Short and Long Term Impacts and Implications of Fetal Alcohol Syndrome Disorders on Cognitive Development in Childhood
Bibliographic record
Abstract
Fetal alcohol syndrome disorders (FASD) represent a collection of disorders with which a child is born, due to maternal consumption of alcohol during pregnancy. Known as an invisible disability, its prevalence is difficult to capture, in part due to societal stigma and the lack of physical markers contributing to diagnostic difficulty. In Canada, FASD prevalence is estimated to be around 4%. The symptoms experienced by a child with FASD are typically classified into two categories: primary disabilities to describe functional deficits since birth as a result of the impact of alcohol on the brain; and secondary disabilities that occur later in life as a result of a child’s environment and primary disabilities. The impacts of FASD will affect each child differently in both the types and severity of disabilities. A major challenge faced by children and youth with FASD is receiving adequate mental health support, as well as evidence-informed practices involved in improving behavioural and cognitive functioning. COVID-19 has dramatically affected both children with FASD and their caregivers, likely exacerbating existing challenges. With increased rates of alcohol consumption and other mediating factors, experts are concerned about rising FASD rates during the pandemic.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".