Bibliographic record
Abstract
Despite being linked to several negative long-term physical and psychological pathologies in adulthood, childhood adversity elicits variable responses in the sufferer. When searching for explanations for this heterogeneity, the concept of resilience has been postulated as a potential mitigating factor. Gene-environmental interactions are a promising avenue in the study of resilience. The premise of gene-environmental research is that interindividual variability in the response to an environmental stressor is due to an individual’s genetic make-up exacerbating or buffering the impact of that stressor. Herein, gene-environmental findings are illustrated in the context of depression and post-traumatic stress disorder (PTSD). Many of the gene loci found to interact with childhood adversity influence both depression and PTSD possibly due to the high degree of shared heritability between these psychopathologies. Variation in the serotonin transporter gene, SLC6A4, and in FKBP5, a gene coding for a glucocorticoid receptor binding protein, interacts with childhood adversity to influence the development and symptomology of depression and of PTSD. Findings in the field of gene-environmental interactions has led to a proposed 3-hit model whereby 3 hits, genetics, early life experiences and later life stressors, interact to determine whether an individual is vulnerable or resilient to the development of psychopathology. As limitations with the current research are addressed and complementary lines of research are integrated, the insight gained on childhood adversity has the potential to better predict children at risk of the long-term sequelae of adversity and to inform potential intervention and prevention strategies.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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 teacher head, 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".