{"id":"W2596730456","doi":"","title":"統合失調症治療における副作用の軽減；抗精神病薬による体重増加，糖・脂質代謝異常などを捉えて","year":2010,"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","research_integrity","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0005847332,0.0005016202,0.0005004071,0.0002475618,0.0002271854,0.00004378182,0.000913023,0.0007809224,0.01323003],"category_scores_gemma":[0.0002515358,0.0005056498,0.0001803442,0.0003825139,0.0006161492,0.0002989377,0.0001410462,0.003023264,0.002319734],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003338523,"about_ca_system_score_gemma":0.0001193198,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006318957,"about_ca_topic_score_gemma":0.00009558319,"domain_scores_codex":[0.9974633,0.00005545922,0.0005737542,0.0005211845,0.0004564125,0.0009298344],"domain_scores_gemma":[0.9984131,0.0001859819,0.00007127951,0.0008201476,0.00006517102,0.0004442958],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002379289,0.0008709385,0.003195812,0.001751643,0.001867554,0.001807116,0.007465799,0.0003590499,0.2689024,0.1650321,0.3610426,0.187467],"study_design_scores_gemma":[0.003468024,0.000246082,0.002540955,0.000191198,0.0004406025,0.000452659,0.001179647,0.03066059,0.02321944,0.02055048,0.9152272,0.001823078],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5011678,0.01128009,0.0004877578,0.006429865,0.01634385,0.0005735828,0.0001307222,0.002581115,0.4610052],"genre_scores_gemma":[0.9937901,0.002076524,0.0009978962,0.0003788215,0.001371344,0.00004993476,0.00003273362,0.00008020453,0.001222417],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5541846,"threshold_uncertainty_score":0.9997395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01242620742157547,"score_gpt":0.2551619172801331,"score_spread":0.2427357098585576,"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."}}