Bibliographic record
Abstract
Dietary iron absorption and systemic iron traffic are tightly controlled by hepcidin, a liver-derived peptide hormone. Hepcidin inhibits iron entry into plasma by binding to and inactivating the iron exporter ferroportin in target cells, such as duodenal enterocytes and tissue macrophages. Hepcidin is induced in response to increased body iron stores to inhibit further iron absorption and prevent iron overload. The mechanism involves the BMP/SMAD signaling pathway, which triggers transcriptional hepcidin induction. Inactivating mutations in components of this pathway cause hepcidin deficiency, which allows inappropriately increased iron absorption and efflux into the bloodstream. This leads to hereditary hemochromatosis (HH), a genetically heterogenous autosomal recessive disorder of iron metabolism characterized by gradual buildup of unshielded non-transferrin bound iron (NTBI) in plasma and excessive iron deposition in tissue parenchymal cells. The predominant HH form is linked to mutations in the HFE gene and constitutes the most frequent genetic disorder in Caucasians. Other, more severe and rare variants are caused by inactivating mutations in HJV (hemojuvelin), HAMP (hepcidin) or TFR2 (transferrin receptor 2). Mutations in SLC40A1 (ferroportin) that cause hepcidin resistance recapitulate the biochemical phenotype of HH. However, ferroportin-related hemochromatosis is transmitted in an autosomal dominant manner. Loss-of-function ferroportin mutations lead to ferroportin disease, characterized by iron overload in macrophages and low transferrin saturation. Aceruloplasminemia and atransferrinemia are further inherited disorders of iron overload caused by deficiency in ceruloplasmin or transferrin, the plasma ferroxidase and iron carrier, respectively.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.035 | 0.010 |
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".