Clinical Orthopaedic Rehabilitation: An Evidence-Based Approach – Third Edition
Bibliographic record
Abstract
The authors of this book have succeeded in providing rehabilitation professionals with a comprehensive resource for managing numerous orthopaedic conditions. The text is divided into chapters that discuss regional problems in depth, including injury assessment, differential diagnoses, and rehabilitation protocols. The chapter on spinal disorders is particularly well done, and covers topics such as whiplash management, core stabilization, McKenzie approach to LBP, and rehabilitation following lumbar disc surgery. At the conclusion of each chapter, non-operative and post-operative treatment protocols are provided in an easy to follow chart format to help guide the practitioner through the rehabilitation process. The breadth of the information presented in this text can be attributed to the extensive reference list with citations as recent as 2010 presented at the end of each chapter. The book is also accompanied by a bonus expert consult feature that provides online access to the book contents and a video library demonstrating exercises and treatment techniques. Overall, this text is an extraordinary presentation of material primarily geared toward chiropractors with an interest in exercise and rehabilitation, and would have the greatest utility for those directly involved with patient care.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.024 | 0.009 |
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".