Pharmacognostical, physiochemical and phytochemical evaluation of leaf, stem and root of orchid Dendrobium ochreatum
Bibliographic record
Abstract
Worldwide, severe pain and disability are caused to patients by Osteoarthritis, which is a common condition of the joints. A need for knee replacement had become a great option for patients when conventional treatment fails in granting appropriate relief in them, especially in elderly patients. Like all joint replacement surgeries, a total knee replacement procedure is also a quite painful and risky procedure that requires sufficient postoperative rehabilitation and therapies to prevent further complications. Post-surgical pain had a great influence on the patients' quality of life and a need to measure pain intensity had become a basic requirement. Measuring pain intensity can be done using traditional pain scales like a visual analogue scale (VAS), and a numerical rating scale (NRS). A risk assessment and predictor tool (RAPT) determines the discharge accuracy in patients. The WOMAC scale which is the abbreviated form of the questionnaire for checking the health status of the patients known as the Western Ontario and McMaster University Osteoarthritis Index. This questionnaire is used to assess the quality of life of the osteoarthritis patients after a surgery for the total knee replacement. The results of the assessment show that pain had become a significant factor in the reduction in quality of life. In conclusion, a well-designed multimodal analgesic regimen should be incorporated into the patient's rehabilitation care, which in turn will intensify the patient's quality of life, lessen the hospital stay, and minimize the socio-economic burden
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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".