Motherless rats show deficits in maternal behavior towards fostered pups
Bibliographic record
Abstract
Complete maternal deprivation in rats, through artificial rearing (AR), produces deficits in subsequent maternal behavior of the offspring. These deficits are partially reversed when isolated pups are provided with additional tactile stimulation designed to simulate maternal licking (e.g., Gonzalez et al. [2001] Developmental Psychobiology, 38, 11-32). These findings highlight the importance of the early maternal environment in subsequent development. However, given the possibility that prenatal environments may differ between AR and maternally reared (MR) offspring, the deficits in the behavior of AR mothers may be driven by the characteristics of their pups derived from the effects of an altered prenatal environment. Hence differences in the neonatal pups of AR mothers may produce the alterations in the AR maternal behavior. To rule out this possibility, we employed a fostering paradigm where AR and MR mothers received cross-fostered mother-reared pups. AR mothers showed the same level of deficits in maternal behavior towards MR foster pups as they do with their own pups and these deficits were partially reversed with additional tactile stimulation. Hence, maternal behavior deficits reported in mothers who had been reared in isolation are due primarily to the direct effects of the earlier experience on mechanisms regulating their maternal behavior and not to the effects on their offspring.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".