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Record W1974928180 · doi:10.1301/002966402320285074

Lessons Learned with Iron Fortification in Central America

2002· review· en· W1974928180 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNutrition Reviews · 2002
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicCassava research and cyanide
Canadian institutionsNutrition International
Fundersnot available
KeywordsFortificationFood fortificationFortified FoodEnvironmental healthMedicineFood scienceChemistryPopulation

Abstract

fetched live from OpenAlex

The countries of Central America have been pioneers in the developing world regarding food fortification initiatives. Salt fortification with iodine was introduced since the late 40s and 50s; sugar fortification with vitamin A is carried out in national programs in Guatemala, Honduras, El Salvador, and Nicaragua, beginning in the 70s; and cereal flour fortification with iron and B vitamins was introduced in the 60s. Salt and sugar fortification have been carefully characterized and evaluated, and the impact of these two interventions to prevent and to control iodine and vitamin A deficiency, respectively, is well established. This did not happen with cereal flour fortification, however, and the effect of this intervention is unknown. Nevertheless, some lessons can be extracted from our experience; these will be discussed in this review.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.243
GPT teacher head0.376
Teacher spread0.133 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it