{"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":"967599b6561f","filters":{"venue":"International Journal of Global Operations Research"}},"results":[{"id":"W4205880214","doi":"10.47194/ijgor.v2i3.111","title":"Does the Covid-19 Outbreak Impacts On Economic Growth? An Evidence from Indonesia","year":2021,"lang":"en","type":"article","venue":"International Journal of Global Operations Research","topic":"SMEs Development and Digital Marketing","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Foreign direct investment; Pandemic; Coronavirus disease 2019 (COVID-19); Quarter (Canadian coin); Panel data; Economics; Variables; Regression analysis; Demographic economics; Investment (military); Time series; Cross-sectional data; Variable (mathematics); Econometrics; Geography; Macroeconomics; Statistics; Mathematics; Political science; Medicine; Politics","authors":[{"name":"Hilda Aprina","is_ca":false},{"name":"Muhammad Majid","is_ca":false},{"name":"Vivi Silvia","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1068859535214211,"gpt":0.4633853424796675,"spread":0.3564993889582463,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.003033398,0.00007457264,0.0001038274,0.00009565971,0.0006296743,0.001498834,0.0009883068,0.00005682811,0.0006170731],"category_scores_gemma":[0.00928153,0.0000441644,0.00007640627,0.0002587984,0.0002336525,0.001240127,0.0001538632,0.0002564855,0.00007524628],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001745536,"about_ca_system_score_gemma":0.004759561,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006374206,"about_ca_topic_score_gemma":0.02246641,"domain_scores_codex":[0.9969462,0.0009329719,0.0003561202,0.0001707063,0.001364228,0.000229733],"domain_scores_gemma":[0.9963721,0.001419083,0.00007137088,0.0001281008,0.001696391,0.0003129613],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007635872,0.0003484634,0.8124003,0.000005096335,0.0003752636,0.0005828131,0.01041711,0.003617345,0.0004931874,0.1398383,0.01990502,0.01125355],"study_design_scores_gemma":[0.002659455,0.0004700042,0.780013,0.0006250528,0.00004155763,0.0002654725,0.04531211,0.001438928,0.001528037,0.04465571,0.1222829,0.000707739],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8899131,0.0001464663,0.000148477,0.1002841,0.001218803,0.00009866157,0.0000525303,0.000009514778,0.008128352],"genre_scores_gemma":[0.996488,0.0004469967,0.0003247264,0.001307606,0.00112656,0.000004601493,0.00000992136,0.000004295528,0.0002873235],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1065749,"threshold_uncertainty_score":0.9995377,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3217152209","doi":"10.47194/ijgor.v2i2.81","title":"Determining Agricultural Premium Insurance in Malang City using Black Scholes Model","year":2021,"lang":"en","type":"article","venue":"International Journal of Global Operations Research","topic":"Leadership, Behavior, and Decision-Making Studies","field":"Decision Sciences","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":"Percentile; Production (economics); Economics; Agriculture; Black–Scholes model; Econometrics; Quarter (Canadian coin); Agricultural science; Agricultural economics; Actuarial science; Mathematics; Statistics; Environmental science; Geography; Microeconomics","authors":[{"name":"Herlia Widi","is_ca":false},{"name":"Dea Nisa Rahma Lani","is_ca":false},{"name":"Faridatul Hasanah","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.4471062417764923,"gpt":0.5628702858025151,"spread":0.1157640440260227,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.003412287,0.0001304153,0.0002945606,0.0003928756,0.0002650327,0.001253849,0.001259336,0.00009061222,0.00009008277],"category_scores_gemma":[0.00942091,0.00009262402,0.0001672847,0.001308454,0.0002220434,0.001311338,0.0004204106,0.0005688309,0.0000415605],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006933013,"about_ca_system_score_gemma":0.0008308977,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006166314,"about_ca_topic_score_gemma":0.0008663728,"domain_scores_codex":[0.9935661,0.0004908765,0.001080644,0.0003380211,0.004202605,0.0003217831],"domain_scores_gemma":[0.9904963,0.0006697393,0.0001503617,0.0002443695,0.008314745,0.0001245107],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0001152058,0.0003667588,0.4254501,0.000002294725,0.00007867912,0.0009529226,0.002229217,0.54847,0.008157321,0.002867218,0.001964157,0.009346058],"study_design_scores_gemma":[0.002167123,0.0001225437,0.7479055,0.0006391332,0.00001672063,0.001537019,0.0232885,0.2107394,0.002174088,0.01047976,0.000519938,0.0004102723],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9895627,0.0002875443,0.004765677,0.002947324,0.0005851957,0.00008056781,0.00005306891,0.000005383507,0.001712551],"genre_scores_gemma":[0.9914134,0.00004678303,0.007695782,0.00008442531,0.0002728013,0.000002458986,0.000002233258,0.000005308894,0.0004768092],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3377306,"threshold_uncertainty_score":0.9997829,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}