Therapeutic Electrophysical Agents, Evidence Behind Practice. Second Edition
Bibliographic record
Abstract
This book is based on the book “The Team Physician’s Handbook,” but includes more appropriate best practice suggestions based on more recent research and advances in treatment strategies. Geared towards the sport clinician, Netter’s Sports Medicine deals with the roles, ethics and responsibilities when dealing with a sports team. The most unique feature of this book is found in Section VIII, which has chapters to separate specific sports. Current research and statistics are reported about the incidence and type of injuries, commonly involved in each sport. At the end of each chapter, a list is featured of recommended readings for further education about that particular sport. This section is an outstanding source of information for the sport clinician, wanting to know the basic premise, and biomechanics for different sports. Being a book in the Netter Collection, this textbook includes many of the famous illustrations and anatomical diagrams from Dr. Frank Netter, which are well known in the rehabilitation world. Various radiographic photographs are also plentiful in this textbook, allowing the reader to gain a further understanding of specific injuries. This book could be used as a quick reference guide to any athletic situation, however it could be argued that the book contains too much information is is difficult to locate the information necessary. The book is very meticulously organized though, using colour coding, a detailed index and thorough headings throughout the text. The reader is guaranteed to learn something new each time this book is opened.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".