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Answer a question about a scanned page from its OCR text. Scored by exact match and ANLS against the accepted answers.

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PromptDocVQA · pagehqvd0227_19.png

what is the % not eating for sugar?

OCR text of the page · 1,063 characters; the scanned image itself is not published
ADMISSION PRENATAL STATUS - TEENAGERS,
U. T. M. B. '64-'66
PATTERN OF FOOD INTAKE
Range
Major
To Not Eating
Food . Groups
# Servings / Day
ADMISSION PRENATAL STATUS - TEENAGERS,
0-30%
1. Bread / cereals etc.
4. 8
0
- white bread
2, 1
U.T. M. B. '64-'66
10-34
2. Milk products
2.4
PATTERN OF NONESSENTIAL FOOD INTAKE
10
- whole milk
. . 1, 3
5-42
3. Meat / legumes
2 .5
Miscellaneous
. 5
- chicken
0. 2
5
- hamburger
0 .2
Not Eating
Food Items
# Servings / Day
18 .
12
- lunch meat
0.5
30
1. Potato chips.
0.2
- pinto beans
0 . 3
. 3
12
4. Eggs
1.0
37.
. 2. Saltines
0.2
38
5. Citrus
0.8
1 1
3. Soda pop
0 .7
20-40
6. Fruits / vegetables
2.4
15-20
7. Fats / oils
0 . 3
34
4. Kool aid
0 .5
2
8. Water
4.8
23
5. Candy
0:4
5
6. Sugar
1 .3
lable 3
Admission Prenatal Status - Teenagers
UTM8 1964-66
Percent Adequacy Nutrient Intake
Thiamine
Riboflavin
120
110
Calories
Protein
- Calcium
iron
Vitamin-A
Vitamin-C
Niacin
100
SO
80
TO
60
Ist group
2nd group
Inicke
2155 Col. 73GM. 780MG. 12.7MG. 5070 1.U. 93M.G.
12MG. 2.0 MG. 15MG.
dustrydocuments.ucsf.edu/docs/hqvd0227
System prompt · identical for every setup
Answer the question using only the OCR text from a single document page. Return only the answer, with no explanation. Preserve the answer wording from the OCR text when possible.
Expected answer
55%
Models
4 of 4 columns · click a model to add or remove it

Ours

Wrong

30

2 characters3 tokens

Aux 2015

Wrong

To determine the % not eating for sugar, we first need to identify the total number of servings of each food item consumed per day.

Looking at the data, we see that the total number of servings per day for each food group is:

  • Bread / cereals etc. = 18 servings
266 characters64 tokens

PiT-FT 2015

Wrong

Empty response.

0 characters

ChronoGPT 2015

Wrong

foods

  • bread
  • milk
  • meat
  • lunch
  • lunch
  • milk
  • white bread
  • white bread
  • white bread
  • white bread
  • white bread
  • white bread
  • white bread
  • white bread
  • white bread
  • white bread
  • white bread
204 characters64 tokens