Consumers’ perception of amaranth in Mexico: A traditional food with characteristics of functional foods
Bibliographic record
Abstract
In recent years, the market of functional foods has grown mainly in developed countries. The Asian-Pacific region, the USA, Canada and Europe consume 78 per cent of total sales (Vicentini et al., 2016). This growth is due to demographic changes as the increase of life expectancy that generates consumers more aware of their health, incorporating in their diets new foods that promise to improve and prolong their quality of life (Vecchio et al., 2016). This phenomenon has influenced other emergent markets like Mexico and Brazil that are the highest consumers of functional foods in Latina America (Vicentini et al., 2016). In Mexico as in other countries, the economic development, and demographic and socio-cultural changes have also promoted modification of lifestyles in different social strata of the population (Espinoza-Ortega et al., 2016). A negative effect of these changes is reflected in the high incidence of diabetes (9.5 per cent) and high overweight in more than 70 per cent of adults (INSP, 2016). From this, Mexican consumers seem to be willing to incorporate foods
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".