The influence of natural variations in maternal care on play fighting in the rat
Bibliographic record
Abstract
Naturally occurring variations in maternal care in the rat influence the sensitivity of offspring to stress in adulthood. The offspring of mothers that show lower levels of pup licking/grooming (i.e., low-LG mothers) demonstrate enhanced responses to stress and increased anxiety compared to those of high-LG mothers. Low-LG offspring are also more sensitive to the influence of environmental enrichment than high-LG offspring. This study examined play fighting in the juvenile offspring of high-LG and low-LG dams in a multiple-play partners housing environment. Male offspring from low-LG dams demonstrated a significantly higher frequency of pouncing, pinning and aggressive social grooming than did high-LG males and high-LG and low-LG females. Consistent with earlier reports, male pups engaged in more play fighting than did females and maternal care was associated with differences in play fighting but only in males. Lower levels of stimulation in the form of LG from the dam during perinatal development may thus increase sensitivity for the stimulating effects of play behavior in periadolescence, in part explaining the increased solicitation of play fighting through increased pouncing in the male offspring of the low-LG mothers. These findings identify a possible influence of variations in maternal care on play fighting and suggest that maternal care in the perinatal period influence social interactions during periadolescence.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".