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@bus_buddy: MASH COOL @masheastafricaltd@mtu_laxadonta@yahumajack @jackbusshot#mashpoa #fyppppppppppppppppppppppp #busbuddy #mtulaxadonta

Bus Buddy 🚎
Bus Buddy 🚎
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Region: KE
Saturday 19 September 2026 11:00:00 GMT
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evalyneatieno3
Evalyne aura :
Office iko wapi Mombasa
2026-09-19 12:12:28
1
mikemikitoh
Mike Mikitoh :
snr Mwangangi himself
2026-09-19 11:39:23
1
untamedglamour
azibrit :
tuwekeeni ofisi ndori yawa!
2026-09-20 18:50:35
1
evaline.sayol.luc
Evaline Sayol lucky rose :
safe journey
2026-09-20 13:28:41
1
cheddars56
cheddars :
deadly 100
2026-09-19 16:25:18
1
yahumajack
Y2J :
hatukai sana
2026-09-19 17:31:21
1
fixer6061
fixer :
nairobi office ziko wapi
2026-11-03 17:17:12
0
bauji220
Bauji :
kakoleni msa njia ya kwenda mwembe tayari mall
2026-09-25 17:48:00
0
rodger111_
Woud Anita 💎 :
hiyo over Hung ni ya Scania gani waku?
2026-11-04 18:39:49
0
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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.

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