Mecanismos cognitivos de reconocimiento de información emocional en jóvenes con y sin alexitimia
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
To measure the recognition of emotional information, different tools are used, such as affective priming, which measures the latency of response of two stimuli, whether congruent or incongruent with each other.Depression and alexithymia can impede recognition.Alexithymia is the difficulty in identifying and describing emotions, as well as externally oriented thinking, impacting on cognition and affection.It was intended to evaluate the recognition of emotional stimuli among young people from 18 to 31 years old with alexithymia and without alexithymia.Of 316 respondents, 39 participated in the implicit measurement by identifying whether the facial expression has emotion.People with alexithymia had high scores in depression, classified into three groups: 1) alexithymia and depression (14 people), 2) depression (10 participants) and 3) without alexithymia and without depression (15 people).The results showed that the group with alexithymia and depression is the one that takes longer to identify the emotion than the nonemotion, accepting hypothesis 1.The three groups performed a longer reaction time in identifying the negative emotions than the positive ones.Hypothesis 2 is accepted due to people without alexithymia or depression are the quickest in identify these emotional expressions, followed by people with alexithymia and depression.This study was carried out remotely because of the confinement by COVID-19.A possible replication of this study in different social conditions could clarify the external variables associated with alexithymia and depression.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.002 | 0.013 |
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