{"id":"W2750172672","doi":"","title":"睡眠障害:超高齢社会における実態とその対策 高齢不眠症患者への非薬物療法","year":2017,"lang":"ja","type":"article","venue":"Pharma Medica","topic":"Military Technology and Strategies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004849444,0.0004096042,0.0004724268,0.0001882983,0.0008166314,0.0001259666,0.001623044,0.0004764248,0.004984266],"category_scores_gemma":[0.0003385372,0.0004136081,0.0001603013,0.00009940243,0.0007464268,0.0004943211,0.0002674992,0.001139519,0.001401503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005552978,"about_ca_system_score_gemma":0.00008182664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001052026,"about_ca_topic_score_gemma":0.00004040528,"domain_scores_codex":[0.9979275,0.00004734644,0.0004339228,0.0004429326,0.0003727727,0.0007754703],"domain_scores_gemma":[0.997968,0.00009085139,0.0001249119,0.001458709,0.00003916993,0.0003183316],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002432111,0.0005489234,0.006496923,0.002188677,0.002423038,0.002994212,0.006249797,0.0003915104,0.01179443,0.08926039,0.3783809,0.4990279],"study_design_scores_gemma":[0.006386662,0.0003610926,0.02068197,0.0008123973,0.0007276923,0.0002250802,0.001696324,0.03659856,0.01287038,0.02761626,0.8895857,0.002437837],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1216919,0.02119506,0.0004628402,0.01008501,0.008043158,0.000429313,0.0001103114,0.001303983,0.8366784],"genre_scores_gemma":[0.9895104,0.006186974,0.0003496711,0.0002052135,0.0009505926,0.00003369113,0.00001442707,0.00005793008,0.002691104],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8678185,"threshold_uncertainty_score":0.9998316,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02388063563345101,"score_gpt":0.2831049655504125,"score_spread":0.2592243299169615,"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."}}