Bibliographic record
Abstract
Aleksitimija yra asmenybės konstruktas, apibūdinantis blogą emocijų atpažinimą, sunkumus išreiškiant emocijas žodžiais, asmenybei būdingą kognityvinę – emocinę orientaciją į aplinkos veiksnius. Šio tyrimo tikslas - įvertinti reumatoidiniu artritu sergančių pacientų aleksitimiškumą ir palyginti jį su nesergančių žmonių aleksitimiškumu. Tyrimo metodai. Aleksitiminiai asmenybės bruožai buvo tiriami naudojant 20-ties teiginių Toronto aleksitimijos skalę (TAS-20). Apklausti 174 asmenys (159 moterys (91,4 proc.) ir 15 vyrų (8,6 proc.)). Reumatoidiniu artritu sirgo 80 (46 proc.), kontrolinę grupę sudarė 94 tiriamieji (54 proc.). Tyrimo išvados: priklausomybės tarp aleksitimiškumo ir RA buvimo nenustatyta (p=0,743). Statistiškai reikšmingos priklausomybės tarp aleksitimiškumo ir lyties nenustatyta (p=0,678). Tarp visų tirtų žmonių nustatyta statistiškai reikšminga priklausomybė tarp alekstimijos pasireiškimo ir amžiaus (p<0.001).
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 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".