Bibliographic record
Abstract
This text attempts to identify the causes of back problems and outlines how to prevent or eliminate them. Much like a patient advancing through Dr. McGill’s stages of rehabilitation, the text follows a logical progression with subsequent chapters building on previously established concepts. The early chapters review the functional anatomy and injury mechanisms of the lumbar spine while challenging many commonly held beliefs and laying the foundation for the rest of text. The middle section outlines how to reduce the stressors that can cause low back disorders with guidelines for both worker and employer. The final chapters focus on a Five-Stage Back Training Program, beginning with identifying faulty movement patterns utilizing provocation tests then progressing to building stability and endurance using variations of Dr. McGill’s “big three” exercises. The text’s strength lays in the author’s research background and the labs that he has developed, which he frequently relies upon when determining spinal loads and when suggesting preventative or rehabilitative strategies. From a chiropractic perspective, a discussion on the role of manipulation in rehabilitation would have been valuable. Little is said about chiropractic other than noting that a small group of patients may benefit from initial mobilization while warning that many make the mistake of trying to mobilize an already unstable joint. Regardless, this text offers a systematic and evidence-based approach to addressing low back disorders that should be read in its entirety and then used as a reference tool by practitioners incorporating exercises into their treatments.
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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.027 | 0.011 |
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".