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NEW INSIGHTS INTO ERYTHROPOIESIS: The Roles of Folate, Vitamin B<sub>12</sub>, and Iron

2004· review· en· W2130190421 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

VenueAnnual Review of Nutrition · 2004
Typereview
Languageen
FieldMedicine
TopicIron Metabolism and Disorders
Canadian institutionsMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsErythropoiesisErythroblastIneffective erythropoiesisVitamin B12HemoglobinAnemiaChemistryIron deficiencyReticulocyteBiochemistryVitaminBiologyInternal medicineRNAMedicine

Abstract

fetched live from OpenAlex

Erythropoiesis is the process in which new erythrocytes are produced. These new erythrocytes replace the oldest erythrocytes (normally about one percent) that are phagocytosed and destroyed each day. Folate, vitamin B12, and iron have crucial roles in erythropoiesis. Erythroblasts require folate and vitamin B12 for proliferation during their differentiation. Deficiency of folate or vitamin B12 inhibits purine and thymidylate syntheses, impairs DNA synthesis, and causes erythroblast apoptosis, resulting in anemia from ineffective erythropoiesis. Erythroblasts require large amounts of iron for hemoglobin synthesis. Large amounts of iron are recycled daily with hemoglobin breakdown from destroyed old erythrocytes. Many recently identified proteins are involved in absorption, storage, and cellular export of nonheme iron and in erythroblast uptake and utilization of iron. Erythroblast heme levels regulate uptake of iron and globin synthesis such that iron deficiency causes anemia by retarded production rates with smaller, less hemoglobinized erythrocytes.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.681
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.296
Teacher spread0.283 · 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