422993,0.001517368,0.09102777],"study_design_scores_gemma":[0.000006307661,0.000008933672,0.0002671171,0.000002572971,0.000003818981,0.000007277571,0.000003580436,0.9960386,0.000133711,0.003398346,0.0001259387,0.000003886241],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07066043,0.000303521,0.9270502,0.0004035418,0.00002978768,0.00002801111,0.0001340698,0.0006983094,0.0006922177],"genre_scores_gemma":[0.7647978,0.0003307903,0.23215,0.0001494836,0.00006895718,0.00006809845,0.0004130341,0.0001474515,0.0018744],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00573803,"threshold_uncertainty_score":0.02248102,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4388455350","doi":"10.1007/s10614-023-10493-1","title":"Computing Longitudinal Moments for Heterogeneous Agent Models","year":2023,"lang":"en","type":"article","venue":"Computational Economics","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"","keywords":"Monte Carlo method; Computer science; Population; Mathematical optimization; Computation; Method of moments (probability theory); Markov chain Monte Carlo; Function (biology); Applied mathematics; Mathematics; Algorithm; Statistics","authors":[{"name":"Sergio Ocampo","is_ca":true},{"name":"B.A. Robinson","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.08935507334048438,"gpt":0.3399895755705446,"spread":0.2506345022300602,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003216183,0.000798095,0.001640884,0.001467475,0.0008548094,0.002201759,0.001849644,0.001655539,0.003675979],"category_scores_gemma":[0.02673301,0.00132379,0.001303696,0.001188415,0.001011916,0.00288416,0.00218055,0.002079691,0.0005559243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00143678,"about_ca_system_score_gemma":0.001433207,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008097717,"about_ca_topic_score_gemma":0.01019386,"domain_scores_codex":[0.9991647,0.0003703721,0.00006699244,0.0001506277,0.0001291632,0.0001182268],"domain_scores_gemma":[0.9813482,0.01558296,0.001016967,0.0008733265,0.0005013504,0.0006772102],"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":[0.000146305,0.00007900996,0.004205644,0.00005568888,0.00009557726,0.0001415816,0.0000729882,0.9571164,0.0003029325,0.02364027,0.001190593,0.01295311],"study_design_scores_gemma":[0.000007508811,0.000004670564,0.0001087512,0.000002713172,0.000004519748,0.000006963031,0.000007258526,0.985297,0.00005020822,0.01442546,0.00008200681,0.000002932341],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1522432,0.0007396723,0.8421428,0.001247913,0.0001241813,0.0000553335,0.0006629723,0.001167228,0.001616703],"genre_scores_gemma":[0.886142,0.000520876,0.1093774,0.0001575697,0.0002240365,0.0001330173,0.001288251,0.0001912878,0.001965543],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008097717,"threshold_uncertainty_score":0.01700896,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4417237146","doi":"10.1007/s10614-025-11168-9","title":"Technical Analysis with Machine Learning Classification Algorithms: Can it Still ‘Beat’ the Buy-and-hold Strategy?","year":2025,"lang":"en","type":"article","venue":"Computational Economics","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Technical analysis; Sharpe ratio; Trading strategy; Trend following; Pairs trade; Statistical arbitrage; Profitability index; Algorithmic trading; Financial market; Equity (law)","authors":[{"name":"Ba Chu","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1093213188330786,"gpt":0.3837547398222899,"spread":0.2744334209892113,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02715723,0.002038253,0.002550563,0.003496678,0.002106571,0.009030758,0.003665784,0.005855707,0.01022909],"category_scores_gemma":[0.1059644,0.0006789701,0.001685537,0.002352753,0.00993209,0.0280468,0.003653118,0.01056947,0.003727787],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002409477,"about_ca_system_score_gemma":0.003399702,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002120329,"about_ca_topic_score_gemma":0.001759344,"domain_scores_codex":[0.9909433,0.00371174,0.0004977002,0.00109403,0.00326195,0.0004914357],"domain_scores_gemma":[0.9402829,0.04000121,0.00387457,0.007676549,0.006769426,0.001395391],"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":[0.0001203173,0.0002063137,0.005406073,0.0003512725,0.0002633741,0.000124587,0.0002655403,0.01031702,0.0006404769,0.7916483,0.03023448,0.1604223],"study_design_scores_gemma":[0.00001812065,0.00004908282,0.0007658086,0.0001308228,0.00002431988,0.00005400609,0.0001102394,0.04442728,0.0003738108,0.9467399,0.00727386,0.000032582],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03275117,0.01056284,0.7240982,0.1808805,0.005957177,0.0001285827,0.0003080572,0.0008537573,0.04445984],"genre_scores_gemma":[0.6669195,0.01104444,0.2519099,0.02831198,0.01466069,0.0003525447,0.0006128932,0.0009228316,0.02526531],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02715723,"threshold_uncertainty_score":0.1436229,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4396613887","doi":"10.1007/s10614-024-10596-3","title":"The Art of Temporal Approximation: An Investigation into Numerical Solutions to Discrete- and Continuous-Time Problems in Economics","year":2024,"lang":"en","type":"article","venue":"Computational Economics","topic":"Economic theories and models","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":false},"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Discrete modelling; Mathematics; Econometrics; Applied mathematics; Economics; Mathematical economics; Computer science; Algorithm; Discrete system","authors":[{"name":"Keyvan Eslami","is_ca":true},{"name":"Thomas Phelan","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02138886493713178,"gpt":0.2180164440213575,"spread":0.1966275790842258,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006839747,0.0007393326,0.001569843,0.001450137,0.001070986,0.005029994,0.003183429,0.003159396,0.003945697],"category_scores_gemma":[0.04827539,0.000897782,0.001608469,0.002481868,0.006796875,0.0124291,0.002814088,0.004960616,0.0003577429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001988803,"about_ca_system_score_gemma":0.002580929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006190957,"about_ca_topic_score_gemma":0.003067408,"domain_scores_codex":[0.9976649,0.001197155,0.0001480296,0.0002274939,0.0006747741,0.00008750377],"domain_scores_gemma":[0.962473,0.03324004,0.00102773,0.001842059,0.0010967,0.000320512],"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":[0.00002153456,0.00001719923,0.0003079723,0.0001445534,0.00001910011,0.00002225869,0.0001347905,0.04932323,0.0001075423,0.9382992,0.001074985,0.01052757],"study_design_scores_gemma":[0.0000120267,0.00000881014,0.00008101175,0.00006303559,0.000007970913,0.00002403873,0.00004737376,0.3044002,0.00007634731,0.6923742,0.002895917,0.000009036234],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01118409,0.01046842,0.9495001,0.01066964,0.0005086625,0.00003738748,0.0001032463,0.0001359996,0.01739231],"genre_scores_gemma":[0.5514055,0.02232528,0.4131569,0.001894876,0.002206429,0.0002672472,0.0002045192,0.0003147291,0.008224607],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006839747,"threshold_uncertainty_score":0.03617251,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4388702818","doi":"10.1007/s10614-023-10513-0","title":"Inflation Targeting Regimes in Emerging Market Economies: To Invest or Not to Invest?","year":2023,"lang":"en","type":"article","venue":"Computational Economics","topic":"Complex Systems and Time Series Analysis","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":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Economics; Inflation (cosmology); Inflation targeting; Monetary economics; Investment (military); Transparency (behavior); Monetary policy","authors":[{"name":"Douglas Silveira","is_ca":true},{"name":"Ricardo Barbosa Lima Mendes Oscar","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0437907812959471,"gpt":0.2540629830630665,"spread":0.2102722017671194,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001573645,0.0001592417,0.0004737746,0.0003103645,0.0001823019,0.001794229,0.0004131536,0.001106433,0.001920719],"category_scores_gemma":[0.01154965,0.0001651739,0.0001717727,0.0002603162,0.001166455,0.002991492,0.0005293917,0.001420564,0.0001578392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003952536,"about_ca_system_score_gemma":0.0003966981,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001368558,"about_ca_topic_score_gemma":0.001345399,"domain_scores_codex":[0.9997889,0.0001019017,0.00001338526,0.00003798811,0.00001823555,0.00003965122],"domain_scores_gemma":[0.995344,0.002969354,0.00105282,0.0001183514,0.0001619428,0.000353552],"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":[0.00101792,0.0002553654,0.09915123,0.0004063373,0.0002860937,0.0006520357,0.0007515947,0.09365562,0.001041792,0.6206045,0.01631268,0.1658649],"study_design_scores_gemma":[0.00007227142,0.00005209752,0.01516637,0.0001259937,0.00006472688,0.0001205898,0.0006819125,0.2063758,0.0002559148,0.7750503,0.00200931,0.00002464828],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.910266,0.00543008,0.03390625,0.03561319,0.0003121979,0.00001205142,0.0001603287,0.0001164716,0.01418337],"genre_scores_gemma":[0.9980715,0.0006425626,0.0006548027,0.0001755422,0.0001028993,0.00000348277,0.00001702192,0.000005563223,0.0003266507],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001920719,"threshold_uncertainty_score":0.008322358,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4414068604","doi":"10.1007/s10614-025-11069-x","title":"Robust Quarterly Recession Forecasts of the U. S. Economy","year":2025,"lang":"en","type":"article","venue":"Computational Economics","topic":"Economic Growth and Productivity","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Categorical variable; Recession; Logit; Consensus forecast; Quarter (Canadian coin); Business cycle; Logistic regression; Forecast error","authors":[{"name":"Rolando F. Peláez","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03025515570510367,"gpt":0.2073624674235112,"spread":0.1771073117184075,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001446554,0.0002729766,0.0003273545,0.0006878846,0.0001059091,0.0006004337,0.0002502655,0.0004209545,0.002399765],"category_scores_gemma":[0.009078022,0.0002075187,0.0002099045,0.0005922159,0.00009986154,0.0005300592,0.000285629,0.0005213442,0.0008253956],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004181269,"about_ca_system_score_gemma":0.0003639133,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01999298,"about_ca_topic_score_gemma":0.01265357,"domain_scores_codex":[0.9997146,0.000116566,0.00001898613,0.00006392395,0.00006448168,0.00002154242],"domain_scores_gemma":[0.9983929,0.000841369,0.0002527933,0.0001268071,0.0003311415,0.00005504265],"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":[0.0003318781,0.00005642232,0.06586024,0.00005874002,0.0001031681,0.00007996974,0.00005567698,0.8596276,0.0008501275,0.006083093,0.01658514,0.05030798],"study_design_scores_gemma":[0.00002040962,0.00002850598,0.02487359,0.00002092337,0.00001476403,0.00001700992,0.00002429467,0.9683575,0.0004061321,0.004158095,0.002062305,0.00001653589],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.89003,0.0006745908,0.0721335,0.002219317,0.0001608212,0.00004527198,0.02506806,0.001456363,0.00821215],"genre_scores_gemma":[0.9875707,0.0001397377,0.004694173,0.00004313446,0.00002622332,0.00001332019,0.006310706,0.00002891829,0.001173144],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01999298,"threshold_uncertainty_score":0.0397532,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2904474279","doi":"10.1007/s10614-018-9874-x","title":"Conditional Correlation Demand Systems","year":2018,"lang":"en","type":"article","venue":"Computational Economics","topic":"Economics of Agriculture and Food Markets","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":false},"ca_institutions":"University of Calgary","funders":"","keywords":"Econometrics; Correlation; Computer science; Mathematics","authors":[{"name":"Apostolos Serletis","is_ca":true},{"name":"Libo Xu","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01874870174464736,"gpt":0.1943148165547952,"spread":0.1755661148101479,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00166191,0.0005690497,0.001415218,0.001049657,0.0006310593,0.002461645,0.001506072,0.002274982,0.01779682],"category_scores_gemma":[0.01570465,0.0007469403,0.001016291,0.001474561,0.001499096,0.003940489,0.001691963,0.002055682,0.001423606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001862074,"about_ca_system_score_gemma":0.001513561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005211281,"about_ca_topic_score_gemma":0.004457674,"domain_scores_codex":[0.9989368,0.0004008502,0.00004679824,0.0002804937,0.0001708605,0.0001641123],"domain_scores_gemma":[0.9901564,0.006494557,0.0007254787,0.00111695,0.001053839,0.0004528508],"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":[0.0000465549,0.00004429984,0.001538122,0.00005038578,0.00004283577,0.0001226245,0.00005655072,0.1552268,0.0002664869,0.8285494,0.00727376,0.006782069],"study_design_scores_gemma":[0.00001653347,0.000009280844,0.0004630153,0.000007988435,0.00000944566,0.00004670012,0.0000197667,0.6950917,0.00009116803,0.3027226,0.001508327,0.00001353041],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1513002,0.0009505784,0.795764,0.00686729,0.0003639298,0.00009944989,0.003453126,0.0008044705,0.04039703],"genre_scores_gemma":[0.9427968,0.0006152188,0.02571393,0.0004908203,0.0002928813,0.0001350878,0.002191446,0.0001666737,0.02759714],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01779682,"threshold_uncertainty_score":0.05953628,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2041675997","doi":"10.1007/s10614-011-9296-5","title":"The Efficient Frontier for Weakly Correlated Assets","year":2011,"lang":"en","type":"article","venue":"Computational Economics","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":false},"ca_institutions":"University of Waterloo","funders":"China Scholarship Council","keywords":"Efficient frontier; Mathematics; Diagonal; Portfolio; Monotonic function; Covariance matrix; Covariance; Parametric statistics; Upper and lower bounds; Order (exchange); Applied mathematics; Mathematical optimization; Economics; Statistics; Finance; Mathematical analysis","authors":[{"name":"Michael J. Best","is_ca":true},{"name":"Xili Zhang","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04044285691872718,"gpt":0.2096919822169376,"spread":0.1692491252982104,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003226225,0.0007311685,0.001881906,0.001761388,0.0006446504,0.003740815,0.001232451,0.001875015,0.004212935],"category_scores_gemma":[0.02509928,0.0008941274,0.0009333298,0.001636637,0.0027762,0.00561496,0.00234551,0.002353562,0.0003367208],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001383128,"about_ca_system_score_gemma":0.001725286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002193373,"about_ca_topic_score_gemma":0.001379693,"domain_scores_codex":[0.9987302,0.0008108409,0.00006218269,0.0001371296,0.0001500202,0.0001096608],"domain_scores_gemma":[0.9842036,0.01362857,0.0006469554,0.0006266244,0.0004944279,0.0003999046],"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":[0.00002431063,0.00002007553,0.0004535117,0.00006476582,0.00002610716,0.00004027987,0.00006117833,0.1545175,0.000162635,0.8357679,0.0009433836,0.007918415],"study_design_scores_gemma":[0.000009817976,0.000004981985,0.0001317758,0.00001627135,0.000004918124,0.00000982532,0.00001288738,0.3200269,0.0000529941,0.679307,0.0004176514,0.000004956815],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08984713,0.001862208,0.8967163,0.001709405,0.00004435673,0.00002697262,0.0002206663,0.000116141,0.009456774],"genre_scores_gemma":[0.9022058,0.002222149,0.08797828,0.0001488486,0.0001603534,0.0001272607,0.0003713423,0.0001339014,0.006651966],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004212935,"threshold_uncertainty_score":0.01706207,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}