Bibliographic record
Abstract
a b s t r a c t The National Commission of Rheumatology has developed a satisfaction survey for residents concern-ing their training period. 37 % of the 176 invited to participate answered the survey. 71 % said they were satisfied or very satisfied with the influence of the assistance activities during their training. 38 % were dissatisfied or very dissatisfied with supervision by staff. 39 % were dissatisfied or very dis-satisfied with their training in polarized light microscopy. 52 % said no regular meetings were structured to monitor their training. 66 % said that there had been no effective evaluation of their training. 39 % were dissatisfied or very dissatisfied on the tools they were given to publish at their teaching unit. Overall satisfaction on classroom training for residents of Rheumatology is high. There are opportunities for improvement relating to training in certain techniques, monitoring and evaluation of the training period and training in research skills. © 2011 Elsevier España, S.L. All rights reserved. ¿Qué opinan los residentes de reumatología sobre su formación? Una encuesta de la Comisión Nacional de Reumatología Palabras clave:
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 | 0.027 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.203 | 0.071 |
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".