A Systematic Review of the Effectiveness of Prevention Approaches for Fetal Alcohol Spectrum Disorder
Bibliographic record
Abstract
This chapter contains sections titled: Introduction Objective and Scope Methodological Approach Studies on the Effectiveness of FASD Preventive Approaches Evidence on the Effectiveness of Universal Prevention Approaches for FASD Evidence on the Effectiveness of Selective Prevention Approaches for FASD Evidence on the Effectiveness of Indicated Prevention Approaches for FASD Discussion Conclusions Acknowledgments Competing Interest Appendix 3.A: Methodology Search Strategy Study Selection Process Data Extraction Methodological Quality Assessment Data Analysis and Synthesis of the Results Appendix 3.B: Excluded Studies, Multiple Publications and Studies Pending Full Publication Excluded Research Studies Multiple Publications of Studies Included in the Review Studies Pending Full Publication Appendix 3.C: Summary Tables of Overall Characteristics of Studies on Prevention Approaches to FASD Appendix 3.D: Operational Definitions of Prevention Approaches to FASD Appendix 3.E: Study Evidence Tables Appendix 3.F: Characteristics of the Interventions Appendix 3.G: Methodological Quality of the Studies Included in the Review References
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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 | 0.024 | 0.094 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.013 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".