Relevance of the <scp>T</scp>hought–<scp>S</scp>hape <scp>F</scp>usion <scp>T</scp>rait <scp>Q</scp>uestionnaire for healthy women and women presenting symptoms of eating disorders and mixed mental disorders
Bibliographic record
Abstract
Thought-shape fusion (TSF) describes the experience of marked concerns about body weight/shape, feelings of fatness, the perception of weight gain, and the impression of moral wrongdoing after thinking about eating fattening/forbidden foods. This study sets out to evaluate the short version of the TSF trait questionnaire (TSF). The sample consists of 315 healthy control women, 244 women with clinical and subthreshold eating disorders, and 113 women with mixed mental disorders (mixed). The factor structure of the TSF questionnaire was examined using exploratory and subsequent confirmatory factor analyses. The questionnaire distinguishes between a Concept scale and a Clinical Impact scale. However, a lack of measurement invariances refers to significant differences between groups in terms of factor loadings, thresholds, and residuals, which questions cross-group validity. Results indicate that the concept is understood differently in the 3 groups and refers to the suitability of the questionnaire primarily for individuals presenting with symptoms of eating disorders.
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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 | 0.002 | 0.011 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".