{"id":"W3166896981","doi":"","title":"心筋血流低下モデルを用いた 99m Tc-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","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009755535,0.0003853104,0.0002876795,0.000932976,0.0006637776,0.001677914,0.0005015563,0.0009302802,0.006511665],"category_scores_gemma":[0.001248649,0.0003482132,0.0002839713,0.0005000529,0.001099476,0.001136679,0.0003034336,0.001179514,0.002060468],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001221516,"about_ca_system_score_gemma":0.001416822,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004962306,"about_ca_topic_score_gemma":0.006253714,"domain_scores_codex":[0.9996606,0.00007521376,0.00002031235,0.00007800479,0.0001090697,0.00005690203],"domain_scores_gemma":[0.9994084,0.0001530833,0.00008293377,0.0000482642,0.000242848,0.00006454781],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001393378,0.0003841587,0.02962063,0.001204734,0.0002357727,0.003057453,0.001562943,0.002064479,0.5617675,0.03533825,0.01095364,0.352417],"study_design_scores_gemma":[0.0002025074,0.001384014,0.04056208,0.0002697693,0.0007700155,0.01110361,0.00140573,0.008241266,0.7685509,0.01732074,0.149987,0.0002023981],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5396183,0.03192665,0.1250814,0.008297766,0.001350273,0.0004465644,0.001026757,0.001325203,0.2909271],"genre_scores_gemma":[0.8873549,0.005542781,0.04435242,0.001650299,0.0003386569,0.0001375348,0.0005017354,0.0002268898,0.05989487],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006511665,"threshold_uncertainty_score":0.02178365,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01677650920329416,"score_gpt":0.2660667429177295,"score_spread":0.2492902337144353,"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."}}