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Figure 1 Population classification for biomass modeling in China.
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Interestingly, of all the individual cranial bones, the sphenoid was revealed to be the most distinct among populations and therefore the most reliable region for population classification.
And parallel population classification is adopted to design parallel mechanism for all sub-populations, which can keep the population diversity according to affinity.
For many of these objects, the kinematic data on velocities are the prime source of population classification.
The concordance of results using both a statistical classification (thirtiles of mean CRP) and an a priori population-based classification (for CRP change) serves to strengthen the findings.
Furthermore, we tested if geographic and genetic distances are correlated (isolation by distance) in the two species, using the biogeographic and taxonomic classification for grouping populations of jungle cat and only the taxonomic classification for leopard cats since the biogeographic grouping in this species had just two populations.
The primary purpose of classification for the population-based cohorts was for epidemiological analyses to identify areas for prevention through practice and policy improvements.
In fact, the low levels of correct classification for these populations suggest that their morphological variation overlaps considerably in the younger age categories.
Body mass index was grouped according to the WHO classification for Asian populations as normal (18.5 <23 kg m−2), overweight (23 <25 kg m−2), and obese (⩾25 kg m−2) (WHO/IASO/IOTF, 2000; WHO Expert Consultation, 2004).
Body mass index was grouped according to the WHO classification for Asian populations where 18.5 to <23 kg m−2 is considered normal, 23 to <25 kg m−2 overweight, and ⩾25 kg m−2 obese (WHO/IASO/IOTF, 2000; WHO Expert Consultation, 2004).
As, we could get only an overall picture of the logistic organization and health system in each camp, we considered the size (maximum population) of camps as a proxy classification for complexity and logistic difficulties.
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