Table 1:

Classification of Error Type: Description and Examples

Error Type	Description and Theoretical Example(s) of Error
Imprecise application of detailed information	Description: Answer selection was based on detailed clinical information, which was applied imprecisely or inaccurately to the clinical context Example: • Recommend medical management rather than surgery as first-line treatment for specific diagnosis, which is accurate, unless symptoms are medically-refractory, which is the case in the question
Imprecise application of general knowledge	Description: Answer selection was based on general knowledge, which was either incompletely accurate or out of scope given context of the question Example: • Recommend against a secondary procedure in a child to avoid additional anesthesia and potential procedural complications
Inability to differentiate relative importance of information	Description: Answer selection was based on accurate information, but did not delineate between more accurate options Example: • Select a laboratory finding which is present in most patients with a specific condition, when a more characteristic finding was intended
Accurate information; circumstantial discrepancy	Description: Response is based on accurate information, which is incorrect based on question interpretation or other circumstantial factors that unlikely reflect competency of GPT Example: • Select the cost-effective, first-line imaging, rather than the gold standard mechanism for diagnosis
Inaccurate information in fact-based question	Description: Response is based on inaccurate information in the context of a single-part, fact-based question Example: • Incorrectly identify the second most common site of pathology
Inaccurate information in complex question	Description: Response is based on inaccurate information in the context of a complex clinical scenario or multi-part question Example: • Inaccurate selection of most appropriate next step in patient with constellation of symptoms and description of imaging