Effect of Seat Tube Angle and Exercise Intensity on Muscle Activity Patterns in Cyclists
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
International Journal of Exercise Science 10(8): 1145-1156, 2017. Previous studies have reported improved efficiency at steeper seat tube angle (STA) during ergometer cycling; however, neuromuscular mechanisms have yet to be fully determined. The current study investigated effects of STA on lower limb EMG activity at varying exercise intensities. Cyclists (n=11) were tested at 2 workloads; 160W and an individualised workload (IWL) equivalent to lactate threshold (TLac) minus 10%δ (derived from maximal incremental data), using 3 STA (70, 75 and 80°). Electromyographic data from Vastus Medialis (VM), Rectus Femoris (RF), Vastus Lateralis (VL) and Biceps Femoris (BF) were assessed. The timing and magnitude of activation were quantified and analysed using a two-way ANOVA. STA had significant (P < 0.05) effects on timing of onset and offset of VM, timing of offset of VL, and angle at peak for RF, all occurring later at 80 vs. 70° STA at IWL. In RF, increased activity occurred during the first 108° of the crank cycle at 80 vs. 70° at IWL (P < 0.01). As most of the power in the pedal stroke is generated during the mid-section of the down-stroke, movement of the activation range of knee extensors into the predominantly power phase of the pedal stroke would potentially account for increased efficiency and decreased cardio-respiratory costs. Greater activity of bi-articular RF, in the first 108º of the crank cycle at IWL (80 vs. 70º) may more closely resemble the pelvic stabilising activity of RF in running biomechanics; and potentially explain the more effective transition from cycling to running reported in triathletes using steeper STA.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it