Bibliographic record
Abstract
Fetal alcohol syndrome (FAS) is marked by pre‐ and/or postnatal growth deficiency (low birth weight and height), central nervous system (CNS) dysfunction, and facial malformations (short palpebral fissures, flat upper lip, smooth philtrum, and flat mid‐face). The syndrome is most commonly associated with maternal alcohol dependency and/or binge‐drinking patterns of alcohol consumption, however the threshold level at which prenatal alcohol exposure becomes dangerous to the developing fetus is unknown and is influenced by several maternal risk factors. Over recent decades the diagnosis FAS has generated much needed global attention to the problem of female addictions. However, while attention to prevention has resulted in some improvement to women‐centered treatment and aftercare supports, appropriate treatment and support is still lacking in most regions of the world. Public health messages aimed a preventing maternal alcohol exposure also focus primarily on a pregnant woman's choice to use or not use, despite the known complexities that contribute to maternal risk such as poverty, poor nutrition, and lifestyle factors. This has resulted in greater surveillance of maternal behavior and to widespread stigma and judgment of pregnant women who consume alcohol without addressing the complexity underlying maternal risk.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.034 | 0.007 |
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".