The science of brain and biological development: implications for mental health research, practice and policy.
Bibliographic record
Abstract
OBJECTIVE: This article provides a summary of the complex interaction between genetics and experience which shapes the development of neurobiological systems, particularly in the prenatal/early childhood and adolescent periods. METHOD: Key factors that influence brain structure and function, and mechanisms through which experience impacts risk for mental health disorders presented in this Special Issue are linked with suggestions for future directions in child and youth mental health research, policy and practice. RESULTS: SUGGESTED AREAS TO APPLY EVIDENCE PRESENTED IN THIS SPECIAL ISSUE INCLUDE: enhancing research in the differential impact of psychoactive drugs on the developing brain; introducing content on brain and biological development to professional development and post-secondary curriculum; increased involvement of the family in recognition, prevention and treatment of mental health disorders; and, creation of evidenced-informed child and youth mental health policies. CONCLUSIONS: As more evidence accumulates on how early experience impacts the structure and function of the developing brain, these findings should be applied to how mental illness may be better prevented, recognized and treated in child and adolescent populations.
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 | 0.015 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.023 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".