{"id":"W2595211705","doi":"","title":"麻薬性鎮痛薬に対する負のイメージの軽減を目的とした，動画教材の作成とその有効性の検討（研究）","year":2011,"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":[0.0004661345,0.0004895622,0.0005057836,0.0002483707,0.0001717178,0.00001846999,0.0008866827,0.0005280775,0.02002957],"category_scores_gemma":[0.0001111314,0.0004924757,0.0001762205,0.0003762473,0.0004822138,0.0003286841,0.0001534097,0.001175912,0.002622396],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006345084,"about_ca_system_score_gemma":0.00009389184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001406772,"about_ca_topic_score_gemma":0.00002888282,"domain_scores_codex":[0.997519,0.00008596975,0.0005911412,0.000496235,0.0003842607,0.0009234658],"domain_scores_gemma":[0.9986912,0.00009178861,0.00007384741,0.0006937652,0.00005458441,0.0003948379],"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":[0.000719017,0.002000066,0.00647467,0.003520019,0.005032576,0.005487705,0.0715698,0.00016183,0.01284159,0.2462454,0.421857,0.2240903],"study_design_scores_gemma":[0.01199561,0.00176609,0.01573262,0.001533612,0.002253128,0.001111317,0.01400822,0.03700576,0.0611411,0.1237302,0.7228593,0.006863029],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.0763555,0.02445014,0.001095257,0.0008722881,0.00478332,0.000504829,0.00009120019,0.002065234,0.8897822],"genre_scores_gemma":[0.9916949,0.004619992,0.001424801,0.0002980409,0.0005096866,0.00005327771,0.00002079826,0.00007824399,0.001300286],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9153394,"threshold_uncertainty_score":0.9997527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03041070002375282,"score_gpt":0.251507951290536,"score_spread":0.2210972512667832,"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."}}