{"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":"c63d448be4b1","filters":{"venue":"국토연구"}},"results":[{"id":"W2118947320","doi":"","title":"광역시 주택가격 변화의 특징과 요인 분석","year":2008,"lang":"ko","type":"article","venue":"국토연구","topic":"Korean Urban and Social Studies","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Metropolitan area; House price; Falling (accident); Economics; Demographic economics; Price index; Panel data; Population; Quarter (Canadian coin); Geography; Econometrics; Demography","authors":[{"name":"한동근","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02288993940954977,"gpt":0.209572893143734,"spread":0.1866829537341842,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001259089,0.0002205373,0.0002640708,0.00001986149,0.0009339193,0.00002634714,0.0002913355,0.0001245355,0.005992166],"category_scores_gemma":[0.00004805053,0.0002096582,0.0001469652,0.0002309947,0.0008408077,0.0001303746,0.0002783982,0.0001953322,0.01184858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002324734,"about_ca_system_score_gemma":0.00002105363,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001580241,"about_ca_topic_score_gemma":0.0002884344,"domain_scores_codex":[0.9983797,0.00006174194,0.0002250653,0.000376708,0.0004369353,0.00051986],"domain_scores_gemma":[0.9994278,0.00004873499,0.0000743755,0.0002616317,0.000008443285,0.0001790435],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003289451,0.0003693692,0.5749867,0.00002263276,0.0001071775,0.0002830607,0.01544992,0.00002751221,0.0009261782,0.001735072,0.3877725,0.01828702],"study_design_scores_gemma":[0.0003691984,0.000093082,0.7894846,0.00001619918,0.0000258415,0.00001362264,0.0008221464,0.00003210753,0.0003819614,0.0005935292,0.2078111,0.000356541],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.691877,0.001705782,0.00002635858,0.001674442,0.000698128,0.000204986,0.00003175374,0.00007474957,0.3037068],"genre_scores_gemma":[0.9473473,0.001850405,0.0001488127,0.0007009907,0.0003680351,0.000006346419,0.000003647745,0.00002132579,0.04955306],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2554704,"threshold_uncertainty_score":0.9949165,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1676439929","doi":"","title":"오피스시장의 시장 자본환원율 추정에 관한 연구","year":2012,"lang":"ko","type":"article","venue":"국토연구","topic":"Advanced Statistical Modeling Techniques","field":"Computer Science","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":"Capitalization; Quarter (Canadian coin); Econometrics; Constant (computer programming); Statistics; Mathematics; Market capitalization; Economics; Geography; Computer science","authors":[{"name":"이동준","is_ca":false},{"name":"이용만","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04023320477353401,"gpt":0.3303867544562675,"spread":0.2901535496827335,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005259335,0.0003377914,0.0003564143,0.0001044782,0.0002145012,0.0001593246,0.001194787,0.0002160284,0.0001959533],"category_scores_gemma":[0.0003719181,0.0003304505,0.0001100135,0.0003811505,0.0001742888,0.0009296104,0.000740371,0.0004961324,0.001198971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001319643,"about_ca_system_score_gemma":0.00008044695,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005236691,"about_ca_topic_score_gemma":0.000004808283,"domain_scores_codex":[0.9972377,0.0001353225,0.0004603594,0.0005775138,0.0005175012,0.001071635],"domain_scores_gemma":[0.9977326,0.000318977,0.000152075,0.001182845,0.0001508007,0.0004627162],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002130739,0.000419618,0.004996141,0.0001086676,0.00003961633,0.00005110163,0.001636827,0.0001092239,0.0009890735,0.7744675,0.01371313,0.2034478],"study_design_scores_gemma":[0.000916308,0.0006842357,0.01723204,0.0005506005,0.0001250639,0.0001316582,0.00006775773,0.3181273,0.01342695,0.5615714,0.08452447,0.002642289],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003755383,0.0007581651,0.9886512,0.001225013,0.001221294,0.0002694198,0.00003214316,0.0007440505,0.003343342],"genre_scores_gemma":[0.5704401,0.00006283582,0.4276818,0.0006783296,0.0003682773,0.0000184748,0.000003394128,0.00002753786,0.0007192463],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5666847,"threshold_uncertainty_score":0.9999148,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}