Does Spine Posture Affect Isometric Torso Muscle Endurance Profiles in Adolescent Children?
Bibliographic record
Abstract
The purpose of this cross-sectional study was to examine mean values of isometric torso muscle profiles of four spinal postures (good posture, thoracic kyphosis, lumbar lordosis and scoliosis) among 743 children from the ages of 7 to 14 years old. It was hypothesized that having good posture, thoracic hyper-kyphosis, lumbar hyper-lordosis and scoliosis is linked to different isometric torso muscle endurance profiles. Torso muscle endurance, established through four tests (Biering-S?rensen Test for extensor endurance, Flexor Endurance Test and right and left Side Bridge Tests for lateral endurance) performed in random order and spine postural screening categorized subjectively by observation was measured. Posture was proved to be linked to endurance scores. Hyper-lordotic spines demonstrated a decreased endurance compared to the three other postures (F = 5.344; p < 0.01); pairwise comparisons confirmed these differences (p < 0.05). Trends further suggested that hyper-lordosis was detrimental in lateral chain torso endurance while a hyper-kyphotic spine was more resilient in anterior chain torso endurance. Understanding the relationship between posture and endurance may be beneficial in clinical, as well as coaching/teaching settings.
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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 | 0.000 | 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".