Indicators of vitamin A status in rural villages in Southern Ethiopia
Bibliographic record
Abstract
This study was part of a cross‐sectional investigation of the nutritional status of lactating women in two rural villages in Southern Ethiopia conducted in January, 2006. A convenience sample of 108 women living in Wondo Genet and Arsi Negele was utilized. Land ownership was significantly greater in Arsi Negele (p<0.0001), while significantly more goods (lamps, radios, hand torches, bicycles, and carts) were owned in Wondo Genet (p<0.01). Vitamin A status was assessed by food consumption patterns and pupillary response testing. Women in Wondo Genet consumed mango, papaya, and sweet potato more frequently than women in Arsi Negele (p<0.0001). Dark adaptation threshold was assessed using the scotopic sensitivity tester‐1 (SST‐1, LKC Technologies, Inc, Gaithersburg, MD). This instrument utilizes a hand‐held illuminator with light intensity ranging from 0dB to 30dB. Subjects underwent binocular partial bleaching with a digital camera flash (Sony Cyber‐shot DSC‐W5) and were then dark adapted for 20 minutes in a portable black tent. Pupillary response was evaluated by use of a night vision scope (ELF‐1, LOMO America Inc.). Women from Wondo Genet had significantly lower pupillary thresholds than women from Arsi Negele (p<0.02). High pupillary thresholds were consistent with lower consumption of vitamin A source foods. (Supported by The Micronutrient Initiative of Canada, Debub University, and Oklahoma State University).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".