{"id":"W2883451194","doi":"10.1007/s12350-018-1378-5","title":"Dose reduction is good but it is image quality that matters","year":2018,"lang":"en","type":"letter","venue":"Journal of Nuclear Cardiology","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"GE Healthcare","keywords":"Medicine; Reduction (mathematics); Image quality; Quality (philosophy); Medical physics; Image (mathematics); Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007787825,0.0002543039,0.00110773,0.000209503,0.00007918025,0.00003124982,0.0003288269,0.0008225181,0.001329361],"category_scores_gemma":[0.00008842618,0.0001996704,0.0007316144,0.0000953882,0.000480958,0.0000832754,0.00009315838,0.002478716,0.0002854179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001666659,"about_ca_system_score_gemma":0.0001109484,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002994015,"about_ca_topic_score_gemma":4.500814e-8,"domain_scores_codex":[0.9978628,0.0002243847,0.0007411565,0.000322426,0.0005172194,0.0003320563],"domain_scores_gemma":[0.9978904,0.0000727762,0.0008303912,0.0006587838,0.0003821078,0.0001655315],"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":[0.00005803624,0.00001995644,0.00004310899,0.0001180331,0.0003487784,0.0004101095,0.0001492285,1.567061e-8,0.005508,0.000006487077,0.9928974,0.0004408578],"study_design_scores_gemma":[0.0004961269,0.0003072724,0.0004551598,0.000204175,0.0004940481,0.008926495,0.0001367649,0.000004652569,0.0002460438,0.0003425968,0.988215,0.0001716849],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.005566717,0.00007346027,0.0005041644,0.9888858,0.0007516574,0.0002185007,0.00005360202,0.00005517786,0.003890965],"genre_scores_gemma":[0.002715724,0.0006261994,0.01165591,0.9681095,0.01433853,0.000004624826,0.00003498798,0.00008463541,0.002429842],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.02077621,"threshold_uncertainty_score":0.9998226,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0605069487880501,"score_gpt":0.3582621278052304,"score_spread":0.2977551790171803,"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."}}