Characterising fetal alcohol spectrum disorder in Canada: a national database protocol study
Bibliographic record
Abstract
INTRODUCTION: Fetal alcohol spectrum disorder (FASD) is one of the most common neurodevelopmental disorders in North America. It is a complex disability, associated with challenges in cognitive, behavioural and socialemotional functioning, as well as an increased risk of physical and mental health comorbidities, and difficulties in daily living across the lifespan. Previous attempts to characterise the profile of this population have been hampered by differences in data collected across studies, regional discrepancies in terminology and definitions, and a lack of tools to integrate comprehensive datasets. METHODS AND ANALYSIS: The goals of this study are to use the Canadian National FASD Database, a national repository of FASD assessment-related information, to better understand the functional profile, comorbidities, intervention needs and difficulties in daily living experienced by individuals assessed for FASD across the lifespan. We will also examine what factors may be the most sensitive predictors of receiving an FASD diagnosis. Data will be analysed from over 3500 records collected between 2010 and 2021 (ongoing) from 26 FASD diagnostic clinics in seven provinces and territories. Data collection is ongoing, and analysis will be performed on a biannual basis to continue to hone our understanding of the profiles, needs and outcomes of individuals assessed for FASD in Canada. This research is critical for refining FASD assessment and diagnostic practice, enabling accurate and early identification of individuals with FASD, and connecting individuals with FASD and their families to comprehensive and effective services and resources to support healthy developmental trajectories. ETHICS AND DISSEMINATION: Ethics approval for the National FASD Database Project was obtained from the Ottawa Health Science Network Research Ethics Board. As new knowledge is gained from this project, findings will be disseminated through publications, presentations and feedback to participating clinics, with the ultimate goal of informing FASD research, practice and policy.
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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 | 0.014 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.013 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".