Development and evaluation of food environment audit instrument: AUDITNOVA
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To develop and assess the reliability of an instrument that enables auditing information on consumer food environment indicators, such as availability, price, promotional and advertising strategies, and quantity of brands available, using the food recommendations adopted by the Dietary Guidelines for the Brazilian Population as a theoretical basis. METHODS: This is a methodological study in two phases: 1. development of the audit instrument and 2. assessment of its reliability and reproducibility . The Content Validity Index was estimated for each instrument item (>0.80 satisfactory). Inter-rater and test-retest reliability were assessed by percentage agreement and Kappa coefficients. Pearson's correlation coefficient and Scatter-plots were used to measure the degree of linear correlation between two quantitative variables. RESULTS: The Content Validity Index was 0.91. Inter-rater and test-retest reliability were mostly high (Kappa> 0.80), for food availability indicators. Among the items that measure advertising, Kappa values for inter-rater reliability ranged from 0.57 to 1.00 and for the test-retest ranged from 0.18 to 0.90. Prices and quantity of brands showed a positive linear correlation between measurements performed by researcher 1 and 2 and between visits 1 and 2. CONCLUSIONS: AUDITNOVA is reliable for measuring aspects such as availability, price, quantity of brands, and advertising of foods available in the consumer food environment.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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 it