Pose® Method Technique Improves Running Performance without Economy Changes
Bibliographic record
Abstract
The aim was to investigate the affects of the Pose® method intervention on running technique, on economy and a time-trial runs. A 2 × 2 mixed factorial ANOVA assessed sixteen research variables where group (Heel-toe vs. Pose®) and trial (pre to post changes) was used. Significant interactions were explored using Tukey post hoc tests, which found significance (Pose® runners pre-post test) for stance time ( p = 0.001), horizontal displacement of the centre of mass to support foot at 25 ms after impact (p = 0.042), centre of mass displacement during stance ( p = 0.001), knee flexion angular velocity during stance ( p = 0.005) and during swing to maximum knee flexion ( p = 0.043) and stride frequency ( p = 0.002). The Pose® group's post-test time-trial (2400 m) was not significant yet they improved by a mean of 24.7 s compared with a 3 s decrease in the heel-toe group. No significant changes pre-post test, were found for an economy run (2400 m) at 3.35 m/s.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.007 | 0.001 |
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".