Nonlinear Optical Microscopy of Murine Abdominal Aortic Aneurysm
Bibliographic record
Abstract
Socio-demographic risks are associated with higher child screen time and higher screen time is associated with poor socioemotional and developmental health. Existing studies have not examined children's screen time as a mechanism through which distal risks may be associated with child outcomes. In the current study, we examined whether two proximal factors, screen time and parenting quality, mediate the relation between distal cumulative risk and child outcomes. Participants (N = 1992) were drawn from a birth cohort of mothers and their children (81% white; 46% female). Mothers reported on cumulative risk factors (maternal income, education, depression, stress, marital status, housing instability, unemployment, and maternal history of childhood adversity) during the prenatal period. Parenting quality (ineffective/hostile, positive interactions) and children's screen time (hours/week) were assessed when children were three years of age. Child socioemotional (internalizing and externalizing problems) and developmental (achievement of developmental milestones) outcomes were measured at five years of age. Path analysis revealed indirect effects from cumulative risk to internalizing symptoms and achievement of developmental milestones via screen time. Indirect effects were observed from cumulative risk to internalizing and externalizing behavior via hostile parenting behavior. Over and above the effects of parenting, screen time may be a factor that links structural forms of social disadvantage during the prenatal period to child socioemotional and developmental outcomes. Due to modest effect sizes of screen time, it remains the case that child socioemotional and developmental health should be conceptualized within the context of distal cumulative risk factors such as caregiver psychological and material resources.
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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".