Bibliographic record
Abstract
Presenting a variety of treatment choices supported by the latest clinical research, this 4th edition is a guide to the safe, most effective use of physical agents in the rehabilitation practice. Coverage in this new edition includes the most up-to-date information on thermal agents, ultrasound, electrical currents, hydrotherapy, traction, compression, lasers, and electromagnetic radiation. Straightforward explanations make it easy to integrate physical agents into patients' overall rehabilitation plans. Includes comprehensive coverage of all physical agents includes the benefits, correct applications, and issues related to thermal agents, hydrotherapy, traction, compression, ultrasound, electrical currents, and electromagnetic radiation. Clinical case studies help sharpen your decision-making skills regarding important treatment choices and effective applications. Up-to-date, evidence-based practices ensure the use of the best approach supported by research. Contraindications and Precautions boxes explain the safe use and application of physical agents with up-to-date warnings for optimum care paths. Clinical Pearl boxes emphasize the tips and tricks of patient practice. Application techniques in step-by-step, illustrated resource boxes help provide safe and effective treatments. New video clips on companion Evolve site demonstrate techniques and procedures described in the text. New content specific to OTs has been added to the core text including upper extremity cases for all physical agent chapters. New organization of the text by agent type increases the book's ease of use. New expanded sections on thermal agents and electrical currents will give students a better understanding of how to use these types of agents in practice.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.329 | 0.207 |
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".