A study on the nature of genetic metabolic practice at a major paediatric referral centre
Bibliographic record
Abstract
A retrospective chart review of new paediatric patients seen during the calendar year 1998 by specialists of the Division of Clinical and Metabolic Genetics of the Hospital for Sick Children in Toronto, the largest such referral centre in the country, showed that 81% of specific genetic metabolic diagnoses were made within one month of being seen in consultation by one of the consultants of the programme. In 5% of cases, a specific diagnosis was not reached 4 years after initial consultation. We concluded from this study that the specific diagnosis of inborn errors of metabolism at a major medical genetic referral centre tended to be made quickly, or never. Some of the causes of delays in diagnosis include (1) the lack of ready access to existing diagnostic laboratory testing; (2) technical barriers to the identification of specific metabolic or genetic defects; and (3) incomplete knowledge of genetic defects causing inherited metabolic diseases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".