Head Posture Influences Low Back Muscle Endurance Tests in 11-Year-Old Children
Bibliographic record
Abstract
Poor low back muscle endurance has been shown to be a predictor of chronic low back pain. While posture is a modulator of low back muscle endurance, it is unclear whether the phenomenon is neural or mechanical. This study examined low back muscle endurance with changing head and neck posture in a sample of 117 children using the Biering-Sørensen test. Each subject performed the test in a neutral posture followed by randomly selected flexed and extended head and neck positions. Head posture was found to significantly influence low back muscle endurance within subjects (p < .001), with extension yielding the highest endurance scores (boys = 186.6 ± 66.2 s; girls = 192.1 ± 59 s), followed by a neutral posture (boys = 171.3 ± 56.5 s; girls = 181.7 ± 57.3 s), and flexion (boys = 146.2 ± 63.8 s; girls = 159.8 ± 49.3 s). Given the minimal influence of changing moment from head and neck posture, it appears other mechanisms influence endurance score.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".