{"meta":{"query_hash":"51f4f708f758","filters":{"venue":"International Journal of Advanced Astronomy"},"cohort_total":1,"direct_labels_cover":0,"predictions_cover":1,"exported":1,"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/51f4f708f758","api":"https://metacan.xera.ac/api/v1/cohort?venue=International+Journal+of+Advanced+Astronomy"},"results":[{"id":"W2948418926","doi":"10.14419/ijaa.v7i1.18029","title":"Big data in astronomy: from evolution to revolution","year":2019,"lang":"en","type":"article","venue":"International Journal of Advanced Astronomy","topic":"CCD and CMOS Imaging Sensors","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Astronomy; Big data; Physics; Computer science","score_opus":0.009724964833568142,"score_gpt":0.23807486765184674,"score_spread":0.2283499028182786,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2948418926","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014766087,0.8905618,0.0110936295,0.07094169,0.0066426704,0.00006806438,0.00025531385,0.00020256943,0.018757673],"genre_scores_gemma":[0.027794365,0.91978705,0.011866873,0.021285674,0.013723914,0.00010401271,0.0002819319,0.00007748817,0.0050785453],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99597114,0.0015059775,0.00032366297,0.00040625574,0.001545928,0.00024693008],"domain_scores_gemma":[0.98823684,0.008266072,0.00049022445,0.0005283446,0.0017727539,0.0007057361],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0048713754,0.0007192992,0.0010204377,0.0036006884,0.0014576834,0.008075731,0.0015939538,0.0034007488,0.0035408745],"category_scores_gemma":[0.009361738,0.0004634974,0.00062526355,0.006557539,0.004488681,0.015800696,0.0033346512,0.0051032407,0.0012457093],"study_design_candidate":"not_applicable","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":[0.000112593465,0.00006638784,0.0018610026,0.0075622792,0.00011551708,0.00032023882,0.0012630384,0.001241208,0.0010576653,0.3873973,0.14864404,0.4503587],"study_design_scores_gemma":[0.000008498183,0.000048063688,0.00095464214,0.0032490257,0.000029277002,0.00036508078,0.0007892588,0.00088962406,0.00030241447,0.13694328,0.8563747,0.000046201905],"about_ca_topic_score_codex":0.0016912315,"about_ca_topic_score_gemma":0.0014049534,"teacher_disagreement_score":0.008075731,"about_ca_system_score_codex":0.0029173668,"about_ca_system_score_gemma":0.003854904,"threshold_uncertainty_score":0.025762558},"labels":[],"label_agreement":null}]}