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
This study examined the effects on recall of story details of congruity or incongruity between the hedonic valence of literary texts and odours inhaled while reading them. During the reading session, 24 undergraduates (12 males and 12 females) read two passages involving positive subject matter and two with negative subject matter while sniffing pleasant or unpleasant odours in a within-subject fully counterbalanced design. Subjects rated their experience of each text on eleven 7-point scales. During the test session 48 hours later, subjects read a two-word title associated with each of the passages and inhaled the odour that was paired with it in the reading session. They also rated their experience on six of the scales that had been used during the reading session. Results showed that hedonic congruence between the passage and the odour fostered enhanced recall during the test session. The combination of positive subject matter and positive odour was reflected in more accurate recall of character details, while pairing negative subject matter and negative odour resulted in more accurate recall of setting details. Regression analysis showed that overall recall accuracy was increased by identifying with the characters in the stories and for passages that were found pleasing and personally meaningful. Consistent with the literature on implicit learning involving odours, recall accuracy varied inversely with perceived odour intensity. Implicit learning involving odours and literary passages is therefore fostered by unity in the reading experience.
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 | 0.000 |
| 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