{"meta":{"query_hash":"33c0ce98975b","filters":{"venue":"Applied Mathematical Finance"},"cohort_total":19,"direct_labels_cover":0,"predictions_cover":19,"exported":19,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/33c0ce98975b","api":"https://metacan.xera.ac/api/v1/cohort?venue=Applied+Mathematical+Finance"},"results":[{"id":"W1973219638","doi":"10.1080/1350486x.2012.678735","title":"Exotic Geometric Average Options Pricing under Stochastic Volatility","year":2012,"lang":"en","type":"article","venue":"Applied Mathematical Finance","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Valuation of options; Stochastic volatility; Implied volatility; SABR volatility model; Financial economics; Volatility smile; Volatility (finance); Econometrics; Economics; Actuarial science; Computer science","score_opus":0.04589439033210992,"score_gpt":0.23586135418444334,"score_spread":0.18996696385233341,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1973219638","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024651168,0.0018071106,0.9535638,0.00016295146,0.00015293187,0.00053683727,0.00005396799,0.00010415443,0.018967075],"genre_scores_gemma":[0.97522235,0.000026146145,0.023674978,0.00017591767,0.0001920311,0.00038407775,0.0000148624395,0.000041982617,0.00026762535],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99790096,0.000003226139,0.0008085231,0.0004824589,0.00009761209,0.0007072038],"domain_scores_gemma":[0.99857235,0.0003050113,0.0003125824,0.00060783786,0.000040268358,0.00016195339],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005846011,0.00026752966,0.0005563406,0.00023218578,0.00027157748,0.000064008644,0.0003333371,0.00015819239,0.0003527195],"category_scores_gemma":[0.00030390793,0.00029232274,0.00011908269,0.001137895,0.00012413049,0.00022736606,0.00012781603,0.0002738986,0.0035936404],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000052740897,0.00031391747,0.00013875184,0.000065559725,0.000012014267,2.0877016e-7,0.00019357401,0.00048253636,0.00001912269,0.997903,0.000047520458,0.0008185166],"study_design_scores_gemma":[0.0002996005,0.000018702543,0.017632978,0.000025136083,0.000016233193,0.000012394223,0.000043303186,0.0038813893,0.000021775391,0.9766277,0.0010383006,0.00038246418],"about_ca_topic_score_codex":0.000007949335,"about_ca_topic_score_gemma":7.096781e-7,"teacher_disagreement_score":0.95057124,"about_ca_system_score_codex":0.00013329808,"about_ca_system_score_gemma":0.000024096225,"threshold_uncertainty_score":0.9999529},"labels":[],"label_agreement":null},{"id":"W1993478052","doi":"10.1080/13527260600963851","title":"Indifference Pricing and Hedging for Volatility Derivatives","year":2007,"lang":"en","type":"article","venue":"Applied Mathematical Finance","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Volatility (finance); Stochastic volatility; Heston model; Economics; Volatility smile; Swap (finance); Econometrics; Incomplete markets; Mathematical economics; Implied volatility; Valuation of options; Volatility swap; Financial market; Variance swap; SABR volatility model; Microeconomics; Finance","score_opus":0.03205081351868246,"score_gpt":0.24728425806307675,"score_spread":0.21523344454439428,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1993478052","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1423728,0.00038536708,0.85010296,0.00010781616,0.000026295233,0.000455857,0.000024512938,0.000036312274,0.0064880815],"genre_scores_gemma":[0.8993481,0.000015290907,0.10024877,0.00009798996,0.00005143634,0.00017058603,0.0000028459888,0.000016087422,0.000048925573],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99873424,5.974181e-7,0.00051181915,0.00039960365,0.000031753993,0.0003220139],"domain_scores_gemma":[0.99911046,0.0003676575,0.00021603979,0.00022370522,0.000027272194,0.000054864726],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005325632,0.00014284391,0.00034510906,0.000066950626,0.00018253532,0.00004024977,0.00014991013,0.00008484354,0.000014121186],"category_scores_gemma":[0.00026750987,0.00015279505,0.00003970676,0.00021721862,0.00011528663,0.00007218572,0.00006164486,0.0001013472,0.0000452675],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013340285,0.000049314534,0.00038697757,0.000115358635,0.000005384275,1.7320234e-7,0.00070378906,4.2302722e-7,0.00012026362,0.99124926,0.000009163025,0.0073465547],"study_design_scores_gemma":[0.00024965592,0.00002212595,0.0137332715,0.000025360827,0.000003660878,0.0000018302704,0.00006532256,0.0018141933,0.00038169738,0.98249435,0.0010268571,0.00018164537],"about_ca_topic_score_codex":0.0000028579973,"about_ca_topic_score_gemma":0.0000011873233,"teacher_disagreement_score":0.7569753,"about_ca_system_score_codex":0.000029274039,"about_ca_system_score_gemma":0.000009953557,"threshold_uncertainty_score":0.62308013},"labels":[],"label_agreement":null},{"id":"W2009157972","doi":"10.1080/13504860701718448","title":"Return and Value at Risk using the Dirichlet Process","year":2008,"lang":"en","type":"article","venue":"Applied Mathematical Finance","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Professional Engineers Ontario; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; University of Illinois at Urbana-Champaign; University of Ottawa","keywords":"Dirichlet distribution; Computer science; Dirichlet process; Monte Carlo method; Bayesian probability; Econometrics; Value at risk; Process (computing); Asset (computer security); Mathematical optimization; Artificial intelligence; Mathematics; Statistics; Risk management; Economics","score_opus":0.02424534989453917,"score_gpt":0.26811299085631213,"score_spread":0.24386764096177296,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2009157972","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13982679,0.0002462673,0.8545425,0.00020413562,0.000027867556,0.00021319384,0.000001199207,0.000050504743,0.0048875283],"genre_scores_gemma":[0.46006408,0.00008269202,0.53946465,0.00019655294,0.000030553398,0.000024450692,1.05055165e-7,0.000009063119,0.00012785617],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99889535,0.000046978577,0.00020750897,0.00036229772,0.000224793,0.0002630794],"domain_scores_gemma":[0.99898374,0.00026708105,0.000110442845,0.0005592643,0.000025651092,0.0000538246],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044241038,0.00015060349,0.00022111458,0.000019279847,0.0004131166,0.000046249803,0.00048821952,0.0000696804,0.0000049764712],"category_scores_gemma":[0.00006017312,0.00009340671,0.00003654175,0.00023809688,0.0001856357,0.00010197361,0.0002559749,0.00018717766,0.000015118331],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000050893773,0.000034518187,0.00004988091,0.000044455766,0.0000066583348,0.000009249825,0.0021405471,0.000023304367,0.00043645312,0.9875481,0.0001963362,0.009505374],"study_design_scores_gemma":[0.00016795844,0.0000131661,0.00018427895,0.000027667611,0.000011934859,0.00018168119,0.000007590123,0.122612484,0.002663251,0.8735091,0.00044520595,0.00017566644],"about_ca_topic_score_codex":0.0000013390229,"about_ca_topic_score_gemma":1.6936794e-7,"teacher_disagreement_score":0.32023728,"about_ca_system_score_codex":0.000018801062,"about_ca_system_score_gemma":0.000028882781,"threshold_uncertainty_score":0.3809015},"labels":[],"label_agreement":null},{"id":"W2026351326","doi":"10.1080/13504860600563143","title":"Liquidity Risk with Coherent Risk Measures","year":2006,"lang":"en","type":"article","venue":"Applied Mathematical Finance","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Market liquidity; Liquidity risk; Risk measure; Portfolio; Martingale (probability theory); Economics; Spectral risk measure; Actuarial science; Econometrics; Portfolio optimization; Financial economics; Business; Finance; Mathematics","score_opus":0.030650612770801923,"score_gpt":0.2857963265549404,"score_spread":0.2551457137841385,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2026351326","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.41793424,0.00013256833,0.516494,0.00007718528,0.000052574982,0.00039835772,0.000026842545,0.00008496147,0.064799316],"genre_scores_gemma":[0.95909745,0.0005022211,0.039002582,0.00002756156,0.00009831671,0.00007752767,0.0000037965297,0.00001964664,0.0011709293],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9971274,0.00009156643,0.0006648326,0.00052070315,0.0012821999,0.0003132798],"domain_scores_gemma":[0.99763846,0.0008275028,0.0005151145,0.0007722448,0.00017927431,0.00006742558],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001765169,0.00021133645,0.00039690282,0.0000816694,0.0002493007,0.0001902815,0.00044843316,0.000103364306,0.00017348329],"category_scores_gemma":[0.00050374237,0.0001289369,0.00007961072,0.00058794173,0.00018052313,0.00012383999,0.0000626813,0.00022033982,0.0011671499],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031369933,0.0007080351,0.014359099,0.00001037013,0.000033697255,0.000014967997,0.00048311186,0.055294756,0.00012137212,0.70063376,0.034352258,0.19367488],"study_design_scores_gemma":[0.0005713806,0.000085464,0.0142478775,0.000019137997,0.000050792903,0.000007824443,0.000070862676,0.0074528605,0.0015560365,0.92646545,0.04914524,0.00032705648],"about_ca_topic_score_codex":0.000041224328,"about_ca_topic_score_gemma":0.000028457089,"teacher_disagreement_score":0.54116315,"about_ca_system_score_codex":0.000022863263,"about_ca_system_score_gemma":0.000045640278,"threshold_uncertainty_score":0.99961054},"labels":[],"label_agreement":null},{"id":"W2045522554","doi":"10.1080/1350486042000271647","title":"A Re‐Examination of Sharpe's Ratio for Log‐Normal Prices","year":2005,"lang":"en","type":"article","venue":"Applied Mathematical Finance","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Sharpe ratio; Estimator; Econometrics; Mathematics; Economics; Statistics; Financial economics; Portfolio","score_opus":0.06081101202475738,"score_gpt":0.2376414408441191,"score_spread":0.1768304288193617,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045522554","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.55516225,0.0006238574,0.23660731,0.0010892132,0.00009942382,0.0011156354,0.00027532526,0.000058047528,0.20496894],"genre_scores_gemma":[0.960512,0.00004960284,0.038104646,0.0002095941,0.0001427645,0.00013862131,0.000015435497,0.00001986274,0.0008074648],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.998603,0.0000033973058,0.0007736309,0.0002961046,0.000029771361,0.00029410815],"domain_scores_gemma":[0.99904144,0.00018141631,0.00041363263,0.00030815828,0.000011194175,0.000044171957],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00064342207,0.00014756483,0.0004497267,0.00010299258,0.00006404295,0.00003089007,0.00021289091,0.00010512463,0.0006129189],"category_scores_gemma":[0.00010555513,0.00016291147,0.000101263104,0.00009807667,0.000064796805,0.00023529991,0.00003299141,0.000076860044,0.00068292586],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021773429,0.00011958116,0.000052075557,0.00014230468,0.000021121808,1.05570955e-7,0.00083724404,0.0010148875,0.00005203474,0.9912513,0.0009360667,0.005551535],"study_design_scores_gemma":[0.002089714,0.00021768891,0.00680186,0.000064697204,0.000026568994,0.0000044558815,0.0001742954,0.17434238,0.0066178213,0.74809545,0.06080835,0.0007567064],"about_ca_topic_score_codex":0.000005070571,"about_ca_topic_score_gemma":0.000003050688,"teacher_disagreement_score":0.40534976,"about_ca_system_score_codex":0.000051634306,"about_ca_system_score_gemma":0.000008490895,"threshold_uncertainty_score":0.8777858},"labels":[],"label_agreement":null},{"id":"W2067843432","doi":"10.1080/13504860110046885","title":"A numerical PDE approach for pricing callable bonds","year":2001,"lang":"en","type":"article","venue":"Applied Mathematical Finance","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":44,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; Royal Bank of Canada","keywords":"Callable bond; Issuer; Valuation (finance); Bond valuation; Notice; Classification of discontinuities; Convertible bond; Computer science; Bond; Mathematical optimization; Economics; Mathematical economics; Finance; Mathematics","score_opus":0.032365981194915426,"score_gpt":0.2328706377323712,"score_spread":0.20050465653745578,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2067843432","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010254807,0.00042930985,0.8666331,0.00025858008,0.0000305919,0.00067099516,0.000032760116,0.000078233345,0.13084093],"genre_scores_gemma":[0.72434306,0.00004472613,0.27247116,0.0003141427,0.00016798137,0.0016641523,0.00001900431,0.000049148377,0.0009266406],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9981853,0.0000010664523,0.0006583625,0.00059292535,0.000057210607,0.00050513813],"domain_scores_gemma":[0.99905765,0.00014311097,0.00024285867,0.00043476254,0.00003810743,0.00008349198],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000306827,0.00021382474,0.00055212073,0.00007724546,0.00020566455,0.00006423369,0.00033683906,0.00014097767,0.000070396825],"category_scores_gemma":[0.00015222059,0.00022852207,0.000099769095,0.00050578354,0.00007227282,0.000079571924,0.00005430267,0.00014753596,0.0005638154],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022796961,0.00023611588,0.000035836565,0.000106094456,0.000010914447,5.614088e-7,0.0001230514,0.00019487995,0.00003484563,0.99702066,0.00046692917,0.0017473162],"study_design_scores_gemma":[0.00046060016,0.000046999947,0.0001424362,0.000013658814,0.000008276341,0.0000109780585,0.000025975956,0.02757632,0.000060306196,0.9388521,0.032487616,0.00031478913],"about_ca_topic_score_codex":0.000009559365,"about_ca_topic_score_gemma":2.0611222e-7,"teacher_disagreement_score":0.72331756,"about_ca_system_score_codex":0.00006261447,"about_ca_system_score_gemma":0.00002370314,"threshold_uncertainty_score":0.93188596},"labels":[],"label_agreement":null},{"id":"W2106641117","doi":"10.1080/13504860600839964","title":"Numerical Methods and Volatility Models for Valuing Cliquet Options","year":2006,"lang":"en","type":"article","venue":"Applied Mathematical Finance","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Volatility (finance); Stochastic volatility; Implied volatility; Econometrics; Jump diffusion; Volatility smile; SABR volatility model; Jump; Forward volatility; Mathematics; Grid; Economics; Valuation of options; Computer science","score_opus":0.0428979843556965,"score_gpt":0.2954471580139106,"score_spread":0.25254917365821405,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106641117","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018771746,0.0010984096,0.97556764,0.0003166081,0.000035240348,0.0005912495,0.00008465412,0.00006333455,0.02036571],"genre_scores_gemma":[0.48686108,0.000020685675,0.5121804,0.00006657296,0.000067685185,0.0006735488,0.0000084832745,0.000020188076,0.00010135949],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9985136,0.000003091895,0.00064276974,0.00049865304,0.000033745328,0.0003081641],"domain_scores_gemma":[0.99904144,0.00034969792,0.0002059402,0.00031524454,0.000037918202,0.00004975979],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005761014,0.0001696969,0.00045600574,0.000056788536,0.00019721685,0.000058713187,0.00016402802,0.00012236586,0.000022331858],"category_scores_gemma":[0.00012167008,0.00018605514,0.00008533292,0.00022528303,0.000100680896,0.00010745721,0.00005051739,0.000116666124,0.00005029921],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008961952,0.0001060507,0.000018594037,0.00008078894,0.000005486024,8.780817e-8,0.000056413097,0.00020073804,0.00003413181,0.9963104,0.00009064844,0.003087671],"study_design_scores_gemma":[0.00021917612,0.000017339697,0.00040259567,0.000009975416,0.0000074600903,0.0000021796336,0.000007394442,0.16522293,0.000075130876,0.8307738,0.0030819073,0.0001801615],"about_ca_topic_score_codex":0.00002023654,"about_ca_topic_score_gemma":6.928999e-7,"teacher_disagreement_score":0.48498392,"about_ca_system_score_codex":0.000034784433,"about_ca_system_score_gemma":0.000014989114,"threshold_uncertainty_score":0.7587108},"labels":[],"label_agreement":null},{"id":"W2123463037","doi":"10.1080/135048600450284","title":"Unstructured meshing for two asset barrier options","year":2000,"lang":"en","type":"article","venue":"Applied Mathematical Finance","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Royal Bank of Canada","keywords":"Polygon mesh; Classification of discontinuities; Finite element method; Computer science; Ellipse; Applied mathematics; Mathematical optimization; Algorithm; Mathematics; Geometry; Mathematical analysis; Structural engineering; Engineering","score_opus":0.021033376825738557,"score_gpt":0.24366244055636035,"score_spread":0.2226290637306218,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2123463037","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0063305255,0.00044814777,0.9190905,0.00041769148,0.0000681997,0.0007285974,0.00047429712,0.00008859459,0.07235343],"genre_scores_gemma":[0.84317553,0.00005038764,0.1535705,0.00037621887,0.00020410112,0.0012089127,0.000029785684,0.00004951898,0.0013350572],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99845165,0.0000012935311,0.0006151982,0.0004954431,0.000047544483,0.00038887974],"domain_scores_gemma":[0.9991394,0.0001498361,0.00016446818,0.00043901877,0.000029438044,0.00007781546],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00026028266,0.00019755072,0.0004384688,0.0000628457,0.00025867787,0.00008453657,0.0003244846,0.00011151898,0.001152818],"category_scores_gemma":[0.000101026955,0.00021575119,0.00012367756,0.00028776738,0.000093151575,0.00010650962,0.00002996926,0.00014084144,0.0014409998],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001344461,0.000055939534,0.0000036375952,0.00003993358,0.000011469053,2.537158e-7,0.00012558862,0.00009817777,0.000056623743,0.9861295,0.00030949162,0.013155903],"study_design_scores_gemma":[0.00053751003,0.0000189607,0.00018572342,0.000015475458,0.000009736152,0.0000046372325,0.000013951985,0.0028566904,0.00012891514,0.9537652,0.042198423,0.00026477216],"about_ca_topic_score_codex":0.0000048101974,"about_ca_topic_score_gemma":0.0000015162665,"teacher_disagreement_score":0.836845,"about_ca_system_score_codex":0.00004166942,"about_ca_system_score_gemma":0.000022782107,"threshold_uncertainty_score":0.99976027},"labels":[],"label_agreement":null},{"id":"W2884230765","doi":"10.1080/1350486x.2018.1492347","title":"Optimal Expected-Shortfall Portfolio Selection with Copula-Induced Dependence","year":2018,"lang":"en","type":"article","venue":"Applied Mathematical Finance","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Copula (linguistics); Expected shortfall; Portfolio; Selection (genetic algorithm); Econometrics; Economics; Computer science; Financial economics; Artificial intelligence","score_opus":0.048219501297631306,"score_gpt":0.33134095545198894,"score_spread":0.28312145415435763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2884230765","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5816692,0.000018032919,0.3436825,0.00006285672,0.00009310394,0.00040402915,0.000002487625,0.00012927713,0.073938526],"genre_scores_gemma":[0.9091823,0.000038983137,0.088799946,0.00010236379,0.00020096233,0.00008975581,0.0000033966753,0.000030329973,0.0015519259],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9965303,0.00004479837,0.0007651937,0.00079177856,0.001391779,0.00047617577],"domain_scores_gemma":[0.9980146,0.00031518732,0.00036038065,0.00071779714,0.00045530664,0.00013667325],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00097118295,0.00027941464,0.0004527229,0.00018925054,0.00029345852,0.00025524898,0.00060982787,0.00017191206,0.001019853],"category_scores_gemma":[0.0003660723,0.00019559021,0.000068785565,0.0014843103,0.00021507898,0.00032107762,0.00009518126,0.0002132075,0.0017971363],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007819152,0.00075579307,0.0048071304,0.000019896193,0.00007384402,0.00006086205,0.002233327,0.0047136536,0.0061574965,0.8446864,0.020591836,0.115117855],"study_design_scores_gemma":[0.004295914,0.0030384876,0.02798304,0.0003142846,0.00025477647,0.0009871688,0.002278234,0.12973887,0.121680625,0.65217316,0.053313263,0.003942164],"about_ca_topic_score_codex":0.0000068152567,"about_ca_topic_score_gemma":0.000011425917,"teacher_disagreement_score":0.32751313,"about_ca_system_score_codex":0.000042905627,"about_ca_system_score_gemma":0.00011944882,"threshold_uncertainty_score":0.99989337},"labels":[],"label_agreement":null},{"id":"W3021602562","doi":"10.1080/1350486x.2020.1754260","title":"Optimal Generation and Trading in Solar Renewable Energy Certificate (SREC) Markets","year":2020,"lang":"en","type":"article","venue":"Applied Mathematical Finance","topic":"Climate Change Policy and Economics","field":"Economics, Econometrics and Finance","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Offset (computer science); Renewable energy; Certificate; Marginal cost; Production (economics); Mathematical optimization; Microeconomics; Business; Industrial organization; Economics; Computer science; Engineering; Mathematics","score_opus":0.17728841282713095,"score_gpt":0.23915821535846885,"score_spread":0.06186980253133789,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3021602562","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8411214,0.0015237245,0.074583195,0.004812954,0.00012964364,0.0003972026,0.00012055202,0.000087065004,0.07722429],"genre_scores_gemma":[0.9907286,0.00066510023,0.0073901955,0.0008004346,0.00014378232,0.00007583954,0.00001422219,0.000029966686,0.0001518335],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99858916,0.0000061249175,0.0005949301,0.00046475526,0.00002255809,0.00032247265],"domain_scores_gemma":[0.9994868,0.000065487504,0.00016320274,0.00018810088,0.000005221114,0.0000912017],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029013155,0.00016403351,0.0004291994,0.00007473909,0.00007124747,0.00009315521,0.00014070788,0.00011355848,0.00026354272],"category_scores_gemma":[0.00007250245,0.00019987281,0.000042901665,0.00016111562,0.000051159353,0.00014487331,0.000066924906,0.0001075749,0.00018140557],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000049121176,0.000082567916,0.00033871472,0.00014825686,0.000014572529,0.0000047994577,0.0018173897,0.0008298657,0.0009840258,0.9921301,0.0020937116,0.0015068781],"study_design_scores_gemma":[0.0011168598,0.00005948539,0.0008224083,0.00004156032,0.000008570357,0.00000926083,0.00016046365,0.6031293,0.00535298,0.3597331,0.02883392,0.0007320615],"about_ca_topic_score_codex":0.000045747864,"about_ca_topic_score_gemma":0.00001595025,"teacher_disagreement_score":0.632397,"about_ca_system_score_codex":0.000048380643,"about_ca_system_score_gemma":0.000006955743,"threshold_uncertainty_score":0.81505764},"labels":[],"label_agreement":null},{"id":"W3122879523","doi":"10.1080/1350486x.2018.1434009","title":"Enhancing trading strategies with order book signals","year":2018,"lang":"en","type":"article","venue":"Applied Mathematical Finance","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":98,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"High-frequency trading; Measure (data warehouse); Econometrics; Sample (material); Computer science; Order (exchange); Order book; Jump; Markov chain; Limit (mathematics); Volume (thermodynamics); Economics; Algorithmic trading; Financial economics; Mathematics; Finance; Data mining","score_opus":0.01566149485570257,"score_gpt":0.22032017479140342,"score_spread":0.20465867993570086,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3122879523","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05584355,0.000088452834,0.13591519,0.00047875108,0.00012025281,0.0006324251,5.384634e-7,0.00027914415,0.8066417],"genre_scores_gemma":[0.9883976,0.000005156136,0.006384952,0.00284442,0.0008394159,0.00011814692,0.0000033136362,0.00004255948,0.0013644086],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986791,0.0000031788677,0.00028750618,0.0003448856,0.00029159393,0.00039372226],"domain_scores_gemma":[0.99941075,0.000050281807,0.00013731346,0.00030432138,0.00008482984,0.000012484979],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000284027,0.00022643025,0.00026235622,0.00010070663,0.00020773448,0.0003706701,0.00025538172,0.00005097612,0.002445745],"category_scores_gemma":[0.000025207763,0.00017646303,0.000036131423,0.00041451945,0.00018695733,0.0006997148,0.000100203935,0.00010312703,0.001667385],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003100126,0.00007971163,0.000011467912,0.00029506936,0.000021246724,0.000006227046,0.00016249437,0.000019396408,0.00142925,0.9889032,0.007761579,0.0012793421],"study_design_scores_gemma":[0.0013777737,0.00009531467,0.00017765515,0.0006022504,0.00013318582,0.0000053721005,0.00299004,0.010542953,0.007339632,0.5645585,0.41105384,0.0011234832],"about_ca_topic_score_codex":0.0000058633927,"about_ca_topic_score_gemma":0.000008481699,"teacher_disagreement_score":0.93255407,"about_ca_system_score_codex":0.000021103408,"about_ca_system_score_gemma":0.000020785048,"threshold_uncertainty_score":0.9991099},"labels":[],"label_agreement":null},{"id":"W3123018500","doi":"10.1080/1350486x.2019.1603183","title":"Mean-Field Game Strategies for Optimal Execution","year":2019,"lang":"en","type":"article","venue":"Applied Mathematical Finance","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":58,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Nash equilibrium; Minor (academic); Mathematical economics; Repeated game; High-frequency trading; Sequential game; Set (abstract data type); Computer science; Population; Property (philosophy); Outcome (game theory); Game theory; Algorithmic trading; Economics; Finance","score_opus":0.02378308821676511,"score_gpt":0.22606546374715247,"score_spread":0.20228237553038736,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3123018500","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.33261043,0.0006139401,0.15097976,0.00039435463,0.00031345483,0.001220023,0.000055830285,0.00010277288,0.5137094],"genre_scores_gemma":[0.9823979,0.00008553572,0.015056833,0.00038928984,0.00008583601,0.00027650085,0.000009719193,0.00003067896,0.0016677177],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9985294,0.0000031978157,0.00056501647,0.00045414484,0.000052137493,0.0003961267],"domain_scores_gemma":[0.9991629,0.00016447304,0.00022721598,0.00038030202,0.000023762015,0.000041333566],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00033264922,0.0002100321,0.00048788395,0.00007321341,0.00006749002,0.00014816663,0.0002415225,0.00015157262,0.0005872783],"category_scores_gemma":[0.00004905104,0.00021626697,0.00012588939,0.00013971908,0.000059757058,0.00029975272,0.00004641701,0.00012670683,0.0016400605],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000051355102,0.00007742138,0.000036125555,0.00016297612,0.000012778264,4.160659e-7,0.00029668823,0.00010053379,0.00014830678,0.99705446,0.0013603645,0.00069859775],"study_design_scores_gemma":[0.0005671366,0.00018301468,0.0004063361,0.000036919377,0.000005066556,0.000001500114,0.00028495476,0.0025253335,0.00042887506,0.95567447,0.039574828,0.00031157135],"about_ca_topic_score_codex":0.000007408984,"about_ca_topic_score_gemma":8.7766597e-7,"teacher_disagreement_score":0.6497875,"about_ca_system_score_codex":0.000038966024,"about_ca_system_score_gemma":0.00003252661,"threshold_uncertainty_score":0.9991373},"labels":[],"label_agreement":null},{"id":"W3125047413","doi":"10.1080/1350486x.2013.771515","title":"Modelling Asset Prices for Algorithmic and High-Frequency Trading","year":2013,"lang":"en","type":"article","venue":"Applied Mathematical Finance","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":88,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"High-frequency trading; Algorithmic trading; Market liquidity; Pairs trade; Market microstructure; Tick size; Volume-weighted average price; Dark liquidity; Econometrics; Trading strategy; Alternative trading system; Financial economics; Economics; Market maker; Profit (economics); Stock market; Monetary economics; Microeconomics; Finance; Order (exchange)","score_opus":0.03112917970222452,"score_gpt":0.20228369753200268,"score_spread":0.17115451782977814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3125047413","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12480799,0.0011072148,0.8562649,0.0002962756,0.00005394738,0.00075642014,0.00005571217,0.00004588463,0.016611693],"genre_scores_gemma":[0.84927535,0.000069284644,0.14972521,0.000036938985,0.00007182397,0.0003986325,0.0000065797367,0.00002479281,0.00039140467],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986391,0.0000023103667,0.00060321175,0.0004135318,0.000037368824,0.00030449344],"domain_scores_gemma":[0.9992584,0.00013829378,0.00023730409,0.00028252383,0.000025015259,0.00005844051],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026241984,0.00016851218,0.0005455036,0.00008686406,0.00013943172,0.00014998263,0.00016326501,0.00007913432,0.00045132678],"category_scores_gemma":[0.000023103095,0.00017052017,0.00008709112,0.0001650762,0.00004944468,0.00017466191,0.000038922662,0.000079460086,0.00033303731],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000015521733,0.000030050243,0.00003450817,0.00012986304,0.000031064093,2.2145323e-7,0.000134772,0.00024830358,0.0000375374,0.9976123,0.00019762508,0.0015422071],"study_design_scores_gemma":[0.00019869494,0.000016675589,0.00009879084,0.000017791102,0.000008177521,0.0000018186623,0.000040589992,0.28753585,0.000019103685,0.7103552,0.0015297043,0.00017757763],"about_ca_topic_score_codex":0.00013491865,"about_ca_topic_score_gemma":0.0000011215645,"teacher_disagreement_score":0.72446734,"about_ca_system_score_codex":0.000028928871,"about_ca_system_score_gemma":0.00000523992,"threshold_uncertainty_score":0.6953611},"labels":[],"label_agreement":null},{"id":"W4362735410","doi":"10.1080/1350486x.2023.2193343","title":"Optimal Execution with Identity Optionality","year":2022,"lang":"en","type":"article","venue":"Applied Mathematical Finance","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Air Force Office of Scientific Research","keywords":"Computer science; Identity (music); Limiting; Population; Differential (mechanical device); Code (set theory); Operations research; Mathematical economics; Economics; Set (abstract data type); Programming language; Mathematics","score_opus":0.023100796068969195,"score_gpt":0.22660929620507358,"score_spread":0.2035085001361044,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362735410","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.041202154,0.00021454816,0.9263697,0.0004289211,0.000046002846,0.0003473396,0.000144666,0.00006152075,0.031185148],"genre_scores_gemma":[0.9532054,0.000009371518,0.045061115,0.00022029757,0.000050948172,0.0011505745,0.00002271634,0.000021087362,0.00025850968],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99877906,0.0000023773885,0.0004217153,0.00042990973,0.0001110811,0.0002558854],"domain_scores_gemma":[0.99929446,0.000049170107,0.00023987392,0.0003486104,0.000023874902,0.000044011205],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003879247,0.0001357172,0.0002954691,0.00006157223,0.0004150328,0.000048133592,0.00032689376,0.000038969487,0.00062201434],"category_scores_gemma":[0.000031342403,0.00014973826,0.000056137316,0.00047261396,0.00009633317,0.00014393065,0.00017132658,0.00020568025,0.00061784114],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002636949,0.0001995725,0.000042989286,0.000027167162,0.000009196171,0.0000013864833,0.00013028362,0.0008490034,0.000014737449,0.998342,0.00014302267,0.00021431001],"study_design_scores_gemma":[0.00032160518,0.000054133627,0.0015706907,0.0000050342687,0.0000060106026,0.000016430367,0.00006973713,0.0012156469,0.000022774617,0.98423684,0.0122578135,0.00022330384],"about_ca_topic_score_codex":0.000008780058,"about_ca_topic_score_gemma":8.004735e-7,"teacher_disagreement_score":0.9120032,"about_ca_system_score_codex":0.00010590948,"about_ca_system_score_gemma":0.000028292514,"threshold_uncertainty_score":0.7941304},"labels":[],"label_agreement":null},{"id":"W4391368157","doi":"10.1080/1350486x.2023.2301354","title":"Robust Risk-Aware Option Hedging","year":2023,"lang":"en","type":"article","venue":"Applied Mathematical Finance","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Toronto","keywords":"Computer science; Actuarial science; Risk analysis (engineering); Econometrics; Economics; Financial economics; Business","score_opus":0.12200367765718867,"score_gpt":0.34473437732558754,"score_spread":0.22273069966839887,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391368157","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17032064,0.000035530513,0.79323345,0.00035061588,0.00018769159,0.0003497381,0.000013973615,0.00031406627,0.035194308],"genre_scores_gemma":[0.9711759,0.00071788504,0.024635363,0.00006347734,0.0001051548,0.00007716771,0.000011616927,0.000024116169,0.003189283],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9977269,0.000042968823,0.00058645185,0.00046581068,0.00085637765,0.00032150175],"domain_scores_gemma":[0.9981004,0.00084971567,0.00026059666,0.0006220864,0.00009887277,0.00006830537],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001974144,0.00014751666,0.0002891193,0.0001905301,0.00023855249,0.00019212018,0.00043956286,0.00010185901,0.00020876642],"category_scores_gemma":[0.0008870506,0.00011166251,0.0000831036,0.0016333481,0.00007465582,0.0001688613,0.00012315933,0.00015742921,0.010480737],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021300762,0.00006632262,0.00058374373,0.000011812764,0.00000803949,0.00001130083,0.00072785356,0.11757675,0.000083763625,0.6538742,0.019737026,0.20729788],"study_design_scores_gemma":[0.00021544633,0.0000140259435,0.0029579836,0.00002098328,0.000010786905,0.000004190239,0.00031731368,0.22413401,0.00027312728,0.7592302,0.0126217585,0.00020014093],"about_ca_topic_score_codex":0.0000014671738,"about_ca_topic_score_gemma":7.6549696e-7,"teacher_disagreement_score":0.8008553,"about_ca_system_score_codex":0.00001885005,"about_ca_system_score_gemma":0.000026678219,"threshold_uncertainty_score":0.9902897},"labels":[],"label_agreement":null},{"id":"W4403943671","doi":"10.1080/1350486x.2024.2410200","title":"A Global-in-Time Neural Network Approach to Dynamic Portfolio Optimization","year":2024,"lang":"en","type":"article","venue":"Applied Mathematical Finance","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Artificial neural network; Computer science; Portfolio; Portfolio optimization; Artificial intelligence; Mathematical optimization; Economics; Financial economics; Mathematics","score_opus":0.012618898137764902,"score_gpt":0.22182597131816403,"score_spread":0.20920707318039913,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403943671","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0019151382,0.001203772,0.89816266,0.0002633515,0.000089132016,0.0006083458,0.0000647068,0.00012978671,0.09756311],"genre_scores_gemma":[0.79833263,0.000048481896,0.1998379,0.0003099299,0.00012482819,0.0008000569,0.00003065836,0.0000470825,0.00046842668],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9981543,0.0000017745189,0.00066082034,0.00065991934,0.00007024054,0.00045297877],"domain_scores_gemma":[0.99938875,0.00006100193,0.00009187489,0.00036152033,0.00001530605,0.000081562015],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00031644956,0.00021250197,0.00045005328,0.000107138585,0.00007230683,0.00015341822,0.00035888446,0.0001258284,0.00011186607],"category_scores_gemma":[0.000052059935,0.00023488388,0.00007971368,0.0015430253,0.000046060533,0.000096264404,0.000108822256,0.00013519888,0.0018012286],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008060719,0.00010466338,0.000020922336,0.000084389336,0.0000070187784,0.0000022378981,0.000066273424,0.091416866,0.0000011503532,0.9062284,0.0005232946,0.0015366877],"study_design_scores_gemma":[0.00009843961,0.000013170703,0.0004349171,0.000042361018,0.0000044902495,0.00000789837,0.000004895548,0.37252396,4.5696487e-7,0.6249611,0.0017033839,0.00020495187],"about_ca_topic_score_codex":0.0000063101015,"about_ca_topic_score_gemma":8.457145e-7,"teacher_disagreement_score":0.7964175,"about_ca_system_score_codex":0.0001402482,"about_ca_system_score_gemma":0.000025453704,"threshold_uncertainty_score":0.998976},"labels":[],"label_agreement":null},{"id":"W4410117844","doi":"10.1080/1350486x.2026.2662658","title":"Multi-Agent Reinforcement Learning for Greenhouse Gas Offset Credit Markets","year":2025,"lang":"en","type":"preprint","venue":"Applied Mathematical Finance","topic":"Banking stability, regulation, efficiency","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Offset (computer science); Reinforcement learning; Greenhouse gas; Reinforcement; Business; Environmental science; Natural resource economics; Monetary economics; Economics; Computer science; Materials science; Artificial intelligence; Geology; Composite material; Operating system","score_opus":0.035124603899856034,"score_gpt":0.2572911741154643,"score_spread":0.2221665702156083,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410117844","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.030588161,0.0011187197,0.9363882,0.00041657724,0.0007726711,0.00341331,0.00026267115,0.0002604176,0.026779285],"genre_scores_gemma":[0.8965199,0.00042969073,0.09260462,0.00011449886,0.00019976137,0.0019459333,0.00019451824,0.000090310314,0.007900752],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9961516,0.000021100446,0.0017312047,0.0013057763,0.00014299621,0.0006473058],"domain_scores_gemma":[0.997078,0.00047340503,0.0009973483,0.001268158,0.00010328592,0.000079796984],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0016124325,0.00052637747,0.0011620383,0.00026067908,0.00026146267,0.00015357272,0.0007635874,0.0005157365,0.0003400016],"category_scores_gemma":[0.00080275966,0.00062086503,0.00036126564,0.0002594297,0.00016272205,0.00006527155,0.0007531277,0.00066573574,0.00034604856],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000061070205,0.00047720558,0.0003252461,0.002477161,0.00008688404,0.0000010266798,0.000707644,0.03437458,0.000006922351,0.95519114,0.0017519107,0.004539189],"study_design_scores_gemma":[0.0011547441,0.00006359011,0.002311955,0.0004232431,0.000047039186,0.0000013407539,0.000027800721,0.34420407,0.00009705547,0.61361593,0.037184272,0.000868936],"about_ca_topic_score_codex":0.000013617306,"about_ca_topic_score_gemma":0.0000031795491,"teacher_disagreement_score":0.86593175,"about_ca_system_score_codex":0.0003651348,"about_ca_system_score_gemma":0.000099671735,"threshold_uncertainty_score":0.99962425},"labels":[],"label_agreement":null},{"id":"W4414299092","doi":"10.1080/1350486x.2025.2548448","title":"Event-Based Limit Order Book Simulation under a Neural Hawkes Process: Application in Market-Making","year":2025,"lang":"en","type":"article","venue":"Applied Mathematical Finance","topic":"Point processes and geometric inequalities","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Mitacs; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Order book; Reinforcement learning; Process (computing); Limit (mathematics); Order (exchange); Artificial neural network; Construct (python library); Event (particle physics)","score_opus":0.0280458450010999,"score_gpt":0.34447845027555657,"score_spread":0.31643260527445666,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414299092","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023879822,0.00037207085,0.9419989,0.0009889768,0.000040378134,0.0011475243,0.0000070188253,0.00017571855,0.031389605],"genre_scores_gemma":[0.9853869,0.000009335037,0.01151313,0.0012172328,0.000030467347,0.00062879926,0.000006226916,0.00003203047,0.0011758838],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.998018,0.00003414526,0.0007553757,0.00043815788,0.00034147667,0.00041282782],"domain_scores_gemma":[0.9973201,0.001816303,0.000235228,0.0004345444,0.00014955045,0.000044275024],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00057974557,0.00027618132,0.00046040004,0.0002960353,0.0001189712,0.00007289156,0.00027548693,0.00016946015,0.00015893472],"category_scores_gemma":[0.0016004186,0.0002523825,0.000068488625,0.001447028,0.00007511511,0.00016584765,0.00006142791,0.00024072707,0.000033917073],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010098463,0.00042570155,0.000058325033,0.0022948303,0.000016647791,0.0000017510415,0.00032272012,0.029264595,0.00003828243,0.9609748,0.00065339427,0.005847933],"study_design_scores_gemma":[0.0005276799,0.000016269174,0.00007751856,0.00034233523,0.000027129287,6.8418166e-7,0.0002591657,0.29516965,0.00024185778,0.701926,0.0011878798,0.00022384374],"about_ca_topic_score_codex":0.000001699669,"about_ca_topic_score_gemma":0.0000058840474,"teacher_disagreement_score":0.9615071,"about_ca_system_score_codex":0.00009208016,"about_ca_system_score_gemma":0.00018213448,"threshold_uncertainty_score":0.99999285},"labels":[],"label_agreement":null},{"id":"W4414409010","doi":"10.1080/1350486x.2025.2544272","title":"Robust Detection of Lead-Lag Relationships in Lagged Multi-Factor Models","year":2025,"lang":"en","type":"article","venue":"Applied Mathematical Finance","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Robustness (evolution); Process (computing); Noise (video); Work (physics)","score_opus":0.1240430626372094,"score_gpt":0.24807041766495222,"score_spread":0.12402735502774281,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414409010","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3601433,0.0005096247,0.62729967,0.000053553285,0.00006750227,0.00029426627,0.000022849037,0.000027469572,0.011581737],"genre_scores_gemma":[0.967637,0.00010310847,0.031790394,0.0000234737,0.000012441416,0.00007665643,0.0000023728364,0.0000156516,0.00033890858],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99835324,0.00001328743,0.0009519438,0.00038604706,0.000044619246,0.0002508344],"domain_scores_gemma":[0.9991443,0.00020432506,0.00022911826,0.00036979085,0.000031090192,0.000021338472],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005777396,0.00015595584,0.0005157394,0.0002505172,0.00008645721,0.000020156018,0.00018470237,0.00020763103,0.00001831642],"category_scores_gemma":[0.00032941156,0.00018273319,0.00008581685,0.00053442526,0.000067504305,0.00015309884,0.000055628498,0.00033475945,0.00010706847],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027571183,0.000196586,0.0014513681,0.00015411027,0.000007356732,3.4870175e-7,0.00049002183,0.0070491536,0.00037571558,0.9881232,0.000009404491,0.0021152063],"study_design_scores_gemma":[0.0004980113,0.000009609847,0.0076349424,0.00008530114,0.0000033730942,1.9396028e-7,0.000047029618,0.37231222,0.0011152521,0.6180416,0.00010765462,0.00014482172],"about_ca_topic_score_codex":0.000040512652,"about_ca_topic_score_gemma":0.0000455928,"teacher_disagreement_score":0.6074937,"about_ca_system_score_codex":0.00009021601,"about_ca_system_score_gemma":0.000024951803,"threshold_uncertainty_score":0.74516433},"labels":[],"label_agreement":null}]}