{"meta":{"query_hash":"6f2d0eba6fab","filters":{"venue":"Borsa Istanbul Review"},"cohort_total":11,"direct_labels_cover":0,"predictions_cover":11,"exported":11,"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/6f2d0eba6fab","api":"https://metacan.xera.ac/api/v1/cohort?venue=Borsa+Istanbul+Review"},"results":[{"id":"W1997236038","doi":"10.1016/j.bir.2014.01.001","title":"Stability of the “returns–growth” relationship in G7: The dynamic conditional lagged correlation approach","year":2014,"lang":"en","type":"article","venue":"Borsa Istanbul Review","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Economics; Volatility (finance); Econometrics; Stock market; Stock (firearms); Positive correlation; Correlation; Financial economics; Monetary economics; Mathematics; Biology; Internal medicine; Geography","score_opus":0.029229731570211876,"score_gpt":0.2336017423350779,"score_spread":0.20437201076486602,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997236038","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.74605155,0.029046515,0.19325933,0.0032218667,0.00019555823,0.000111934714,0.002307596,0.00026548465,0.025540216],"genre_scores_gemma":[0.981631,0.0073668,0.0070195645,0.00013518332,0.00013435612,0.00005196069,0.0012367242,0.000032345564,0.0023921127],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99954885,0.00014040271,0.00003646285,0.00012526155,0.000079254714,0.00006981648],"domain_scores_gemma":[0.99666446,0.0019427628,0.00068274373,0.00021964128,0.00039414738,0.00009633303],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022097446,0.0003654574,0.0005865507,0.0021195384,0.00029954466,0.0015342947,0.00092200836,0.00073311996,0.00211902],"category_scores_gemma":[0.0054497737,0.000236451,0.0010175175,0.0023873625,0.0007654852,0.0014158693,0.000688887,0.0009336567,0.00043392362],"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":[0.00018991235,0.00010404994,0.3029191,0.0007916574,0.0012304432,0.0023254773,0.0007589058,0.14432308,0.0032607685,0.35744876,0.0078332275,0.17881465],"study_design_scores_gemma":[0.000028525701,0.00019555447,0.16160762,0.0003486814,0.000538641,0.00086753396,0.00042229053,0.70656496,0.0017061405,0.10944431,0.018159537,0.000116172],"about_ca_topic_score_codex":0.0092918575,"about_ca_topic_score_gemma":0.005128488,"teacher_disagreement_score":0.0092918575,"about_ca_system_score_codex":0.00084349787,"about_ca_system_score_gemma":0.0009173266,"threshold_uncertainty_score":0.018475533},"labels":[],"label_agreement":null},{"id":"W2904286662","doi":"10.1016/j.bir.2018.12.001","title":"Examining the dynamics of illiquidity risks within the phases of the business cycle","year":2018,"lang":"en","type":"article","venue":"Borsa Istanbul Review","topic":"Financial Markets and Investment Strategies","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":"Wilfrid Laurier University; University of Ottawa","funders":"","keywords":"Business cycle; Kalman filter; Econometrics; Economics; Dynamic factor; Context (archaeology); Risk premium; Factor analysis; Generalized method of moments; Capital asset pricing model; Mathematics; Panel data; Macroeconomics; Statistics","score_opus":0.09149904063724268,"score_gpt":0.2745148663671499,"score_spread":0.1830158257299072,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2904286662","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.051866885,0.9107503,0.014785248,0.009098327,0.00057802646,0.000025415597,0.00026036345,0.000036423804,0.01259905],"genre_scores_gemma":[0.23851267,0.7526196,0.0021949566,0.00075105386,0.0017764454,0.000031307613,0.00023456763,0.00003061605,0.003848846],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99965274,0.0001070866,0.000024083998,0.00007025054,0.00009975155,0.000046094992],"domain_scores_gemma":[0.99589574,0.002681645,0.00060078915,0.000084854924,0.00063327333,0.00010367059],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001816996,0.00038760633,0.0006868123,0.0017596078,0.00018676689,0.0021964796,0.000559978,0.0011101015,0.0019716376],"category_scores_gemma":[0.009576448,0.00018230958,0.00037402072,0.0022012775,0.0005665538,0.0025690468,0.0005588764,0.0012247104,0.0003474803],"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":[0.0003831029,0.00008987007,0.018485423,0.0052143224,0.00036021363,0.0003905364,0.0004302255,0.025333313,0.0030529005,0.26969603,0.021388931,0.6551751],"study_design_scores_gemma":[0.00008116394,0.0005068491,0.081049524,0.007172673,0.0007859221,0.0012453602,0.0014656238,0.03604682,0.003932231,0.36089107,0.50666434,0.00015845259],"about_ca_topic_score_codex":0.0016806921,"about_ca_topic_score_gemma":0.0012216752,"teacher_disagreement_score":0.0021964796,"about_ca_system_score_codex":0.00083408743,"about_ca_system_score_gemma":0.0010160238,"threshold_uncertainty_score":0.009609342},"labels":[],"label_agreement":null},{"id":"W2980737191","doi":"10.1016/j.bir.2019.09.003","title":"The impact of universal banking on macroeconomic dynamics: A nonlinear local projection approach","year":2019,"lang":"en","type":"article","venue":"Borsa Istanbul Review","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais; Université du Québec à Montréal","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Economics; Nonlinear system; Stock market; Benchmark (surveying); Real economy; Monetary economics; Stock (firearms); Stock price; Projection (relational algebra); Econometrics; Computer science; Series (stratigraphy)","score_opus":0.032990377542206434,"score_gpt":0.2525950090548124,"score_spread":0.21960463151260598,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2980737191","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6071464,0.006695292,0.34496582,0.0032545654,0.00013732424,0.00005491683,0.0004750125,0.00035849522,0.036912125],"genre_scores_gemma":[0.9903222,0.0031936949,0.004253055,0.00007674628,0.000060875325,0.00001886738,0.00007230634,0.000025685562,0.0019765757],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996749,0.00017584051,0.000013201365,0.00005357097,0.000042304193,0.000040194074],"domain_scores_gemma":[0.99884975,0.00072454684,0.00014832598,0.000082716055,0.0001446905,0.000049934646],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011051244,0.00054736185,0.0006901612,0.00048600748,0.00026710515,0.0012967847,0.000647546,0.0004918819,0.0029313401],"category_scores_gemma":[0.0032814557,0.00029837407,0.0006955469,0.0006782868,0.00085346075,0.00154013,0.0020311938,0.000899146,0.00025272564],"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":[0.000119625205,0.000063618805,0.010260029,0.00032796396,0.00025465633,0.00049239816,0.00029170595,0.81111556,0.0018803685,0.12980916,0.0012636266,0.044121258],"study_design_scores_gemma":[0.000008363446,0.000054697517,0.0041855993,0.00003206076,0.00006310758,0.00006125942,0.00008799049,0.948035,0.00039121398,0.046217483,0.00084863295,0.000014542676],"about_ca_topic_score_codex":0.0036954943,"about_ca_topic_score_gemma":0.001979308,"teacher_disagreement_score":0.0036954943,"about_ca_system_score_codex":0.0005869301,"about_ca_system_score_gemma":0.0006529556,"threshold_uncertainty_score":0.009806275},"labels":[],"label_agreement":null},{"id":"W4245141449","doi":"10.1016/j.bir.2021.05.004","title":"Is short-term debt a substitute for or complementary to good governance?","year":2021,"lang":"en","type":"article","venue":"Borsa Istanbul Review","topic":"Corporate Finance and Governance","field":"Business, Management and Accounting","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":"Simon Fraser University","funders":"","keywords":"Corporate governance; Debt; Creditor; Shareholder; Business; Internal debt; Good governance; Financial system; Maturity (psychological); Debt levels and flows; External debt; Agency cost; Monetary economics; Agency (philosophy); Accounting; Finance; Economics; Political science; Law","score_opus":0.06118113404621406,"score_gpt":0.3012567533616128,"score_spread":0.24007561931539873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4245141449","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16069138,0.7287227,0.0068352576,0.039678816,0.0010462513,0.00007665213,0.0008046623,0.000046911686,0.06209746],"genre_scores_gemma":[0.7566397,0.2300515,0.0027724635,0.003987435,0.001450993,0.000042427284,0.0005741832,0.000023712779,0.0044575604],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99752134,0.0010964108,0.0002760566,0.00035907523,0.0004564409,0.00029081324],"domain_scores_gemma":[0.9859388,0.006212653,0.005301916,0.0006685183,0.0012663247,0.00061177206],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0042995163,0.00020633393,0.0008379299,0.0013182429,0.00025673557,0.0031704456,0.00059138244,0.0010451687,0.0050520515],"category_scores_gemma":[0.012033581,0.00020514219,0.00051629887,0.0024700218,0.001685168,0.0039705364,0.00090197905,0.0011591905,0.00045200813],"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":[0.00027622562,0.0001815262,0.08131231,0.010065835,0.0010021107,0.00064199365,0.0007065211,0.0014385161,0.0017779275,0.34218714,0.015373986,0.54503596],"study_design_scores_gemma":[0.00025413212,0.0006093923,0.32479438,0.01905884,0.0014853403,0.0029782145,0.0026771026,0.0024383808,0.0021396857,0.15596133,0.48749465,0.00010854795],"about_ca_topic_score_codex":0.0020122956,"about_ca_topic_score_gemma":0.0036596535,"teacher_disagreement_score":0.0050520515,"about_ca_system_score_codex":0.0010267299,"about_ca_system_score_gemma":0.0014625953,"threshold_uncertainty_score":0.022738338},"labels":[],"label_agreement":null},{"id":"W4327693011","doi":"10.1016/j.bir.2023.03.002","title":"How does green finance asymmetrically affect greenhouse gas emissions? Evidence from the top-ten green bond issuer countries","year":2023,"lang":"en","type":"article","venue":"Borsa Istanbul Review","topic":"Energy, Environment, Economic Growth","field":"Economics, Econometrics and Finance","cited_by":24,"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":"Greenhouse gas; Sustainability; Economics; Issuer; Quantile; Climate Finance; China; Panel data; Natural resource economics; Finance; Econometrics; Developing country; Economic growth; Geography","score_opus":0.03430602288973066,"score_gpt":0.24693856469871175,"score_spread":0.21263254180898108,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4327693011","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97206026,0.01734155,0.00057996134,0.0014107457,0.000035704885,0.000010639051,0.0007666201,0.000005300098,0.0077890977],"genre_scores_gemma":[0.9918859,0.007106273,0.00009077245,0.00014073453,0.000033234242,0.0000032023438,0.00042569987,0.000002883238,0.00031130703],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99933654,0.00024255694,0.00003951357,0.00010412067,0.0001401324,0.0001371099],"domain_scores_gemma":[0.99501157,0.0015210438,0.0025219182,0.00022155797,0.00055400794,0.00016988441],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017440227,0.00019138295,0.00044899603,0.0009137762,0.00032036882,0.0012384569,0.0002449165,0.00038878058,0.0015943424],"category_scores_gemma":[0.0039360523,0.00011845157,0.00041636746,0.0018221645,0.0006024796,0.00088502583,0.0007323756,0.00056382926,0.00022475769],"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":[0.0006765624,0.00014589219,0.90418756,0.0006188612,0.00097243796,0.00071009377,0.00083611184,0.0017438153,0.0005803451,0.01493241,0.0033103433,0.07128554],"study_design_scores_gemma":[0.000032288455,0.0001063473,0.9801633,0.0004004284,0.00045889296,0.0002318638,0.0017697796,0.0011336224,0.0009841186,0.0026672909,0.012024957,0.000027192356],"about_ca_topic_score_codex":0.008286099,"about_ca_topic_score_gemma":0.0074429424,"teacher_disagreement_score":0.008286099,"about_ca_system_score_codex":0.00041252098,"about_ca_system_score_gemma":0.0003608784,"threshold_uncertainty_score":0.016475737},"labels":[],"label_agreement":null},{"id":"W4389461484","doi":"10.1016/j.bir.2023.12.002","title":"Do psychological factors exert greater influence on investment decisions than physiological factors? Evidence from Borsa Istanbul","year":2023,"lang":"en","type":"article","venue":"Borsa Istanbul Review","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Earnings; Investment (military); Economics; Quarter (Canadian coin); Monetary economics; Psychology; Demographic economics; Finance","score_opus":0.20839360119535139,"score_gpt":0.3309502829859407,"score_spread":0.12255668179058932,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389461484","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99387074,0.0026472535,0.00006225927,0.00043833102,0.000038934784,0.000005555722,0.0003397893,0.000003576073,0.0025935578],"genre_scores_gemma":[0.99761057,0.0013018608,0.00006684424,0.00011486291,0.000031888918,0.000005497904,0.00043619378,0.0000037611271,0.00042842637],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99907553,0.00029928432,0.000056265882,0.0001709809,0.00015585354,0.00024211162],"domain_scores_gemma":[0.99635065,0.001452001,0.0012320846,0.00016051438,0.00041672555,0.00038801625],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016620908,0.00052689726,0.0005513303,0.0010249844,0.0006335812,0.0018280369,0.0005540599,0.0006589894,0.0035623126],"category_scores_gemma":[0.0025470294,0.0003039562,0.0005074972,0.0011415831,0.0009486344,0.0005945865,0.001142824,0.00079339446,0.0007843542],"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":[0.0012642299,0.00048271392,0.9632227,0.00041605718,0.00034510856,0.0011240402,0.003854123,0.00049200206,0.0008310164,0.0011232322,0.0021349238,0.024709856],"study_design_scores_gemma":[0.0000148839845,0.00014695305,0.9937674,0.00010228965,0.00005958956,0.000085640306,0.003382469,0.0001714075,0.00011823672,0.00010602129,0.0020342665,0.000010867384],"about_ca_topic_score_codex":0.030768162,"about_ca_topic_score_gemma":0.03598692,"teacher_disagreement_score":0.030768162,"about_ca_system_score_codex":0.001342487,"about_ca_system_score_gemma":0.0012593163,"threshold_uncertainty_score":0.061178148},"labels":[],"label_agreement":null},{"id":"W4390561418","doi":"10.1016/j.bir.2024.01.001","title":"Does the financialization of agricultural commodities impact food security? An empirical investigation","year":2024,"lang":"en","type":"article","venue":"Borsa Istanbul Review","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":31,"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":"Financialization; Agriculture; Food security; Economics; Agricultural economics; Monetary economics; Finance; Geography","score_opus":0.034093667285294824,"score_gpt":0.28589200428113515,"score_spread":0.2517983369958403,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390561418","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99130005,0.0017307573,0.0003576835,0.0015151765,0.00001902851,0.000028534736,0.0004701248,0.0000065805307,0.0045720804],"genre_scores_gemma":[0.99689996,0.0016201625,0.00013042087,0.00015863508,0.000043299526,0.000014467883,0.00043157858,0.0000026912624,0.000698856],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99907887,0.00032982818,0.00006482963,0.00012910187,0.00014582385,0.00025163803],"domain_scores_gemma":[0.98192275,0.011053811,0.0053278883,0.000316347,0.0006551247,0.00072413136],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001915291,0.00039596698,0.0004592284,0.0014075133,0.0005369922,0.0018719309,0.00049547834,0.00088133285,0.006446972],"category_scores_gemma":[0.0078943,0.00019791398,0.00083690934,0.002833618,0.001055123,0.0022734867,0.00100388,0.0014895585,0.00044436258],"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":[0.0002644969,0.00040403687,0.96977276,0.00019874486,0.00033430473,0.00063860125,0.0005139364,0.0027029107,0.00028709773,0.004809812,0.0013329765,0.018740278],"study_design_scores_gemma":[0.00003087545,0.00034423286,0.9774729,0.00022042145,0.00043519176,0.00013959651,0.00462787,0.00884589,0.00043158853,0.0035771332,0.003850867,0.000023337552],"about_ca_topic_score_codex":0.011359187,"about_ca_topic_score_gemma":0.007676132,"teacher_disagreement_score":0.011359187,"about_ca_system_score_codex":0.0012789633,"about_ca_system_score_gemma":0.0013109241,"threshold_uncertainty_score":0.022586107},"labels":[],"label_agreement":null},{"id":"W4403471899","doi":"10.1016/j.bir.2024.10.005","title":"Market reactions to the Israel-hamas conflict: A comparative event study of the US and Chinese markets","year":2024,"lang":"en","type":"article","venue":"Borsa Istanbul Review","topic":"Economic Sanctions and International Relations","field":"Economics, Econometrics and Finance","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"U.S. Department of Defense","keywords":"Event study; Event (particle physics); Chinese market; Economics; Financial economics; Political science; China; History; Law; Archaeology","score_opus":0.04761727019942626,"score_gpt":0.3121508725701918,"score_spread":0.26453360237076556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403471899","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98874474,0.006690857,0.0000891498,0.0003154985,0.00003459551,0.000031596028,0.00010718042,0.000001396051,0.0039848196],"genre_scores_gemma":[0.99197805,0.006931101,0.000057563902,0.00016564615,0.0000892972,0.000017359725,0.00018877357,0.000001255065,0.00057091593],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99962497,0.00014776427,0.000022728344,0.000032954256,0.00008641161,0.000085162435],"domain_scores_gemma":[0.9989242,0.00036323466,0.00044380006,0.000036738405,0.00015411347,0.00007790043],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012986091,0.00016633146,0.00022304604,0.0011166086,0.00041070717,0.0010875982,0.0002370372,0.00037238857,0.0012485826],"category_scores_gemma":[0.0018659506,0.000073012845,0.00029312595,0.0019360929,0.0005393354,0.00085436064,0.0005513755,0.0002881654,0.000090186775],"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":[0.001108426,0.0006681105,0.7978774,0.002529824,0.00094904593,0.004618728,0.034381066,0.0016514594,0.0026232328,0.015825102,0.008544053,0.12922366],"study_design_scores_gemma":[0.00002507294,0.00027495212,0.96010906,0.0002572783,0.000138724,0.00036023607,0.02207519,0.0006687766,0.00046655198,0.00055936974,0.015038251,0.000026642198],"about_ca_topic_score_codex":0.01181011,"about_ca_topic_score_gemma":0.0122690555,"teacher_disagreement_score":0.01181011,"about_ca_system_score_codex":0.0007683856,"about_ca_system_score_gemma":0.000578982,"threshold_uncertainty_score":0.02348274},"labels":[],"label_agreement":null},{"id":"W4405835161","doi":"10.1016/j.bir.2024.12.011","title":"US Treasury market default risk and global interbank liquidity risk","year":2024,"lang":"en","type":"article","venue":"Borsa Istanbul Review","topic":"Credit Risk and Financial Regulations","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"NSAF Joint Fund; Natural Science Foundation of Hunan Province; National Natural Science Foundation of China","keywords":"Treasury; Market liquidity; Liquidity risk; Interbank lending market; Business; Financial system; Credit risk; Market risk; Monetary economics; Economics; Actuarial science; Finance","score_opus":0.01704248713873112,"score_gpt":0.247059856963333,"score_spread":0.23001736982460186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405835161","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08655513,0.88935536,0.0027476158,0.0023500014,0.00013847518,0.000016736374,0.0006776238,0.00001722079,0.018141776],"genre_scores_gemma":[0.48687515,0.50925577,0.0009123601,0.00032187358,0.00036689106,0.0000178437,0.00044476287,0.0000051852307,0.0018001075],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99947494,0.000220921,0.00005207477,0.0000823987,0.00013270482,0.000036939644],"domain_scores_gemma":[0.99756444,0.001144664,0.0008146422,0.00006741366,0.0003593854,0.000049551283],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001429069,0.0002559476,0.00038497374,0.0021091858,0.00012574045,0.0010762792,0.00018832891,0.00042379566,0.001595158],"category_scores_gemma":[0.0038642462,0.000092705086,0.0004070208,0.00341025,0.00034941343,0.00075445813,0.00035825555,0.00050948665,0.00015751524],"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":[0.00037565042,0.00010441368,0.17421,0.009564024,0.0023067351,0.0005778504,0.00055103935,0.011431397,0.0010556628,0.12155081,0.01981486,0.6584574],"study_design_scores_gemma":[0.000095807925,0.00049372914,0.6312259,0.017922346,0.002849407,0.0016796293,0.0013880904,0.012097311,0.002257235,0.0521074,0.2777563,0.000126944],"about_ca_topic_score_codex":0.005446782,"about_ca_topic_score_gemma":0.007353678,"teacher_disagreement_score":0.005446782,"about_ca_system_score_codex":0.0006237737,"about_ca_system_score_gemma":0.000748795,"threshold_uncertainty_score":0.010830164},"labels":[],"label_agreement":null},{"id":"W4409259573","doi":"10.1016/j.bir.2025.03.008","title":"Electricity prices through the lens of sentiments for the UN and the IMF: An asymmetric approach for Türkiye","year":2025,"lang":"en","type":"article","venue":"Borsa Istanbul Review","topic":"Global Energy Security and Policy","field":"Energy","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"Yükseköğretim Kurulu","keywords":"Economics; Electricity; Keynesian economics; Lens (geology); Monetary economics; Macroeconomics; Physics; Optics","score_opus":0.024762776277647353,"score_gpt":0.30842483888033106,"score_spread":0.28366206260268373,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409259573","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.64331555,0.16797672,0.0025385073,0.020735135,0.00053961185,0.000045426485,0.00042002255,0.000015742076,0.16441324],"genre_scores_gemma":[0.96511024,0.03164936,0.00047258343,0.0005024322,0.00016373467,0.000014961329,0.00010710112,0.000005963085,0.001973543],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99964094,0.00019392943,0.000015176753,0.000025549796,0.0000748368,0.00004958255],"domain_scores_gemma":[0.9993318,0.0003688738,0.00014806564,0.0000151717695,0.00012099284,0.0000150505875],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00085684436,0.0003994811,0.00030731384,0.0022469705,0.0009835857,0.0029307979,0.00033453936,0.00073124585,0.0026942603],"category_scores_gemma":[0.0017122525,0.00009426034,0.0001966711,0.0027476875,0.0012819574,0.003028124,0.00079947966,0.0007456175,0.00018483655],"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":[0.0004706475,0.00014396258,0.058379687,0.0035513244,0.00027522485,0.0041555003,0.060867522,0.0021136673,0.0019058007,0.48511288,0.02223474,0.360789],"study_design_scores_gemma":[0.000068363566,0.00025474644,0.25833777,0.0082634175,0.0004330095,0.0020583058,0.23480457,0.0061605745,0.0014463523,0.112282924,0.37575147,0.00013863988],"about_ca_topic_score_codex":0.0094241835,"about_ca_topic_score_gemma":0.011672126,"teacher_disagreement_score":0.0094241835,"about_ca_system_score_codex":0.0020066728,"about_ca_system_score_gemma":0.0012429648,"threshold_uncertainty_score":0.018738627},"labels":[],"label_agreement":null},{"id":"W4410732839","doi":"10.1016/j.bir.2025.05.013","title":"Network readiness, financial inclusion, and sustainable development goals: Insights from a clustering approach","year":2025,"lang":"en","type":"article","venue":"Borsa Istanbul Review","topic":"Economic Growth and Development","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"FP7 Coordination of Research Activities; Horizon Therapeutics","keywords":"Inclusion (mineral); Financial inclusion; Cluster analysis; Sustainable development; Business; Finance; Psychology; Computer science; Financial services; Political science; Artificial intelligence","score_opus":0.009082272411464407,"score_gpt":0.21802628450505612,"score_spread":0.2089440120935917,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410732839","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8145655,0.025297152,0.086485125,0.006781859,0.00015434842,0.00060169405,0.0018052189,0.000118584474,0.06419046],"genre_scores_gemma":[0.9768091,0.0049746465,0.016410356,0.00010283151,0.000029313098,0.00013560097,0.0005446421,0.000016146401,0.0009772693],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9986343,0.00078475644,0.00007382824,0.00016643338,0.0002298185,0.000110929665],"domain_scores_gemma":[0.99658054,0.0019149211,0.0004993267,0.00017690189,0.00068180717,0.00014656482],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028759625,0.0004716878,0.0005179057,0.0061195,0.0010464626,0.0021691695,0.0006487358,0.00051040604,0.0014869084],"category_scores_gemma":[0.0068680733,0.00016498112,0.0007352322,0.008760207,0.0012699964,0.0018279274,0.0017044019,0.0005197082,0.00015431187],"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":[0.00021441918,0.00021307767,0.3573208,0.0031060667,0.0015083303,0.00057847396,0.022039548,0.029069211,0.00068284024,0.20509212,0.007427454,0.3727476],"study_design_scores_gemma":[0.000028726421,0.000185277,0.66953826,0.0026245336,0.00078908633,0.0005897976,0.059497047,0.067921914,0.00068325066,0.15439479,0.04359291,0.00015445243],"about_ca_topic_score_codex":0.014452987,"about_ca_topic_score_gemma":0.020072661,"teacher_disagreement_score":0.014452987,"about_ca_system_score_codex":0.002653336,"about_ca_system_score_gemma":0.0022423752,"threshold_uncertainty_score":0.028737724},"labels":[],"label_agreement":null}]}