Sex differences in risk-taking and associative learning in rats
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In many species, males tend to have lower parental investment than females and greater variance in their reproductive success. Males might therefore be expected to adopt more high-risk, high-return behaviours than females. Next to risk-taking behaviour itself, sexes might also differ in how they respond to information and learn new associations owing to the fundamental link of these cognitive processes with the risk-reward axis. Here we investigated sex differences in both risk-taking and learned responses to risk by measuring male and female rats' (Rattus norvegicus) behaviour across three contexts in an open field test containing cover. We found that when the environment was novel, males spent more time out of cover than females. Males also hid less when exposed to the test arena containing predator odour. By contrast, females explored more than males when the predator odour was removed (associatively learned risk). These results suggest that males are more risk-prone but behave more in line with previous experiences, while females are more risk-averse and more responsive to changes in their current environment. Our results suggest that male and female rats differ in how they cope with risk and highlight that a general link may exist between risk-taking behaviour and learning style.
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.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it