{"id":"W2931628922","doi":"","title":"心筋血流低下モデルを用いた99mTc-1日法負荷心筋血流SPECT検査の投与量比に関する基礎的検討 ―心筋ファントムを用いた画像比較―","year":2018,"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; Environmental 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":[0.0006205395,0.0006549092,0.0006552997,0.0003652814,0.0004091951,0.00005840108,0.00106581,0.0006425502,0.01821845],"category_scores_gemma":[0.0002282003,0.0006716039,0.0002180542,0.0007099027,0.001471156,0.0003705638,0.0001916169,0.001326041,0.007455471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000141196,"about_ca_system_score_gemma":0.0001537299,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009635724,"about_ca_topic_score_gemma":0.00007163752,"domain_scores_codex":[0.9965198,0.0001174218,0.000753363,0.000735427,0.0005844618,0.001289525],"domain_scores_gemma":[0.9981098,0.0001744255,0.00009857305,0.0009577952,0.0001435037,0.0005158925],"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":[0.0004069774,0.0007238813,0.001634152,0.001450041,0.002289897,0.001467283,0.0128388,0.0001355673,0.03118343,0.07762302,0.7688795,0.1013674],"study_design_scores_gemma":[0.004940275,0.001277404,0.002525357,0.0006711442,0.0007153616,0.0004800853,0.00296788,0.03687201,0.04414108,0.02561739,0.8770287,0.002763332],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1637083,0.02310474,0.001646298,0.00538336,0.01146309,0.0007397891,0.0001568757,0.003282123,0.7905155],"genre_scores_gemma":[0.9894001,0.003417319,0.000898,0.0006320528,0.003448986,0.00004647002,0.00002858944,0.0001112699,0.002017235],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8256918,"threshold_uncertainty_score":0.9995735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01676452955487632,"score_gpt":0.2661502139340817,"score_spread":0.2493856843792054,"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."}}