{"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":"6a01426c59a9","filters":{"venue":"Chinese Journal of Drug Application and Monitoring"}},"results":[{"id":"W2374058115","doi":"","title":"Bibliometric analysis of research papers on mutant prevention concentration","year":2010,"lang":"en","type":"article","venue":"Chinese Journal of Drug Application and Monitoring","topic":"Tuberculosis Research and Epidemiology","field":"Medicine","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":"Medicine; China; MEDLINE; Bibliometrics; Science Citation Index; Citation; Family medicine; Library science","authors":[{"name":"You-ning Liu","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03777798816639439,"gpt":0.435835863956052,"spread":0.3980578757896576,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.0135291,0.001219373,0.004135975,0.2388744,0.001356408,0.00516495,0.001454169,0.0009306867,0.007221493],"category_scores_gemma":[0.09852274,0.000376693,0.003828486,0.253774,0.0008373545,0.004162463,0.001928532,0.0005019308,0.001032511],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003733559,"about_ca_system_score_gemma":0.005921344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00455441,"about_ca_topic_score_gemma":0.004221315,"domain_scores_codex":[0.9712922,0.00448311,0.008341145,0.001647224,0.01355808,0.0006782099],"domain_scores_gemma":[0.896338,0.05897566,0.02171323,0.00209089,0.01970376,0.001178346],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001366736,0.0003489714,0.3349382,0.137003,0.0107586,0.001675004,0.003061505,0.003684648,0.003768211,0.00396972,0.02116557,0.4782599],"study_design_scores_gemma":[0.0003525949,0.0008703735,0.8478055,0.02025787,0.01851644,0.003905909,0.007204696,0.008978626,0.004254514,0.006356794,0.08118299,0.0003136155],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4715449,0.3788918,0.008496648,0.004627109,0.001127051,0.003330427,0.09363587,0.0008259024,0.03752027],"genre_scores_gemma":[0.8150198,0.1330156,0.01293172,0.0003301629,0.001167373,0.00249604,0.03221447,0.000104633,0.002720203],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7611256,"threshold_uncertainty_score":0.07154959,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2352966579","doi":"","title":"Impact and analysis of the utilization of antibacterial drugs for special use in a first-class hospital with special rectification activities of antibacterials","year":2013,"lang":"en","type":"article","venue":"Chinese Journal of Drug Application and Monitoring","topic":"Pharmacy and Medical Practices","field":"Pharmacology, Toxicology and Pharmaceutics","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":"Medicine; Quarter (Canadian coin); Antibiotics; Antibacterial activity; Toxicology; Microbiology","authors":[{"name":"Chen Ji-zh","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05642297238130507,"gpt":0.4135181285135342,"spread":0.3570951561322291,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008615633,0.0002321381,0.0003248964,0.001172968,0.0002342236,0.0006904306,0.000355387,0.0002997235,0.001805091],"category_scores_gemma":[0.004026002,0.0001496575,0.001004437,0.001348872,0.0002788606,0.0004270477,0.0006614188,0.0005137899,0.0001311317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001627042,"about_ca_system_score_gemma":0.002806572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01785896,"about_ca_topic_score_gemma":0.01966362,"domain_scores_codex":[0.998147,0.0004187561,0.0002485637,0.0002286954,0.0004776934,0.0004793024],"domain_scores_gemma":[0.9952037,0.0005056456,0.002737603,0.0001367724,0.0005921996,0.0008240615],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000153309,0.0001043489,0.9909058,0.00006746056,0.00009183302,0.0001240597,0.00009956324,0.0001414665,0.0003204037,0.00003418526,0.0002025921,0.007754984],"study_design_scores_gemma":[0.000002530288,0.00009474999,0.9992393,0.000008968101,0.00002333654,0.00005306119,0.0002041278,0.0001415657,0.0000802057,0.000006530252,0.0001430015,0.000002678776],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982349,0.0004710591,0.00007285446,0.0002195135,0.000009744779,0.00001766255,0.0003768689,0.000006171799,0.000591307],"genre_scores_gemma":[0.9992589,0.0002248594,0.0000869132,0.00003821732,0.00001134093,0.000006842076,0.000227868,0.000001328248,0.0001436408],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01785896,"threshold_uncertainty_score":0.03551,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}