Linking early brain and biological development to psychiatry: introduction and symposia review.
Bibliographic record
Abstract
OBJECTIVE: This paper introduces the special issue of the Journal of the Canadian Academy of Child and Adolescent Psychiatry on the theme of how multiple factors in early brain and biological development can influence a variety of outcomes in mental health and addictions in childhood, adolescence and adulthood. METHOD: In Part 1, we preview three papers in this issue. In Part 2, we highlight two recent innovative knowledge-transfer symposia featuring the application of the science in early development and addictions. RESULTS: The papers focus on the subtopics of brain plasticity, mood disorders, and comparative research with monkeys on gene-environment interactions and parent-child attachment. In addition, the research presented at the Early Brain and Biological Development Symposium and the Recovery from Addiction Symposium is also reviewed. Held in 2010 in Banff, Alberta, each five-day program was intended to bridge the gap between scientific and clinical experts and those in the province responsible for policy, programs, and services. CONCLUSIONS: The science now links common neurobiological maturation processes, adverse early childhood experiences, and key aspects of the social environment with risks for mental health disorders and addictions later in life. The final paper in this issue examines the clinical and policy implications of this research knowledge.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".