{"meta":{"query_hash":"95d475f15232","filters":{"venue":"The Journal of Risk Finance"},"cohort_total":32,"direct_labels_cover":0,"predictions_cover":32,"exported":32,"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/95d475f15232","api":"https://metacan.xera.ac/api/v1/cohort?venue=The+Journal+of+Risk+Finance"},"results":[{"id":"W1556042350","doi":"10.1108/jrf-02-2015-0020","title":"The dynamics of risk premium: the case of the Taiwan real estate market","year":2015,"lang":"en","type":"article","venue":"The Journal of Risk Finance","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Francis Xavier University","funders":"","keywords":"Real estate; Volatility (finance); Real estate investment trust; Autoregressive conditional heteroskedasticity; Risk premium; Economics; Financial economics; Capitalization rate; Cost approach; Investment (military); Business; Finance","score_opus":0.015316269298991497,"score_gpt":0.20840717952171664,"score_spread":0.19309091022272515,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1556042350","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":[0.9739139,0.0010448995,0.00040136257,0.0010481217,0.00095030846,0.00015618408,0.00025577823,0.0000040039345,0.022225432],"genre_scores_gemma":[0.9546841,0.04450491,0.00023993787,0.000018078501,0.00013256948,0.0000016597024,4.8097326e-7,0.000024153793,0.00039414136],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9980392,0.00027800072,0.0011990429,0.00012980701,0.00007189592,0.00028203908],"domain_scores_gemma":[0.99415433,0.00082783477,0.003952271,0.00084419624,0.00016883292,0.00005253737],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00785779,0.00016761992,0.000450854,0.00006081781,0.00039864684,0.000050619852,0.0011196587,0.0000800516,0.000016098027],"category_scores_gemma":[0.0010907399,0.00008457288,0.00025570957,0.00027396897,0.00047552065,0.00017236886,0.0001755004,0.00059197017,0.00001139817],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0025961024,0.00042547373,0.58065015,0.00008311844,0.00068483374,0.00008428742,0.02785715,0.040005166,0.000005302849,0.062032137,0.04125149,0.24432482],"study_design_scores_gemma":[0.0048678485,0.000770661,0.30116037,0.0002569121,0.00059047376,0.0023720786,0.01770249,0.27986157,0.00019110017,0.29916307,0.09204894,0.0010144635],"about_ca_topic_score_codex":0.002930417,"about_ca_topic_score_gemma":0.003218309,"teacher_disagreement_score":0.27948976,"about_ca_system_score_codex":0.00015691898,"about_ca_system_score_gemma":0.00012656441,"threshold_uncertainty_score":0.44299334},"labels":[],"label_agreement":null},{"id":"W1566359812","doi":"10.1108/15265940810853904","title":"Reputation entrenchment or risk minimization?","year":2008,"lang":"en","type":"article","venue":"The Journal of Risk Finance","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":10,"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 Saskatchewan","funders":"","keywords":"Agency (philosophy); Asset allocation; Principal–agent problem; Reputation; Economics; Portfolio; Investment strategy; Microeconomics; Investment management; Business; Risk management; Asset (computer security); Originality; Principal (computer security); Actuarial science; Variance (accounting); Finance; Incentive; Computer science; Corporate governance; Accounting","score_opus":0.026344371707031956,"score_gpt":0.2145474210187161,"score_spread":0.18820304931168413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1566359812","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":[0.9806231,0.006348091,0.005411709,0.00046028887,0.0006758383,0.00012506581,0.00007470758,0.000010224134,0.006270927],"genre_scores_gemma":[0.9361357,0.060213037,0.0022152842,0.000108693836,0.00018474618,0.0000023957273,0.0000016458547,0.000008847637,0.0011296158],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988036,0.000060476516,0.0007814281,0.00011609406,0.00006938776,0.00016899743],"domain_scores_gemma":[0.9975955,0.000178204,0.0019059902,0.00021058378,0.000078376666,0.000031330525],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00081558304,0.00011576856,0.00028631202,0.000109376975,0.00030849362,0.000024183833,0.00024844334,0.000048288544,0.00018294732],"category_scores_gemma":[0.00051537884,0.00007851305,0.00010024119,0.00025470566,0.000113474845,0.00034412844,0.000023087743,0.00021898633,0.00007654531],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019833304,0.000848776,0.5164149,0.000049779537,0.00032025258,0.0001368957,0.019951131,0.033880387,0.000016980379,0.27940837,0.124579005,0.022410221],"study_design_scores_gemma":[0.0011258192,0.0004890798,0.783672,0.00004409128,0.00003767661,0.00014373848,0.00022521074,0.0014342507,0.00012325757,0.066408485,0.14606035,0.00023607399],"about_ca_topic_score_codex":0.00015799857,"about_ca_topic_score_gemma":0.000015832937,"teacher_disagreement_score":0.2672571,"about_ca_system_score_codex":0.00005760181,"about_ca_system_score_gemma":0.00006203612,"threshold_uncertainty_score":0.32016692},"labels":[],"label_agreement":null},{"id":"W1965418053","doi":"10.1108/15265940710732350","title":"On the surplus prior to ruin in the perturbed classical risk process","year":2007,"lang":"en","type":"article","venue":"The Journal of Risk Finance","topic":"Probability and Risk Models","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Ruin theory; Mathematics; Brownian motion; First-hitting-time model; Joint probability distribution; Mathematical economics; Type (biology); Risk model; Applied mathematics; Random variable; Argument (complex analysis); Marginal distribution; Econometrics; Statistics","score_opus":0.06567979412222792,"score_gpt":0.37105853075423767,"score_spread":0.30537873663200976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1965418053","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":[0.97394687,0.00049531076,0.010092887,0.014370533,0.00028393834,0.00031422055,0.000010505328,0.000004566642,0.00048117473],"genre_scores_gemma":[0.9977531,0.0004592982,0.00028659886,0.0010847071,0.0001882642,0.0000032728444,4.1718415e-8,0.000007150982,0.00021761023],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9951946,0.0014557893,0.00096403464,0.0002138966,0.0018075807,0.0003641103],"domain_scores_gemma":[0.98234236,0.015516548,0.00090353616,0.0008195341,0.00035038777,0.00006764224],"candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.040378194,0.00015710406,0.00031837486,0.00013938949,0.0004989752,0.00012570554,0.0028462808,0.00008362001,0.000025509205],"category_scores_gemma":[0.016179638,0.000050789346,0.00017398984,0.0011595495,0.00026895103,0.00021108876,0.000088302106,0.001301907,0.000100764904],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00924975,0.0014710475,0.047529574,0.000011164164,0.00006218154,0.00015516895,0.14899516,0.11839463,0.00016812388,0.031690225,0.05479573,0.58747727],"study_design_scores_gemma":[0.0007660506,0.00060043676,0.45961463,0.00011123558,0.00004212758,0.00012267225,0.0045433496,0.004229046,0.0006048088,0.5109926,0.018169567,0.00020350202],"about_ca_topic_score_codex":0.00006235185,"about_ca_topic_score_gemma":0.0006564779,"teacher_disagreement_score":0.5872737,"about_ca_system_score_codex":0.000063394764,"about_ca_system_score_gemma":0.00015907003,"threshold_uncertainty_score":0.9921075},"labels":[],"label_agreement":null},{"id":"W1987359399","doi":"10.1108/15265941011025215","title":"Interest rates, commodity prices, and the cost‐of‐carry model","year":2010,"lang":"en","type":"article","venue":"The Journal of Risk Finance","topic":"Market Dynamics and Volatility","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":"Wilfrid Laurier University","funders":"","keywords":"Spot contract; Interest rate; Economics; Contango; Carry (investment); Commodity; Commodity swap; Futures contract; Monetary economics; Spot market; Convenience yield; Mean reversion; Financial economics; Macroeconomics; Finance; Electricity","score_opus":0.026845201899035526,"score_gpt":0.2337947307893054,"score_spread":0.20694952889026988,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1987359399","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":[0.98434883,0.0023996576,0.010713775,0.0007122611,0.000329864,0.00012647794,0.00015111579,0.0000022508061,0.0012157711],"genre_scores_gemma":[0.99342525,0.005393558,0.0009770759,0.00005892895,0.00006228048,0.0000015741898,6.389266e-7,0.0000079317615,0.00007277439],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990427,0.000052653024,0.00064276735,0.0000926932,0.00003853178,0.00013067828],"domain_scores_gemma":[0.9976454,0.00047875263,0.0013985299,0.00036358184,0.00008144446,0.000032288546],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004132996,0.00009880761,0.00037020014,0.000049193393,0.00013182734,0.000033053446,0.00047369287,0.0000619161,0.000018147302],"category_scores_gemma":[0.00048300286,0.000059040878,0.00010125002,0.00010348799,0.0003407406,0.00013225726,0.00009460154,0.00069100707,0.0000023728176],"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":[0.001219115,0.00017724495,0.25830436,0.000050828785,0.00011839278,0.0000020797818,0.0024794394,0.0014983827,0.000050165603,0.72044545,0.0017653652,0.013889152],"study_design_scores_gemma":[0.0012827639,0.000042240248,0.1295901,0.000022410639,0.000025441313,0.000028047934,0.000040540686,0.6394269,0.000027597272,0.2195174,0.009883734,0.00011282811],"about_ca_topic_score_codex":0.00021038785,"about_ca_topic_score_gemma":0.0003505429,"teacher_disagreement_score":0.63792855,"about_ca_system_score_codex":0.000013945345,"about_ca_system_score_gemma":0.000026934817,"threshold_uncertainty_score":0.30021203},"labels":[],"label_agreement":null},{"id":"W1987714019","doi":"10.1108/15265941011092068","title":"A simple parallel algorithm for large‐scale portfolio problems","year":2010,"lang":"en","type":"article","venue":"The Journal of Risk Finance","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":9,"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 Manitoba; Ontario Tech University","funders":"","keywords":"Portfolio; Selection (genetic algorithm); Computer science; Mathematical optimization; Portfolio optimization; Variance (accounting); Scale (ratio); Quadratic programming; Quadratic equation; Function (biology); Modern portfolio theory; Process (computing); Simple (philosophy); Algorithm; Mathematics; Economics; Machine learning; Finance","score_opus":0.026035616477904144,"score_gpt":0.32328885607647595,"score_spread":0.2972532395985718,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1987714019","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":[0.2970444,0.0005564565,0.7004131,0.0003516051,0.000866911,0.00024804327,0.00008184887,0.000009386148,0.00042821374],"genre_scores_gemma":[0.80593896,0.012086159,0.17746049,0.00023025315,0.0010374375,0.000014106506,0.0000052631376,0.000034226134,0.0031931053],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9977815,0.000127831,0.000887668,0.00015644525,0.0007567594,0.00028979403],"domain_scores_gemma":[0.9961583,0.0009114985,0.0015935793,0.00048706343,0.0007722144,0.00007732244],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006838002,0.00012791484,0.00031512967,0.00014308425,0.00032772365,0.00010518695,0.0009293002,0.00008896353,0.00008856582],"category_scores_gemma":[0.0010488079,0.00006889209,0.0002043997,0.00049205107,0.00007006118,0.00040563318,0.000054225286,0.000435787,0.000036324564],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022516095,0.0002650514,0.02659251,0.0000021503095,0.00003798603,0.000009970976,0.0040304344,0.040071476,0.00021812013,0.001335314,0.15550077,0.77171105],"study_design_scores_gemma":[0.0012821613,0.0002369344,0.033802837,0.000011294703,0.000062919375,0.00017075737,0.00044938954,0.10888669,0.00026239193,0.11410192,0.7405544,0.00017828646],"about_ca_topic_score_codex":0.00002384947,"about_ca_topic_score_gemma":0.00013275146,"teacher_disagreement_score":0.7715328,"about_ca_system_score_codex":0.000008940803,"about_ca_system_score_gemma":0.00011957688,"threshold_uncertainty_score":0.2809338},"labels":[],"label_agreement":null},{"id":"W1988533354","doi":"10.1108/jrf-10-2014-0140","title":"Hedging and debt overhang: a conceptual note","year":2015,"lang":"en","type":"article","venue":"The Journal of Risk Finance","topic":"Risk Management in Financial Firms","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Debt overhang; Economics; Debt; Volatility (finance); Financial economics; Corporate finance; Monetary economics; Internal debt; Finance","score_opus":0.022206835490708232,"score_gpt":0.22996326339542697,"score_spread":0.20775642790471874,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1988533354","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":[0.98647356,0.0025665285,0.004526971,0.0010449617,0.000816595,0.00012186565,0.000001541991,0.000022687176,0.004425294],"genre_scores_gemma":[0.99591917,0.0009851377,0.00067248225,0.00076335855,0.0014385862,0.0000010718632,4.848714e-7,0.000018342293,0.00020137338],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99897045,0.000027743821,0.0003398496,0.00010023733,0.00033600396,0.00022571109],"domain_scores_gemma":[0.9986274,0.00011058215,0.00082368846,0.00019665924,0.00022683304,0.0000148115205],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015539632,0.000140565,0.00022898604,0.00012266399,0.00017032388,0.00012029868,0.0003958414,0.000040172454,0.000009502278],"category_scores_gemma":[0.0006226295,0.0000939609,0.000057724697,0.00032397587,0.00016617014,0.0010501086,0.00020547477,0.0002824611,0.000069225],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018390404,0.0002768232,0.20917048,0.00014989944,0.0001563478,0.0002836779,0.00869918,0.00901925,0.00029257857,0.21283776,0.22285444,0.33442056],"study_design_scores_gemma":[0.0025401488,0.00009712006,0.124229416,0.00023381884,0.0003276343,0.00006439113,0.0019231297,0.0049663917,0.00008785076,0.06252307,0.802565,0.00044203777],"about_ca_topic_score_codex":0.0002666687,"about_ca_topic_score_gemma":0.000041553983,"teacher_disagreement_score":0.57971054,"about_ca_system_score_codex":0.00003172644,"about_ca_system_score_gemma":0.000030126286,"threshold_uncertainty_score":0.38316143},"labels":[],"label_agreement":null},{"id":"W2005292135","doi":"10.1108/15265940610712669","title":"Fuzzy random‐coefficient volatility models with financial applications","year":2006,"lang":"en","type":"article","venue":"The Journal of Risk Finance","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":11,"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 Manitoba","funders":"","keywords":"Kurtosis; Volatility (finance); Fuzzy logic; Econometrics; Fuzzy number; Mathematics; Statistics; Fuzzy set; Computer science; Economics; Artificial intelligence","score_opus":0.04194372600765835,"score_gpt":0.3290481971198192,"score_spread":0.28710447111216086,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2005292135","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":[0.38319856,0.00066859677,0.61215967,0.00015956574,0.00012686895,0.00018945162,0.000013732872,0.000008144888,0.0034754525],"genre_scores_gemma":[0.9553789,0.00006900163,0.043751806,0.00003560561,0.00027583478,0.000009065792,2.3199733e-7,0.000010458261,0.00046909158],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9963512,0.0008556154,0.0009918476,0.00021084984,0.0013351297,0.00025537674],"domain_scores_gemma":[0.9913531,0.005325819,0.0016854202,0.00070076867,0.0008863833,0.00004853247],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.014464843,0.00015409572,0.0004076103,0.00015368547,0.00040900192,0.00007680811,0.0011339319,0.00005640823,0.000015872747],"category_scores_gemma":[0.003046119,0.000076622775,0.00015714296,0.0011346755,0.00025422088,0.0002573043,0.00007910555,0.00043479854,0.000014084377],"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":[0.0034058883,0.00028910817,0.014580926,0.000004754392,0.00001778266,0.000010496038,0.00092399947,0.5979906,0.000082816805,0.010801626,0.014359563,0.35753247],"study_design_scores_gemma":[0.002438854,0.00022502075,0.16125809,0.000052262625,0.00010402126,0.0002327134,0.00010614019,0.057903428,0.00031360236,0.7556925,0.021446547,0.00022684573],"about_ca_topic_score_codex":0.000072504256,"about_ca_topic_score_gemma":0.00007985712,"teacher_disagreement_score":0.74489087,"about_ca_system_score_codex":0.000049652837,"about_ca_system_score_gemma":0.00022229023,"threshold_uncertainty_score":0.5013255},"labels":[],"label_agreement":null},{"id":"W2005374667","doi":"10.1108/jrf-09-2014-0132","title":"Computing value-at-risk using genetic algorithm","year":2015,"lang":"en","type":"article","venue":"The Journal of Risk Finance","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":10,"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 Manitoba","funders":"","keywords":"Value at risk; Computation; Volatility (finance); Selection (genetic algorithm); Computer science; Population; Monte Carlo method; Portfolio; Mathematical optimization; Genetic algorithm; Econometrics; Originality; Risk management; Set (abstract data type); Expected shortfall; Actuarial science; Algorithm; Finance; Economics; Mathematics; Statistics; Machine learning","score_opus":0.07691649418869266,"score_gpt":0.35202347813252555,"score_spread":0.2751069839438329,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2005374667","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":[0.5861306,0.0025388391,0.4105207,0.000054004027,0.00057642604,0.00003983457,0.000006511489,0.0000041063877,0.00012895466],"genre_scores_gemma":[0.7572553,0.008286593,0.23360722,0.000060703485,0.00052445324,1.07540814e-7,2.3554462e-7,0.00001452222,0.00025087703],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9968321,0.0007287623,0.00088517804,0.0001362304,0.0012038426,0.00021391775],"domain_scores_gemma":[0.99562806,0.0008678858,0.0023073358,0.00039348257,0.0007026151,0.00010059675],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0076082335,0.00011914662,0.00028738732,0.00014948408,0.0003526069,0.00009075058,0.0007737675,0.000054263346,0.000011387325],"category_scores_gemma":[0.0018949172,0.000067466746,0.00011593472,0.0006571114,0.00010351406,0.00024040978,0.0001348293,0.00030483337,0.00006728031],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038345865,0.000013626118,0.023329206,1.4107414e-7,0.000007835734,0.000010498212,0.0015012696,0.72081155,0.000006246627,0.000012744918,0.0028401238,0.25142843],"study_design_scores_gemma":[0.00069465756,0.00014386952,0.08985018,0.000027752789,0.00009700301,0.0005696772,0.0005029738,0.87266743,0.00021849603,0.01567173,0.019409202,0.00014702826],"about_ca_topic_score_codex":0.00016560503,"about_ca_topic_score_gemma":0.0000059608765,"teacher_disagreement_score":0.25128138,"about_ca_system_score_codex":0.00007768727,"about_ca_system_score_gemma":0.00016942744,"threshold_uncertainty_score":0.2751214},"labels":[],"label_agreement":null},{"id":"W2042234687","doi":"10.1108/15265940910938233","title":"Corporate risk management and investment decisions","year":2009,"lang":"en","type":"article","venue":"The Journal of Risk Finance","topic":"Capital Investment and Risk Analysis","field":"Economics, Econometrics and Finance","cited_by":21,"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 Saskatchewan","funders":"","keywords":"Downside risk; Capital budgeting; Investment decisions; Capital allocation line; Investment (military); Risk management; Corporate finance; Venture capital; Economics; Financial risk; Investment strategy; Economic capital; Actuarial science; Business; Finance; Expected utility hypothesis; Financial risk management; Risk analysis (engineering); Microeconomics; Financial economics; Portfolio","score_opus":0.030700412527353158,"score_gpt":0.20999086053740107,"score_spread":0.1792904480100479,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2042234687","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":[0.9192379,0.0754955,0.0019290181,0.00049583375,0.00017550954,0.00009641692,0.000041361214,0.000006074017,0.0025223978],"genre_scores_gemma":[0.73821574,0.25710952,0.0035395105,0.00035214185,0.00006453812,8.213949e-7,8.2047546e-7,0.000006545731,0.00071037194],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989212,0.00004393173,0.0006580794,0.00013565988,0.00006823352,0.00017288241],"domain_scores_gemma":[0.997048,0.0001094683,0.0024585736,0.00028111253,0.000037615304,0.000065192056],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011906959,0.0001280022,0.0003354622,0.00020531967,0.0002189084,0.00004842871,0.00027300074,0.000038664173,0.000025970297],"category_scores_gemma":[0.000116670344,0.0000893796,0.0001411123,0.0002998211,0.00008594923,0.00018009443,0.00004283707,0.00024229064,0.000083871455],"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":[0.000106537,0.00016778926,0.03585843,0.0000031192444,0.0002135724,0.00002816234,0.0010982017,0.001811096,0.0000035791263,0.9333188,0.009501414,0.017889323],"study_design_scores_gemma":[0.0004967928,0.00016752063,0.28439185,0.000024285624,0.0001098392,0.000019412493,0.00009789772,0.0012685324,0.000021838103,0.69720054,0.016083617,0.00011789899],"about_ca_topic_score_codex":0.00005259103,"about_ca_topic_score_gemma":0.00001332316,"teacher_disagreement_score":0.24853343,"about_ca_system_score_codex":0.00004341368,"about_ca_system_score_gemma":0.000007152479,"threshold_uncertainty_score":0.36447945},"labels":[],"label_agreement":null},{"id":"W2047503222","doi":"10.1108/15265941011092077","title":"Option pricing for jump diffussion model with random volatility","year":2010,"lang":"en","type":"article","venue":"The Journal of Risk Finance","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Kurtosis; Volatility (finance); Jump diffusion; Volatility smile; Stochastic volatility; Econometrics; Implied volatility; Valuation of options; SABR volatility model; Jump; Forward volatility; Economics; Financial models with long-tailed distributions and volatility clustering; Mathematics; Statistics; Physics","score_opus":0.01453778441759833,"score_gpt":0.2182805493499261,"score_spread":0.20374276493232776,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2047503222","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":[0.3491364,0.00039396127,0.649828,0.00021354367,0.00014485247,0.0001520992,0.000044788943,0.0000044183394,0.00008192835],"genre_scores_gemma":[0.9708437,0.00033199458,0.028470537,0.000035376335,0.00022130455,0.000017416227,0.0000010905065,0.0000126985915,0.0000659386],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99919975,0.0000037143288,0.00048301835,0.00011974832,0.000042792446,0.00015098673],"domain_scores_gemma":[0.9982778,0.00019596981,0.0010560992,0.00022854371,0.00020978336,0.000031830692],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009914163,0.00009619509,0.00027364143,0.00006218775,0.00024939148,0.000021635622,0.00026441988,0.00005957914,0.000002719156],"category_scores_gemma":[0.00051144394,0.000063417865,0.000084577405,0.00016348329,0.000065411376,0.00017354591,0.000019255664,0.00032231899,0.00000635627],"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":[0.0018326414,0.00026161093,0.006443446,0.000045890876,0.0000424311,4.651491e-7,0.0015364356,0.016290417,0.0006786711,0.95472544,0.00037626817,0.017766276],"study_design_scores_gemma":[0.0018996976,0.00013681826,0.024842639,0.000030054916,0.00003433442,0.000012565655,0.00002633317,0.27692407,0.00020287765,0.6918036,0.003947396,0.00013964664],"about_ca_topic_score_codex":0.000034329933,"about_ca_topic_score_gemma":0.000030931464,"teacher_disagreement_score":0.62170726,"about_ca_system_score_codex":0.000021960921,"about_ca_system_score_gemma":0.000041718144,"threshold_uncertainty_score":0.25861055},"labels":[],"label_agreement":null},{"id":"W2055228949","doi":"10.1108/15265940510585789","title":"Diffusion models of insurer net worth: can one dimension suffice?","year":2005,"lang":"en","type":"article","venue":"The Journal of Risk Finance","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Laplace transform; Dimension (graph theory); Diffusion; Homogeneous; Computer science; Dimensional modeling; Distribution (mathematics); Mathematical optimization; Value (mathematics); Mathematics; Mathematical analysis","score_opus":0.0183361005300694,"score_gpt":0.25575389266887716,"score_spread":0.23741779213880776,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2055228949","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":[0.9923423,0.002533754,0.0008517292,0.0013771737,0.0003539665,0.00019922576,0.0000141521705,0.000013686155,0.0023140311],"genre_scores_gemma":[0.97273165,0.025397982,0.0011576767,0.00012335429,0.00034007622,0.0000013615391,5.779776e-7,0.000012928576,0.00023439438],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9975184,0.00048255434,0.00061629934,0.0001238014,0.00093621353,0.00032271424],"domain_scores_gemma":[0.99796915,0.00018700221,0.001130191,0.00032839415,0.00031732052,0.00006795167],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003007204,0.00013808256,0.0003311359,0.00014348244,0.00043708013,0.000024792434,0.00059429556,0.00007941691,0.000027484135],"category_scores_gemma":[0.000114249255,0.00009935316,0.00016789405,0.0005091921,0.00034788094,0.000324785,0.00008251311,0.0003769216,0.0000062688346],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013561491,0.0028283522,0.31305966,0.00008292061,0.00043357437,0.000039866456,0.1358631,0.18502405,0.0011466803,0.06864025,0.012905701,0.2786197],"study_design_scores_gemma":[0.0015065949,0.00028093506,0.9346858,0.0003584323,0.00032237492,0.000007538091,0.0024287002,0.0024371678,0.00049285986,0.018246561,0.038830448,0.0004025771],"about_ca_topic_score_codex":0.0031349452,"about_ca_topic_score_gemma":0.0067753796,"teacher_disagreement_score":0.62162614,"about_ca_system_score_codex":0.00008290086,"about_ca_system_score_gemma":0.00010045402,"threshold_uncertainty_score":0.47391203},"labels":[],"label_agreement":null},{"id":"W2068715670","doi":"10.1108/15265940610712678","title":"Financial applications of ARMA models with GARCH errors","year":2006,"lang":"en","type":"article","venue":"The Journal of Risk Finance","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":14,"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 Manitoba","funders":"","keywords":"Autoregressive conditional heteroskedasticity; Kurtosis; Heteroscedasticity; Econometrics; Autoregressive–moving-average model; Economics; Series (stratigraphy); Mathematics; Finance; Autoregressive model; Volatility (finance); Statistics","score_opus":0.017708001537044896,"score_gpt":0.20579079277231344,"score_spread":0.18808279123526855,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2068715670","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":[0.6385877,0.0056095263,0.35413793,0.00012623888,0.000072146344,0.0001407491,0.00007622772,0.0000054402276,0.001244036],"genre_scores_gemma":[0.9913886,0.0019231406,0.0062765777,0.000023279556,0.00020317755,0.0000075873486,0.000001526948,0.000017650182,0.00015842059],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99850214,0.00003027939,0.0009889178,0.00014794656,0.00009829303,0.00023243327],"domain_scores_gemma":[0.997738,0.0001308126,0.0015763479,0.00034404345,0.00018722001,0.000023558112],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012216596,0.00013996038,0.0004481199,0.00016854359,0.00017092603,0.0000133399235,0.00044200887,0.000075275675,0.000011422774],"category_scores_gemma":[0.00006999758,0.00010749559,0.00013787264,0.0004240768,0.00015392095,0.00026122734,0.000034741573,0.0003322214,0.00001214133],"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":[0.00068464514,0.00041302887,0.059036613,0.000059038866,0.000046285775,0.000004841815,0.0017534328,0.34419614,0.000045700057,0.5798197,0.0017473086,0.012193309],"study_design_scores_gemma":[0.0013070063,0.00033199295,0.1051164,0.0000974959,0.00006759309,0.00004271736,0.000085980915,0.048390776,0.00045778803,0.8251795,0.018584061,0.0003386455],"about_ca_topic_score_codex":0.00086552155,"about_ca_topic_score_gemma":0.00020429268,"teacher_disagreement_score":0.35280094,"about_ca_system_score_codex":0.00004532472,"about_ca_system_score_gemma":0.00008822459,"threshold_uncertainty_score":0.43835428},"labels":[],"label_agreement":null},{"id":"W2076026081","doi":"10.1108/15265940610688982","title":"Option pricing for some stochastic volatility models","year":2006,"lang":"en","type":"article","venue":"The Journal of Risk Finance","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":15,"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 Manitoba","funders":"","keywords":"Kurtosis; Heteroscedasticity; Autoregressive conditional heteroskedasticity; Autoregressive model; Stochastic volatility; Valuation of options; Econometrics; Volatility (finance); Economics; Implied volatility; Mathematics; Statistics","score_opus":0.03031639442665071,"score_gpt":0.2229074650268448,"score_spread":0.1925910706001941,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2076026081","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":[0.48572433,0.0035976977,0.5101101,0.00008594161,0.00023743414,0.00012124904,0.00005820311,0.000006069825,0.0000589626],"genre_scores_gemma":[0.99380946,0.00068814267,0.004897129,0.000030218873,0.00044623355,0.000004857301,0.0000020140972,0.000018510695,0.000103411905],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9984743,0.000028276238,0.0010055449,0.00016086544,0.00006545535,0.00026553418],"domain_scores_gemma":[0.9979785,0.00028556935,0.0013265839,0.0002551693,0.00012809031,0.00002610445],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022571238,0.00013891618,0.00040812182,0.00012108817,0.00026359883,0.000032652526,0.0002967263,0.00006866512,0.000004571734],"category_scores_gemma":[0.0002936317,0.00011734279,0.00019890514,0.0001579126,0.000057360663,0.00059110834,0.000028521119,0.0002914358,0.0000135209875],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002803879,0.000102794365,0.003422551,0.000023494445,0.000018045983,6.8957337e-7,0.0006259357,0.6611163,0.000026571815,0.32969162,0.0003331874,0.0043584],"study_design_scores_gemma":[0.0003533892,0.00005988995,0.011012368,0.000023909814,0.000014736081,0.000004756897,0.000015289968,0.46297333,0.00002860252,0.5247906,0.0006376129,0.00008556684],"about_ca_topic_score_codex":0.0004478315,"about_ca_topic_score_gemma":0.000035902965,"teacher_disagreement_score":0.50808513,"about_ca_system_score_codex":0.00010390251,"about_ca_system_score_gemma":0.00003750918,"threshold_uncertainty_score":0.47851},"labels":[],"label_agreement":null},{"id":"W2080897276","doi":"10.1108/15265941111100030","title":"Airfare price insurance: a real option model","year":2010,"lang":"en","type":"article","venue":"The Journal of Risk Finance","topic":"Aviation Industry Analysis and Trends","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":"Ontario Tech University","funders":"","keywords":"Ticket; Volatility (finance); Revenue; Strike price; Economics; Liberian dollar; Luck; Business; Price discrimination; Actuarial science; Financial economics; Microeconomics; Finance","score_opus":0.020187853613061954,"score_gpt":0.22586801878311757,"score_spread":0.2056801651700556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2080897276","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":[0.9739437,0.0005947273,0.018671054,0.000591674,0.00032960557,0.000031410356,0.00008580298,0.000006649379,0.005745339],"genre_scores_gemma":[0.9936096,0.0035137015,0.001839152,0.000044171862,0.0002324213,0.0000014476392,0.0000013926923,0.000009839688,0.00074828713],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990355,0.000021410444,0.00063092663,0.00010385742,0.00006244172,0.00014589001],"domain_scores_gemma":[0.9979983,0.00006394723,0.0015197734,0.00027400808,0.00010603162,0.000037960872],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011923291,0.000094834446,0.00026545604,0.00011405816,0.00017819318,0.00003218414,0.00032868155,0.0000996461,0.00008244632],"category_scores_gemma":[0.00016389792,0.00007342049,0.00013826767,0.00029046735,0.00005343873,0.0002863911,0.000024151255,0.00069089537,0.00007121756],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017783044,0.00024826944,0.4348459,0.00001162915,0.00015207642,0.000007550975,0.0024654095,0.15022339,0.0002551479,0.3960829,0.0038005167,0.011729386],"study_design_scores_gemma":[0.00095656875,0.00008062622,0.8286205,0.000024859586,0.00004784885,0.00006246851,0.00009997004,0.072757415,0.0001751361,0.076510556,0.020386538,0.0002775122],"about_ca_topic_score_codex":0.000070612725,"about_ca_topic_score_gemma":0.000029286892,"teacher_disagreement_score":0.3937746,"about_ca_system_score_codex":0.000027681059,"about_ca_system_score_gemma":0.000029081742,"threshold_uncertainty_score":0.30016348},"labels":[],"label_agreement":null},{"id":"W2087241853","doi":"10.1108/15265940810853931","title":"Asian options versus vanilla options: a boundary analysis","year":2008,"lang":"en","type":"article","venue":"The Journal of Risk 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":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Saint Mary's University","funders":"","keywords":"Asian option; Exotic option; Valuation of options; Dividend; Economics; Dividend yield; Financial economics; Stock (firearms); Put option; Interest rate; Strike price; Binomial options pricing model; Black–Scholes model; Volatility (finance); Non-qualified stock option; Option value; Originality; Econometrics; Restricted stock; Microeconomics; Dividend policy; Monetary economics; Finance; Stock market","score_opus":0.02867355593061617,"score_gpt":0.23801212013255724,"score_spread":0.20933856420194108,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2087241853","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":[0.18285434,0.02712476,0.78608674,0.0010314247,0.00046047592,0.000113120506,0.00022436077,0.000016351243,0.002088446],"genre_scores_gemma":[0.9726453,0.016802657,0.010067477,0.000051829335,0.00024996337,0.000010970874,0.0000036498404,0.000013991319,0.00015420072],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99882656,0.000013700503,0.0007252125,0.00015257951,0.00007188659,0.00021004859],"domain_scores_gemma":[0.9981091,0.00017808832,0.0011455334,0.00037278238,0.0001397352,0.000054766086],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006177881,0.00012536753,0.00040511653,0.0002763201,0.0006232897,0.000028602508,0.0004646068,0.00006521334,0.000060626568],"category_scores_gemma":[0.00027707688,0.000107794396,0.00029041874,0.001210922,0.00018374712,0.00020542968,0.00004209925,0.00031907592,0.00020058636],"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":[0.00033140637,0.00030632943,0.0060832216,0.00000889742,0.0006391807,0.000015917401,0.002806504,0.010764103,0.000014771034,0.9725776,0.0018490845,0.004602994],"study_design_scores_gemma":[0.002385773,0.00047430486,0.43251637,0.00003240482,0.00085022784,0.00026497638,0.00047261076,0.0035083275,0.000041490242,0.41859367,0.14025085,0.0006090051],"about_ca_topic_score_codex":0.0001193913,"about_ca_topic_score_gemma":0.00005452679,"teacher_disagreement_score":0.7897909,"about_ca_system_score_codex":0.000080880825,"about_ca_system_score_gemma":0.00008188686,"threshold_uncertainty_score":0.47939038},"labels":[],"label_agreement":null},{"id":"W2089822100","doi":"10.1108/jrf-05-2014-0072","title":"Measuring infrastructure investment option value","year":2015,"lang":"en","type":"article","venue":"The Journal of Risk Finance","topic":"Capital Investment and Risk Analysis","field":"Economics, Econometrics and Finance","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Finance; Financial risk; Financial engineering; Investment (military); Financial modeling; Project finance; Value at risk; Option value; Risk management; Actuarial science; Value (mathematics); Investment strategy; Economics; Risk analysis (engineering); Business; Computer science; Microeconomics; Market liquidity","score_opus":0.04373291177427216,"score_gpt":0.20885608664319774,"score_spread":0.16512317486892558,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2089822100","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":[0.9508576,0.04420055,0.0023582743,0.00045221488,0.0005580755,0.000062527295,0.000018003142,0.000006982602,0.0014857919],"genre_scores_gemma":[0.9812083,0.015929358,0.0020721308,0.00021965172,0.00027354434,0.0000010853147,0.0000011491263,0.000012313764,0.000282467],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989827,0.00005134391,0.00060488575,0.000100926474,0.0000973481,0.0001627431],"domain_scores_gemma":[0.99839485,0.000045119734,0.0011539408,0.00023681582,0.00009046296,0.00007880576],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015495995,0.00011625644,0.0003128978,0.00015877781,0.000113424394,0.00003969438,0.00032063754,0.000055654666,0.000019123849],"category_scores_gemma":[0.00021948713,0.00008231615,0.00015509575,0.0002607724,0.000071458635,0.00028863692,0.000045146877,0.00028552022,0.000115181276],"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":[0.00012524759,0.000086440436,0.029469144,0.000008686135,0.0002038291,0.0000099868475,0.005305097,0.077343665,0.000035331464,0.8745033,0.011245414,0.0016638527],"study_design_scores_gemma":[0.0010755014,0.00021255178,0.0826489,0.00004002647,0.000104605875,0.00006872154,0.0004662135,0.012002142,0.00039024255,0.84832424,0.05441877,0.00024807907],"about_ca_topic_score_codex":0.00015732592,"about_ca_topic_score_gemma":0.000011143474,"teacher_disagreement_score":0.065341525,"about_ca_system_score_codex":0.00015444754,"about_ca_system_score_gemma":0.000038313523,"threshold_uncertainty_score":0.33567554},"labels":[],"label_agreement":null},{"id":"W2117390786","doi":"10.1108/eb043499","title":"Dimension Reduction in the Computation of Value‐at‐Risk","year":2002,"lang":"en","type":"article","venue":"The Journal of Risk Finance","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":12,"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":"Value at risk; Portfolio; Dimensionality reduction; Computation; Dimension (graph theory); Econometrics; Order (exchange); Economics; Reduction (mathematics); Curse of dimensionality; Value (mathematics); Financial economics; Risk management; Computer science; Mathematics; Finance; Statistics; Algorithm","score_opus":0.04901928401463922,"score_gpt":0.32076507495587575,"score_spread":0.2717457909412365,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2117390786","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":[0.9850629,0.0021238634,0.011408962,0.0006176113,0.00036440918,0.000089602196,0.0000037996062,0.000002173518,0.00032667888],"genre_scores_gemma":[0.9742679,0.0241115,0.0013836179,0.00002368616,0.00008442497,4.1146717e-7,2.7786314e-7,0.000004170857,0.0001239846],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9971178,0.00097213325,0.0008077027,0.000091710426,0.00090717955,0.00010348108],"domain_scores_gemma":[0.9965324,0.00087805785,0.002001399,0.00026716237,0.0003050259,0.00001599259],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0062949928,0.00007469736,0.00019303859,0.00017026388,0.00018926765,0.000027177672,0.00044342986,0.000042446805,0.000020102383],"category_scores_gemma":[0.0010227041,0.00003521351,0.00008764166,0.00083737524,0.00009543737,0.0002733443,0.000029452438,0.0002568752,0.000028972812],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015637382,0.00009001294,0.01633932,7.219231e-7,0.000006251414,0.0000033778836,0.010450871,0.7987426,0.00016463705,0.00019799428,0.012641352,0.16120648],"study_design_scores_gemma":[0.001446369,0.00055065745,0.64872086,0.00010712157,0.00012686104,0.0005053181,0.0027568263,0.28165373,0.0018246828,0.052570254,0.00954695,0.00019035501],"about_ca_topic_score_codex":0.00007495451,"about_ca_topic_score_gemma":0.000014063838,"teacher_disagreement_score":0.63238156,"about_ca_system_score_codex":0.000029353188,"about_ca_system_score_gemma":0.000015172996,"threshold_uncertainty_score":0.21817313},"labels":[],"label_agreement":null},{"id":"W2210828402","doi":"10.1108/jrf-01-2015-0004","title":"Does R&amp;D create or resolve uncertainty?","year":2015,"lang":"en","type":"article","venue":"The Journal of Risk Finance","topic":"Capital Investment and Risk Analysis","field":"Economics, Econometrics and Finance","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lakehead University; Simon Fraser University","funders":"","keywords":"Endogeneity; Shadow (psychology); Economics; Value (mathematics); Volatility (finance); Interpretation (philosophy); Econometrics; Computer science","score_opus":0.05516057330603533,"score_gpt":0.24772207545186847,"score_spread":0.19256150214583315,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2210828402","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":[0.9566783,0.037194833,0.0012905382,0.0017734106,0.0009334079,0.000090718604,0.00009827416,0.000012350117,0.0019282001],"genre_scores_gemma":[0.9167251,0.06699232,0.002140204,0.00024611596,0.00052383676,0.0000022658032,0.000002923932,0.000022971246,0.013344249],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.998771,0.000054666714,0.0007374211,0.0001301797,0.000085940694,0.00022077645],"domain_scores_gemma":[0.9979715,0.00017235868,0.0012871451,0.00035318043,0.00012315759,0.00009269224],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018566408,0.00013811525,0.0004430449,0.00016346446,0.0001248317,0.00005249272,0.0004498309,0.000061011928,0.0001442109],"category_scores_gemma":[0.0005157544,0.000063320185,0.00020451918,0.00034615735,0.00012427753,0.0002514651,0.00005401349,0.00028700934,0.0003484666],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0056131575,0.00096956926,0.1643061,0.00005828706,0.001666027,0.00017658487,0.042840898,0.052917052,0.000054008196,0.48007143,0.23884171,0.012485169],"study_design_scores_gemma":[0.0016877685,0.0003711429,0.013524203,0.000060853683,0.0001653538,0.00006381201,0.0011103901,0.0023381985,0.00013061287,0.36533868,0.61482894,0.00038003156],"about_ca_topic_score_codex":0.0009072285,"about_ca_topic_score_gemma":0.00047601198,"teacher_disagreement_score":0.37598726,"about_ca_system_score_codex":0.000097399075,"about_ca_system_score_gemma":0.00005230684,"threshold_uncertainty_score":0.44789493},"labels":[],"label_agreement":null},{"id":"W2598194679","doi":"10.1108/jrf-11-2016-0145","title":"Estimates and inferences in accounting panel data sets: comparing approaches","year":2017,"lang":"en","type":"article","venue":"The Journal of Risk Finance","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":5,"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":"Econometrics; Monte Carlo method; Statistics; Regression; Regression analysis; Value (mathematics); Standard error; Panel data; Accounting; Economics; Mathematics","score_opus":0.3815111676549715,"score_gpt":0.28906216763312204,"score_spread":0.09244900002184947,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2598194679","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":[0.9926496,0.0051339203,0.00040006783,0.00047997152,0.00014608419,0.000044775727,0.000066317996,0.0000023962832,0.0010768423],"genre_scores_gemma":[0.9930388,0.0053568208,0.001460403,0.000026033696,0.00009368137,4.6530513e-7,0.0000017552264,0.0000071055942,0.000014950833],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990574,0.000017308172,0.000563745,0.00014122555,0.000021716232,0.00019857158],"domain_scores_gemma":[0.99755937,0.0001913886,0.0016063,0.0006102094,0.000005659123,0.000027081844],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023366297,0.00010356048,0.00038976036,0.000089496825,0.0002961676,0.00018827952,0.0010491096,0.00004102709,0.000010525368],"category_scores_gemma":[0.000629843,0.00008235752,0.000027677643,0.000030076893,0.00013906231,0.0011355832,0.00026013964,0.0002869995,0.000019467248],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027602962,0.000016366545,0.9863206,0.000011121613,0.000023351451,0.0000018693765,0.0010486296,0.0041501946,4.9676754e-7,0.0014377636,0.00016701485,0.0067949733],"study_design_scores_gemma":[0.00033279948,0.000018048286,0.8242388,0.000047475,0.000009148963,0.000028964545,0.000116976735,0.15320171,0.0000062409604,0.021094518,0.00081184955,0.00009348372],"about_ca_topic_score_codex":0.0020947466,"about_ca_topic_score_gemma":0.00029115917,"teacher_disagreement_score":0.16208184,"about_ca_system_score_codex":0.000021511765,"about_ca_system_score_gemma":0.000012459289,"threshold_uncertainty_score":0.33584422},"labels":[],"label_agreement":null},{"id":"W2763446786","doi":"10.1108/jrf-09-2016-0125","title":"Bond valuation for generalized Langevin processes with integrated Lévy noise","year":2017,"lang":"en","type":"article","venue":"The Journal of Risk Finance","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":0,"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 Manitoba","funders":"","keywords":"Vasicek model; Bond valuation; Zero-coupon bond; Stochastic differential equation; Bond; Interest rate; Short-rate model; Bond market; Mathematical economics; Economics; Econometrics; Applied mathematics; Mathematics; Finance","score_opus":0.04054590372521309,"score_gpt":0.2582658565617088,"score_spread":0.2177199528364957,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2763446786","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":[0.19219019,0.0042841216,0.80133146,0.0011172715,0.00015215535,0.0002687806,0.00020538965,0.000007306866,0.00044330556],"genre_scores_gemma":[0.9781821,0.0031683743,0.018014327,0.00007573595,0.00026913706,0.000046235054,0.0000049248692,0.000020364621,0.00021884547],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.999237,0.0000044621734,0.00043370068,0.00012306139,0.000049094953,0.00015265762],"domain_scores_gemma":[0.9971119,0.00016564487,0.0020013656,0.00034220333,0.0003513304,0.000027550173],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00079071015,0.00010835002,0.000290782,0.00005963294,0.00050390733,0.000086783315,0.00054323726,0.00004653748,0.000004851502],"category_scores_gemma":[0.0013767172,0.00007298748,0.000058469082,0.00013050457,0.00009759387,0.00026306667,0.000024183737,0.000143053,0.000018861538],"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":[0.001700906,0.0003581303,0.020899361,0.00026744007,0.00018700123,0.0000040250693,0.0030239592,0.0019407475,0.00015837031,0.9332201,0.0057658134,0.032474153],"study_design_scores_gemma":[0.0032213207,0.0005622378,0.123822294,0.0002274596,0.00016982616,0.000051636634,0.00014815303,0.0027809492,0.0008744424,0.8002128,0.06752782,0.00040103594],"about_ca_topic_score_codex":0.00019625977,"about_ca_topic_score_gemma":0.0001802194,"teacher_disagreement_score":0.78599185,"about_ca_system_score_codex":0.000035605983,"about_ca_system_score_gemma":0.00013214548,"threshold_uncertainty_score":0.38756984},"labels":[],"label_agreement":null},{"id":"W2899277624","doi":"10.1108/jrf-07-2017-0114","title":"A multi-factor HJM and PCA approach to risk management of VIX futures","year":2018,"lang":"en","type":"article","venue":"The Journal of Risk Finance","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Surrey Place Centre; Université Laval","funders":"","keywords":"Futures contract; Heath–Jarrow–Morton framework; Econometrics; Volatility (finance); Economics; Portfolio; Financial economics","score_opus":0.02427175960567294,"score_gpt":0.2326155325036286,"score_spread":0.20834377289795566,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2899277624","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":[0.3539975,0.0045974236,0.6399516,0.00008932836,0.0001551883,0.00016007139,0.00015544324,0.0000039878237,0.00088947744],"genre_scores_gemma":[0.92561454,0.0051649287,0.06889131,0.000048106616,0.00019576478,0.000008364775,3.295077e-7,0.000011724423,0.0000649304],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99908644,0.00000840862,0.0005416567,0.00015060008,0.000050810602,0.00016208699],"domain_scores_gemma":[0.99850184,0.000058185706,0.0010314628,0.00026287712,0.000098520155,0.000047146314],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005556517,0.00010889051,0.00030057685,0.00010291227,0.00019191051,0.00001723373,0.00036722413,0.00004492316,0.0000073210053],"category_scores_gemma":[0.00009348719,0.00008417982,0.000066242974,0.00030660184,0.00011748527,0.0000824984,0.000083935054,0.0001699553,0.000032308573],"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":[0.0006003691,0.0008674024,0.025073431,0.00019676353,0.00037844785,0.0000030195204,0.015499999,0.00076510845,0.00008516616,0.830739,0.0020498775,0.12374139],"study_design_scores_gemma":[0.0012428522,0.00041014233,0.85861844,0.00008931546,0.00008354569,0.000027358199,0.00062594883,0.0023913702,0.00019025539,0.11117529,0.024860797,0.00028467277],"about_ca_topic_score_codex":0.000114532304,"about_ca_topic_score_gemma":0.000016915881,"teacher_disagreement_score":0.833545,"about_ca_system_score_codex":0.000022422528,"about_ca_system_score_gemma":0.0000114577815,"threshold_uncertainty_score":0.34327534},"labels":[],"label_agreement":null},{"id":"W2958837228","doi":"10.1108/jrf-11-2018-0172","title":"Asset sales, recourse and investor reactions to initial securitizations","year":2019,"lang":"en","type":"article","venue":"The Journal of Risk Finance","topic":"Banking stability, regulation, efficiency","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":"Bank of Canada","funders":"","keywords":"Securitization; Business; Leverage (statistics); Structured finance; Issuer; Equity (law); Off-balance-sheet; Stock (firearms); Asset (computer security); Valuation (finance); Finance; Financial economics; Economics; Financial crisis","score_opus":0.019434468750864513,"score_gpt":0.24511077706209672,"score_spread":0.2256763083112322,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2958837228","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":[0.9912348,0.0018088853,0.0038940026,0.0012962207,0.00059230166,0.00014981761,0.00012328684,0.000008739369,0.0008919936],"genre_scores_gemma":[0.9965669,0.001206505,0.0017151793,0.00009945688,0.0001360271,0.0000018437161,0.0000021032154,0.000013477378,0.0002585237],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99902076,0.000055384873,0.00058303267,0.00013603357,0.000055150478,0.0001496696],"domain_scores_gemma":[0.9985727,0.00024709036,0.00073111156,0.00029563476,0.000106674044,0.00004679811],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014525843,0.00008878045,0.00023310244,0.00017414725,0.00015605192,0.000039128074,0.00021964317,0.000053416574,0.00007089902],"category_scores_gemma":[0.0005830596,0.00008041577,0.00005404963,0.00034873886,0.00007426837,0.00027067686,0.000035853478,0.00024385565,0.0001454415],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015969158,0.00040649148,0.59753466,0.00006530075,0.000088880086,0.000004630306,0.012902282,0.021003813,0.0001422967,0.3504672,0.009772099,0.007452664],"study_design_scores_gemma":[0.0004895163,0.0001885634,0.8234941,0.00006493144,0.000019757694,0.00009351091,0.00014685918,0.0014705583,0.000037331152,0.07040221,0.103400506,0.00019216085],"about_ca_topic_score_codex":0.00009416279,"about_ca_topic_score_gemma":0.000057037814,"teacher_disagreement_score":0.28006497,"about_ca_system_score_codex":0.00007363065,"about_ca_system_score_gemma":0.0000485345,"threshold_uncertainty_score":0.32792598},"labels":[],"label_agreement":null},{"id":"W3122868937","doi":"10.1108/15265940610648571","title":"Empirical study of value‐at‐risk and expected shortfall models with heavy tails","year":2006,"lang":"en","type":"article","venue":"The Journal of Risk Finance","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":73,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Econometrics; Economics; Value at risk; Generalized Pareto distribution; Extreme value theory; Liberian dollar; Us dollar; Empirical research; Gaussian; Value (mathematics); Risk measure; Financial economics; Risk management; Mathematics; Statistics; Finance; Exchange rate","score_opus":0.029551705364539632,"score_gpt":0.23411761421743907,"score_spread":0.20456590885289944,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3122868937","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":[0.9670556,0.0075796605,0.024619507,0.0000703947,0.00008560831,0.00021043404,0.00006322001,0.000008174945,0.000307385],"genre_scores_gemma":[0.99494314,0.003053659,0.0017795567,0.000015956124,0.00010527287,0.0000030562724,7.291338e-7,0.000022618846,0.00007597992],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981216,0.00010546811,0.001149454,0.00023292408,0.00013042495,0.00026011004],"domain_scores_gemma":[0.99758965,0.00022808836,0.0016239024,0.00037068783,0.00014219286,0.00004545195],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015135497,0.0001924627,0.0006740317,0.000162933,0.00024231814,0.000024672396,0.00030130273,0.000082085244,0.000007467498],"category_scores_gemma":[0.000116898074,0.00014053413,0.00009794877,0.00031370312,0.00012181316,0.00028399055,0.000076982564,0.00042816153,0.0000039188385],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00096501986,0.00057761534,0.8722047,0.000011361123,0.000058707257,0.000008624747,0.0055561326,0.11619372,0.000008433758,0.003038761,0.000346601,0.0010302981],"study_design_scores_gemma":[0.002610092,0.001580554,0.8531495,0.0000666376,0.00012079705,0.00004964007,0.00068507466,0.06918352,0.00011484013,0.07127603,0.00083070644,0.00033265096],"about_ca_topic_score_codex":0.0024771595,"about_ca_topic_score_gemma":0.0006748478,"teacher_disagreement_score":0.068237275,"about_ca_system_score_codex":0.00007264894,"about_ca_system_score_gemma":0.000037365367,"threshold_uncertainty_score":0.57308155},"labels":[],"label_agreement":null},{"id":"W3125885382","doi":"10.1108/eb043490","title":"The Impact of Liquidity Risk on the Prices of Swaps with Default Risk","year":2002,"lang":"en","type":"article","venue":"The Journal of Risk Finance","topic":"Credit Risk and Financial Regulations","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":"Saint Mary's University","funders":"","keywords":"Market liquidity; Interest rate swap; Liquidity risk; Swap (finance); Credit default swap; Proxy (statistics); Business; Financial economics; Valuation (finance); Economics; Variance swap; Monetary economics; Liquidity crisis; Credit risk; Econometrics; Actuarial science; Volatility (finance); Finance; Implied volatility; Volatility swap; Computer science","score_opus":0.023022685836731605,"score_gpt":0.21815831592591786,"score_spread":0.19513563008918625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3125885382","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":[0.9870158,0.008540245,0.0021450026,0.00034691513,0.00019118197,0.00017948574,0.00042030882,0.0000044061994,0.0011566574],"genre_scores_gemma":[0.94468504,0.054761253,0.00019959024,0.000004591338,0.0001860988,0.000003108346,3.9500935e-7,0.000017049748,0.00014286295],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983501,0.00012971237,0.000976169,0.00013566205,0.00014477497,0.00026360273],"domain_scores_gemma":[0.99278176,0.0015467809,0.0047821044,0.00065001094,0.00019797073,0.000041362546],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026078734,0.00018464132,0.00048285778,0.00010915206,0.0005535314,0.000031938303,0.0007430345,0.0000768152,0.000059610353],"category_scores_gemma":[0.0012883367,0.00008432149,0.00035964235,0.00049646175,0.00039474102,0.00016689356,0.000045888188,0.00065107853,0.000030637937],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016164614,0.00072677335,0.76968426,0.000018002338,0.0006460473,0.0000049089053,0.008244783,0.11475407,0.000028790684,0.04669656,0.016263384,0.04131597],"study_design_scores_gemma":[0.0005672419,0.0010402771,0.966338,0.00006131904,0.00007770294,0.000015326916,0.00015437306,0.005031819,0.0002346336,0.01772948,0.008609361,0.00014049398],"about_ca_topic_score_codex":0.0014223177,"about_ca_topic_score_gemma":0.00014840171,"teacher_disagreement_score":0.19665372,"about_ca_system_score_codex":0.000069696,"about_ca_system_score_gemma":0.000043567983,"threshold_uncertainty_score":0.4257372},"labels":[],"label_agreement":null},{"id":"W3125902651","doi":"10.1108/15265940610664933","title":"Effects of maturity choices on loan‐guarantee portfolios1","year":2006,"lang":"en","type":"article","venue":"The Journal of Risk Finance","topic":"Insurance and Financial Risk Management","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":"Université Laval","funders":"","keywords":"Maturity (psychological); Loan; Portfolio; Leverage (statistics); Actuarial science; Debt; Business; Value at risk; Economics; Finance; Risk management; Computer science","score_opus":0.006198098114071269,"score_gpt":0.1904142916428625,"score_spread":0.18421619352879123,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3125902651","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":[0.9769852,0.014377309,0.0012032008,0.00014058157,0.0006891896,0.00016511005,0.000053845622,0.0000068487916,0.0063786744],"genre_scores_gemma":[0.98415023,0.014729819,0.00022343032,0.00009348321,0.0003165924,0.000002412788,5.444113e-7,0.000016061987,0.0004674044],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.998572,0.000038152997,0.0008977786,0.00013945995,0.00010488849,0.00024771373],"domain_scores_gemma":[0.99730694,0.00021247247,0.0020977652,0.00029495455,0.000072163464,0.000015716363],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011245968,0.00015990007,0.0005185326,0.00019298683,0.00011984679,0.00001997023,0.00047288724,0.00007176677,0.000016369697],"category_scores_gemma":[0.00014760786,0.00012393657,0.0002157138,0.00029646745,0.000095269024,0.00019727969,0.000036964273,0.00034143715,0.000090951515],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014864851,0.0015144965,0.10031226,0.00036568908,0.00022459879,0.00014002991,0.0012608536,0.012601815,0.00024566776,0.8234562,0.018344615,0.04004727],"study_design_scores_gemma":[0.0010907095,0.00032633447,0.84331334,0.00014835321,0.000040779363,0.000011431795,0.000016907581,0.00015291868,0.0035195702,0.099794455,0.05139017,0.00019504136],"about_ca_topic_score_codex":0.0005302848,"about_ca_topic_score_gemma":0.00003840416,"teacher_disagreement_score":0.74300104,"about_ca_system_score_codex":0.000046058896,"about_ca_system_score_gemma":0.000016060649,"threshold_uncertainty_score":0.50539863},"labels":[],"label_agreement":null},{"id":"W4281681547","doi":"10.1108/jrf-03-2021-0037","title":"The cross-section of expected stock returns and components of idiosyncratic volatility","year":2022,"lang":"en","type":"article","venue":"The Journal of Risk Finance","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":5,"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 Northern British Columbia","funders":"","keywords":"Stock (firearms); Economics; Econometrics; Portfolio; Volatility (finance); Financial economics; Predictability; Systematic risk; Modern portfolio theory; Covariance; Capital asset pricing model; Mathematics; Statistics","score_opus":0.02672392019308921,"score_gpt":0.2283950702890412,"score_spread":0.201671150095952,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281681547","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":[0.9904725,0.008096823,0.00015265403,0.0001233148,0.00049879076,0.000109630084,0.000096156604,0.0000023374948,0.00044780687],"genre_scores_gemma":[0.9962573,0.0034910848,0.000081630955,0.000013022537,0.00004791611,0.0000030107458,8.0607333e-7,0.0000069068733,0.00009829105],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99874073,0.00011492434,0.00084560923,0.00008864498,0.000086953434,0.00012315973],"domain_scores_gemma":[0.99737304,0.00026143942,0.0020414782,0.00022866364,0.000078827165,0.000016574597],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018838281,0.00008531237,0.00031905805,0.00006558512,0.00040716704,0.000021613943,0.0002968678,0.000027745979,0.000032075957],"category_scores_gemma":[0.00026177734,0.00005943445,0.0000900465,0.00021033188,0.00023272431,0.00016749879,0.00008210858,0.00030132802,4.6804405e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013599659,0.00026256414,0.9383224,0.000074383206,0.00014337228,0.0000025309384,0.0047999616,0.0017104059,0.00077051483,0.04921855,0.0015661388,0.0017691734],"study_design_scores_gemma":[0.00044912432,0.0003599918,0.9625713,0.000016862206,0.000012343986,0.000014922027,0.0002925143,0.0015944556,0.00013923841,0.031322494,0.0031599775,0.00006676225],"about_ca_topic_score_codex":0.00027077796,"about_ca_topic_score_gemma":0.00002389397,"teacher_disagreement_score":0.024248872,"about_ca_system_score_codex":0.000046017754,"about_ca_system_score_gemma":0.00002705517,"threshold_uncertainty_score":0.3131641},"labels":[],"label_agreement":null},{"id":"W4288682765","doi":"10.1108/jrf-01-2022-0003","title":"Bitcoin's hedging attributes against equity market volatility: empirical evidence during the COVID-19 pandemic","year":2022,"lang":"en","type":"article","venue":"The Journal of Risk Finance","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Athabasca University","funders":"","keywords":"Economics; Granger causality; Econometrics; Volatility (finance); Equity (law); Coronavirus disease 2019 (COVID-19); Autoregressive conditional heteroskedasticity; Pandemic; Safe haven; Financial economics","score_opus":0.07829175922331127,"score_gpt":0.3283387281436043,"score_spread":0.25004696892029304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4288682765","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":[0.84331715,0.005089098,0.13332795,0.017843366,0.00015671381,0.00015789625,0.000013594313,0.00007166148,0.000022550086],"genre_scores_gemma":[0.9945003,0.0027424893,0.0013488638,0.0012653794,0.00006389903,0.000019435156,1.60258e-7,0.000006084982,0.0000534129],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9976692,0.00079130504,0.0004848149,0.00022604202,0.0005054803,0.00032314818],"domain_scores_gemma":[0.99602544,0.002023131,0.00078592164,0.0009843066,0.00011078564,0.00007041458],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.007335931,0.00013759772,0.00023464843,0.00009269419,0.001954168,0.00005828174,0.0034816477,0.00005525302,0.000021782764],"category_scores_gemma":[0.0012758138,0.00008457245,0.00012455414,0.0009383854,0.0002671522,0.0002505504,0.0019304736,0.0014033976,0.0000026642233],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004160581,0.00036260523,0.8373529,0.000080020334,0.00012664868,0.0001340211,0.010508905,0.020842347,0.0009937382,0.007587031,0.032918256,0.08867748],"study_design_scores_gemma":[0.0014690484,0.00038123637,0.46707875,0.00011433562,0.00011731833,0.0041017327,0.00096832786,0.25729865,0.0005509879,0.10971363,0.15752405,0.0006819481],"about_ca_topic_score_codex":0.00003727996,"about_ca_topic_score_gemma":0.000026181897,"teacher_disagreement_score":0.37027416,"about_ca_system_score_codex":0.000330414,"about_ca_system_score_gemma":0.0003081719,"threshold_uncertainty_score":0.9993451},"labels":[],"label_agreement":null},{"id":"W4313332456","doi":"10.1108/jrf-07-2022-0179","title":"The Russia–Ukraine conflict and foreign stocks on the US market","year":2022,"lang":"en","type":"article","venue":"The Journal of Risk Finance","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":22,"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 Northern British Columbia","funders":"","keywords":"Stock market; Capital market; Politics; Economics; Event study; Quality (philosophy); Stock (firearms); Business; Financial economics; Market economy; Monetary economics; Finance; Political science","score_opus":0.02039627070782505,"score_gpt":0.19937475889977757,"score_spread":0.17897848819195253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313332456","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":[0.8912564,0.026663536,0.00011396378,0.0061955787,0.00059810275,0.00028748586,0.0001584229,0.000007307423,0.07471919],"genre_scores_gemma":[0.9664406,0.030213896,0.00003901256,0.0009210569,0.00014989836,0.000017437842,4.549093e-7,0.000016074275,0.0022015602],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987764,0.00016692425,0.0005699563,0.00012800723,0.00010516138,0.00025358915],"domain_scores_gemma":[0.997579,0.00086015865,0.0011404586,0.00036121125,0.000030153838,0.000029063625],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0039353613,0.0001449294,0.00027069642,0.000061077866,0.0014451668,0.00009440144,0.00063815806,0.000029410648,0.00026899515],"category_scores_gemma":[0.00032340348,0.00007471259,0.00011362229,0.00019531978,0.00025323156,0.00012117119,0.00013025977,0.0006222898,0.000015407251],"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":[0.00048710057,0.000050747836,0.00634206,0.000004232368,0.00006019924,0.0000071931568,0.0007151927,0.0006382669,0.0000026209173,0.8973655,0.09126142,0.0030654732],"study_design_scores_gemma":[0.0004320923,0.00047231023,0.15182345,0.000013746634,0.000014540085,0.000052566444,0.00044347654,0.0010133045,0.000010362519,0.09801074,0.74759036,0.0001230617],"about_ca_topic_score_codex":0.000118179625,"about_ca_topic_score_gemma":0.000009988365,"teacher_disagreement_score":0.79935473,"about_ca_system_score_codex":0.000059443762,"about_ca_system_score_gemma":0.00003792561,"threshold_uncertainty_score":0.9998548},"labels":[],"label_agreement":null},{"id":"W4386469222","doi":"10.1108/jrf-10-2022-0283","title":"Contagion in the Euro area sovereign CDS market: a spatial approach","year":2023,"lang":"en","type":"article","venue":"The Journal of Risk Finance","topic":"Credit Risk and Financial Regulations","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Hearst","funders":"","keywords":"Financial contagion; Economics; Contagion effect; Credit default swap; Spatial econometrics; Spatial dependence; Value (mathematics); Financial economics; Sovereignty; Swap (finance); Monetary economics; Sovereign credit; Financial crisis; Econometrics; Credit risk; Macroeconomics; Finance","score_opus":0.03156088895315291,"score_gpt":0.21480964501484678,"score_spread":0.18324875606169388,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386469222","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":[0.9556609,0.002379071,0.02218119,0.0011668976,0.0006372558,0.00025032915,0.000199374,0.000014980129,0.017510023],"genre_scores_gemma":[0.99302,0.005918691,0.0001981098,0.00005073391,0.00036269586,0.0000069950797,0.000004715181,0.000015355758,0.00042273098],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99867207,0.00010350119,0.00072011456,0.00013982294,0.000104194805,0.00026031325],"domain_scores_gemma":[0.99826896,0.00043178682,0.00088959857,0.0003381383,0.000046714635,0.000024824207],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032461712,0.00012892859,0.00033459568,0.00021856787,0.00019820096,0.000045144243,0.00058025814,0.000071740644,0.000043810574],"category_scores_gemma":[0.00051263714,0.0000864199,0.00016098974,0.00075047475,0.00009325406,0.0001666969,0.000047465288,0.00046658577,0.00008177009],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009958732,0.00055970036,0.4698274,0.00003933464,0.000103085964,0.00010439986,0.017995557,0.02318243,0.000017631308,0.30133724,0.1422551,0.04358223],"study_design_scores_gemma":[0.00062853453,0.00008410026,0.88420147,0.000021275933,0.0000139840595,0.000046082427,0.00035297495,0.010056388,0.000006291841,0.05458231,0.049883626,0.00012294842],"about_ca_topic_score_codex":0.00032508833,"about_ca_topic_score_gemma":0.00010312855,"teacher_disagreement_score":0.41437408,"about_ca_system_score_codex":0.000052409505,"about_ca_system_score_gemma":0.000037373055,"threshold_uncertainty_score":0.3524101},"labels":[],"label_agreement":null},{"id":"W4393077247","doi":"10.1108/jrf-09-2023-0217","title":"How do gender diversity and CEO profile impact dividend policy in banking? Evidence from Islamic and conventional banks","year":2024,"lang":"en","type":"article","venue":"The Journal of Risk Finance","topic":"Corporate Finance and Governance","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Athabasca University","funders":"","keywords":"Dividend policy; Dividend; Gender diversity; Corporate governance; Diversity (politics); Originality; Islam; Accounting; Shareholder; Business; Value (mathematics); Risk aversion (psychology); Distribution (mathematics); Economics; Monetary economics; Financial system; Financial economics; Finance; Political science; Law","score_opus":0.02506380456811447,"score_gpt":0.2427972575977525,"score_spread":0.21773345302963804,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393077247","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":[0.9806006,0.01689774,0.0006895028,0.0014069873,0.00021551432,0.00008655752,0.000041500978,0.000008545686,0.000053073996],"genre_scores_gemma":[0.99089384,0.008069259,0.00005647156,0.000109838285,0.0007389908,9.172228e-7,0.0000010080751,0.000009928022,0.00011972687],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991437,0.000029713208,0.00020801325,0.0001652034,0.00027053483,0.00018283926],"domain_scores_gemma":[0.99912,0.00022039187,0.00044421427,0.00012744017,0.00008032138,0.000007609131],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072790706,0.00014319766,0.0002042363,0.00015675809,0.0002585447,0.00028327457,0.00024336326,0.000047690435,0.000030827436],"category_scores_gemma":[0.0002100952,0.000096857555,0.000071355265,0.00040505466,0.0001034656,0.0020914134,0.00036982642,0.00035496656,0.000008495069],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016133838,0.000019715004,0.9807754,0.000092199894,0.000037191003,0.00007475836,0.0008029663,0.00013525864,0.00010982818,0.0025012267,0.0036082969,0.0116818305],"study_design_scores_gemma":[0.00035590533,0.000019817338,0.96248245,0.00067649386,0.000070600865,0.00002267916,0.00005005214,0.0014801277,0.00001043648,0.033121347,0.0015933332,0.00011673821],"about_ca_topic_score_codex":0.0030423615,"about_ca_topic_score_gemma":0.00018047691,"teacher_disagreement_score":0.03062012,"about_ca_system_score_codex":0.00005657729,"about_ca_system_score_gemma":0.00005899376,"threshold_uncertainty_score":0.45991609},"labels":[],"label_agreement":null},{"id":"W4412774799","doi":"10.1108/jrf-03-2025-0133","title":"Crisis misread: the interplay of governance and financial literacy in Lebanon’s 2019 downfall","year":2025,"lang":"en","type":"article","venue":"The Journal of Risk Finance","topic":"Insurance and Financial Risk Management","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ministry of Children, Community and Social Services","funders":"","keywords":"Financial literacy; Corporate governance; Financial system; Financial crisis; Accounting; Economics; Political science; Business; Finance; Keynesian economics","score_opus":0.005220255474197066,"score_gpt":0.22199638941737124,"score_spread":0.21677613394317416,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412774799","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":[0.94825256,0.041614268,0.003598694,0.0028560886,0.0008463012,0.0002222314,0.00014124735,0.0000038210615,0.0024648053],"genre_scores_gemma":[0.95059973,0.047789063,0.00031911372,0.00049194164,0.00008720799,0.00000482582,4.990097e-7,0.000009575396,0.00069806114],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9982623,0.000065433764,0.0011479292,0.0001832015,0.00008035351,0.00026078682],"domain_scores_gemma":[0.9977196,0.00027720755,0.0014808917,0.0004063288,0.000097328004,0.00001862939],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002002642,0.00017184531,0.00055058184,0.0001823291,0.00012761258,0.00004057551,0.00069004187,0.00008065461,0.00001661149],"category_scores_gemma":[0.00045491607,0.00011933049,0.00014967014,0.0005607331,0.00014457678,0.00032795014,0.00013516369,0.00050005724,0.000017871747],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014729549,0.00045378142,0.30935743,0.00017799895,0.0001408815,0.00003518474,0.015562916,0.002178203,0.000032574022,0.47401398,0.078307554,0.11826653],"study_design_scores_gemma":[0.0010284492,0.00012585141,0.784898,0.00027006472,0.00002972187,0.000009547807,0.00015886957,0.00028874408,0.00013666514,0.05722871,0.1556605,0.00016488053],"about_ca_topic_score_codex":0.0012206323,"about_ca_topic_score_gemma":0.00026431135,"teacher_disagreement_score":0.47554058,"about_ca_system_score_codex":0.00008051509,"about_ca_system_score_gemma":0.000055694294,"threshold_uncertainty_score":0.48661563},"labels":[],"label_agreement":null},{"id":"W4415017967","doi":"10.1108/jrf-02-2025-0062","title":"Benchmarking technical, financial analysis and economic efficiency in Maritime Canadian agriculture","year":2025,"lang":"en","type":"article","venue":"The Journal of Risk Finance","topic":"Agricultural Economics and Policy","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Benchmarking; Diversification (marketing strategy); Productivity; Agriculture; Resource efficiency; Resource (disambiguation); Production (economics); Economic efficiency; Farm income","score_opus":0.003209659791858458,"score_gpt":0.18666789588794397,"score_spread":0.1834582360960855,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415017967","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":[0.9961536,0.0008178443,0.0000058996247,0.0021011431,0.00008436366,0.00006494527,0.000045222772,0.0000026313287,0.0007243741],"genre_scores_gemma":[0.9964959,0.0029979716,0.00006173277,0.00019735597,0.00016059433,9.327093e-7,0.0000033538763,2.7057217e-7,0.00008189863],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992532,0.00006198976,0.00032351547,0.00010665934,0.0000422937,0.00021233836],"domain_scores_gemma":[0.99941045,0.00022164236,0.00023930834,0.000040454735,0.00003248738,0.000055661745],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005170838,0.000098532146,0.00023892756,0.000061663995,0.00021413516,0.000044294,0.0003089907,0.0000866181,0.000035878053],"category_scores_gemma":[0.000057382444,0.000030859468,0.00010648238,0.0006198584,0.000056206827,0.000087069326,0.000042640375,0.00026474698,0.000002968368],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011898429,0.00009112363,0.8134594,0.000010413591,0.00011327132,0.000020634274,0.00044678943,0.0077626426,0.0034941663,0.008434269,0.013644211,0.1524041],"study_design_scores_gemma":[0.00009206345,0.000048180347,0.9889305,0.00002258892,0.00006457531,0.000013026679,0.000043817225,0.00017045686,0.00004653058,0.0008277071,0.0096601555,0.00008039811],"about_ca_topic_score_codex":0.08259331,"about_ca_topic_score_gemma":0.66956025,"teacher_disagreement_score":0.58696693,"about_ca_system_score_codex":0.000115680006,"about_ca_system_score_gemma":0.00005575884,"threshold_uncertainty_score":0.9235158},"labels":[],"label_agreement":null}]}