{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":2,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":2,"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":"7993d2afe6a6","filters":{"venue":"AWARI"}},"results":[{"id":"W4403038106","doi":"10.47909/awari.65","title":"Impact of COVID-19 on Indian biomedical research: A bibliometric analysis using online data from 2017 to 2022","year":2024,"lang":"en","type":"article","venue":"AWARI","topic":"COVID-19 Clinical Research Studies","field":"Medicine","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":"Coronavirus disease 2019 (COVID-19); 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Bibliometrics; Data science; Library science; Computer science; Virology; Medicine; Internal medicine; Outbreak","authors":[{"name":"Mohit Kumar Patralekh","is_ca":false},{"name":"Raju Vaishya","is_ca":false},{"name":"Abhishek Vaish","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.5728260737664915,"gpt":0.6527992317427705,"spread":0.07997315797627902,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","bibliometrics","insufficient_payload"],"consensus_categories":["bibliometrics"],"category_scores_codex":[0.005151142,0.0002078193,0.0008243861,0.1123674,0.0001618141,0.00009224467,0.0009716288,0.0001822468,0.001885352],"category_scores_gemma":[0.1787955,0.000148241,0.0003745153,0.23968,0.0004952022,0.0001310913,0.001985619,0.001111933,0.0002382633],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009288756,"about_ca_system_score_gemma":0.004042753,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03260732,"about_ca_topic_score_gemma":0.00068047,"domain_scores_codex":[0.9944724,0.000395617,0.0006497038,0.001066783,0.002696451,0.0007190653],"domain_scores_gemma":[0.9681395,0.02658707,0.0000889343,0.002702525,0.0004113214,0.002070692],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.002371946,0.005341639,0.387418,0.002176998,0.02399738,0.007111485,0.002876096,0.0009820423,0.01059812,0.00004932151,0.4626014,0.09447552],"study_design_scores_gemma":[0.001872259,0.004136964,0.8042898,0.0005510942,0.001573725,0.000004957848,0.0003963407,0.06980131,0.00004520829,0.0004834369,0.116477,0.0003679313],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9697381,0.001470819,0.002460709,0.01814082,0.0001586839,0.000602644,0.007276908,0.00008539962,0.00006593076],"genre_scores_gemma":[0.9945822,0.001269756,0.0008813789,0.0008791923,0.0005321305,0.00001079696,0.00146731,0.0000303158,0.0003469185],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4168718,"threshold_uncertainty_score":0.9990271,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4313023361","doi":"10.47909/awari.149","title":"When the attributive becomes relational. A look at the innovative sector in Argentina based on regional customer and supplier networks by activity branch (2012-2018)","year":2022,"lang":"en","type":"article","venue":"AWARI","topic":"Global Trade and Competitiveness","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Centrality; Business; Attributive; Economic geography; Latin Americans; Industrial organization; Marketing; Regional science; Commerce; Geography; Political science; Mathematics","authors":[{"name":"Nicolás Vladimir Chuchco","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02421326739000654,"gpt":0.2142972697740829,"spread":0.1900840023840764,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004738999,0.0001584945,0.0001445571,0.0000803242,0.0006235329,0.00007485723,0.0002046165,0.00004225245,0.001269685],"category_scores_gemma":[0.00002331176,0.0001071786,0.00004560322,0.0006735383,0.0001212803,0.0002990688,0.0002944912,0.0003568678,0.00004468641],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001153398,"about_ca_system_score_gemma":0.00003260803,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003601146,"about_ca_topic_score_gemma":0.0001528644,"domain_scores_codex":[0.998907,0.00008003169,0.0001425024,0.0002881825,0.0003256018,0.0002567335],"domain_scores_gemma":[0.9992715,0.0003079441,0.0001470672,0.0001914124,0.00007358599,0.000008460072],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004623828,0.0003815296,0.7215008,0.00002649252,0.00008165686,0.000009960409,0.0001840555,0.005146429,0.0001180508,0.05457016,0.2161594,0.001359071],"study_design_scores_gemma":[0.0005971334,0.000011798,0.488454,0.00001204397,0.00001486702,0.00000150242,0.0001416897,0.003693678,0.00001301907,0.001113014,0.5057978,0.0001494125],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.959609,0.0002763975,0.0006553766,0.02762489,0.0004188711,0.0007048686,0.00008254757,0.00004515254,0.01058284],"genre_scores_gemma":[0.9917107,0.000004476368,0.000003731738,0.006554515,0.000210817,0.000132288,0.0001752884,0.00001411507,0.001194113],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2896384,"threshold_uncertainty_score":0.9996433,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}