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@martha.eraabo.eye:

Jesus is Lord
Jesus is Lord
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Region: SA
Monday 09 November 2026 22:28:52 GMT
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betisha2645
betisha :
❤️❤️❤️
2026-11-10 07:08:08
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aswdgnvgghggggg
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2026-11-12 13:38:32
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وَاُجعلَنِي مِن وَرثِةَ جنهٍ النعِيٍم✨ {وَاغفِر لأَِبِي}🤍
وَاُجعلَنِي مِن وَرثِةَ جنهٍ النعِيٍم✨ {وَاغفِر لأَِبِي}🤍
ayo chill mr beast😭 #caucavancan #aeccvc #mrbeast #mrbeastchill #youtuber
ayo chill mr beast😭 #caucavancan #aeccvc #mrbeast #mrbeastchill #youtuber
#ايران🇮🇷 #بس #لايك #الاماكن السياحية #هورمان#پلنگانی
#ايران🇮🇷 #بس #لايك #الاماكن السياحية #هورمان#پلنگانی
já entregaram tanta quimica em 4 episodios 😍 ansiosa pelos próximos #theremarriedempress #kdrama #leejongsuk #shinminah #kdramaedit
já entregaram tanta quimica em 4 episodios 😍 ansiosa pelos próximos #theremarriedempress #kdrama #leejongsuk #shinminah #kdramaedit
Female data isn't noisy. Researchers were just measuring it wrong. In this conversation, Dr. Jennifer Garrison breaks down a fundamental flaw in how female biology has been studied — and why it's been hiding in plain sight. For years, researchers have used chronological age to organize and interpret data from female subjects. The problem? Chronological age doesn't account for the enormous variability that exists between women. When you use age of natural menopause as the reference point instead, something remarkable happens. The noise disappears. Sharp, clear biological signatures emerge from data that was previously dismissed as too variable to be useful. And here's what makes this even more striking: researchers were able to go back into large-scale historical datasets that already existed — datasets that weren't originally designed to capture this information — and clean them up simply by changing how the data was organized. The data was never the problem. The framework was. Tune into the full conversation, out on all major streaming platforms.
Female data isn't noisy. Researchers were just measuring it wrong. In this conversation, Dr. Jennifer Garrison breaks down a fundamental flaw in how female biology has been studied — and why it's been hiding in plain sight. For years, researchers have used chronological age to organize and interpret data from female subjects. The problem? Chronological age doesn't account for the enormous variability that exists between women. When you use age of natural menopause as the reference point instead, something remarkable happens. The noise disappears. Sharp, clear biological signatures emerge from data that was previously dismissed as too variable to be useful. And here's what makes this even more striking: researchers were able to go back into large-scale historical datasets that already existed — datasets that weren't originally designed to capture this information — and clean them up simply by changing how the data was organized. The data was never the problem. The framework was. Tune into the full conversation, out on all major streaming platforms.
Wenn du bei REWE den meisterhaften Kaka-Wurst-Prank durchziehst und der Handscanner des Mitarbeiters vor Schreck durch die Luft fliegt… 😭💩🛒 #lupazalupa #prank #rewe #fail #brainrot
Wenn du bei REWE den meisterhaften Kaka-Wurst-Prank durchziehst und der Handscanner des Mitarbeiters vor Schreck durch die Luft fliegt… 😭💩🛒 #lupazalupa #prank #rewe #fail #brainrot

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