Evidence of abnormal scalar timing property in alexithymia
Bibliographic record
Abstract
Evidence suggests that incidental modulation of affective states affects the ability to keep track of time. Alexithymia represents an ideal condition to further address the emotion-time processing link, as it refers to a trait characterized by a deficit of affective processing. 31 healthy participants completed an online version of the TAS-20 scale, which measures alexithymia, and a time reproduction task of visual stimuli related to positive (i.e., happiness) and negative (i.e., anger) facial expressions. Results documented a positive correlation between TAS-20 score and the variability in reproducing sub-second durations of the anger expression stimuli We also found an overestimation of sub-second durations of non-affective expressions in borderline/alexithymic participants. Finally, in line with the literature, we confirmed the overall tendency to overestimate the duration of anger expression stimuli. These findings, which can be interpreted in terms of abnormal scalar timing property in alexithymia, expand previous investigations linking this personality trait with abnormal processing of negative emotions. The evidence that alexithymia predicts the reproduction variability of sub-second durations of negative affective stimuli corroborates previous neuroimaging studies documenting cerebellar deficits in these individuals.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".