JoVE Video Dataset
Bibliographic record
Abstract
Social adversity in adolescence is prevalent and can negatively impact mental health trajectories. Modeling social stress in adolescent male and female rodents is needed to understand its effects on ongoing brain development and behavioral outcomes. The chronic social defeat stress paradigm (CSDS) has been widely used to model social stress in adult C57BL/6 male mice by leveraging on the aggressive behavior displayed by an adult male rodent to an intruder invading its territory. An advantage of this paradigm is that it allows to categorize defeated mice into resilient and susceptible groups based on their individual differences in social behavior 24 h after the last defeat session. Implementing this model in adolescent C57BL/6 mice has been challenging because adult or adolescent mice do not typically attack early adolescent male or female mice and because adolescence is a short period of life, encompassing discreet temporal windows of vulnerability. This limitation was overcome by adapting an accelerated version of the CSDS to be used for adolescent male and female mice. This 4-day stress paradigm with 2 physical attack sessions per day uses a C57BL/6 male adult to prime the CD-1 mouse for aggressiveness such that it readily attacks the male or female adolescent mouse. This model was termed accelerated social defeat stress (AcSD) for adolescent mice. Adolescent exposure to AcSD induces social avoidance 24 h later in both males and females, but only in a subset of defeated mice. This vulnerability occurs despite the number of attacks being consistent across sessions between resilient and susceptible groups. The AcSD model is short enough to allow exposure during discrete periods within adolescence, allows the segregation of mice according to the presence or absence of social avoidance behavior, and is the first model available to study social defeat stress in adolescent C57BL/6 female mice.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.396 | 0.260 |
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".