Dreaming activity in bariatric surgery candidates.
Bibliographic record
Abstract
The objective of this article was to contribute to the comprehension of thepsychological aspects of severe obesity by analyzing the dream characteristics ofbariatric surgery candidates. Given the lack of previous studies comparing controlsubjects and obese patients, we did not formulate specific hypotheses on possibledifferences between the 2 groups. We conducted a pilot study, generating hypothesesfor future research. The study observed 41 severely obese individuals in presurgicalpsychiatric evaluation for bariatric surgery and 41 healthy volunteers of similar age.The last recalled dream of each participant was recorded and transcribed (dreamreport). According to the Jungian approach to dreams as texts, the dream reportswere evaluated according to the canons of textual analysis. Structural differencesbetween bariatric surgery candidates and the control group emerged: The bariatricsurgery candidates tend not to alternate between tenses, their narration inferior indrive and dynamism. They tend to characterize the dream setting in a descriptivemanner and they express less their emotional state in respect to the control group. Themean score of the 20-item Toronto Alexithymia Scale was significantly higher in thebariatric surgery candidates group. Our results suggest that severe obesity-acomplex condition pertaining to both mind and body-correlates with psychologicaltraits.
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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 | 0.002 |
| 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".