The effects of the Alexander Technique training on neck and shoulder biomechanics and posture in healthy people
Bibliographic record
Abstract
Le but de ce projet de maîtrise était de mesurer les effets d'un programme de huit semaines, 20 leçons de technique Alexander (AT) sur l'alignement postural cou-épaule, l'amplitude de mouvement et l'activité musculaire de personnes en bonne santé pendant des tâches qui visaient la relation tête-cou-épaule. Les évaluations de laboratoire post-entraînement ont indiqué une diminution de la cyphose thoracique durant des tâches statiques d'assise et d'entrée de texte à l'ordinateur. Il y avait une augmentation d'amplitude d'activité du muscle serratus antérieur à 120 degrés d'une tâche de flexion d'épaule avec charge et d'amplitude de flexion d'épaule. Puisque la posture semble être un facteur de risque pour des troubles musculo-squelettiques et que les déficits d'amplitude ainsi que le maintient de postures de travail spécifiques avec l'activation musculaire sont associés aux troubles chroniques de cou-épaule, l'AT pourrait présenter un avantage clinique comme approche de réadaptation et de prévention des troubles cou-épaule.
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 | 0.001 | 0.001 |
| 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) | 0.002 | 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".