{"id":"W2135079443","doi":"10.1016/j.jacr.2013.02.026","title":"The Image Gently Pediatric Digital Radiography Safety Checklist: Tools for Improving Pediatric Radiography","year":2013,"lang":"en","type":"article","venue":"Journal of the American College of Radiology","topic":"Radiation Dose and Imaging","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hospital for Sick Children","funders":"","keywords":"Checklist; Workflow; Radiography; Medical physics; Digital radiography; Image quality; Medicine; Quality (philosophy); Patient safety; Radiology; Computer science; Health care; Psychology; Image (mathematics); Artificial intelligence; Database","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":[],"consensus_categories":[],"category_scores_codex":[0.0008270122,0.000245382,0.0009212051,0.0006899591,0.0003369575,0.00008438319,0.000676632,0.00006283463,0.00001747561],"category_scores_gemma":[0.001161927,0.000139712,0.001256939,0.001715846,0.0005997614,0.0005986465,0.00007700713,0.0004148066,0.000003697423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009228149,"about_ca_system_score_gemma":0.0003687347,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001741884,"about_ca_topic_score_gemma":6.135595e-7,"domain_scores_codex":[0.9975525,0.0001632218,0.001207835,0.0002170431,0.000329922,0.0005294622],"domain_scores_gemma":[0.9950863,0.001333031,0.002406434,0.0004765845,0.0004845769,0.0002130395],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002873985,0.0005036693,0.5410123,0.0002883493,0.001556119,0.00005976786,0.0003481994,0.0001355449,0.009900117,0.0005624409,0.3531611,0.08959838],"study_design_scores_gemma":[0.008420676,0.004457156,0.9261175,0.00003599109,0.002275042,0.005616102,0.002296247,0.001455971,0.0007591079,0.001283351,0.04661836,0.0006644493],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9810783,0.00453971,0.001902862,0.009814218,0.0009401148,0.001071653,0.0001621772,0.00001954681,0.0004713722],"genre_scores_gemma":[0.9910164,0.003264437,0.00274898,0.0006407874,0.002030146,0.00002447354,0.000004766875,0.00004273395,0.0002272168],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3851052,"threshold_uncertainty_score":0.5697291,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006024795320994666,"score_gpt":0.23540447568643,"score_spread":0.2293796803654353,"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."}}