Incidence of nonresponse and individual patterns of response following sprint interval training
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
The current study sought to explore the incidence of nonresponders for maximal or submaximal performance following a variety of sprint interval training (SIT) protocols. Data from 63 young adults from 5 previously published studies were utilized in the current analysis. Nonresponders were identified using 2 times the typical error (TE) of measurement for peak oxygen uptake (2 × TE = 1.74 mL/(kg·min)), lactate threshold (2 × TE = 15.7 W), or 500 kcal time-to-completion (TTC; 2 × TE = 306 s) trial. TE was determined on separate groups of participants by calculating the test-retest variance for each outcome. The overall rate of nonresponders for peak oxygen uptake across all participants studied was 22% (14/63) with 4 adverse responders observed. No nonresponders for peak oxygen uptake were observed in studies where participants trained 4 times per week (n = 18), while higher rates were observed in most studies requiring training 3 times per week (30%-50%; n = 45). A nonresponse rate of 44% (8/18) and 50% (11/22) was observed for the TTC test and lactate threshold, respectively. No significant correlations were observed between the changes in peak oxygen uptake and TTC (r = 0.014; p = 0.96) or lactate threshold (r = 0.17; p = 0.44). The current analysis demonstrates a significant incidence of nonresponders for peak oxygen uptake and heterogeneity in the individual patterns of response following SIT. Additionally, these data support the importance of training dose and suggest that the incidence of nonresponse may be mitigated by utilizing the optimal dose of SIT.
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) | 0.002 | 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) | 0.000 | 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