Inherited Metabolic Disorders and Nutritional Genomics: Choosing the Wrong Parents
Bibliographic record
Abstract
Many countries, including the United States, Canada, along with those in the EU, have established screening services in place for the detection of inherited metabolic disorders (IMD) in newborns. These disorders are not individually common within the population. However, in aggregation they are relatively common among genetic disorders, and they are a significant cause of morbidity in infants, affecting one in 1500 to one in 5000 live births (J Res Med Sci 9,801–8, 2013). Many inherited metabolic disorders (IMD) have severe symptoms, which may lead to significant disability and mortality, if not rapidly diagnosed and treated shortly after birth. IMD primarily result from toxic accumulation of precursors or end products of metabolism. Specific disorders are difficult to diagnose due to the fact that many IMD show similar symptom profiles. Thus, rapid testing after birth is required to determine the exact disorder afflicting the patient to determine the correct course of treatment.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.022 | 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".