{"meta":{"query_hash":"b56d635493ab","filters":{"venue":"International Journal of Innovative Research in Engineering & Management"},"cohort_total":2,"direct_labels_cover":0,"predictions_cover":2,"exported":2,"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/b56d635493ab","api":"https://metacan.xera.ac/api/v1/cohort?venue=International+Journal+of+Innovative+Research+in+Engineering+%26+Management"},"results":[{"id":"W4399807558","doi":"10.55524/ijirem.2024.11.3.9","title":"Global Financial Resilience: Assessing Opportunities and Challenges in Cross-Border Insolvency under the Paradigms of Universalism and Territorialism","year":2024,"lang":"en","type":"article","venue":"International Journal of Innovative Research in Engineering & Management","topic":"Corporate Insolvency and Governance","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":"Regent College","funders":"","keywords":"Universalism; Insolvency; Harmonization; Sovereignty; Creditor; Vulnerability (computing); Political science; International regime; Financial distress; Resilience (materials science); Bankruptcy; Business; Finance; Financial system; Law; Debt","score_opus":0.09842895654229471,"score_gpt":0.39619239147745333,"score_spread":0.2977634349351586,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399807558","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":[0.92680836,0.0010750184,0.005986295,0.0041228575,0.00004396823,0.00009284173,0.00014572816,0.000020855758,0.061704155],"genre_scores_gemma":[0.9989458,0.00020480521,0.00047370925,0.00005991053,0.000007284522,0.000025100499,0.000037710404,0.0000039165016,0.0002417484],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9975562,0.0011998097,0.00011106668,0.00023219832,0.00035273176,0.0005479473],"domain_scores_gemma":[0.993901,0.0021623257,0.0017482672,0.0005416776,0.00076833507,0.0008783118],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0044991807,0.0005550737,0.0004764802,0.0041855834,0.0016076734,0.005607268,0.00060129125,0.0012385567,0.003229504],"category_scores_gemma":[0.011291672,0.0001830689,0.00051931676,0.003684193,0.0072774896,0.011424784,0.010772838,0.0012576298,0.00019807841],"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":[0.00045205117,0.00022182187,0.45103177,0.0005694198,0.0003887749,0.0019373915,0.04067226,0.018273806,0.0009886661,0.39071506,0.0036178532,0.09113116],"study_design_scores_gemma":[0.00003195781,0.00061161735,0.4107388,0.0011337631,0.00022311625,0.0013778863,0.2556522,0.0171003,0.0010181342,0.28473166,0.027255144,0.0001254402],"about_ca_topic_score_codex":0.0021559165,"about_ca_topic_score_gemma":0.0028046386,"teacher_disagreement_score":0.005607268,"about_ca_system_score_codex":0.0024106782,"about_ca_system_score_gemma":0.0018224336,"threshold_uncertainty_score":0.023794234},"labels":[],"label_agreement":null},{"id":"W4400240895","doi":"10.55524/ijirem.2024.11.3.12","title":"Investigating Financial Risk Behavior Prediction Using Deep Learning and Big Data","year":2024,"lang":"en","type":"article","venue":"International Journal of Innovative Research in Engineering & Management","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","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":"","funders":"","keywords":"Deep learning; Artificial intelligence; Model risk; Computer science; Financial market; Machine learning; Robustness (evolution); Risk management; Transaction data; Big data; Artificial neural network; Trading strategy; Supervised learning; Financial risk; Unsupervised learning; Finance; Database transaction; Data mining; Business; Database","score_opus":0.3318535365674535,"score_gpt":0.5100316850812813,"score_spread":0.1781781485138278,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400240895","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.68829477,0.0020781953,0.29935205,0.0041900584,0.00015013205,0.000102066566,0.0009949214,0.0005790207,0.004258787],"genre_scores_gemma":[0.9727568,0.00047610013,0.025513783,0.00015278351,0.000045967518,0.00003441853,0.0004479428,0.000012092587,0.0005602287],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99948716,0.00017606688,0.000035068835,0.00009582172,0.00014169136,0.000064247164],"domain_scores_gemma":[0.9959978,0.0028289072,0.00041666479,0.0002883774,0.00031636926,0.0001519403],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021476827,0.0008894285,0.00046724384,0.00094913295,0.0003045079,0.0013424507,0.001051051,0.0011170406,0.0006963889],"category_scores_gemma":[0.007985048,0.0003495872,0.0004193538,0.00085014716,0.00061292225,0.0025186625,0.0010007856,0.0017657073,0.00013256566],"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":[0.0001984421,0.00048031966,0.08381091,0.00017324694,0.00023919684,0.00025910058,0.0001758856,0.8192041,0.0020985766,0.012249097,0.0020330276,0.07907817],"study_design_scores_gemma":[0.0000026091273,0.000016342716,0.001811649,0.0000084639305,0.0000050835265,0.000009817713,0.000018289049,0.9932805,0.00042143895,0.004268386,0.00015347151,0.0000040150885],"about_ca_topic_score_codex":0.007014957,"about_ca_topic_score_gemma":0.00788131,"teacher_disagreement_score":0.007014957,"about_ca_system_score_codex":0.0008392876,"about_ca_system_score_gemma":0.0008955807,"threshold_uncertainty_score":0.013948262},"labels":[],"label_agreement":null}]}