This piece looks at how AI governance can support threat assessment without replacing human judgment
Threat assessment teams are starting to use AI models to help sort warning signs, and the governance around that work matters as much as the output
**Primary (200-255 characters, 218 characters):** When AI models disagree on a threat assessment, who makes the call? Log each model's output, record your assumptions, name the human owner, and set a follow-up review date that fits the case
When AI models disagree on a threat assessment, the disagreement gets logged. Each review records its assumptions, names the human who owns the final call, and schedules a follow-up check. The review interval is set per case, not fixed at 30 days
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Safety monitoring watches for infrequent topics like slipped capital femoral epiphysis or intracranial high blood pressure for the period of GH, permitting quickly reaction.
Bone density monitoring, through DXA when indicated, tracks skeletal wellbeing and fitness for the duration of therapies that have an impact on hormones, making sure mineral accrual assists in keeping tempo with linear expansion.
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