Bibliographic record
Abstract
【In order to understand the psychological charateristics of Sasang Constitution. the Korean version of 20-item Toronto Alexithymia Scale(TAS-20K) was completed by 59 sixth grade students of oriental medical college of KyungHee university who defined as one of Sasang constitution from June 2000 to August, and the mean scores of Yangin versus Eumin and Sasang constitution on TAS-20K was compared. The results of this study were as follows.1. Comparison between male and female on Means of TAS-20K ScoreMann-Whitney U test detected no significant differences between mean ranks of TAS-20K scores of male and those of female in F1, F2 and Total, but significant difference in F3(Mann-Whitney U test, t=2.493. p=.018)2. Comparison between Yangin and Eumin on Means of TAS-20K ScoreMann-whitney U test detected no significant differences between mean ranks of TAS-20K scores of Yangin and those of Eumin in F1. F3 and Total, but significant difference in F2(Mann-Whitney U test. t=-2.805. p=.008)3. Comparison among Sasang constitution on Means of TAS-20K ScoreAlthough mean of TAS-20K score of Taeyangin. Soyangin and Soeumin, there were no significant differences among Sasang constitution in F1, F2 and F3 as well as Total when mean ranks of TAS-20K scores of Sasang constitution were compaed by one-way ANOVA.】
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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; both teacher heads agree on what is shown here.
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".