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
Theories of mood and its effect on cognitive processing suggest that positive mood may allow for increased cognitive flexibility. This increased flexibility is associated with the prefrontal cortex and the anterior cingulate cortex, both of which play crucial roles in hypothesis testing and rule selection. Thus, cognitive tasks that rely on behaviors such as hypothesis testing and rule selection may benefit from positive mood, whereas tasks that do not rely on such behaviors should not be affected by positive mood. We explored this idea within a category-learning framework. Positive, neutral, and negative moods were induced in our subjects, and they learned either a rule-described or a non-rule-described category set. Subjects in the positive-mood condition performed better than subjects in the neutral- or negative-mood conditions in classifying stimuli from rule-described categories. Positive mood also affected the strategy of subjects who classified stimuli from non-rule-described categories.
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 | 0.000 | 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 | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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