Response
Bibliographic record
Abstract
Dear Editor-in-Chief: The purpose of our recent study (6) was to establish, in a single group of subjects, whether various indices identifying boundaries of sustainable performance shared common characteristics (e.g., pulmonary O2 uptake (V˙O2p)), this being done before attempting to address a mechanistic basis for these indices. Indeed, we showed with a high level of accuracy and precision that the V˙O2p associated with each of critical power (CP), maximal lactate steady state, respiratory compensation point (RCP), and the near-infrared spectroscopy-derived muscle deoxygenation breakpoint were not different (6). Given that in our carefully controlled study, each of the examined “thresholds” occurred at similar V˙O2p values, we believed that this observation could not be ignored and that speculation regarding a common underlying physiological mechanism among indices was warranted. However, Craig et al. (5) strongly oppose this possibility on the basis of their findings, reporting i) an absence of correlation between parameters (specifically RCP and CP) (4) and ii) the existence of a high degree of intrasubject variability among selected parameters (3). First, we question the use of correlational analyses to test correspondence between parameters, where Bland–Altman analysis is considered more appropriate (1). Second, the lack of correlation between V˙O2p associated with CP and RCP in the study of Broxterman et al. (4) may be partly attributable to measurement variability associated with CP, as the variability of V˙O2p at CP seems to be twice that of RCP. In our study, variability was narrower and consistent among all parameters and, as a consequence, minimized the likelihood of a type II error. Therefore, contrary to Craig et al. (5), “absence of evidence” can be considered “evidence of absence,” and thus, the lack of difference among parameters in our study may be appropriately interpreted as equivalence. Regarding the “disservice to the readership by ignoring recent work,” we were unaware of the article by Boone et al. (2) that appeared online a few days before our original submission and was regretfully missed during revision. However, we cannot apologize for lacking the clairvoyance to anticipate the publication of the study of Broxterman et al. (4), which became available online only 4 d before final acceptance of our article. Finally, by no means do we proclaim that our article is the “final word” on the association among these indices, nor do we believe that the issue related to the equivalence between these paradigms is “settled.” That an abundance of methods and indices (each with their own nomenclature) exist to define the intensity beyond which physiological homeostasis can no longer be maintained limits the comparability of data and the availability of a common reference point for subject evaluation, training design, and exercise prescription. In contrast to the opinion of Craig et al. (5), we believe that our study does provide meaningful contribution to this body of literature and does so in a nondictatorial manner. Future work should strive to examine and include the observable “threshold-like” physiological phenomena associated with high intensities of exercise to uncover their mechanistic bases—only then can equivalence or coincidence of their manifestation be concluded. Daniel A. Keir Canadian Centre for Activity and Aging School of Kinesiology University of Western Ontario London, Ontario, CANADA Department of Neurological and Movement Sciences University of Verona Verona, ITALY Federico Y. Fontana Department of Neurological and Movement Sciences University of Verona Verona, ITALY Taylor C. Robertson Canadian Centre for Activity and Aging School of Kinesiology University of Western Ontario London, Ontario, CANADA Juan M. Murias Faculty of Kinesiology University of Calgary Calgary, Alberta, CANADA Donald H. Paterson John M. Kowalchuk Canadian Centre for Activity and Aging School of Kinesiology Department of Physiology and Pharmacology University of Western Ontario London, Ontario, CANADA Silvia Pogliaghi Department of Neurological and Movement Sciences University of Verona Verona, ITALY
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 | 0.002 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.307 | 0.178 |
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".