{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":11,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":11,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12","author_layer_release":"2026-06-26"},"query_hash":"6f2d0eba6fab","filters":{"venue":"Borsa Istanbul Review"}},"results":[{"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,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Financialization; Agriculture; Food security; Economics; Agricultural economics; Monetary economics; Finance; Geography","authors":[{"name":"R. L. Manogna","is_ca":false},{"name":"Nishil Kulkarni","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03409366728529482,"gpt":0.2858920042811351,"spread":0.2517983369958403,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001915291,0.000395967,0.0004592284,0.001407513,0.0005369922,0.001871931,0.0004954783,0.0008813328,0.006446972],"category_scores_gemma":[0.0078943,0.000197914,0.0008369093,0.002833618,0.001055123,0.002273487,0.00100388,0.001489558,0.0004443626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001278963,"about_ca_system_score_gemma":0.001310924,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01135919,"about_ca_topic_score_gemma":0.007676132,"domain_scores_codex":[0.9990789,0.0003298282,0.00006482963,0.0001291019,0.0001458239,0.000251638],"domain_scores_gemma":[0.9819227,0.01105381,0.005327888,0.000316347,0.0006551247,0.0007241314],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002644969,0.0004040369,0.9697728,0.0001987449,0.0003343047,0.0006386013,0.0005139364,0.002702911,0.0002870977,0.004809812,0.001332977,0.01874028],"study_design_scores_gemma":[0.00003087545,0.0003442329,0.9774729,0.0002204215,0.0004351918,0.0001395965,0.00462787,0.00884589,0.0004315885,0.003577133,0.003850867,0.00002333755],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9913,0.001730757,0.0003576835,0.001515176,0.00001902851,0.00002853474,0.0004701248,0.000006580531,0.00457208],"genre_scores_gemma":[0.9969,0.001620163,0.0001304209,0.0001586351,0.00004329953,0.00001446788,0.0004315786,0.000002691262,0.000698856],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01135919,"threshold_uncertainty_score":0.02258611,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"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","authors":[{"name":"Changzheng Li","is_ca":false},{"name":"Muhammad Zahir Faridi","is_ca":false},{"name":"Raima Nazar","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03430602288973066,"gpt":0.2469385646987118,"spread":0.2126325418089811,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001744023,0.0001913829,0.000448996,0.0009137762,0.0003203688,0.001238457,0.0002449165,0.0003887806,0.001594342],"category_scores_gemma":[0.003936052,0.0001184516,0.0004163675,0.001822165,0.0006024796,0.0008850258,0.0007323756,0.0005638293,0.0002247577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000412521,"about_ca_system_score_gemma":0.0003608784,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008286099,"about_ca_topic_score_gemma":0.007442942,"domain_scores_codex":[0.9993365,0.0002425569,0.00003951357,0.0001041207,0.0001401324,0.0001371099],"domain_scores_gemma":[0.9950116,0.001521044,0.002521918,0.000221558,0.0005540079,0.0001698844],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006765624,0.0001458922,0.9041876,0.0006188612,0.000972438,0.0007100938,0.0008361118,0.001743815,0.0005803451,0.01493241,0.003310343,0.07128554],"study_design_scores_gemma":[0.00003228846,0.0001063473,0.9801633,0.0004004284,0.000458893,0.0002318638,0.00176978,0.001133622,0.0009841186,0.002667291,0.01202496,0.00002719236],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9720603,0.01734155,0.0005799613,0.001410746,0.00003570488,0.00001063905,0.0007666201,0.000005300098,0.007789098],"genre_scores_gemma":[0.9918859,0.007106273,0.00009077245,0.0001407345,0.00003323424,0.000003202344,0.0004256999,0.000002883238,0.000311307],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008286099,"threshold_uncertainty_score":0.01647574,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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","authors":[{"name":"Rizky Yudaruddin","is_ca":false},{"name":"Dadang Lesmana","is_ca":false},{"name":"İbrahim Halil Ekşi̇","is_ca":false},{"name":"William Ginn","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04761727019942626,"gpt":0.3121508725701918,"spread":0.2645336023707656,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001298609,0.0001663315,0.000223046,0.001116609,0.0004107072,0.001087598,0.0002370372,0.0003723886,0.001248583],"category_scores_gemma":[0.001865951,0.00007301284,0.000293126,0.001936093,0.0005393354,0.0008543606,0.0005513755,0.0002881654,0.00009018678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007683856,"about_ca_system_score_gemma":0.000578982,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01181011,"about_ca_topic_score_gemma":0.01226906,"domain_scores_codex":[0.999625,0.0001477643,0.00002272834,0.00003295426,0.00008641161,0.00008516244],"domain_scores_gemma":[0.9989242,0.0003632347,0.0004438001,0.00003673841,0.0001541135,0.00007790043],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001108426,0.0006681105,0.7978774,0.002529824,0.0009490459,0.004618728,0.03438107,0.001651459,0.002623233,0.0158251,0.008544053,0.1292237],"study_design_scores_gemma":[0.00002507294,0.0002749521,0.9601091,0.0002572783,0.000138724,0.0003602361,0.02207519,0.0006687766,0.000466552,0.0005593697,0.01503825,0.0000266422],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9887447,0.006690857,0.0000891498,0.0003154985,0.00003459551,0.00003159603,0.0001071804,0.000001396051,0.00398482],"genre_scores_gemma":[0.991978,0.006931101,0.0000575639,0.0001656462,0.0000892972,0.00001735973,0.0001887736,0.000001255065,0.0005709159],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01181011,"threshold_uncertainty_score":0.02348274,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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","authors":[{"name":"Deniz Anginer","is_ca":true},{"name":"Asli Demirgüç‐Kunt","is_ca":false},{"name":"Şerif Aziz Şimşir","is_ca":false},{"name":"Mete Tepe","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06118113404621406,"gpt":0.3012567533616128,"spread":0.2400756193153987,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004299516,0.0002063339,0.0008379299,0.001318243,0.0002567356,0.003170446,0.0005913824,0.001045169,0.005052052],"category_scores_gemma":[0.01203358,0.0002051422,0.0005162989,0.002470022,0.001685168,0.003970536,0.000901979,0.001159191,0.0004520081],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00102673,"about_ca_system_score_gemma":0.001462595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002012296,"about_ca_topic_score_gemma":0.003659653,"domain_scores_codex":[0.9975213,0.001096411,0.0002760566,0.0003590752,0.0004564409,0.0002908132],"domain_scores_gemma":[0.9859388,0.006212653,0.005301916,0.0006685183,0.001266325,0.0006117721],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002762256,0.0001815262,0.08131231,0.01006583,0.001002111,0.0006419937,0.0007065211,0.001438516,0.001777928,0.3421871,0.01537399,0.545036],"study_design_scores_gemma":[0.0002541321,0.0006093923,0.3247944,0.01905884,0.00148534,0.002978215,0.002677103,0.002438381,0.002139686,0.1559613,0.4874946,0.000108548],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.1606914,0.7287227,0.006835258,0.03967882,0.001046251,0.00007665213,0.0008046623,0.00004691169,0.06209746],"genre_scores_gemma":[0.7566397,0.2300515,0.002772463,0.003987435,0.001450993,0.00004242728,0.0005741832,0.00002371278,0.00445756],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005052052,"threshold_uncertainty_score":0.02273834,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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","authors":[{"name":"François‐Éric Racicot","is_ca":true},{"name":"William F. Rentz","is_ca":true},{"name":"Alfred L. Kahl","is_ca":true},{"name":"Olivier Mesly","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.09149904063724268,"gpt":0.2745148663671499,"spread":0.1830158257299072,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001816996,0.0003876063,0.0006868123,0.001759608,0.0001867669,0.00219648,0.000559978,0.001110101,0.001971638],"category_scores_gemma":[0.009576448,0.0001823096,0.0003740207,0.002201278,0.0005665538,0.002569047,0.0005588764,0.00122471,0.0003474803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008340874,"about_ca_system_score_gemma":0.001016024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001680692,"about_ca_topic_score_gemma":0.001221675,"domain_scores_codex":[0.9996527,0.0001070866,0.000024084,0.00007025054,0.00009975155,0.00004609499],"domain_scores_gemma":[0.9958957,0.002681645,0.0006007891,0.00008485492,0.0006332733,0.0001036706],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003831029,0.00008987007,0.01848542,0.005214322,0.0003602136,0.0003905364,0.0004302255,0.02533331,0.003052901,0.269696,0.02138893,0.6551751],"study_design_scores_gemma":[0.00008116394,0.0005068491,0.08104952,0.007172673,0.0007859221,0.00124536,0.001465624,0.03604682,0.003932231,0.3608911,0.5066643,0.0001584526],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.05186689,0.9107503,0.01478525,0.009098327,0.0005780265,0.0000254156,0.0002603634,0.0000364238,0.01259905],"genre_scores_gemma":[0.2385127,0.7526196,0.002194957,0.0007510539,0.001776445,0.00003130761,0.0002345676,0.00003061605,0.003848846],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00219648,"threshold_uncertainty_score":0.009609342,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"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)","authors":[{"name":"Christian Calmès","is_ca":true},{"name":"Raymond Théoret","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03299037754220643,"gpt":0.2525950090548124,"spread":0.219604631512606,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001105124,0.0005473619,0.0006901612,0.0004860075,0.0002671051,0.001296785,0.000647546,0.0004918819,0.00293134],"category_scores_gemma":[0.003281456,0.0002983741,0.0006955469,0.0006782868,0.0008534607,0.00154013,0.002031194,0.000899146,0.0002527256],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005869301,"about_ca_system_score_gemma":0.0006529556,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003695494,"about_ca_topic_score_gemma":0.001979308,"domain_scores_codex":[0.9996749,0.0001758405,0.00001320136,0.00005357097,0.00004230419,0.00004019407],"domain_scores_gemma":[0.9988497,0.0007245468,0.000148326,0.00008271605,0.0001446905,0.00004993465],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001196252,0.00006361881,0.01026003,0.000327964,0.0002546563,0.0004923982,0.0002917059,0.8111156,0.001880368,0.1298092,0.001263627,0.04412126],"study_design_scores_gemma":[0.000008363446,0.00005469752,0.004185599,0.00003206076,0.00006310758,0.00006125942,0.00008799049,0.948035,0.000391214,0.04621748,0.0008486329,0.00001454268],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6071464,0.006695292,0.3449658,0.003254565,0.0001373242,0.00005491683,0.0004750125,0.0003584952,0.03691212],"genre_scores_gemma":[0.9903222,0.003193695,0.004253055,0.00007674628,0.00006087533,0.00001886738,0.00007230634,0.00002568556,0.001976576],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003695494,"threshold_uncertainty_score":0.009806275,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Guelph","funders":"Yükseköğretim Kurulu","keywords":"Economics; Electricity; Keynesian economics; Lens (geology); Monetary economics; Macroeconomics; Physics; Optics","authors":[{"name":"Pınar Deniz","is_ca":false},{"name":"Thanasis Stengos","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02476277627764735,"gpt":0.3084248388803311,"spread":0.2836620626026837,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008568444,0.0003994811,0.0003073138,0.002246971,0.0009835857,0.002930798,0.0003345394,0.0007312458,0.00269426],"category_scores_gemma":[0.001712253,0.00009426034,0.0001966711,0.002747688,0.001281957,0.003028124,0.0007994797,0.0007456175,0.0001848366],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002006673,"about_ca_system_score_gemma":0.001242965,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009424184,"about_ca_topic_score_gemma":0.01167213,"domain_scores_codex":[0.9996409,0.0001939294,0.00001517675,0.0000255498,0.0000748368,0.00004958255],"domain_scores_gemma":[0.9993318,0.0003688738,0.0001480656,0.00001517177,0.0001209928,0.00001505059],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004706475,0.0001439626,0.05837969,0.003551324,0.0002752249,0.0041555,0.06086752,0.002113667,0.001905801,0.4851129,0.02223474,0.360789],"study_design_scores_gemma":[0.00006836357,0.0002547464,0.2583378,0.008263418,0.0004330095,0.002058306,0.2348046,0.006160574,0.001446352,0.1122829,0.3757515,0.0001386399],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6433156,0.1679767,0.002538507,0.02073514,0.0005396119,0.00004542648,0.0004200226,0.00001574208,0.1644132],"genre_scores_gemma":[0.9651102,0.03164936,0.0004725834,0.0005024322,0.0001637347,0.00001496133,0.0001071011,0.000005963085,0.001973543],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009424184,"threshold_uncertainty_score":0.01873863,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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","authors":[{"name":"Mirjana Jemović","is_ca":false},{"name":"Ivana Marković","is_ca":false},{"name":"Adela Ljajić","is_ca":true},{"name":"Srđan Marinković","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.009082272411464407,"gpt":0.2180262845050561,"spread":0.2089440120935917,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002875963,0.0004716878,0.0005179057,0.0061195,0.001046463,0.002169169,0.0006487358,0.000510406,0.001486908],"category_scores_gemma":[0.006868073,0.0001649811,0.0007352322,0.008760207,0.001269996,0.001827927,0.001704402,0.0005197082,0.0001543119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002653336,"about_ca_system_score_gemma":0.002242375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01445299,"about_ca_topic_score_gemma":0.02007266,"domain_scores_codex":[0.9986343,0.0007847564,0.00007382824,0.0001664334,0.0002298185,0.0001109297],"domain_scores_gemma":[0.9965805,0.001914921,0.0004993267,0.0001769019,0.0006818072,0.0001465648],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002144192,0.0002130777,0.3573208,0.003106067,0.00150833,0.000578474,0.02203955,0.02906921,0.0006828402,0.2050921,0.007427454,0.3727476],"study_design_scores_gemma":[0.00002872642,0.000185277,0.6695383,0.002624534,0.0007890863,0.0005897976,0.05949705,0.06792191,0.0006832507,0.1543948,0.04359291,0.0001544524],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8145655,0.02529715,0.08648513,0.006781859,0.0001543484,0.000601694,0.001805219,0.0001185845,0.06419046],"genre_scores_gemma":[0.9768091,0.004974646,0.01641036,0.0001028315,0.0000293131,0.000135601,0.0005446421,0.0000161464,0.0009772693],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01445299,"threshold_uncertainty_score":0.02873772,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Earnings; Investment (military); Economics; Quarter (Canadian coin); Monetary economics; Psychology; Demographic economics; Finance","authors":[{"name":"Şenay Açıkgöz","is_ca":false},{"name":"Cem Onur Karatas","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2083936011953514,"gpt":0.3309502829859407,"spread":0.1225566817905893,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001662091,0.0005268973,0.0005513303,0.001024984,0.0006335812,0.001828037,0.0005540599,0.0006589894,0.003562313],"category_scores_gemma":[0.002547029,0.0003039562,0.0005074972,0.001141583,0.0009486344,0.0005945865,0.001142824,0.0007933945,0.0007843542],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001342487,"about_ca_system_score_gemma":0.001259316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03076816,"about_ca_topic_score_gemma":0.03598692,"domain_scores_codex":[0.9990755,0.0002992843,0.00005626588,0.0001709809,0.0001558535,0.0002421116],"domain_scores_gemma":[0.9963506,0.001452001,0.001232085,0.0001605144,0.0004167256,0.0003880163],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00126423,0.0004827139,0.9632227,0.0004160572,0.0003451086,0.00112404,0.003854123,0.0004920021,0.0008310164,0.001123232,0.002134924,0.02470986],"study_design_scores_gemma":[0.00001488398,0.0001469531,0.9937674,0.0001022896,0.00005958956,0.00008564031,0.003382469,0.0001714075,0.0001182367,0.0001060213,0.002034266,0.00001086738],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9938707,0.002647253,0.00006225927,0.000438331,0.00003893478,0.000005555722,0.0003397893,0.000003576073,0.002593558],"genre_scores_gemma":[0.9976106,0.001301861,0.00006684424,0.0001148629,0.00003188892,0.000005497904,0.0004361938,0.000003761127,0.0004284264],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03076816,"threshold_uncertainty_score":0.06117815,"prediction_status":"machine_predicted_unvalidated"},"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,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"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","authors":[{"name":"Simon Cottrell","is_ca":false},{"name":"Jinghua Lei","is_ca":false},{"name":"Yihong Ma","is_ca":false},{"name":"Sarath Delpachitra","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01704248713873112,"gpt":0.247059856963333,"spread":0.2300173698246019,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001429069,0.0002559476,0.0003849737,0.002109186,0.0001257405,0.001076279,0.0001883289,0.0004237957,0.001595158],"category_scores_gemma":[0.003864246,0.00009270509,0.0004070208,0.00341025,0.0003494134,0.0007544581,0.0003582556,0.0005094867,0.0001575152],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006237737,"about_ca_system_score_gemma":0.000748795,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005446782,"about_ca_topic_score_gemma":0.007353678,"domain_scores_codex":[0.9994749,0.000220921,0.00005207477,0.0000823987,0.0001327048,0.00003693964],"domain_scores_gemma":[0.9975644,0.001144664,0.0008146422,0.00006741366,0.0003593854,0.00004955128],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003756504,0.0001044137,0.17421,0.009564024,0.002306735,0.0005778504,0.0005510394,0.0114314,0.001055663,0.1215508,0.01981486,0.6584574],"study_design_scores_gemma":[0.00009580793,0.0004937291,0.6312259,0.01792235,0.002849407,0.001679629,0.00138809,0.01209731,0.002257235,0.0521074,0.2777563,0.000126944],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.08655513,0.8893554,0.002747616,0.002350001,0.0001384752,0.00001673637,0.0006776238,0.00001722079,0.01814178],"genre_scores_gemma":[0.4868751,0.5092558,0.0009123601,0.0003218736,0.0003668911,0.0000178437,0.0004447629,0.000005185231,0.001800108],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005446782,"threshold_uncertainty_score":0.01083016,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"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,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"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","authors":[{"name":"Štefan Lyócsa","is_ca":false},{"name":"Eduard Baumöhl","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02922973157021188,"gpt":0.2336017423350779,"spread":0.204372010764866,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002209745,0.0003654574,0.0005865507,0.002119538,0.0002995447,0.001534295,0.0009220084,0.00073312,0.00211902],"category_scores_gemma":[0.005449774,0.000236451,0.001017518,0.002387363,0.0007654852,0.001415869,0.000688887,0.0009336567,0.0004339236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008434979,"about_ca_system_score_gemma":0.0009173266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009291857,"about_ca_topic_score_gemma":0.005128488,"domain_scores_codex":[0.9995489,0.0001404027,0.00003646285,0.0001252615,0.00007925471,0.00006981648],"domain_scores_gemma":[0.9966645,0.001942763,0.0006827437,0.0002196413,0.0003941474,0.00009633303],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0001899123,0.0001040499,0.3029191,0.0007916574,0.001230443,0.002325477,0.0007589058,0.1443231,0.003260768,0.3574488,0.007833228,0.1788146],"study_design_scores_gemma":[0.0000285257,0.0001955545,0.1616076,0.0003486814,0.000538641,0.000867534,0.0004222905,0.706565,0.00170614,0.1094443,0.01815954,0.000116172],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7460515,0.02904652,0.1932593,0.003221867,0.0001955582,0.0001119347,0.002307596,0.0002654846,0.02554022],"genre_scores_gemma":[0.981631,0.0073668,0.007019565,0.0001351833,0.0001343561,0.00005196069,0.001236724,0.00003234556,0.002392113],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009291857,"threshold_uncertainty_score":0.01847553,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}