{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":5,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":5,"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"},"query_hash":"4028bb28922e","filters":{"venue":"Finance Research Open"}},"results":[{"id":"W4408567212","doi":"10.1016/j.finr.2025.100006","title":"Supervised learning models, statistical models or hybrid models? A prediction of clean energy stock based on fear and fundamental factors","year":2025,"lang":"en","type":"article","venue":"Finance Research Open","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Trinity College","funders":"","keywords":"Computer science; Statistical learning; Artificial intelligence; Machine learning; Stock (firearms); Predictive modelling; Statistical model; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.4432901866504693,"gpt":0.4878487706345707,"spread":0.04455858398410134,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01104322,0.0002477492,0.0006056171,0.0008184332,0.0006164226,0.0005891097,0.001595268,0.0001159553,0.0001991573],"category_scores_gemma":[0.00693774,0.0001862115,0.0000783655,0.001468939,0.00041713,0.001103201,0.00135555,0.0006730796,0.000003663851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002279898,"about_ca_system_score_gemma":0.0008892258,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001377852,"about_ca_topic_score_gemma":0.0001153778,"domain_scores_codex":[0.9922886,0.002589959,0.0007776396,0.001089065,0.002545706,0.0007090156],"domain_scores_gemma":[0.9892737,0.008902336,0.0001643815,0.0008081027,0.0006620142,0.0001894495],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004048582,0.0003183053,0.002953239,0.00005187774,0.00003368332,0.00002570253,0.000488231,0.4596369,0.000106561,0.04407489,0.008338497,0.4799235],"study_design_scores_gemma":[0.001016831,0.0007987815,0.003887303,0.0002012621,0.000006073717,0.000001846263,0.000507751,0.8703913,0.0005223993,0.1214443,0.001091618,0.0001305415],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2154619,0.00005257801,0.762307,0.0002580994,0.0001226834,0.0009015731,0.0003388426,0.00003732554,0.02051997],"genre_scores_gemma":[0.9698055,0.0000692922,0.02272453,0.00004305627,0.00001945057,0.0001245969,0.00003488686,0.00002974337,0.007148904],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7543436,"threshold_uncertainty_score":0.8305624,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4413479467","doi":"10.1016/j.finr.2025.100047","title":"Volatility discovery in G-7 stock markets based on evidence from realized kernels","year":2025,"lang":"en","type":"article","venue":"Finance Research Open","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":"Price discovery; Volatility (finance); Stock (firearms); Financial economics; Econometrics; Business; Monetary economics; Economics; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.1430246268484885,"gpt":0.3908380483696591,"spread":0.2478134215211706,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009022688,0.0002122623,0.0006536449,0.0004915592,0.0002146174,0.0005791113,0.001708566,0.0001776514,0.0007598379],"category_scores_gemma":[0.004109638,0.000233982,0.0001106895,0.001330366,0.0001553119,0.0009284474,0.0008401949,0.0007390613,0.00008000516],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006259566,"about_ca_system_score_gemma":0.0003537253,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01789981,"about_ca_topic_score_gemma":0.002089213,"domain_scores_codex":[0.9966865,0.0004245403,0.0008381337,0.001178844,0.0001803733,0.0006916148],"domain_scores_gemma":[0.9960954,0.002023764,0.0001848164,0.001514803,0.0001043797,0.00007690364],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001821837,0.0003638057,0.9598387,0.00008808523,0.00001877682,0.00001722627,0.0000747884,0.00008004566,0.00001088199,0.02500676,0.005876778,0.006802286],"study_design_scores_gemma":[0.0007281116,0.00004848126,0.5882872,0.0005016205,7.645555e-7,3.2262e-8,0.000007327585,0.3354208,0.0000160302,0.06409059,0.01075596,0.000143091],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8700373,0.001274042,0.004195732,0.003635573,0.0002781376,0.002036387,0.0009060418,0.00002107464,0.1176158],"genre_scores_gemma":[0.9875064,0.0005242912,0.0007986892,0.0001919072,0.00002775011,0.0003354735,0.00004620222,0.00001873667,0.01055055],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3715515,"threshold_uncertainty_score":0.9886401,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W7114894119","doi":"10.1016/j.finr.2025.100082","title":"Greenwashing and the efficiency of new information price discovery","year":2025,"lang":"en","type":"article","venue":"Finance Research Open","topic":"Auditing, Earnings Management, Governance","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Trinity Western University; Western University; Simon Fraser University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Greenwashing; Corporate governance; Stock (firearms); Stock price; Price discovery","retraction":null,"screen_n_in":null,"score":{"opus":0.02434157570433123,"gpt":0.3055512530631353,"spread":0.2812096773588041,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.003011432,0.0000921731,0.0001781727,0.0002100501,0.0003919301,0.001345344,0.001167043,0.00002996477,0.00002824829],"category_scores_gemma":[0.01150419,0.00006717385,0.00002948619,0.001342283,0.00022477,0.00705529,0.002742987,0.000277139,0.00007786979],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003750959,"about_ca_system_score_gemma":0.0001174866,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006176846,"about_ca_topic_score_gemma":0.0000823856,"domain_scores_codex":[0.9986963,0.00003342823,0.0002763576,0.0001876033,0.0004866044,0.0003197141],"domain_scores_gemma":[0.9970394,0.0002178828,0.00220489,0.0003313995,0.0002006194,0.000005741644],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001781568,0.0000216096,0.006047062,0.0003264884,0.00001617981,0.000001253494,0.0002281503,0.0001848308,0.00002387628,0.7427378,0.04146275,0.2087719],"study_design_scores_gemma":[0.001873423,0.00001131362,0.07743263,0.0004938789,0.00001174292,2.355443e-7,0.000525261,0.003295817,0.00009672472,0.01575165,0.9003806,0.0001267896],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3575158,0.0006089864,0.1833807,0.02161877,0.0002405746,0.003014079,0.000005167836,0.00005001442,0.433566],"genre_scores_gemma":[0.9827653,0.0001935018,0.0002083387,0.0008948439,0.0001219603,0.00005311551,0.000005748611,0.00000714155,0.01575001],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8589178,"threshold_uncertainty_score":0.9996914,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4415956441","doi":"10.1016/j.finr.2025.100073","title":"Does the yield curve affect the systemic risk between the stocks of FinTech and traditional finance companies?","year":2025,"lang":"en","type":"article","venue":"Finance Research Open","topic":"FinTech, Crowdfunding, Digital Finance","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"","keywords":"Social connectedness; Systemic risk; Affect (linguistics); Yield curve; Yield (engineering); Financial market","retraction":null,"screen_n_in":null,"score":{"opus":0.09944394463848207,"gpt":0.3415747791733205,"spread":0.2421308345348384,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.004808354,0.0002293618,0.0003838332,0.0001734682,0.001390583,0.001212032,0.002964879,0.00009679449,0.00003506335],"category_scores_gemma":[0.002153056,0.00009966713,0.0001025815,0.001633606,0.001104825,0.001090649,0.001963346,0.001018631,0.00006412606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007337249,"about_ca_system_score_gemma":0.0001537464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002935211,"about_ca_topic_score_gemma":0.0005567716,"domain_scores_codex":[0.9977046,0.0001588491,0.0004360937,0.000487739,0.0006383717,0.0005743479],"domain_scores_gemma":[0.9953316,0.003077943,0.0003563937,0.0008610623,0.000365082,0.000007854909],"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":[0.0002978689,0.0001625441,0.2029792,0.0009183241,0.0001842145,0.00001243076,0.0003520966,0.0002053239,0.0001448708,0.5448717,0.195271,0.05460036],"study_design_scores_gemma":[0.0006039821,0.00008236129,0.7363303,0.002528823,0.00005285743,0.000005143866,0.0007138883,0.002091179,0.0005823957,0.07350382,0.1831873,0.0003178632],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9414901,0.001713959,0.0009120995,0.01568151,0.00040261,0.003905649,0.0002417187,0.00005018226,0.03560217],"genre_scores_gemma":[0.9952537,0.0004066349,0.0000276139,0.0002141308,0.0003105541,0.0004491576,0.00001361569,0.00002100517,0.003303598],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5333511,"threshold_uncertainty_score":0.9999095,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4416333281","doi":"10.1016/j.finr.2025.100072","title":"Evasive shareholder meetings, meeting announcement lag, and stock price crash risk","year":2025,"lang":"en","type":"article","venue":"Finance Research Open","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Shareholder; Stock price; Stock (firearms); Shareholder value; Crash","retraction":null,"screen_n_in":null,"score":{"opus":0.1046869288896011,"gpt":0.3473528437535053,"spread":0.2426659148639042,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004705443,0.0002172765,0.0004872987,0.0003541862,0.0008725208,0.000835183,0.0009772327,0.0001292247,0.0002608327],"category_scores_gemma":[0.001612527,0.0002322602,0.00006142264,0.0008874611,0.0002445989,0.000750969,0.001317042,0.0005171988,0.000193443],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000225839,"about_ca_system_score_gemma":0.0002097081,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003439789,"about_ca_topic_score_gemma":0.0001867812,"domain_scores_codex":[0.9974194,0.0001276256,0.0006308886,0.0008724876,0.0001462711,0.0008033175],"domain_scores_gemma":[0.9985716,0.0002995878,0.0002978225,0.0005432445,0.0002037762,0.00008391145],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00010051,0.0001897176,0.1333984,0.0001847829,0.00008082208,0.00001363926,0.0005853129,0.00005657311,0.00003546536,0.7525439,0.1032563,0.00955455],"study_design_scores_gemma":[0.0008687348,0.0002069898,0.2859706,0.0003748304,0.000004455217,8.834654e-7,0.0003161808,0.0007660933,0.0001163452,0.1180601,0.5930009,0.0003137871],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2778368,0.01025772,0.000196512,0.003790259,0.000311126,0.002084238,0.0004094475,0.00003912099,0.7050748],"genre_scores_gemma":[0.9470055,0.01524831,0.002976222,0.0006442157,0.0001575538,0.0008432717,0.00004154479,0.00004709969,0.03303628],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6720385,"threshold_uncertainty_score":0.9471295,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}