Assessment of Common Problems of Post Graduate Students Pursuing F.C.P.S and M.D.S in Orthodontics and Dentofacial Orthopedics, Due To COVID 19 Lockdown
Bibliographic record
Abstract
Abstract Objective: To assess the common concerns of FCPS and MDS trainees in Orthodontics due to COVID-19 lockdown. Methods: This cross-sectional study was conducted in different institutes of Sindh which offered FCPS/MDS training in Orthodontics. The study was carried out after approval from the ethical commit- tee. A questionnaire was designed comprising of 15 questions. Each question aiming to assess the difficulties faced by trainees due to the imposition of lockdown. The questionnaire was distributed amongst 80 participants/trainees in the training year 2 to 4. Results: The average age of study participants was 29 years with range of 27 to 38 years. In this study a large number of subjects said that they were unsure regarding completion of cases due to lockdown i.e; n=63,(77.8%). Approximately half of the study subjects thought that there will be mas- sive patient burden after resuming to the normal practice i.e 40(49.4%). Nearly quarter of them were puzzled that due to lockdown it was difficult to focus on thesis and research work i.e 18(22.2%). Few of them also responded that after resuming to the normal practice there would be pressure from su- perior authorities for academic works i.e; n=9,(11.1%). Conclusion: This study analyzed those major concerns were non-availability of basic materials for procedures, fear of completion of cases due to lockdown and massive patient burden in clinics after uplifting of lockdown. Therefore, Covid-19 lockdown has in many ways affected the academic and clinical activities of the post-graduate students. The uncertainty to tackle this surprise situation is still an unanswered question.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".