{"meta":{"query_hash":"b4669cef076c","filters":{"venue":"NAIST Digital Library (Nara Institute of Science and Technology)"},"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/b4669cef076c","api":"https://metacan.xera.ac/api/v1/cohort?venue=NAIST+Digital+Library+%28Nara+Institute+of+Science+and+Technology%29"},"results":[{"id":"W7018314500","doi":"","title":"Designing Efficient Neural Attention Systems Towards Achieving Human-level Sharp Vision","year":2019,"lang":"en","type":"article","venue":"NAIST Digital Library (Nara Institute of Science and Technology)","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Artificial neural network; Feature (linguistics); Deep learning; Key (lock)","score_opus":0.017263353830875326,"score_gpt":0.24793699155279364,"score_spread":0.23067363772191832,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7018314500","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021960884,0.00027897098,0.97382754,0.00019425247,0.000070823466,0.00008274703,0.00004121974,0.0013447464,0.0021988065],"genre_scores_gemma":[0.59168404,0.0003589732,0.39719826,0.000408436,0.00006865015,0.00016627023,0.00016774442,0.00031213334,0.009635391],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99960023,0.0000732388,0.000020171794,0.00013472489,0.00008216198,0.00008943359],"domain_scores_gemma":[0.9996277,0.00010508326,0.000030974665,0.00006423549,0.00013723032,0.000034661836],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000911405,0.00083339354,0.0006416163,0.00034130513,0.00042915816,0.0013227082,0.0012548437,0.0014048818,0.0047760494],"category_scores_gemma":[0.002127776,0.0005544516,0.00050292915,0.00035260967,0.00045386227,0.0015731839,0.001456522,0.0015182074,0.0013808636],"study_design_candidate":"simulation_or_modeling","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":[0.00033470232,0.00030616246,0.001140491,0.00023668486,0.0001416462,0.00018197135,0.00026823618,0.2878223,0.17445156,0.019467557,0.007876922,0.5077718],"study_design_scores_gemma":[0.000016577418,0.00009913666,0.00032726472,0.000009985851,0.000027656617,0.000040284835,0.0000426969,0.9643596,0.025847672,0.006931707,0.0022886829,0.000008805695],"about_ca_topic_score_codex":0.0046712533,"about_ca_topic_score_gemma":0.008229654,"teacher_disagreement_score":0.0047760494,"about_ca_system_score_codex":0.0009068068,"about_ca_system_score_gemma":0.0012439785,"threshold_uncertainty_score":0.015977502},"labels":[],"label_agreement":null}]}