Bibliographic record
Abstract
The purpose of this research was to study the relationship between Big Five personality traits and alexithymia and to determine differences of alexithymic compare with non- alexithymic individuals in these personality traits in university students. In present study, 150 university students at Tabriz University were selected and asked to answer NEO – Five Factor Inventory (NEO - FFI), and Toronto Alexithymia Scale (TAS - 20). Results showed that there are negative and significant relationships between conscientiousness and openness to experiences with alexithymia and positive and significant relationships between neuroticism with alexithymia. As well as, there is significant difference between alexithymic and non-alexithymic individuals in neuroticism and openness to experiences. In one hand, these results suggest that neuroticism, conscientiousness and openness to experiences are determinant of alexithymia; and in the other hand, high level of neuroticism and low level of openness to experiences are the characteristic of alexithymic people based on Big-five. Therefore, it can be conclude that high neuroticism and low openness to experiences are the alexithymic individual’s traits.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".