{"meta":{"query_hash":"4162f1ed035f","filters":{"venue":"Jisuanji shenghuojia."},"cohort_total":2,"direct_labels_cover":0,"predictions_cover":2,"exported":2,"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/4162f1ed035f","api":"https://metacan.xera.ac/api/v1/cohort?venue=Jisuanji+shenghuojia."},"results":[{"id":"W4401667168","doi":"10.54097/ntsgdq10","title":"Integrating Blockchain and Deep Reinforcement Learning for Secure and Efficient Supply Chain Management in Tertiary Institutions","year":2024,"lang":"en","type":"article","venue":"Jisuanji shenghuojia.","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":1,"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 Toronto","funders":"","keywords":"Blockchain; Reinforcement learning; Supply chain; Computer science; Supply chain management; Architecture; Computer security; Process management; Artificial intelligence; Business; Marketing","score_opus":0.00930446441421307,"score_gpt":0.25538435424557177,"score_spread":0.2460798898313587,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401667168","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18637708,0.0025245077,0.80528,0.0035820522,0.00016636742,0.0010230442,0.0000017489996,0.00043593146,0.000609244],"genre_scores_gemma":[0.98006237,0.00013483997,0.018986737,0.00018764372,0.000030394873,0.00045425264,0.0000081808685,0.000012056843,0.000123549],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985696,0.0000372241,0.00032080343,0.0005930286,0.00013773872,0.00034159815],"domain_scores_gemma":[0.9994111,0.0001308966,0.00004466718,0.00030773287,0.00003132342,0.00007427493],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059464143,0.0001931808,0.00016922374,0.00042595263,0.00031143927,0.00018287358,0.0003108474,0.00012975668,0.000004065064],"category_scores_gemma":[0.000037246587,0.00017918574,0.000043398148,0.0005308934,0.00011701169,0.00008380775,0.00040837706,0.0003810497,0.0000040006835],"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":[0.0000037979898,0.000047011177,0.00054561626,0.00016959418,0.0000344715,0.000022887902,0.0029209107,0.0069599687,0.000096131225,0.88381565,0.00006620435,0.10531776],"study_design_scores_gemma":[0.0003589866,0.00006462891,0.00093133195,0.00013482632,0.00001555936,0.000026583348,0.00058481004,0.98162174,0.0001398366,0.007021756,0.008893139,0.00020681832],"about_ca_topic_score_codex":0.00003211249,"about_ca_topic_score_gemma":0.00009540267,"teacher_disagreement_score":0.97466177,"about_ca_system_score_codex":0.00008315731,"about_ca_system_score_gemma":0.000033961736,"threshold_uncertainty_score":0.7306982},"labels":[],"label_agreement":null},{"id":"W4401667261","doi":"10.54097/f09tdt83","title":"Adaptive Neural Network Architectures for Cross-Domain Generalization","year":2024,"lang":"en","type":"article","venue":"Jisuanji shenghuojia.","topic":"Domain Adaptation and Few-Shot Learning","field":"Computer Science","cited_by":3,"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 British Columbia","funders":"","keywords":"Computer science; Modular design; Robustness (evolution); Adaptability; Artificial intelligence; Artificial neural network; Benchmark (surveying); Machine learning; Domain (mathematical analysis)","score_opus":0.026714083933541872,"score_gpt":0.3048156728266197,"score_spread":0.27810158889307784,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401667261","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02923758,0.0011759078,0.96342283,0.00091694127,0.0019028627,0.0004102065,0.0000071333,0.00075452187,0.002172031],"genre_scores_gemma":[0.8801165,0.0000067389196,0.115376376,0.0011542779,0.0010863631,0.00009449228,0.000023904731,0.000041601765,0.0020997291],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99811697,0.0001176177,0.0003233388,0.00061197113,0.00031509984,0.0005149996],"domain_scores_gemma":[0.9990135,0.00031589402,0.0000719136,0.00036384616,0.000099382865,0.0001354584],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005361009,0.00022927961,0.0001945096,0.00015682886,0.00034333125,0.0008372483,0.00055876217,0.00009914774,0.00005650404],"category_scores_gemma":[0.00007158349,0.00020831006,0.00018024753,0.0006496746,0.000071955175,0.00026185982,0.00013551247,0.00024017281,0.000060339004],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006186763,0.000035635025,0.00072334916,0.00006622188,0.00008349911,0.000042288102,0.0033471172,0.43933094,0.00027182783,0.42284554,0.011471397,0.121720314],"study_design_scores_gemma":[0.00030806597,0.00012411442,0.0021129085,0.000035880137,0.000008464142,0.000019971107,0.00003229294,0.8871136,0.00007111196,0.036370076,0.073538944,0.0002645874],"about_ca_topic_score_codex":0.000010381444,"about_ca_topic_score_gemma":0.000017308617,"teacher_disagreement_score":0.85087895,"about_ca_system_score_codex":0.00006429512,"about_ca_system_score_gemma":0.00008763335,"threshold_uncertainty_score":0.84946376},"labels":[],"label_agreement":null}]}