{"id":"W2289065632","doi":"","title":"국가기록관의 포털의 패싯 내비게이션 기능에 관한 연구","year":2015,"lang":"ko","type":"article","venue":"한국도서관정보학회 동계 학술발표회","topic":"Technology and Data Analysis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Facet (psychology); World Wide Web; Computer science; Selection (genetic algorithm); Function (biology); Information retrieval; Subject (documents); Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002065049,0.0002350092,0.000256704,0.003171629,0.001633017,0.002779993,0.00056413,0.0003795843,0.004260138],"category_scores_gemma":[0.009281508,0.0001916499,0.0005827728,0.005613182,0.001260839,0.003207268,0.001436308,0.000315458,0.001289744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001444506,"about_ca_system_score_gemma":0.003049725,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04310336,"about_ca_topic_score_gemma":0.06158937,"domain_scores_codex":[0.9975147,0.0006085818,0.00033414,0.0003569887,0.0009079542,0.0002776492],"domain_scores_gemma":[0.9898987,0.003035832,0.001540669,0.001488664,0.003763798,0.0002723518],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003214297,0.0001567263,0.5372077,0.0009820833,0.0001197621,0.003098448,0.05600752,0.001283719,0.009544767,0.02190442,0.009383149,0.3599903],"study_design_scores_gemma":[0.00002134819,0.0003306064,0.5694785,0.000812554,0.000229643,0.007616749,0.1091836,0.009241489,0.01265262,0.01037919,0.2798083,0.0002454558],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8844875,0.0008070591,0.03355953,0.0005052576,0.00004327345,0.0004640101,0.002447577,0.0007315974,0.07695413],"genre_scores_gemma":[0.9617409,0.0004541406,0.02542009,0.0001154132,0.00000920373,0.0001267439,0.001665218,0.00008817454,0.01038021],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04310336,"threshold_uncertainty_score":0.08570498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03131441793246742,"score_gpt":0.2628208633613944,"score_spread":0.231506445428927,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}