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This saved simulator starts with fifteen thousand nine hundred ninety-one impressions. With its premium box checked, it assumes three dollars per thousand impressions for ad sharing, producing forty-seven dollars ninety-seven when rounded for display. Sponsor value uses an entered twenty-five dollars per thousand, yielding three hundred ninety-nine dollars seventy-eight. Bars use one point two pixels per unrounded modeled dollar. Those rates are authored assumptions, not verified platform payouts or signed sponsor contracts. The simulator does not inspect an account, eligibility, audience geography, qualifying interactions or actual advertiser revenue. The total adds unrounded ad and sponsor values before rounding to cents. Under the default inputs it displays four hundred forty-seven dollars seventy-five. Unchecking premium makes ad sharing zero but keeps the sponsor value, so total becomes three hundred ninety-nine dollars seventy-eight. Bars use one point one pixels per unrounded modeled dollar. The effective revenue-per-thousand label drops from twenty-eight to twenty-five. This toggle models a program condition, not evidence of any real payout entitlement. Rounding the two components first and then summing can differ by a cent from the rounded total. Engagement and completion inputs do not alter either revenue formula. At four-point-five-percent engagement, impressions times the fraction rounds to seven hundred twenty interactions. The label nevertheless says high, fifteen thousand plus interactions, because its condition checks whether impressions exceed fifteen thousand. Bars compare actual estimated interaction count and entered impression count at point zero five pixels per item. The program splits the rounded interaction count into sixty-percent likes, twenty-five-percent reposts and fifteen-percent replies, each rounded separately. Thirty-five-percent completion gives five thousand five hundred ninety-seven completed views, rounded. These estimates are authored allocations, not observed engagement. The narrative and native tests preserve the existing label behavior without endorsing its wording.