{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":1,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":1,"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":"d204f94d00b6","filters":{"venue":"人間学研究"}},"results":[{"id":"W1388586","doi":"10.1016/0001-4575(92)90020-j","title":"『走れメロス』(太宰治)の登場人物の心理学的把握 : SD法によるイメージ測定と「ジョハリの窓」による内容分析","year":2013,"lang":"en","type":"article","venue":"人間学研究","topic":"Urban Transport and Accessibility","field":"Social Sciences","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":"Computer science","authors":[{"name":"裕明 大野木","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02005361078921239,"gpt":0.2936732359757318,"spread":0.2736196251865194,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001151031,0.0001875864,0.0001404689,0.0009643983,0.0002715701,0.0006306132,0.0003276987,0.000198014,0.003954814],"category_scores_gemma":[0.00295567,0.0002141498,0.000156749,0.0006305234,0.0006663622,0.0004139113,0.0004345325,0.0002942098,0.0007531421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007277923,"about_ca_system_score_gemma":0.000298442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03517356,"about_ca_topic_score_gemma":0.03370066,"domain_scores_codex":[0.9996338,0.00005501664,0.00003906424,0.00009359307,0.0001300833,0.00004831732],"domain_scores_gemma":[0.9989091,0.0002888992,0.0002930122,0.00009403769,0.0002769396,0.0001378769],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.00007653859,0.00001919795,0.9865201,0.00001007237,0.00003912711,0.0000325293,0.0003800371,0.000179753,0.0002988536,0.0002080354,0.0003012162,0.01193452],"study_design_scores_gemma":[0.000003000817,0.00006015976,0.998385,0.000003171368,0.00001337434,0.00006653836,0.0003961369,0.0003646959,0.0002162791,0.000189876,0.0002981019,0.000003747463],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971426,0.0001576493,0.000332031,0.00005156586,0.000007455311,0.000007685412,0.0004483276,0.00001666025,0.001835926],"genre_scores_gemma":[0.9989298,0.00004220237,0.000206253,0.000005115195,0.000004026834,0.000007686759,0.0003227562,0.000002078011,0.0004801085],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03517356,"threshold_uncertainty_score":0.06993765,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}