Genotypic Approaches to Therapy in Children (GATC): Using Information Technology to Improve Drug Safety
Bibliographic record
Abstract
Adverse drug reactions (ADRs) are a major cause of morbidity and mortality in children. Current models of ADR surveillance have repeatedly demonstrated little pragmatic value to practicing clinicians. ADR reporting rates in the US and Canada suggest that only 5% of ADRs are reported. The Genotypic Approaches to Therapy in Children (GATC) network was established to identify and solve drug safety problems in paediatrics. We hypothesized that genetic polymorphisms underlie a significant portion of concentration-dependent ADRs in children. Our objective was to establish an ADR active surveillance network in paediatric hospitals across Canada. Surveillance clinicians evaluate clinical information from ADR cases and drug-matched controls, and collected DNA samples from all patients. The surveillance network will enable the identification of predictive genomic-markers for ADRs. With this knowledge, children at risk can be identified before therapy is initiated and enable personalized adjustments to therapy based on genetic make-up.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".