Bibliographic record
Abstract
Ultimate Back Fitness and Performance, 2nd Edition Author: Stuart McGill. Bibliographic Data: (ISBN: 978-0-9735018-0-3, Backfitpro Inc., 2nd edition, 2006, $44.95). Specialties: Chiropractic, Physical Therapy, Sports Medicine. DESCRIPTION: This book presents an integrated and evidence-based approach to treatment and training strategies used to achieve a healthy back and improve athletic performance by conditioning the structures of the trunk and spine. PURPOSE: The author's intention is to review and summarize the latest biomechanical research and apply these findings to enhance low-back performance in the safest possible manner. This bridging of the gap between science and training is a worthy and unique objective. The author has successfully accomplished his goal. AUDIENCE: The first edition was written for clinicians in2002. However, the author modified his writing style for this edition. Scientists, clinicians, and lay persons will find this book informative. FEATURES: Three major divisions define the book. Part one describes the scientific foundation of exercise and the biomechanics of the lumbar spine. The second part discusses performance testing and training principles for creating a healthy back and preventing injuries. Part three outlines beginning, intermediate, and advanced training regimens. Case studies exemplify how the author applies the information. ASSESSMENT: This is an excellent book that is clearly written. The second edition has a new section on performance training. The writing style, evidence-based material, and practical applications make this an excellent resource for anyone interested in the training and treatment of the lumbar spine, to improve performance or recover from an injury. RATING: ★★★★★ Reviewed by: Chris Hughes (Slippery Rock University)
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.156 | 0.089 |
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".